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Giorgia FOCA
Ricercatore Universitario
Dipartimento di Scienze della Vita sede ex-Agraria
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Pubblicazioni
2023
- Design and application of a smartphone-based device for in vineyard determination of anthocyanins content in red grapes
[Articolo su rivista]
Menozzi, C; Calvini, R; Nigro, G; Tessarin, P; Bossio, D; Calderisi, M; Ferrari, V; Foca, G; Ulrici, A
abstract
The choice of the proper moment for harvesting is a crucial aspect in winemaking process, since the chemical attributes of grape berries strongly influence red wine quality. In particular, phenolic composition of red grapes plays a significant role in many sensory properties of wine related to color and taste. Anthocyanins are the most important phenolic compounds for red grapes: they accumulate in the grape skin during ripening, and they are responsible for the purple color of ripe berries. Routine analysis for the determination of grapes phenolic maturity includes chromatographic and spectroscopic techniques, that are time-consuming and expensive. In this work, we propose an innovative device conceived for the determination of grape phenolic maturity based on RGB images of grape berries acquired with a smartphone. The device has been designed to be used directly in the vineyard thanks to its small size and to the possibility of acquiring geolocated images of the berries under controlled lighting conditions. In this study, grape samples of three different varieties (Ancellotta, Lambrusco Salamino and Sangiovese) were collected at different harvest times from veraison to maturity and imaged by means of a common smartphone using the device. The RGB images were then converted into one-dimensional signals, named colourgrams, which codify the color properties of the images. The dataset of colourgrams was then used to calculate calibration models using Partial Least Squares (PLS) regression in order to relate color information with chemical parameters generally employed to evaluate grape phenolic maturity, such as total anthocyanins content and extractable anthocyanins content. The calibration models were implemented in a software interface that allows to acquire geolocated images of the grape samples, visualize the outcomes of the analysis, visualize maps and plots related to phenolic maturity, store data and share relevant information.
2023
- Mixture design and multivariate image analysis to monitor the colour of strawberry yoghurt purée
[Articolo su rivista]
Rolando, P. L.; Calvini, R.; Foca, G.; Ulrici, A.
abstract
Food colour is a commercial added value, since it represents the first appealing factor for consumers. In this context, this study was aimed at evaluating the effect of strawberry yoghurt purée (SYP) formulation on the corresponding colour and on its variation over time, which is mainly due to degradation and browning phenomena. To this aim, a combined approach was used that included mixture design and multivariate analysis of RGB images. Strawberry purée, sugar, lemon juice and two types of thickener were mixed in different proportions by I-optimal mixture design to obtain 44 SYP formulations. The samples were subjected to light and temperature stress conditions for five weeks; during this time the RGB images of the samples were acquired using a flatbed scanner, along with the images of the corresponding control samples. The dimensionality of the acquired images was reduced by two different approaches: i) the conversion of images into signals, namely colourgrams, which can be seen as the colour fingerprint of the imaged samples, and ii) the calculation of the median values of various colour-related parameters. The colourgrams dataset was then subjected to exploratory data analysis using Principal Component Analysis, while the median values of colour-related parameters were analysed using Response Surface Methodology and Partial Least Squares-Discriminant Analysis. The aim of data analysis was both to find the best colour parameters to describe colour variability over time, and to investigate the cause-effect relationship between mixture proportions and colour response. The results highlighted that, among the considered colour parameters, relative green (i.e., the ratio of green to lightness) and red could be used to monitor colour changes. Colour variation due to stress conditions was more pronounced for samples with a high percentage of strawberry purée, and the type of thickener also affected the colour degradation kinetics.
2022
- Improved fed-batch processes with Wickerhamomyces anomalus WC 1501 for the production of D-arabitol from pure glycerol
[Articolo su rivista]
Raimondi, Stefano; Foca, Giorgia; Ulrici, Alessandro; Destro, Lorenza; Leonardi, Alan; Buzzi, Raissa; Candeliere, Francesco; Rossi, Maddalena; Amaretti, Alberto
abstract
D-Arabitol, a five-carbon sugar alcohol, represents a main target of microbial biorefineries aiming to valorize cheap substrates. The yeast Wickerhamomyces anomalus WC 1501 is known to produce arabitol in a glycerol-based nitrogen-limited medium and preliminary fed-batch processes with this yeast were reported to yield 18.0 g/L arabitol.
2022
- Preliminary evaluation of the use of a disposable electrochemical sensor for selective identification of Δ9-tetrahydrocannabinol and cannabidiol by multivariate analysis
[Articolo su rivista]
Zanfrognini, B.; Monari, A.; Foca, G.; Ulrici, A.; Pigani, L.; Zanardi, C.
abstract
The widespread diffusion of products deriving from Cannabis sativa L. led to the necessity of rapid and reliable
methods for the identification of samples containing Δ9-tetrahydrocannabinol (THC), the psychoactive component
of the plant, which imparts mental distortions and hallucinations. Although some efficient electrochemical
sensors have been already proposed for such a purpose, they do not consider that the plant may also contain huge
amounts of cannabidiol (CBD), which possesses an electroactive moiety quite similar to that of THC. The definition
of both THC and CBD concentration is at the basis of discrimination between recreational-type and fibretype
cannabis samples; detection of these species is not only important in vegetable samples but also in relevant
commercial products and in biological fluids. We proposed here a screen-printed electrode coated with a layer of
carbon black for the rapid identification of samples containing THC irrespectively of the simultaneous presence
of CBD. The most performing carbon black typology used for such a purpose was chosen among various commercial
products tested on the basis of preliminary tests performed on 1,3-dihydroxybenzene, constituting the
redox active moiety of cannabinoids. The voltammetric responses collected in various solutions containing
different amount of THC and CBD were initially elaborated by Principal Component Analysis, assessing the
possibility of identifying samples with similar concentrations of THC irrespectively of the CBD concentration
values, and vice-versa. Afterwards a preliminary Partial Last Square regression was performed to evaluate the
possibility of a quantitative analysis of both THC and CBD. This approach suggests the possibility of using the
sensor proposed to screen samples containing THC even in the presence of high amounts of CBD.
2022
- Sensory evaluation and mixture design assessment of coffee-flavored liquor obtained from spent coffee grounds
[Articolo su rivista]
Masino, Francesca; Montevecchi, Giuseppe; Calvini, Rosalba; Foca, Giorgia; Antonelli, Andrea
abstract
Spent coffee grounds are a source of bioactive compounds, including caffeine and other valuable substances, such as volatiles, fats, and alkaloids, which are currently not exploited. In this research, the water content was separated through absolute ethanol extraction yielding a hydroalcoholic solution of volatiles that could be an optimal base for a coffee-flavored liquor. This work was aimed at assessing the potential of coffee-flavored liquor formulations with the use of sensory techniques and mixture design.
Based on a mixture experimental design, a total of 17 coffee-flavored liquors, including replicates, were obtained at lab-scale by adding variable amounts of water, glucose syrup, and caramel to a fixed amount of hydroalcoholic extract flavored with vanillin.
First, a total of 328 consumers were asked to answer a questionnaire about the attributes of an ideal coffeeflavored liquor and their intensity in order to draw an ideal profile from a consumer point of view. Then, judges trained on the attributes of industrially-produced coffee liquors were involved in two descriptive sensory evaluation sessions of the 17 samples. Data analysis pointed to the coffee-flavored liquors with a sensory profile close to the ideal one. They showed
an intense black color (mean score 7) related to a higher caramel concentration in comparison with the other samples. In addition, they scored higher in flavor and body (mean score 7) due to the relative amount of syrup and water. It is noteworthy to mention that the judges regarded these samples as more balanced than the others in terms of alcohol strength, bitterness, and sweetness.
2021
- Chemometrics, imaging and spectroscopy laboratory – Department of Life Sciences, University of Modena and Reggio Emilia
[Articolo su rivista]
Calvini, Rosalba; Foca, Giorgia; Ulrici, Alessandro
abstract
2021
- Evaluation of the effect of factors related to preparation and composition of grated Parmigiano Reggiano cheese using NIR hyperspectral imaging
[Articolo su rivista]
Calvini, R.; Michelini, S.; Pizzamiglio, V.; Foca, G.; Ulrici, A.
abstract
The present study is focused on the evaluation of the effect of grater type and fat content of the pulp on the spectral response obtained by near infrared hyperspectral imaging (NIR-HSI), when this technique is used to determine the rind percentage in Parmigiano Reggiano (P-R) cheese. To this aim, grated P-R cheese samples were prepared considering all the possible combinations between three levels of rind amount (8%, 18% and 28%), two levels of fat content of the pulp and two different grater types, and the corresponding hyperspectral images were acquired in the 900–1700 nm spectral range. In a first step, the average spectrum (AS) was calculated from each hyperspectral image, and the corresponding dataset was analysed by means of Analysis of Variance Simultaneous Component Analysis (ASCA) to assess the effect of the three considered factors and their two-way interactions on the spectral response. Then, the hyperspectral images were converted into Common Space Hyperspectrograms (CSH), which are signals obtained by merging in sequence the frequency distribution curves of quantities calculated from a Principal Component Analysis (PCA) model common to the whole hyperspectral image dataset. ASCA was also applied to the CSH dataset, in order to evaluate the effect of the considered factors on this kind of signals. Generally, all the three factors resulted to have a significant effect, but with a different extent according to the method used to analyse the hyperspectral images. Indeed, while fat content of the pulp and rind percentage showed a comparable effect on the spectral response of AS dataset, in the case of CSH signals rind percentage had a greater effect compared to the other main factors. However, CSH were also more sensitive to differences ascribable to the natural variability between diverse Parmigiano Reggiano cheese samples.
2021
- Simultaneous Detection of Glucose and Fructose in Synthetic Musts by Multivariate Analysis of Silica-Based Amperometric Sensor Signals
[Articolo su rivista]
Crespo-Rosa, Joaquin Rafael; Foca, Giorgia; Ulrici, Alessandro; Pigani, Laura; Zanfrognini, Barbara; Cubillana-Aguilera, Laura; Palacios-Santander, José María; Zanardi, Chiara
abstract
Silica-based electrodes which permanently include a graphite/Au nanoparticles composite were tested for non-enzymatic detection of glucose and fructose. The composite material showed an effective electrocatalytic activity, to achieve the oxidation of the two analytes at quite low potential values and with good linearity. Reduced surface passivation was observed even in presence of organic species normally constituting real samples. Electrochemical responses were systematically recorded in cyclic voltammetry and differential pulse voltammetry by analysing 99 solutions containing glucose and fructose at different concentration values. The analysed samples consisted both in glucose and fructose aqueous solutions at pH 12 and in solutions of synthetic musts of red grapes, to test the feasibility of the approach in a real frame. Multivariate exploratory analyses of the electrochemical signals were performed using the Principal Component Analysis (PCA). This gave evidence of the effectiveness of the chemometric approach to study the electrochemical sensor responses. Thanks to PCA, it was possible to highlight the different contributions of glucose and fructose to the voltammetric signal, allowing their selective determination.
2021
- Stink bug study reveals Gold3 preference
[Articolo su rivista]
Preti, M.; Moretti, C.; Landi, M.; Bombardini, E.; Tommasini, M. G.; Foca, G.; Ulrici, A.; Maistrello, L.
abstract
An Italian study of feeding damage by brown marmorated stink bug found major damage in the month before harvest in Gold3, when high fruit-drop occurred. Injured Hayward had much lower fruit drop and there were no differences in post harvest storage performance between injured and non-injured fruit.
2020
- Colourgrams GUI: A graphical user-friendly interface for the analysis of large datasets of RGB images
[Articolo su rivista]
Calvini, R.; Orlandi, G.; Foca, G.; Ulrici, A.
abstract
Colourgrams GUI is a graphical user-friendly interface developed in order to facilitate the analysis of large datasets of RGB images through the colourgrams approach. Briefly, the colourgrams approach consists in converting a dataset of RGB images into a matrix of one-dimensional signals, the colourgrams, each one codifying the colour content of the corresponding original image. This matrix of signals can be in turn analysed by means of common multivariate statistical methods, such as Principal Component Analysis (PCA) for exploratory analysis of the image dataset, or Partial Least Squares (PLS) regression for the quantification of colour-related properties of interest. Colourgrams GUI allows to easily convert the dataset of RGB images into the colourgrams matrix, to interactively visualize the signals coloured according to qualitative and/or quantitative properties of the corresponding samples and to visualize the colour features corresponding to selected colourgram regions into the image domain. In addition, the software also allows to analyse the colourgrams matrix by means of PCA and PLS.
2020
- Exploring the potential of NIR hyperspectral imaging for automated quantification of rind amount in grated Parmigiano Reggiano cheese
[Articolo su rivista]
Calvini, R.; Michelini, S.; Pizzamiglio, V.; Foca, G.; Ulrici, A.
abstract
Parmigiano Reggiano (P-R) is one of the most important Italian food products labelled with Protected Designation of Origin (PDO). The PDO denomination is applied also to grated P-R cheese products meeting the requirements regulated by the Specifications of Parmigiano Reggiano Cheese. Different quality parameters are monitored, including the percentage of rind, which is edible and should not exceed the limit of 18% (w/w). The present study aims at evaluating the possibility of using near infrared hyperspectral imaging (NIR-HSI) to quantify the rind percentage in grated Parmigiano Reggiano cheese samples in a fast and non-destructive manner. Indeed, NIR-HSI allows the simultaneous acquisition of both spatial and spectral information from a sample, which is more suitable than classical single-point spectroscopy for the analysis of heterogeneous samples like grated cheese. Hyperspectral images of grated P-R cheese samples containing increasing levels of rind were acquired in the 900–1700 nm spectral range. Each hyperspectral image was firstly converted into a one-dimensional signal, named hyperspectrogram, which codifies the relevant information contained in the image. Then, the matrix of hyperspectrograms was used to calculate a calibration model for the prediction of the rind percentage using Partial Least Squares (PLS) regression. The calibration model was validated considering two external test sets of samples, confirming the effectiveness of the proposed approach.
2020
- Hermetia illucens (L.) larvae as chicken manure management tool for circular economy
[Articolo su rivista]
Bortolini, Sara; Macavei, Laura Ioana; Saadoun, Jasmine Hadj; Foca, Giorgia; Ulrici, Alessandro; Bernini, Fabrizio; Malferrari, Daniele; Setti, Leonardo; Ronga, Domenico; Maistrello, Lara
abstract
The increased request for poultry meat and eggs of a rising human population requires more efficient and cleaner methods to manage increasing quantities of chicken manure. The black soldier fly Hermetia illucens is known as an efficient bio-converter of organic waste in proteins and fats, with the advantage that the larval frass is supposed to have compost-like properties. In the view to identify the operating conditions for the sustainable management and valorization of livestock waste at a pre-industrial scale, this study is aimed at: i) optimizing the growth of H. illucens on a mixture of chicken manure, chabazite and water; ii) assessing the soil amendment properties of the larval frass obtained from the optimized mixture. Preliminary trials allowed defining the basic rearing conditions in terms of temperature and substrate components. A mixture design based on a special cubic model allowed identifying the best mixture for H. illucens larvae growth, which consists in 34.5% chicken manure, 58.3% water and 7.2% coarse chabazite. This mix led to about 86% of alive prepupae weighting 90 mg on average, and to a reduction of the initial substrate amount by more than 75%. The larval frass obtained from this mixture showed soil improver properties, suggesting its use to supply the common peat based growing media for potted baby-leaf lettuce production. Overall, H. illucens larvae have proved to be a useful tool to favor a more sustainable management of chicken manure by strongly reducing its amount and closing its recovery cycle obtaining high value products for agricultural purposes.
2020
- Potential of wickerhamomyces anomalus in glycerol valorization
[Articolo su rivista]
Amaretti, A.; Russo, B.; Raimondi, S.; Leonardi, A.; Foca, G.; Mucci, A.; Zambon, A.; Rossi, M.
abstract
Five-carbons polyalcohols, such as xylitol and arabitol, and microbial oils are important targets for biotechnological industries. Polyalcohols can find application as low-calories sweeteners and as building block in the synthesis of valuable compounds, while lipids are interesting for both biofuel and food industry. The osmophilic yeast Wickerhamomyces anomalus WC 1501 was preliminary known to produce arabitol from glycerol. Production kinetics were investigated in this study. Production was not growth-associated and occurred during a nitrogen-limited stationary phase, in presence of an excess of carbon source. Typical bioreactor batch cultures, carried out with 160 g/L glycerol, yielded 16.0 g/L arabitol in 160 h. A fed-batch process was developed, in which growth is carried out batchwise in a balanced medium containing 20 g/L glycerol, and arabitol production is induced at the entrance into the stationary phase with a pulse of concentrated glycerol to provide the remaining 140 g/L carbon source. At the end of the process 18.0 g/L arabitol were generated. Under these conditions, the yeast also accumulated intracellular triacylglycerols, with fatty acids of 16-18 carbons bearing 0 to 2 unsaturations, reaching up the 23% of biomass dry weight. Therefore, W. anomalus WC 1501 is a good candidate for the development of a fermentative process yielding arabitol and has potential also as oleaginous yeast for producing lipids, further improving the interest in this strain for glycerol biorefinery. The utilization of a fed-batch process allows to carry out distinct growth and production phases and thus allows the optimization of both phases separately, in order to achieve the highest concentration of catalytic biomass during growth and the maximum efficiency during production. This strain deserves further investigation to better exploit its biotechnological potential in the valorization of glycerol.
2020
- Red horse-chestnut of Aesculus X Carnea : a new way for health and food design?
[Capitolo/Saggio]
Baraldi, Cecilia; Foca, Giorgia; Maletti, Laura; Marchetti, Andrea; Roncaglia, Fabrizio; Sighinolfi, Simona; Tassi, Lorenzo
abstract
Some investigations have been performed about the composition of Aesculus X carnea seeds (Red horse-chestnuts). Different experimental techniques have been used to gain more information on morphological structure and proximate chemical composition of this product. Surface analysis by SEM showed internal typical structure of globular-form bodies, containing starch, lipids, proteins, mineral components and many others species, confined in cell walls and cemented by a gelled hydrocolloid. The most representative data related to the chemical composition of naturally desiccated specimen are as follows: proteins 3.16%; lipids 4.34%; total glucides 15.6%. Obviously, this chemical faces modulate some other undifferentiated chemical parameters, such as Cold Water Solubility (CWS = 53.9%), and Total Inorganic Soluble Salts (TISS = 2.79%). A stringent comparison of the present findings has been made with our previous results obtained by working with the seeds of two Hippocastanaceae parent cultivars.
2020
- Sustainable innovation: sensory study of coffee-flavoured liqueur from spent coffee grounds
[Poster]
Masino, F.; Montevecchi, G.; Calvini, R.; Foca, G.; Antonelli, A.
abstract
2019
- Data fusion of electronic eye and electronic tongue signals to monitor grape ripening
[Articolo su rivista]
Orlandi, Giorgia; Calvini, Rosalba; Foca, Giorgia; Pigani, Laura; Vasile Simone, Giuseppe; Ulrici, Alessandro
abstract
Two separate artificial sensors, an electronic eye (EE) and an electronic tongue (ET), were recently developed to monitor grape ripening based on the analysis of must. The aim of this research is to exploit the complementary information obtained by means of EE and ET sensing systems using different data fusion strategies, in order to develop an integrated device able to quickly and easily quantify the physico-chemical parameters that are used to assess phenolic ripeness. To this purpose, both low-level and mid-level data fusion approaches were investigated. Partial Least Squares (PLS) regression was applied to the fused data, with the aim of relating the information brought by the two sensors with twelve physico-chemical parameters measured on the must samples by standard analytical methods. The results achieved with mid-level data fusion outperformed those obtained using EE and ET separately, and highlighted that both the artificial sensors have made a significant contribution to the prediction of each one of the considered physico-chemical parameters.
2019
- INDURENTI NON MIGRATORI PER MATERIALI PROTEICI
[Brevetto]
Foca, Giorgia; Leoni, Diego; Lusvardi, Gigliola; Marchetti, Andrea; Roncaglia, Fabrizio; Tassi, Lorenzo
abstract
L’invenzione è relativa ad un processo di preparazione di nuovi materiali copolimerici a base di proteine di origine animale e di origine vegetale, indurite mediante agenti reticolanti a struttura furanica recanti gruppi funzionali carbonilici. Il processo produttivo dei biopolimeri consiste nella preparazione di una soluzione / sospensione delle proteine in ambiente acquoso per ottenere la massima distensione delle micelle, eventualmente miscelate con coloranti o pigmenti finemente dispersi, cui si aggiunge infine un agente cross-linkante di tipo furanico solubilizzato o sospeso in un solvente non acquoso e sotto vigorosa agitazione. I prodotti copolimerici termoindurenti ottenibili presentano caratteristiche meccaniche e prestazionali analoghe a quelle della galalite, e sono privi di qualunque rilascio di VOC.
2019
- Microbiota of sliced cooked ham packaged in modified atmosphere throughout the shelf life: Microbiota of sliced cooked ham in MAP
[Articolo su rivista]
Raimondi, Stefano; Luciani, Rosaria; Sirangelo, Tiziana Maria; Amaretti, Alberto; Leonardi, Alan; Ulrici, Alessandro; Foca, Giorgia; D'Auria, Giuseppe; Moya, Andrés; Zuliani, Véronique; Seibert, Tim Martin; Søltoft-Jensen, Jakob; Rossi, Maddalena
abstract
Fourteen lots of cooked ham in modified atmosphere packaging (CH) were analyzed within a few days from packaging (S) and at the end of the shelf-life (E), after storage at 7 °C to simulate thermal abuse. Five more lots, rejected from the market because spoiled (R), were included in the study. Quality of the products was generally compromised during the shelf life, with only 4 lots remaining unaltered. Analysis of 16S rRNA gene amplicons resulted in 801 OTUs. S samples presented a higher diversity than E and R ones. At the beginning of the shelf life, Proteobacteria and Firmicutes dominated the microbiota, with Acinetobacter, Brochothrix, Carnobacterium, Lactobacillus, Prevotella, Pseudomonas, Psychrobacter, Weissella, Vibrio rumoiensis occurring frequently and/or abundantly. E and R samples were dominated by Firmicutes mostly ascribed to Lactobacillales. It is noteworthy the appearance of abundant Leuconostoc, negligible in S samples, in some E and R samples, while in other LAB were outnumbered by V. rumoiensis or Brochothrix thermosphacta. The microbiota of spoiled and R samples could not be clustered on the basis of specific defects (discoloration, presence of slime, sourness, and swollen packages) or supplemented additives. LAB population of S samples, averaging 2.9 log10(cfu/g), increased to 7.7 log10(cfu/g) in the E and R samples. Dominant cultivable LAB belonged to the species Lactobacillus sakei and Leuconostoc carnosum. The same biotypes ascribed to different species where often found in the corresponding S and R samples, and sometime in different batches provided from the same producer, suggesting a recurrent contamination from the plant of production. Consistently with growth of LAB, initial pH (6.26) dropped to 5.74 in E samples. Volatiles organic compound (VOCs) analysis revealed that ethanol was the major metabolite produced during the shelf life. The profile of volatile compounds got enriched with other molecules (e.g. 2-butanone, ethyl acetate, acetic acid, acetoin, butanoic acid, ethyl ester, butanoic acid, and 2,3-butanediol) mainly ascribed to microbial metabolism.
2019
- Occhio e lingua elettronici ci dicono se l’uva è matura
[Articolo su rivista]
Foca, G.; Calvini, R.; Orlandi, G.; Pigani, L.; Masino, F.; Ulrici, A.
abstract
2018
- Apparato e metodo per determinare parametri fisici e chimici di un campione disomogeneo tramite acquisizione ed elaborazione di immagini a colori del campione
[Brevetto]
Ulrici, Alessandro; Calvini, Rosalba; Foca, Giorgia; Orlandi, Giorgia; Antonelli, Andrea
abstract
L’invenzione consiste in un dispositivo portatile compatto, economico e di semplice utilizzo per il monitoraggio in campo del grado di maturazione fenolica dell’uva mediante l'analisi di immagini acquisite utilizzando uno smartphone.
2018
- Automated quantification of defective maize kernels by means of Multivariate Image Analysis
[Articolo su rivista]
Orlandi, Giorgia; Calvini, Rosalba; Foca, Giorgia; Ulrici, Alessandro
abstract
This article describes the development of a fast and inexpensive method based on digital image analysis for the automated quantification of the percentage of defective maize (%DM). Defective kernels tend to foster high levels of mycotoxins like Deoxynivalenol (DON), which represents a risk for the health of humans and of farm animals. In this work, 332 RGB images of 83 mixtures containing different amounts of defective maize kernels were acquired using a digital camera. The mixtures were also analysed with a commercial ELISA test kit to determine their concentration of DON, that resulted highly correlated with the amount of defective kernels. Each image was then converted into a signal, named colourgram, which codifies its colour-related information content. The colourgrams were firstly explored using Principal Component Analysis. Then, calibration models of the %DM values were developed using Partial Least Squares (PLS) and interval PLS. The best interval PLS model allowed to predict the %DM values of external test set samples with a root mean square error value equal to 2.6%. Based on the output of this model it was also possible to highlight the defective-maize areas within the images, confirming the significance of the proposed approach. (C) 2017 Elsevier Ltd. All rights reserved.
2018
- Cimice Asiatica: fitofago chiave in Pianura Padana
[Articolo su rivista]
Maistrello, L.; Costi, E.; Bortolini, S.; Macavei, L.; Foca, G.; Ulrici, A.; Vaccari, G.; Caruso, S.; Bortolotti, P. P.; Nannini, R.; Fornaciari, M.; Casoli, L.; Mazzoli, G. L.; Dioli, P.
abstract
Halyomorpha halys a soli due anni dalla sua scoperta ufficiale in Italia nel 2012 era già la specie predominante tra gli eterotteri, oggi è l’insetto chiave dei frutteti. I bordi dei frutteti e le siepi sono i luoghi dove si è registrata la maggiore presenza. Lo studio della sua biologia permetterà di elaborare opportune strategie di difesa integrata, comprendente anche la gestione delle fasce perimetrali
2018
- Developmentof a classification algorithm for efficient handling of multiple classes in sorting systems based on hyperspectral imaging
[Articolo su rivista]
Calvini, Rosalba; Orlandi, Giorgia; Foca, Giorgia; Ulrici, Alessandro
abstract
When dealing with practical applications of hyperspectral imaging, the development of efficient, fast and flexible classification algorithms is of the utmost importance. Indeed, the optimal classification method should be able, in a reasonable time, to maximise the separation between the classes of interest and, at the same time, to correctly reject possible outlier samples. To this aim, a new extension of Partial Least Squares Discriminant Analysis (PLS-DA), namely Soft PLS-DA, has been implemented. The basic engine of Soft PLS-DA is the same as PLS-DA, but class assignment is subjected to some additional criteria which allow samples not belonging to the target classes to be identified and rejected. The proposed approach was tested on a real case study of plastic waste sorting based on near infrared hyperspectral imaging. Household plastic waste objects made of the six recyclable plastic polymers commonly used for packaging were collected and imaged using a hyperspectral camera mounted on an industrial sorting system. In addition, paper and not recyclable plastics were also considered as potential foreign materials that are commonly found in plastic waste. For classification purposes, the Soft PLS-DA algorithm was integrated into a hierarchical classification tree for the discrimination of the different plastic polymers. Furthermore, Soft PLS-DA was also coupled with sparse-based variable selection to identify the relevant variables involved in the classification and to speed up the sorting process. The tree-structured classification model was successfully validated both on a test set of representative spectra of each material for a quantitative evaluation, and at the pixel level on a set of hyperspectral images for a qualitative assessment.
2018
- Electronic eye for the prediction of parameters related to grape ripening
[Articolo su rivista]
Orlandi, G.; Calvini, R.; Pigani, L.; Foca, G.; Vasile Simone, G.; Antonelli, A.; Ulrici, A.
abstract
An electronic eye (EE) for fast and easy evaluation of grape phenolic ripening has been developed. For this purpose, berries of different grape varieties were collected at different harvest times from veraison to maturity, then an amount of the derived must was deposited on a white sheet of absorbent paper to obtain a sort of paper chromatography. Thus, RGB images of the must spots were collected using a flatbed scanner and converted into one-dimensional signals, named colourgrams, which codify the colour properties of the images. The dataset of colourgrams was used to build calibration models to relate the colour of the images with the phenolic composition of the samples – determined by reference analytical methods – and therefore to follow the ripening trend. Satisfactory calibration models were obtained for the prediction of the most important parameters related to phenolic ripening of grapes, such as colour index, tonality, total anthocyanins content, malvidin-3-O-glucoside and petunidin-3-O-glucoside.
2018
- L’invasiva Halyomorpha halys è fitofago chiave dei frutteti: risultati del monitoraggio triennale in Emilia.
[Relazione in Atti di Convegno]
Maistrello, L.; Vaccari, G.; Caruso, S.; Costi, E.; Bortolini, S.; Macavei, LAURA IOANA; Foca, G.; Ulrici, A.; Bortolotti, P. P.; Nannini, R.; Casoli, L.; Fornaciari, M.; Mazzoli, G. L.; Dioli, P.
abstract
The brown marmorated stink bug Halyomorpha halys was detected for the first time in Italy in 2012 in the province of Modena. Between 2014 and 2016, a specific monitoring program was carried out in some farms in the provinces of Modena and Reggio Emilia, focusing on pear orchards and the adjacent uncultivated areas (hedges and herbaceous areas) using active techniques to assess the abundance, seasonality and impact of H. halys and other phytophagous Heteroptera. The results showed that just a few years after the first detection, this invasive species largely outperforms all other Heteroptera, and is a seasonal-long pest that caused considerable damage in several farms, with over 50% deformed fruits. The mirids are found mainly in herbaceous areas and crops, while the other phytophagous Heteroptera, only occasionally found in the orchard, are mainly found on the hedges and in other crops. The present survey demonstrates for the first time the great damaging potential of H. halys as a new key pest for fruit orchards in southern Europe.
2018
- Prediction of parameters related to grape ripening by multivariate calibration of voltammetric signals acquired by an electronic tongue
[Articolo su rivista]
Pigani, Laura; VASILE SIMONE, Giuseppe; Foca, Giorgia; Ulrici, Alessandro; Masino, Francesca; Cubillana Aguilera, L.; Calvini, Rosalba; Seeber, Renato
abstract
An electronic tongue (ET) consisting of two voltammetric sensors, namely a poly-ethylendioxythiophene modified
Pt electrode and a sonogel carbon electrode, has been developed aiming at monitoring grape ripening. To
test the effectiveness of device and measurement procedures developed, samples of three varieties of grapes have
been collected from veraison to harvest of the mature grape bunches. The derived musts have been then submitted
to electrochemical investigation using Differential Pulse Voltammetry technique. At the same time,
quantitative determination of specific analytical parameters for the evaluation of technological and phenolic
maturity of each sample has been performed by means of conventional analytical techniques. After a preliminary
inspection by principal component analysis, calibration models were calculated both by partial least squares
(PLS) on the whole signals and by the interval partial least squares (iPLS) variable selection algorithm, in order
to estimate physico-chemical parameters. Calibration models have been obtained both considering separately
the signals of each sensor of the ET, and by proper fusion of the voltammetric data selected from the two sensors
by iPLS. The latter procedure allowed us to check the possible complementarity of the information brought by
the different electrodes. Good predictive models have been obtained for estimation of pH, total acidity, sugar
content, and anthocyanins content. The application of the ET for fast evaluation of grape ripening and of most
suitable harvesting time is proposed.
2018
- Screening of environmental yeasts for the fermentative production of arabitol from lactose and glycerol
[Articolo su rivista]
Amaretti, Alberto; Anfelli, Igor; Foca, Giorgia; Ulrici, Alessandro; Raimondi, Stefano; Leonardi, Alan; Rossi, Maddalena
abstract
Arabitol is a sugar alcohol, stereoisomer to xylitol, which is enlisted among the main target for biorefineries. It can serve as low calorie sweetener and as building block in the enantiopure synthesis of immunosuppressive glycolipids, herbicides, and drugs. Several studies described the fermentative production of arabitol by osmophilic yeasts, cultured with high concentrations of D-glucose. The utilization of cheaper carbon sources, such as glycerol or lactose, is of great interest for biorefinery implementation, but information on exploitation to arabitol production is still scarce. In the present study 50 yeasts belonging to 24 ascomycetous species were screened for the ability to grow and produce arabitol in presence of 80 g/L lactose or glycerol. Production from lactose was generally unsuccessful, the best producer being Kluyveromyces lactis WC 1401 with 0.94 g/L in 160 h. Production from glycerol was promising, with Zygosaccharomyces rouxii WC 1206, Pichia guilliermondii CBS 566, Hansenula anomala WC 1501, and Candida freyschussii ATCC 18737 yielding 3 to 4.5 g/L arabitol, with conversion yield (YP/S) ranging from 11 to 21.7%. Batch growth with high initial glycerol amount (160 g/L) resulted in higher production, with H. anomala WC 1501 yielding 10.0 g/L arabitol (YP/S = 12%) in 160 h. Preliminary bioreactor fermentations with H. anomala WC 1501 indicated that production is not growth associated and revealed some major parameters affecting production, such as the pH and the C:N ratio, that will be the target of following studies aiming at process optimization. Cultivation under controlled oxygenation (DOT = 20%) and pH (= 3.0) resulted in improvement in the performance of H. anomala WC 1501, yielding 16.1 g/L arabitol. Cultivation in a medium with high C:N ratio, lacking inorganic nitrogen yielded 17.1 g/L arabitol. Therefore, this strain was selected for the development of a fed-batch process, aiming to improve the efficiency of the biomass, generated in the growth phase, and increasing the production in the stationary phase.
2018
- Valorisation of chicken manure using insects: Hermetia illucens in the VALORIBIO Project
[Abstract in Atti di Convegno]
Bortolini, S.; Macavei, L. I.; Foca, G.; Ulrici, A.; Bernini, F.; Malferrari, D.; Maistrello, L.
abstract
Over the last decades, the need to manage organic waste in a more efficient way and the need to find new sources of energy have opened new horizons in the use of insects for various purposes (e.g. food, feed, biodiesel).
The ValoriBio project focuses on the valorisation of chicken manure through the use of Hermetia illucens (Diptera, Stratiomyidae), for the production of high quality compost and bioplastics for agricultural purposes.
This study is aimed at the optimisation of the growth parameters of H. illucens on a substrate formed by a mixture of chicken manure, zeolitic tuff (Ca-chabazite), soil improver obtained from pruning shears of urban green, and water. The addition of the Ca-chabazite aims to reduce unpleasant smells, trap the excess of ammonium, and contribute to the formation of a post-breeding substrate which can be used as high-quality compost. The parameters to be maximized were: percentage and maximum average weight of prepupae and percentage of emerged adult flies. Results of a first trial, based on a special cubic model of combined mixture design that tested different ranges of the substrates at 27 and 33°C, recommended the removal of the soil improver and the selection of 27°C as preferred rearing temperature.
A second trial considered different ranges of chicken manure, Ca-chabazite (at two different particle sizes) and water. Results from this experiment allowed the definition of the optimal composition for the substrates to obtain the highest percentage of prepupae (71-74%) and the highest average prepupae weight (0.069-0.072g), and were therefore used to plan the validation test, where chicken manure ranged between 34.5 and 45.0%, Ca-chabazite (larger particle size) between 5.0 and 7.2%, and water between 50.0 and 58.3%. These results are the basis to develop an optimized rearing cycle of H. illucens in an automatized pilot plant for organic waste conversion.
2017
- MICROBIOTA OF FRESH CURED PORK SAUSAGE OVER THE SHELF-LIFE
[Poster]
Luciani, Rosaria; Raimondi, Stefano; Tabanelli, Giulia; Montanari, Chiara; SIRANGELO Tiziana, M.; Amaretti, Alberto; Leonardi, Alan; Ulrici, Alessandro; Foca, Giorgia; Gardini, Fausto; Rossi, Maddalena
abstract
Italian style fresh sausage is a traditional pork food, commonly consumed after cooking. It is a perishable product that over the time can be colonized by spoilage bacteria that render the product inacceptable because of undesirable modifications of sensorial properties, such as appearance, texture, odor, and flavor. Indeed, being fresh meat a matrix with high water activity, slightly acidic pH, and high level of nutrients including glucose, lactic acid, nitrogenous compounds, and amino acids, it allows growth and proliferation of several bacteria.
Temperatures and MAP (Modified Atmosphere Packaging) are the most important extrinsic factors affecting growth of microorganism. Generally fresh sausages are conserved refrigerated in MAP to maintain the red colour of the meat. The refrigeration of raw meat slows down growth of bacteria, allowing selection and blooming of psychrotrophic aerobic and aerotolerant species.
2017
- Monitoring of the invasive Halyomorpha halys, a new key pest of fruit orchards in northern Italy
[Articolo su rivista]
Maistrello, Lara; Vaccari, Giacomo; Caruso, Stefano; Costi, Elena; Bortolini, Sara; Macavei, LAURA IOANA; Foca, Giorgia; Ulrici, Alessandro; Bortolotti, Pier Paolo; Nannini, Roberta; Casoli, Luca; Fornaciari, Massimo; Mazzoli, Gian Lorenzo; Dioli, Paride
abstract
Halyomorpha halys is an invasive polyphagous pest with a high negative impact on fruit orchards and other agricultural crops in the USA. In Italy, it was first detected in 2012 in Emilia Romagna, a northern region that is among the major European tree fruit production areas. A specific monitoring programme using active techniques was carried out in pear orchards and adjacent uncultivated areas between 2014 and 2016 to assess the abundance, seasonality and impact of H. halys and other phytophagous Heteroptera in the field. It emerged that just a few years after first discovery, this invasive species already largely outnumbers all the other Heteroptera and that it is a season-long pest for pear crops. Severe yield losses are reported in different farms, especially on the orchard borders, with more than 50% deformed fruits. Mirids are mostly found in the grassy areas and crops, and the other phytophagous Heteroptera, only occasionally detected in the orchard trees, occur mainly on hedges and other crops. Our survey demonstrates for the first time the great damaging potential of H. halys as a new key pest of orchards in southern Europe. The study also identified the patterns of seasonal abundance of adults and nymphs in the orchards and their uncultivated surroundings, providing baseline data for the development of specific strategies for sustainable management.
2017
- Produzioni castanicole e identità territoriale: parliamone!
[Capitolo/Saggio]
Durante, Caterina; Ferrari, Erika; Foca, Giorgia; Benvenuti, Stefania; Tassi, Lorenzo
abstract
Il capitolo del volume tratta, in forma divulgativa, il problema della tracciabilità merceologica di alcune varietà castanicole della provincia di Modena. La caratterizzazione chimico-analitica effettuata su diversi campioni rappresentativi di altrettante cultivar geograficamente localizzate, consente la eventuale discriminazione delle varietà medesime. Il volume editato da Artestampa, appartiene ad una Collana che si sviluppa nel tempo, con l'obiettivo di far conoscere, descrivere e rappresentare alcune eccellenze agroalimentari e produzioni specifiche dei territori modenesi.
2016
- Data dimensionality reduction and data fusion for fast characterization of green coffee samples using hyperspectral sensors
[Articolo su rivista]
Calvini, Rosalba; Foca, Giorgia; Ulrici, Alessandro
abstract
Hyperspectral sensors represent a powerful tool for chemical mapping of solid-state samples, since they provide spectral information localized in the image domain in very short times and without the need of sample pretreatment. However, due to the large data size of each hyperspectral image, data dimensionality reduction (DR) is necessary in order to develop hyperspectral sensors for real-time monitoring of large sets of samples with different characteristics. In particular, in this work, we focused on DR methods to convert the three-dimensional data array corresponding to each hyperspectral image into a one-dimensional signal (1D-DR), which retains spectral and/or spatial information. In this way, large datasets of hyperspectral images can be converted into matrices of signals, which in turn can be easily processed using suitable multivariate statistical methods. Obviously, different 1D-DR methods highlight different aspects of the hyperspectral image dataset. Therefore, in order to investigate their advantages and disadvantages, in this work, we compared three different 1D-DR methods: average spectrum (AS), single space hyperspectrogram (SSH) and common space hyperspectrogram (CSH). In particular, we have considered 370 NIR-hyperspectral images of a set of green coffee samples, and the three 1D-DR methods were tested for their effectiveness in sensor fault detection, data structure exploration and sample classification according to coffee variety and to coffee processing method. Principal component analysis and partial least squares-discriminant analysis were used to compare the three separate DR methods. Furthermore, low-level and mid-level data fusion was also employed to test the advantages of using AS, SSH and CSH altogether. [Figure not available: see fulltext.]
2016
- Determination of polyphenol content and colour index in wines through PEDOT-modified electrodes
[Articolo su rivista]
Pigani, Laura; Rioli, Cristina; Foca, Giorgia; Ulrici, Alessandro; Seeber, Renato; Terzi, Fabio; Zanardi, Chiara
abstract
Poly(3,4-ethylenedioxythiophene)-modified electrodes have been used for the estimation of the polyphenolic content and of the colour index of different samples of wines. Synthetic wine solutions, prepared with different amount of oenocyanins, have been analysed spectrophotometrically and electrochemically in order to find a correlation between the total polyphenolic content or colour index and the current peak. The regression curves obtained have been used as external calibration lines for the analysis of several commercial wines, ranging from white to dark red wines. In this way, a rapid estimation of the total polyphenolic content and of the colour index may be accomplished from a single voltammetric measurement. Furthermore, principal component analysis has also been used to evaluate the effect of total polyphenolic content and colour index on the whole voltammetric signals within a selected potential range, both for the synthetic solutions and for the commercial products.
2016
- Electronic tongue and electronic eye for monitoring maturation level of grapes
[Abstract in Atti di Convegno]
Pigani, L.; Vasile Simone, G.; Foca, G.; Ulrici, A.; Masino, F.; Seeber, R.
abstract
2016
- Imaging techniques: A rapid tool for food analysis
[Relazione in Atti di Convegno]
Foca, Giorgia
abstract
In the last few decades there has been a continuous increase of industrial applications of image analysis-based techniques, thanks to their ability to monitor quickly and inexpensively both products and processes, and with the advantage of being non-invasive. When performing image analysis, chemometrics is an essential tool for different aims, including data reduction or compression, extraction of useful information, and efficient representation of the most chemically-meaningful features of the analysed scene.
2016
- Iodine Value and Fatty Acids Determination on Pig Fat Samples by FT-NIR Spectroscopy: Benefits of Variable Selection in the Perspective of Industrial Applications
[Articolo su rivista]
Foca, Giorgia; Ferrari, Carlotta; Ulrici, Alessandro; Ielo, Maria Cristina; Minelli, Giovanna; LO FIEGO, Domenico Pietro
abstract
In this work, FT-NIR spectroscopy was employed to determine iodine value (IV) and fatty acids (FA) content of pig fat samples, through the combined use of signal preprocessing, multivariate calibration, and variable selection methods. In particular, the main focus was on the use of variable selection methods, both in order to improve the predictive performance of the calibration models, and to identify relevant wavelengths that could be subsequently used for the development of simple, fast, and cheap hand-held devices, able to measure IV and FA content directly on the fat without the need of any sample pretreatment. Firstly, for each property of interest, partial least squares (PLS) multivariate calibration models were calculated considering the whole spectral range and testing different signal preprocessing methods. Then, once chosen the optimal signal preprocessing method, a two-step variable selection procedure was applied. In the first step, the interval-PLS variable selection algorithm was used to calculate a set of calibration models, whose outcomes were considered altogether in the second step, in order to select the optimal calibration model. The variable selection procedure allowed to lower the number of spectral variables retained by the model, and often led to an increase of the performance in prediction of the external test set samples.
2016
- Preliminary analysis of RGB images for the identification of defective maize kernels
[Relazione in Atti di Convegno]
Orlandi, Giorgia; Calvini, Rosalba; Foca, Giorgia; Ulrici, Alessandro
abstract
In order to investigate the effectiveness of multivariate image analysis for the evaluation of maize defects, RGB images of maize samples containing different percentages of defective kernels were acquired and then converted into colourgrams, i.e., signals codifying colour-related features. Multivariate analysis of the colourgrams matrix showed a distribution of the acquired samples according to the amount of defective kernels.
2016
- The potential of spectral and hyperspectral-imaging techniques for bacterial detection in food: A case study on lactic acid bacteria
[Articolo su rivista]
Foca, Giorgia; Ferrari, Carlotta; Ulrici, Alessandro; Sciutto, Giorgia; Prati, Silvia; Morandi, Stefano; Brasca, Milena; Lavermicocca, Paola; Lanteri, Silvia; Oliveri, Paolo
abstract
Official methods for the detection of bacteria are based on culture techniques. These methods have limitations such as time consumption, cost, detection limits and the impossibility to analyse a large number of samples. For these reasons, the development of rapid, low-cost and non-destructive analytical methods is a task of growing interest. In the present study, the capability of spectral and hyperspectral techniques to detect bacterial surface contamination was investigated preliminarily on gel cultures, and subsequently on sliced cooked ham. In more detail, two species of lactic acid bacteria (LAB) were considered, namely Lactobacillus curvatus and Lactobacillus sakei, both of which are responsible for common alterations in sliced cooked ham. Three techniques were investigated, with different equipment, respectively: a macroscopic hyperspectral scanner operating in the NIR (10,470-5880 cm-1) region, a FT-NIR spectrophotometer equipped with a transmission arm as the sampling tool, working in the 12,500-5800 cm-1 region, and a FT-MIR microscopy operating in the 4000-675 cm-1 region. Multivariate exploratory data analysis, in particular principal component analysis (PCA), was applied in order to extract useful information from original data and from hyperspectrograms. The results obtained demonstrate that the spectroscopic and imaging techniques investigated can represent an effective and sensitive tool to detect surface bacterial contamination in samples and, in particular, to recognise species to which bacteria belong.
2015
- Characterization of common wheat flours (Triticum aestivum L.) through multivariate analysis of conventional rheological parameters and gluten peak test indices
[Articolo su rivista]
Marti, Alessandra; Ulrici, Alessandro; Foca, Giorgia; Quaglia, Lucio; Pagani, Maria Ambrogina
abstract
The GlutoPeak consists in high speed mixing of a small amount of wheat flour (<10 g) added with water, and in registering a torque vs. time curve in a very short time (<10 min). Peak torque, peak maximum time, and energy values are calculated from the curve, and used to estimate the aggregation behavior of gluten. The information brought by the GlutoPeak indices is still difficult to interpret correctly, also in relation to the conventional approaches in the field of cereal science. A multivariate approach was used to investigate the correlations existing between the GlutoPeak indices and the conventional rheological parameters. 120 wheat flours- different for protein, dough stability, extensibility, tenacity, and strength, and end-uses - were analyzed using the GlutoPeak and conventional instrumentation. The parameters were subjected to a data exploration step through Principal Component Analysis. Then, multivariate Partial Least Squares Regression (PLSR) models were developed using the GlutoPeak indices to predict the conventional parameters. The values of the squared correlation coefficients in prediction of an external test set showed that acceptable to good results (0.61 ≤ R2PRED ≤ 0.96) were obtained for the prediction of 18 out of the 26 conventional parameters here considered.
2015
- Fast exploration and classification of large hyperspectral image datasets for early bruise detection on apples
[Articolo su rivista]
Ferrari, Carlotta; Foca, Giorgia; Calvini, Rosalba; Ulrici, Alessandro
abstract
Hyperspectral imaging allows to easily acquire tens of thousands of spectra for a single sample in few seconds; though valuable, this data-richness poses many problems due to the difficulty of handling a representative amount of samples altogether. For this reason, we recently proposed an approach based on the idea of reducing each image into a one-dimensional signal, named hyperspectrogram, which accounts both for spatial and for spectral information. In this manner, a dataset of hyperspectral images can be easily and quickly converted into a set of signals (2D data matrix), which in turn can be analyzed using classical chemometric techniques. In this work, the hyperspectrograms obtained from a dataset of 800 NIR-hyperspectral images of two different apple varieties were used to discriminate bruised from sound apples using iPLS-DA as variable selection algorithm, which allowed to efficiently detect the presence of bruises. Moreover, the reconstruction as images of the selected variables confirmed that the automated procedure led to the exact identification of the spatial features related to the onset and to the subsequent evolution with time of the bruise defect.
2014
- Algorithms and strategies for extracting optimal information from chemical sensing systems
[Relazione in Atti di Convegno]
Ulrici, Alessandro; Foca, Giorgia; Seeber, Renato
abstract
The output signals of chemical sensing systems, i.e. of sensors used to detect chemical quantities, typically consist of a complex superimposition of three different contributions: useful information, non relevant (but systematic) variations, and noise. For an efficient extraction of the highest possible amount of useful information, the application of multivariate methods is definitely more effective than commonly used univariate approaches. However, multivariate methods themselves could not allow the extraction of the whole information content of interest. The goal may be achieved by an efficient use of additional strategies, suitable to consider other aspects such as signal shape, time-evolution of a given sensor response or interactions among signals measured with different sensors. The performance of the sensor(s) is improved and the final output may consist of an optimized set of parameter values.
2014
- Applicazione della spettroscopia FT-NIR per la determinazione degli acidi grassi e del numero di iodio in campioni di grasso suino prelevati da diversi strati sottocutanei
[Abstract in Atti di Convegno]
Foca, Giorgia; Ulrici, Alessandro; Ferrari, Carlotta; Calvini, Rosalba; Ielo, Maria Cristina; Minelli, Giovanna; LO FIEGO, Domenico Pietro
abstract
La qualità tecnologica e organolettica del grasso suino può essere stimata mediante analisi
chimiche quali il numero di iodio e la determinazione gascromatografica della composizione in
acidi grassi. Tali metodi, tuttavia, sono lunghi, costosi, dannosi per l’ambiente e non sono adatti per
seguire un processo in tempo reale.
In questo lavoro, abbiamo valutato la potenzialità della spettroscopia NIR, accoppiata a
tecniche chemiometriche appropriate, per predire il numero di iodio e la composizione in acidi
grassi di campioni di grasso suino estratti da due diversi strati sottocutanei1, partendo da misure di
riferimento acquisite con i metodi tradizionali, analisi di Wijs e analisi gascromatografica. Gli
spettri NIR sono stati acquisiti utilizzando due diversi accessori: sfera integratrice e sonda a fibre
ottiche. Riguardo alle tecniche chemiometriche, abbiamo utilizzato PCA come metodo di analisi
esplorativa, che ha consentito di eliminare i campioni outlier, quindi abbiamo costruito diversi
modelli di calibrazione mediante PLS. Successivamente, abbiamo applicato agli spettri anche un
metodo di calibrazione con selezione di variabili, iPLS. Poiché non è possibile sapere a priori quale
sia il miglior pretrattamento per estrarre l’informazione utile dagli spettri, sono state confrontate
diverse combinazioni di pretrattamenti per ottenere il miglior modello.
Concludendo, abbiamo discusso i modelli ottenuti al fine di: i) individuare le condizioni
operative (considerando sia le condizioni strumentali che le procedure chemiometriche utilizzate)
che hanno portato all’ottenimento dei modelli migliori; ii) individuare le regioni spettrali più
informative ai fini della calibrazione; iii) ottenere una migliore comprensione delle caratteristiche
chimiche del grasso proveniente dai due diversi strati sottocutanei; iv) comprendere quali acidi
grassi possano effettivamente essere quantificati con la spettroscopia NIR in un processo reale.
2014
- Classification of Arabica and Robusta coffee samples subjected to different technological treatments using various image analysis methods
[Abstract in Atti di Convegno]
Calvini, Rosalba; Foca, Giorgia; Bellucci, L.; Ulrici, Alessandro
abstract
Coffee varietal differentiation based on NIR spectroscopy has been widely investigated in the last
20 years [1-3]. In this work, we have applied hyperspectral imaging in the NIR range (900-1700
nm) for the classification of Arabica and Robusta coffee varieties, considering coffee beans
subjected to different processing methods, i.e., the so-called dry method (to produce natural coffee),
wet method (to produce washed coffee) and a somewhat intermediate processing method, referred to
as polishing method (to produce polished coffee).
PCA has been used as an exploratory technique both on the image mean spectra and on the
hyperspectrograms obtained from the images. The hyperspectrograms are built by compressing the
useful information contained in each hyperspectral image into a signal composed by the frequency
distribution curves of quantities calculated by PCA [4]. This procedure allows to compress the
information conveyed by the hyperspectral images, maintaining at the same time both spatial- and
spectral-related features.
The PCA models obtained showed a clear clustering of Arabica and Robusta samples, whereas,
considering the technological treatment, the polished coffee samples are clearly distinguishable
from the others, while natural and washed coffee samples are quite superimposed.
Image mean spectra and hyperspectrograms were then subjected to PLS-DA classification after
preprocessing using SNV followed by meancentering or meancentering only. Concerning the
discrimination of coffee samples between Arabica and Robusta categories, the same value of
classification efficiency in prediction (EFFPRED = 86.3%) has been obtained considering both the
mean spectra and the hyperspectrograms. After forward iPLS-DA variable selection, EFFPRED
increased up to 98.6% for models calculated using the mean spectra and up to 100% for the models
calculated using the hyperspectrograms.
As for the discrimination of the coffee samples into the three natural, polished and washed
processing categories, the PLS-DA models calculated using mean spectra led to EFFPRED values
equal to 81.1%, 95.7% and 49.8%, respectively, while the PLS-DA models calculated using
hyperspectrograms led to EFFPRED values equal to 94.7%, 100% and 92.4%, respectively. In this
case, iPLS-DA variable selection led to an increase of the performances of the model calculated on
mean spectra (EFFPRED equal to 82.9%, 98.6% and 86.5%, respectively) and to a decrease of the
performances of the model calculated using hyperspectrograms (EFFPRED equal to 82.9%, 89.3%
and 86.5%, respectively).
2014
- Data reduction di immagini iperspettrali: applicazione a problemi di classificazione
[Abstract in Atti di Convegno]
Calvini, Rosalba; Ferrari, Carlotta; Foca, Giorgia; Ulrici, Alessandro
abstract
L'imaging iperspettrale (HSI) consente di acquisire in pochi secondi ipercubi di grandi
dimensioni, composti da milioni di spettri, che corrispondono a file spesso più grandi di 50 MB.
Questa ricchezza di dati rappresenta il principale vantaggio dell’HSI, sebbene causi seri problemi
per la gestione dei dati, tali da complicare lo sviluppo di applicazioni industriali efficienti per il
controllo in linea. Il nostro gruppo di ricerca ha recentemente proposto un’alternativa1 per trattare
dataset composti da decine o centinaia di immagini iperspettrali, che consiste nel convertire ogni
immagine iperspettrale in un segnale, chiamato iperspettrogramma, costruito in modo da
considerare sia l’informazione di natura spaziale che spettrale. Risulta così possibile trasformare
dataset composti da un elevato numero di immagini iperspettrali in matrici bidimensionali di
iperspettrogrammi, che a loro volta possono essere analizzate utilizzando i più comuni metodi
chemiometrici quali PCA, PLS o PLS-DA.
In questo contesto, presentiamo due applicazioni degli iperspettrogrammi per la soluzione di
problemi di classificazione. Una prima applicazione riguarda l'individuazione precoce di difetti
superficiali in diverse varietà di mele, con particolare attenzione ai campioni in cui il difetto non
risulta apprezzabile ad occhio nudo. Le 800 immagini iperspettrali acquisite sono state convertite in
iperspettrogrammi permettendo così la riduzione delle dimensioni del dataset da 18.6 GB a 4.7 MB.
Inoltre la selezione di variabili mediante iPLS-DA ha permesso di ridurre ulteriormente le
dimensioni del dataset e identificare le regioni più rilevanti nel segnale. Il migliore modello iPLSDA,
calcolato utilizzando solo 30 variabili delle 1200 iniziali, ha portato ad un valore di efficienza
in predizione sul test set esterno pari a 89.6%. Una seconda applicazione riguarda la classificazione
di caffè verde appartenente a diverse tipologie: Arabica e Robusta. Prove preliminari hanno
mostrato come la classificazione mediante PLS-DA effettuata sugli iperspettrogrammi ha portato ad
un valore di efficienza in predizione del 98.3%.
2014
- Detection of contamination by aflatoxins on apricot kernels using NIR-hyperspectral imaging
[Abstract in Atti di Convegno]
Calvini, Rosalba; Zivoli, R.; Piemontese, L.; Ferrari, Carlotta; Foca, Giorgia; Perrone, G.; Ulrici, Alessandro; Solfrizzo, M.
abstract
Aflatoxins can be found as contaminants in a wide range of foods, such as nuts, cereals, dried fruits
and milk. Due to their hepatotoxic and carcinogenic effects, the maximum allowed concentration of
aflatoxins is nowadays regulated in many countries, with levels up to 50 μg/kg.
In routine analysis, the main methods used to determine aflatoxins are based on high-performance
liquid chromatography (HPLC) and enzyme-linked immunosorbent assay (ELISA) [1]. Despite the
very high sensitivity of these methods, they are destructive, expensive, time consuming and not
appropriate for real time control, e.g., online.
Consequently, the development of fast, non destructive and economic methods for aflatoxins
detection and monitoring in food industry is becoming more and more important.
Our studies showed that manual sorting of dark or spotted apricot kernels removed 97.3-99.5% of
total aflatoxins [2]. However, discolored seeds could be visually identified only after removing the
skins from each seed by means of a time-consuming operation.
For these reasons, in this work we investigated the possibility to use NIR–HSI for the fast and nondestructive
automated identification of aflatoxin contaminated unpeeled apricot kernels.
On the whole 9 hyperspectral images, each one containing 48 kernels, were acquired in the 900-
1700 nm range. After image acquisition, the kernels were peeled to identify the dark or spotted
kernels and subjected to HPLC analysis for AFB1 quantification.
Classification models were then calculated on a training set of NIR spectra extracted from a
representative number of non-contaminated and dark seeds, selected on 5 images on the basis of
HPLC analysis results as well as of the visual evaluation of the peeled kernels. The remaining 4
images were instead used as independent test set for model validation. Since dark seeds were found
to have a higher concentration of AFB1 than spotted seeds, the latter ones were not included in the
training set.
Different iPLS-DA classification models, built using different signal preprocessing methods and
different interval size values, were then evaluated in terms of classification efficiency in cross
validation of the training set pixels, in order to select the optimal conditions. The results were
reported under the form of predicted probability maps, and for each single kernel the contamination
was estimated as the percentage of pixels assigned to the “contaminated” class by the iPLS-DA
model.
2014
- Exploration of datasets of hyperspectral images
[Abstract in Atti di Convegno]
Ferrari, Carlotta; Calvini, Rosalba; Foca, Giorgia; Ulrici, Alessandro
abstract
Hyperspectral images of size usually greater than 50 MB can be easily acquired in very short times,
generally without the need of sample pretreatment. While Multivariate Image Analysis (MIA) tools
can be efficiently used for the exploration of single hyperspectral images or of groups composed by
a limited number (say up to 10) of merged images, the exploration of datasets composed by a large
number (>10) of images is less straightforward. However, a representative sampling of a large
number of specimens is frequently required to correctly estimate both intra- and inter-sample
variability. This implies the acquisition of datasets composed by a large number of hyperspectral
images and of several GB in size, especially in those cases where only one or a few samples can be
included in a single image scene. In this context, the exploration of the dataset by applying MIA to
single images or to subgroups of merged images does not allow to gain a global overview of the
entire dataset variability and to properly highlight the possible presence of outliers, clusters and/or
trends. A fast procedure which can be adopted to deal with this issue consists in computing the
average spectrum of each image, to build a matrix of average spectra of the analyzed hyperspectral
images. Although this approach leads sometimes to satisfactory results (especially when dealing
with homogeneous materials), the information related to spatial variability is lost, and the
hyperspectral image data are turned into “common” (i.e., not spatially resolved) spectral data. By
averaging spectra, for example, the useful information related to the presence of a defect localized
in a relatively narrow image area could be diluted within the massive amount of other “well
behaving” pixels, becoming no longer detectable.
Aiming to develop a fast and easy-to-use tool able to facilitate the exploration of large datasets of
hyperspectral images while maintaining both spectral- and spatial-related information of the
original images, we have proposed an approach which consists in automatically converting each
hyperspectral image into a signal named hyperspectrogram [1]. Essentially, the hyperspectrogram
can be viewed as a fingerprint containing the relevant information brought by the original
hyperspectral image, and is composed by a first part accounting for the spatial information and by a
second part accounting for the spectral information. By representing each image with a vector of
few hundreds of points, this procedure enables to compare simultaneously up to hundreds of images
by means of common multivariate analysis methods, such as PCA.
In order to facilitate the exploration of datasets of hyperspectral images through hyperspectrograms,
we have recently developed a Matlab Graphical User Interface (GUI), which easily allows
calculation and visualization of hyperspectrograms, exploration of the dataset and visualization of
the features of interest contained within each single sample directly in the original image domain.
2013
- Classification of pig fat samples from different subcutaneous layers by means of fast and non-destructive analytical techniques
[Articolo su rivista]
Foca, Giorgia; Salvo, Davide; Cino, Adelaide; Ferrari, Carlotta; Lo Fiego, Domenico Pietro; Minelli, Giovanna; Ulrici, Alessandro
abstract
In the meat industry the fat portions coming from two different subcutaneous layers, i.e., inner and outer, are destined to the manufacturing of different products, hence the availability of cheap, rapid and affordable methods for the characterization of the overall fat quality is desirable. In this work the potential usefulness of three techniques, i.e. tristimulus colorimetry, FT-NIR spectroscopy and NIR hyperspectral imaging, were tested to rapidly discriminate fat samples coming from the two different layers. To this aim, various multivariate classificationmethodswere used, also including signal processing and feature selection techniques. The classification efficiency in prediction obtained using colorimetric data did not reach excellent results (78.1%); conversely, the NIR-based spectroscopic methods gavemuchmore satisfactorymodels, since they allowed to reach a prediction efficiency higher than 95%. In general, the samples of the outer layer showed a high degree of variability with respect to the samples of the inner layer. This is probably due to a greater variability of the outer samples in terms of fatty acid composition and water amount.
2013
- Efficient chemometric strategies for PET–PLA discrimination in recycling plants using hyperspectral imaging
[Articolo su rivista]
Ulrici, Alessandro; S., Serranti; Ferrari, Carlotta; D., Cesare; Foca, Giorgia; G., Bonifazi
abstract
The effectiveness of Hyperspectral imaging (HSI) in the near infrared (NIR) range (1000–1700 nm) was evaluated to discriminate PET (polyethylene terephthalate) from PLA (poly(lactic acid)), two polymers commonly utilized as packaging for foodstuff, in order to improve their further recycling process. An internal calibration based on five reference materials was initially used to eliminate the variability existing among images, then Partial Least Squares-Discriminant Analysis (PLS-DA) was used to distinguish and classify the three classes, i.e., background, PET and PLA. Considering the high amount of data conveyed by the training image, the PLS-DA models were also calculated using as training set a reduced version of the original matrix, with the twofold aim to reduce the computational time and to deal with an equal number of spectra for each class, independently from the initial selected areas. A variable selection procedure by means of iPLS-DA was also applied on both the whole and the reduced matrix. The results obtained on the reduced matrix using only six variables provided a prediction efficiency higher than 98%. Moreover, the possibility to recognize PET and PLA polymers by HSI in the NIR range was further confirmed by using Multivariate Curve Resolution (MCR) as an alternative approach, which also allowed to evaluate the effect of thickness of the transparent plastic samples.
2013
- Handling large datasets of hyperspectral images: Reducing data size without loss of useful information
[Articolo su rivista]
Ferrari, Carlotta; Foca, Giorgia; Ulrici, Alessandro
abstract
HyperSpectral Imaging (HSI) is gaining increasing interest in the field of analytical chemistry, since this fast and non-destructive technique allows one to easily acquire a large amount of spectral and spatial information on a wide number of samples in very short times. However, the large size of hyperspectral image data often limits the possible uses of this technique, due to the difficulty of evaluating many samples altogether, for example when one needs to consider a representative number of samples for the implementation of on-line applications. In order to solve this problem, we propose a novel chemometric strategy aimed to significantly reduce the dataset size, which allows to analyse in a completely automated way from tens up to hundreds of hyperspectral images altogether, without losing neither spectral nor spatial information. The approach essentially consists in compressing each hyperspectral image into a signal, named hyperspectrogram, which is created by combining several quantities obtained by applying PCA to each single hyperspectral image. Hyperspectrograms can then be used as a compact set of descriptors and subjected to blind analysis techniques. Moreover, a further improvement of both data compression and calibration/classification performances can be achieved by applying proper variable selection methods to the hyperspectrograms. A visual evaluation of the correctness of the choices made by the algorithm can be obtained by representing the selected features back into the original image domain. Likewise, the interpretation of the chemical information underlying the selected regions of the hyperspectrograms related to the loadings is enabled by projecting them in the original spectral domain. Examples of applications of the hyperspectrogram-based approach to hyperspectral images of food samples in the NIR range (1000-1700 nm) and in the Vis-NIR range (400-1000 nm), facing a calibration and a defect detection issue respectively, demonstrate the effectiveness of the proposed approach.
2013
- Soils sampling planning in traceability studies by means of experimental design approaches
[Articolo su rivista]
Totaro, Sara; Coratza, Paola; Durante, Caterina; Foca, Giorgia; LI VIGNI, Mario; Marchetti, Andrea; Marchetti, Mauro; Cocchi, Marina
abstract
The present research is part of a project dealing with the development of analytical methodologies mainly based on primary indicators, such as isotopic ratio of radiogenic elements, for theauthenticity and geographical traceability of oenological food, typical of the Modena district. In particular, considering the objective of establishing a food-territory link by means of these analytical indicators, it is straightforward how the representativeness of sampling for both food and soils, covers a primary role in the robustness of the traceability models. With the aim of building traceability models for oenological matrices, the issue of selecting a set of representative, informative and different soil samples is tackled. In this case, the goal is not obtaining a set of soil samples uniformly spanning the territory to be investigated, since the planning of a punctual sampling extended in the whole district of Modena is not feasible considering the total number of samples affordable by the study, but rather to choose a representative set of vineyards were to locate the soil samples. Thus, all the vineyard-registered producers of the district of Modena were considered and different variables (geological features of the soils, winegrowing coverage, grapes varieties, yearly productions of the farms, etc.) were handled with Experimental Design (DoE) techniques in order to simultaneously taking into account the different kinds of information for achieving a sustainable and rational site sampling. In particular, D-Optimal Onion design was chosen since it is widely used for mapping and planning purposes, hence it consents to achieve the maximum coverage and uniformity of the selected samples in the whole domain. An efficient mapping of geographical region has been obtained ensuring coverage of farms characterized by main grape production and insisting on soils with different geological features.
2012
- A feature selection strategy for the analysis of spectra from a photoacoustic sensing system
[Relazione in Atti di Convegno]
Ulrici, Alessandro; Seeber, Renato; Calderisi, Marco; Foca, Giorgia; Juho, Uotila; Mathieu, Carras; Anna Maria, Fiorello
abstract
In the frame of the EU project CUSTOM, a new sensor system for the detection of drug precursors in gaseous samples is being developed, which also includes an External Cavity-Quantum Cascade Laser Photo Acoustic Sensor (ECQCLPAS). In order to define the characteristics of the laser source, the optimal wavenumbers within the most effective 200 cm -1 range in the mid-infrared region must be identified, in order to lead to optimal detection of the drug precursor molecules in presence of interfering species and of variable composition of the surrounding atmosphere. To this aim, based on simulations made with FT-IR spectra taken from literature, a complex multivariate analysis strategy has been developed to select the optimal wavenumbers. Firstly, the synergistic use of Experimental Design and of Signal Processing techniques led to a dataset of 5000 simulated spectra of mixtures of 33 different gases (including the 4 target molecules). After a preselection, devoted to disregard noisy regions due to small interfering molecules, the simulated mixtures were then used to select the optimal wavenumber range, by maximizing the classification efficiency, as estimated by Partial Least Squares - Discriminant Analysis. A moving window 200 cm -1 wide was used for this purpose. Finally, the optimal wavenumber values were identified within the selected range, using a feature selection approach based on Genetic Algorithms and on resampling. The work made will be relatively easily turned to the spectra actually recorded with the newly developed EC-QCLPAS instrument. Furthermore, the proposed approach allows progressive adaptation of the spectral dataset to real situations, even accounting for specific, different environments.
2012
- Automated identification and visualization of food defects using RGB imaging: Application to the detection of red skin defect of raw hams
[Articolo su rivista]
Ulrici, Alessandro; Foca, Giorgia; Ielo, Maria Cristina; Volpelli, Luisa Antonella; LO FIEGO, Domenico Pietro
abstract
Colourgrams are signals that codify the colour-related information content of a Red-Green-Blue (RGB) image, and which can be elaborated by means of proper multivariate analysis/feature selection techniques to easily identify those image features that are more useful to solve a specific problem. The reconstruction of the selected features as segmented images allows to evaluate in a critical manner the choices made automatically by the algorithm. In the present paper colourgrams are used for the detection of the red skin defect of raw hams, in order to render more objective and transferable the evaluation usually made by expert assessors. To this aim, after a preselection of 95 raw ham samples by a panel test, the corresponding RGB images were converted into colourgrams, which in turn were used to build classification models using Partial Least Squares-Discriminant Analysis (PLS-DA) and a Wavelet Packet Transform-based feature selection/classification algorithm (WPTER). Feature selection allowed to discriminate the defective samples using only three variables, with a Classification Efficiency in prediction of an external test set equal to 97.8%. The reconstruction of the samples images using only the selected features confirmed the reliability of the obtained classification model.
Industrial Relevance: The evaluation of pig thighs is currently carried out by subjective methods, i.e. expert, long-trained personnel is needed to detect the presence or absence of defects. The method presented here would allow to uniform and drastically shorten the time needed for evaluation, and to avoid the main problems connected with human evaluation, i.e., subjectivity, possible unreliability, non-transferability and difficulty to collect historical data. Furthermore, it might represent a first step for setting up a comprehensive method of evaluation, aiming to take into account also other types of defects of raw hams destined to seasoning. More in general, thanks to its flexibility, this approach could be also successfully applied for the detection of other types of aspect-related features, even to monitor different kinds of products.
2011
- Adulteration of the anthocyanin content of red wines: perspectives for authentication by FT-NIR and 1H NMR spectroscopies
[Articolo su rivista]
Ferrari, Erika; Foca, Giorgia; M., Vignali; Tassi, Lorenzo; Ulrici, Alessandro
abstract
In the Italian oenological industry, the regular practice used to naturally increase the colour of red wines consists in blending them with a wine very rich in anthocyanins, namely Rossissimo. In the Asian market, on the other hand, anthocyanins extracted by black rice are frequently used as correctors for wine colour. This practice does not produce negative effects on health; however, in many countries, it is considered as a food adulteration. The present study is therefore aimed to discriminate wines containing anthocyanins originated from black rice and grapevine by using reliable spectroscopic techniques requiring minimum sample preparation. Two series of samples have been prepared from five original wines, that were added with different amounts of Rossissimo or of black rice anthocyanins solution, until the desired Colour Index was reached. The samples have been analysed by FT-NIR and 1H NMR spectroscopies and the resulting spectra matrices were subjected to multivariate classification. Initially, PLS-DA was used as classification method, then also variable selection/classification methods were applied, i.e. iPLS-DA and WILMA-D. The classification with variable selection of NIR spectra permitted to classify the test set samples with an efficiency of about 70%. Probably these not excellent performances are due to the matrix effect, together with the lack of sensitivity of NIR with respect to minor compounds. On the contrary, very satisfactory results were obtained on NMR spectra in the aromatic region between 6.5÷9.5 ppm. The classification method based on wavelet-based variables selection, permitted to reach an efficiency in validation greater than 95%. Finally, 2D correlation analysis was applied to FT-NIR and 1H NMR matrices, in order to recognise the spectral zones bringing the same chemical information.
2011
- Minimisation of instrumental noise in the acquisitionof FT-NIR spectra of bread wheat using experimental designand signal processing techniques
[Articolo su rivista]
Foca, Giorgia; Ferrari, Carlotta; N., Sinelli; M., Mariotti; M., Lucisano; R., Caramanico; Ulrici, Alessandro
abstract
Spectral resolution (R) and number of repeatedscans (S) have a significant effect on the S/N ratio of Fouriertransform-near infrared (FT-NIR) spectra, but the optimalvalues of these two parameters have to be determinedempirically for a specific problem, considering separatelyboth the nature of the analysed matrix and the specificinstrumental setup. To achieve this aim, the instrumentalnoise of replicated FT-NIR spectra of wheat samples wasmodelled as a function of R and S by means of the Doehlertdesign. The noise amounts in correspondence to differentexperimental conditions were estimated by analysing thevariance signals derived from replicate measurements withtwo different signal processing tools, Savitzky–Golay (SG)filtering and fast wavelet transform (FWT), in order toseparate the “pure” instrumental noise from other variabilitysources, which are essentially connected to sample inhomogeneity.Results confirmed that R and S values leading tominimum instrumental noise can vary considerably dependingon the type of analysed food matrix and on the differentinstrumental setups, and helped in the selection of theoptimal measuring conditions for the subsequent acquisitionof a wide spectral dataset.
2011
- Modelling of Experimental Thermophysical Data by Mixing of a Ternary Solvent System
[Capitolo/Saggio]
Foca, Giorgia; Marchetti, Andrea; Tassi, Lorenzo; Ulrici, Alessandro
abstract
Thermomechanic and thermodynamic properties of mixing solvents in the liquid state have proven a powerful tool in elucidating the specific interactions and structural features supporting the liquid structure in multicomponent nonelectrolytic solutions. Mass transport properties (density, viscosity), thermophysical properties (relative permittivity, refractive index), and related thermodynamics can deepen elucidate the solvent – solvent specific interactions and behavioural peculiarities of the complex real systems. In this paper, we will primarily deal with the experimental measurements and correlative studies both on temperature and composition, of the above mentioned properties (Y), working with a ternary solvent system containing 1,2-ethanediol (ED), 2-methoxyethanol (ME) and 1,2-dimethoxyethane (DME), at various temperatures in the range -10 £ t (°C) £ 80, and with different compositions covering the whole miscibility field of the selected species. These components are strictly parent species, all being 1,2-ethanedyil-derivatives (-CH2-CH2-), pertaining to the amphiphile class molecules, with different balancing degree of hydrophobic and hydrophilic properties. Furthermore, the excess properties (YE) and deviation functions (DY) are largely stressed and examined along the text in order to identify the presence of solvent – cosolvent adducts in these ternary mixtures.
2011
- Monitoring Flour Performance in Bread Making
[Capitolo/Saggio]
LI VIGNI, Mario; Baschieri, Carlo; Foca, Giorgia; Marchetti, Andrea; Ulrici, Alessandro; Cocchi, Marina
abstract
A methodology to monitor flour performance in industrial bread-making based on evaluation of rheological and chemical properties of flour, as well as near infrared (NIR) spectra, is presented. The approach considers Multivariate Control Charts for both kinds of measurements, developed on flour batches employed in production. It can be adopted at the Millers laboratories, where rheological flours properties are routinely determined, to monitor flour quality; as well as, at the Bakeries plants, where NIR spectra of every flour batch entering the production can be acquired.Moreover, the variation of protein subunits in flour batches is discussed comparatively with flours properties and bread quality. Overall, flour batches leading to lousy performance can be individuated and they also show a non-optimal protein profile.This is of particular interest from the point of view of assessing flour workability and to rationalize it in terms of flour features. Finally, NIR potentiality allows considering on-line implementation in the control of incoming raw materials.
2011
- PEDOT modified electrodes in amperometric sensing for analysis of red wine samples
[Articolo su rivista]
Pigani, Laura; A., Culetu; Ulrici, Alessandro; Foca, Giorgia; M., Vignali; Seeber, Renato
abstract
A poly(3,4-ethylendioxythiophene) modified electrode has been considered as a potentially useful amperometric sensor to use either alone or in the frame of a set of sensors bearing complementary information, i.e. within an electronic tongue. The sensor is proposed in blind analysis of red wines, for classificationand calibration purposes. The data obtained from voltammetric measurements have been treated using partial least squares analysis. A calibration procedure has been performed to correlate results from analyses of wines, executed with traditional analytical methods, with the corresponding voltammetricresponses. Moreover, classification models of the wine samples, based on quantitative parameters and qualitative information about origin and variety, have been built. The developed electrochemical sensor also allows the fast identification of samples exceeding threshold limits of meaningful parameters forquality control in the wine industry, such as SO2, colour intensity and total polyphenols. The application of the system within a sensor array (electronic tongue) to fast pre-screening routine control procedure is proposed.
2011
- Prediction of compositional and sensory characteristics using RGB digital images and multivariate calibration techniques
[Articolo su rivista]
Foca, Giorgia; Masino, Francesca; Antonelli, Andrea; Ulrici, Alessandro
abstract
In the present paper, the possibility to use the information contained in RGB digital images to gain a fast and inexpensive quantification of colour-related properties of food is explored. To this aim, we present an approach which consists, as first step, in condensing the colour related information contained in RGB digital images of the analysed samples in one-dimensional signals, named colourgrams. These signals are then used as descriptor variables in multivariate calibration models. The feasibility of this approach has been tested using as a benchmark a series of samples of pesto sauce, whose RGB images have been used to predict both visual attributes defined by a panel test and the content of various pigments (chlorophylls a and b, pheophytins a and b, b-carotene and lutein).The possibility to predict correctly the values of some of the studied parameters suggests the feasibility of this approach for fast monitoring of the main aspect-related properties of a food matrix. The values of the squared correlation coefficient computed in prediction on a test set (R2Pred) for green and yellow hues were greater than 0.75, while R2Pred values greater than 0.85 were obtained for the prediction of total chlorophylls content and of chlorophylls/pheophytins ratio. The great flexibility of this blind analysis method for the quantitative evaluation of colour related features of matrices with an inhomogeneous aspect suggests that it is possible to implement automated, objective, and transferable systems for fast monitoring of raw materials, different stages of the manufacture and end products, not necessarily for the food industry only.
2011
- Seeds of Horse Chestnut (Aesculus hippocastanum L.) and Their Possible Utilization for Human Consumption
[Capitolo/Saggio]
Foca, Giorgia; Ulrici, Alessandro; Cocchi, Marina; Durante, Caterina; LI VIGNI, Mario; Marchetti, Andrea; Sighinolfi, Simona; Tassi, Lorenzo
abstract
This chapter appraises the seeds of horse chestnuts (. Aesculus hippocastanum [AH]) and their derived products. Escin, the major bioactive principle in AH seeds, has shown satisfactory evidence of clinically significant activity in the treatment of chronic venous insufficiency, hemorrhoids, postoperative edema, and mammary induration. There is some evidence that various escin molecules, such as saponins and sapogenins, show beneficial effects when administered at the right concentration, exhibiting an ethanol absorption inhibitory effect and hypoglycemic activity in the oral glucose tolerance test in vivo. Horse chestnut extract has a higher antioxidant activity than vitamin E, showing one of the highest "active-oxygen" scavenging abilities compared to other natural products. β-Escin from AH extracts was also tested to evaluate the chemopreventive efficacy of its dietary intake on azoxymethane-induced colonic aberrant crypt foci. The main adverse effects of escins in humans are due to their hemolytic activity. Research efforts in this field are devoted to improving the selectivity for aberrant red corpuscles, promoting the β-escin fraction as a useful candidate agent for exploring new potential antileukemic drugs. Fresh or naturally desiccated seeds are usually treated by long leaching with water or wooden ashes to remove harshness and bitterness. These treatments cause a variation in the molecular structures of escin fractions, reducing the toxicity but maintaining their nutraceutical potential and anti-obesity effects. Alternatively, the slow roasting of nuts makes the escins harmless and the seeds edible. The claimed toxicity of these extracts makes them natural antibacterials, antimicrobials, antivirals, and antifungals, to some extent, that also act as environmentally biocompatible phytotherapeutics.
2010
- Applicazione della spettroscopia FT-NIR per la classificazione tecnologica del frumento tenero: Parte I
[Relazione in Atti di Convegno]
N., Sinelli; M., Mariotti; M., Lucisano; Foca, Giorgia; Ulrici, Alessandro
abstract
-
2010
- Applicazione della spettroscopia FT-NIR per la classificazione tecnologica del frumento tenero: Parte II
[Relazione in Atti di Convegno]
Ulrici, Alessandro; Foca, Giorgia; C., Ferrari; N., Sinelli; M., Mariotti; R., Caramanico
abstract
-
2010
- Wheat flour formulation by mixture design and multivariate study of its technological properties
[Articolo su rivista]
LI VIGNI, Mario; Durante, Caterina; Foca, Giorgia; Ulrici, Alessandro; Birthe Pontoppidan Møller, Jespersen; Rasmus, Bro; Cocchi, Marina
abstract
Wheat flour plays a pivotal role in determining the overall quality of bread (loaf dimensions, crumb texture and consistency). A precise knowledge of flour chemical and technological properties is of paramount importance for the baking industry, to tune the modifications of the recipe and production parameters. However, it is still common to have to deal with an empirical, trial and error-based approach, and generally, time consuming techniques are employed to determine the quality indexes for flour.In the context of an industrial bread-making process, this study addresses the evaluation of the effect of a systematic variation in the mixture composition of wheat flours on their properties. The main objective is to offer this field a more rigorous method to evaluate and improve flour properties, by employing experimental design methodologies and interpreting the results in a multivariate way, instead of the common one variable at a time approach. The results show that a careful planning of flour mixtures when testing new varieties and formulation helps to obtain meaningful and easy-to-understand results as far as their properties are concerned.
2009
- Application of signal processing and experimental design techniques for the minimisation of instrumental noise in the acquisition of FT-NIR spectra of bread wheat samples
[Relazione in Atti di Convegno]
Ulrici, Alessandro; Foca, Giorgia; N., Sinelli; M., Mariotti; LI VIGNI, Mario; Cocchi, Marina; P., Belloni
abstract
-
2009
- Classification of NMR spectra collected on wines added with anthocyanins from grape and black rice
[Relazione in Atti di Convegno]
Foca, Giorgia; Ferrari, Erika; M., Vignali; Tassi, Lorenzo; Ulrici, Alessandro
abstract
-
2009
- Classification of Red Wines by Chemometric Analysis of Voltammetric Signals from Pedot-Modified Electrodes.
[Articolo su rivista]
Pigani, Laura; Foca, Giorgia; Ulrici, Alessandro; K., Ionescu; V., Martina; Terzi, Fabio; M., Vignali; Zanardi, Chiara; Seeber, Renato
abstract
Nine different types of Italian red wines of four different varieties were analysed, without any samplepre-treatments, by voltammetric techniques using a poly(3,4-ethylenedioxythiophene)-modified electrode.The data matrices consisting of the currents measured at different potentials, by repeated CyclicVoltammetry or Differential Pulse Voltammetry, are submitted to chemometric analysis. After explorativetests based on Principal Component Analysis, Partial Least Squares-Discriminant Analysis classificationmodels are built both for the training and for the test sets. To this aim, different classification strategiesare adopted, considering the responses from the two techniques either separately or joined together toform a data matrix including the whole voltammetric information.
2009
- Colorigrammi: impiego di fotocamere digitali come sensori ottici per l’analisi del colore di matrici alimentari disomogenee
[Relazione in Atti di Convegno]
Ulrici, Alessandro; Foca, Giorgia
abstract
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2009
- Different Feature Selection Strategies in the Wavelet Domain applied to NIR-Based Quality Classification Models of Bread Wheat Flours
[Articolo su rivista]
Foca, Giorgia; Cocchi, Marina; LI VIGNI, Mario; R., Caramanico; M., Corbellini; Ulrici, Alessandro
abstract
The Synthetic Quality Index method (Indice Sintetico di Qualità, ISQ) is used in the Italian cereal trade context for the classification of bread wheat in different quality categories, and consists in the assignation by an expert assessor of each wheat sample to the most fitting class, on the basis of parameters reflecting chemical and rheological properties of the flour. The high uncertainty of this procedure has been recently proved by some of us using a panel test, which confirmed a quite large degree of subjectivity in the assignation of samples to the quality classes.However, the results obtained with the panel test allowed to identify samples whose class assignation is sufficiently univocal, to be used for the development of automated classification methods based on NIR spectra. In the present work, multivariate classification models have been calculated using the WPTER algorithm, which aims at selecting — among the wavelet coefficients derived by application of the Wavelet Packet Transform to the analysed NIR spectra — only those features leading to the best possible discrimination among the considered classes. In particular, WPTER has been used following three different strategies to choose the optimal conditions for the development of SIMCA class models. Due to the restricted number of objects, the statistical validity of the models has been evaluated using a newly developed algorithm, which performs a double cross-validation of the SIMCA models, and by comparison with the results obtained by permutation tests.
2009
- Dohelert experimental design and signal processing techniques applied to the minimization of instrumental noise in FT-NIR spectra of wheat samples
[Relazione in Atti di Convegno]
Foca, Giorgia; Ulrici, Alessandro; N., Sinelli; M., Mariotti
abstract
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2009
- Hyperspectral image analysis for bread characterization in the baking industry
[Relazione in Atti di Convegno]
LI VIGNI, Mario; J., Manuel Amigo; Ulrici, Alessandro; Foca, Giorgia; Cocchi, Marina; R., Bro; B. P., Møller Jespersen
abstract
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2009
- Mid and Near Infrared Spectroscopy to analyse surface defectiveness in bread
[Relazione in Atti di Convegno]
Foca, Giorgia; LI VIGNI, Mario; Ulrici, Alessandro; Cocchi, Marina
abstract
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2009
- Minimisation of instrumental noise in the acquisition of FT-NIR spectra by means of Doehlert design and signal processing techniques
[Relazione in Atti di Convegno]
Foca, Giorgia; Ferrari, Carlotta; N., Sinelli; M., Mariotti; Ulrici, Alessandro
abstract
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2009
- Near Infrared Spectroscopy and Multivariate Analysis methods for monitoring flour performance in an industrial bread-making process
[Articolo su rivista]
LI VIGNI, Mario; Durante, Caterina; Foca, Giorgia; Marchetti, Andrea; Ulrici, Alessandro; Cocchi, Marina
abstract
The present study is aimed at evaluating the possibility to predict bread specifications, for an industrial bread-making process, on the basis of the properties of flour employed in production. The flour delivered at the production plant, of which rheological and chemical properties were available, were analysed by means of Near Infrared Spectroscopy (NIRS). Based on the flour properties and NIR signals, multivariate control charts were constructed in order to detect flour batches leading to a bread with non-optimal behaviour. The results show that it is possible to distinguish flour batches leading to a product with a particularly negative performance, by modelling the properties commonly measured on flours and the acquired Near Infrared signals. In spite of the absence of monitoring of process variables, which could have offered a more sound basis for the interpretation, especially when false positives and negatives are detected, these results are of particular interest from the point of view of raw material evaluation in process monitoring. Also, the potentiality of Near Infrared Spectroscopy allows considering this approach for an on-line implementation in the control of incoming raw materials in this industrial process.
2009
- Study of protein content of wheat flour in relation to technological properties using chromatography, NIRS and chemometrics
[Relazione in Atti di Convegno]
Baschieri, Carlo; LI VIGNI, Mario; Cocchi, Marina; Foca, Giorgia; Marchetti, Andrea; Ulrici, Alessandro
abstract
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2009
- Wheat Flour formulation by Mixture Design and study of its properties and performance
[Relazione in Atti di Convegno]
LI VIGNI, Mario; Cocchi, Marina; Durante, Caterina; Ulrici, Alessandro; Foca, Giorgia; R., Bro; B. P., Møller Jespersen
abstract
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2008
- A chemometric study of pesto sauce appearance and of its relation to pigment concentration
[Articolo su rivista]
Masino, Francesca; Foca, Giorgia; Ulrici, Alessandro; Arru, Laura; Antonelli, Andrea
abstract
Pesto sauce is a typical example of a food matrix in which aspect is of key importance to the final judgment of the consumer, and whose color strongly depends on the production process and on the ingredients. In view of this, the aim of the present work is to evaluate the possibility of quantifying the variability of visual aspect of different brands of pesto sauce, and its relation to the concentration of the main pigments. Sensory evaluation of the appearance of 12 commercial pesto samples was carried out by a panel of 16 assessors who evaluated quantitatively six visual attributes, suitably defined for the description of pesto aspect. A quantitative estimate of the performance of the panel was carried out by means of both univariate and multivariate–multiway chemometric tools (parallel factor analysis, PARAFAC). In addition, the relationship between the mean sensory scores values and the concentrations of chlorophylls, pheophytins and carotenoids was investigated by principal components analysis (PCA). Both PCA and PARAFAC showed good clustering of thesamples and a satisfactory degree of homogeneity of the assessors. Data analysis showed that assessors fundamentally agree about the main visual characteristics of pesto sauces, which are partly correlated with the concentration values of the main pigments.
2008
- Amperometric sensors based on poly(3,4-ethylenedioxythiophene)-modified electrodes: Discrimination of white wines
[Articolo su rivista]
Pigani, Laura; Foca, Giorgia; K., Ionescu; Martina, Virginia; Ulrici, Alessandro; Terzi, Fabio; M., Vignali; Zanardi, Chiara; Seeber, Renato
abstract
The voltammetric responses on selected white wines of different vintages and origins havebeen systematically collected by three different modified electrodes, in order to check theireffectiveness in performing blind analysis of similar matrices. The electrode modifiers consistof a conducting polymer, namely poly(3,4-ethylenedioxythiophene) (PEDOT) and of compositematerials of Au and Pt nanoparticles embedded in a PEDOT layer. Wine samples havebeen tested, without any prior treatments, with differential pulse voltammetry technique.The subsequent chemometric analysis has been carried out both separately on the signals ofeach sensor, and on the signals of two or even three sensors as a unique set of data, in order tocheck the possible complementarity of the information brought by the different electrodes.After a preliminary inspection by principal component analysis, classification models havebeen built and validated by partial least squares-discriminant analysis. The discriminantcapability has been evaluated in terms of sensitivity and specificity of classification; in allcases quite good results have been obtained.
2008
- At-line control of an industrial bread-making process
[Abstract in Atti di Convegno]
LI VIGNI, Mario; Brettagna, B; Cocchi, Marina; DE MARCO, T; Foca, Giorgia; Marchetti, Andrea; Ulrici, Alessandro
abstract
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2008
- At-line monitoring of the leavening process in industrial bread making by near infrared spectroscopy
[Articolo su rivista]
Ulrici, Alessandro; LI VIGNI, Mario; Durante, Caterina; Foca, Giorgia; P., Belloni; B., Brettagna; T., DE MARCO; Cocchi, Marina
abstract
The potential of near infrared (NIR) spectroscopy to characterise doughs for industrial bread making, directly at the production plant, was investigated. Different stages of dough processing have been monitored at-line, employing a Fourier transform-NIR instrument equipped with an optical fi bre. Parallel factors analysis has been used to study the spectral variation throughout the production line, with the aim of acquiring indications on the modifi cations the dough undergoes during the process. Moreover, wavelet interface for linear modelling analysis, which performs variable selection in the wavelet domain, has been employed to explore the possibility of monitoring the leavening step by identifying a relationship between the NIR signal and the leavening phase, considering the leavening time and the total titrable acidity of the dough. Results show that some aspects of the leavening process can be calibrated from the NIR spectra, thus corroborating the fact that the NIR signal is infl uenced by the modifi cations that occur along with the production process.
2008
- Caratterizzazione di vini addizionati di antociani di diversa origine mediante spettroscopia NIR e analisi chemiometrica dei segnali
[Abstract in Atti di Convegno]
Foca, Giorgia; Ulrici, Alessandro; Tassi, Lorenzo; Vignali, M.
abstract
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2008
- Classificazione multivariata di spettri NIR di vini addizionati di antociani provenienti da uva e da riso nero
[Abstract in Atti di Convegno]
Foca, Giorgia; Ulrici, Alessandro; Tassi, Lorenzo; Vignali, M.
abstract
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2008
- Controllo di un processo industriale di panificazione mediante NIRS ed analisi multivariata
[Abstract in Atti di Convegno]
LI VIGNI, Mario; Brettagna, B; Cocchi, Marina; DE MARCO, T; Foca, Giorgia; Marchetti, Andrea; Ulrici, Alessandro; Quaglia, L.
abstract
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2008
- Metodi rapidi di valutazione qualitativa del frumento tenero
[Articolo su rivista]
Foca, Giorgia; Ulrici, Alessandro; M., Corbellini; R., Caramanico; M., Lucisano; M. A., Pagani; Cocchi, Marina; Tassi, Lorenzo; G., Boggini
abstract
SommarioNella classificazione di frumenti teneri mediante il metodo ISQ (Indice Sintetico di Qualità), un valutatore esperto classifica ogni campione di grano in diverse categorie qualitative, definite in base ad alcuni parametri chimici e reologici. Le analisi impiegate per la determinazione di tali parametri richiedono lunghi tempi di esecuzione e l’impiego di personale esperto, mentre durante le transazioni commerciali i prodotti devono essere caratterizzati in tempi molto brevi. Per questa ragione, è stato sviluppato un metodo veloce ed automatizzato per la classificazione del frumento, basato sull’accoppiamento della spettroscopia nel vicino infrarosso (NIR) con metodi di analisi multivariata dei dati.SummaryDuring the classification of bread wheats by means of the ISQ method (Synthetic Index of Quality), an expert assessor classifies each wheat sample in different quality categories, defined on the basis of some chemical and rheological parameters. The analyses involved in the determination of such parameters require long times of execution and the employing of skilled personnel, whereas, during the commercial transactions, the products need to be characterized in very short times. For this reason, we developed a fast and automated method of wheat classification based on the coupling of the Near InfraRed spectroscopy (NIR) and multivariate data analysis methods.
2008
- Modelling of Experimental Thermophysical Data by Mixing of a Ternary Solvent System, in Solution Chemistry
[Capitolo/Saggio]
Foca, Giorgia; Marchetti, Andrea; Tassi, Lorenzo; Ulrici, Alessandro
abstract
Thermomechanic and thermodynamic properties of mixing solvents in the liquid state have proven a powerful tool in elucidating the specific interactions and structural features supporting the liquid structure in multicomponent nonelectrolytic solutions. Mass transport properties (density, viscosity), thermophysical properties (relative permittivity, refractive index), and related thermodynamics can deepen elucidate the solvent – solvent specific interactions and behavioural peculiarities of the complex real systems. In this paper, we will primarily deal with the experimental measurements and correlative studies both on temperature and composition, of the above mentioned properties (Y), working with a ternary solvent system containing 1,2-ethanediol (ED), 2-methoxyethanol (ME) and 1,2-dimethoxyethane (DME), at various temperatures in the range -10 £ t (°C) £ 80, and with different compositions covering the whole miscibility field of the selected species. These components are strictly parent species, all being 1,2-ethanedyil-derivatives (-CH2-CH2-), pertaining to the amphiphile class molecules, with different balancing degree of hydrophobic and hydrophilic properties. Furthermore, the excess properties (YE) and deviation functions (DY) are largely stressed and examined along the text in order to identify the presence of solvent – cosolvent adducts in these ternary mixtures.
2008
- Multivariate analysis of analytical signals to decipher relevant chemical information
[Capitolo/Saggio]
Ulrici, Alessandro; Cocchi, Marina; Durante, Caterina; Foca, Giorgia; Marchetti, Andrea; Tassi, Lorenzo
abstract
Two main elements have recently characterized the research in the analytical field: on one hand the huge development of instrumental analysis in the direction of hyphenated techniques and, on the other hand, the huge development and decreasing cost of computers together with the increased capacity of computational tools. Moreover, new issues are presented to the analytical researcher by new regulations that impose to demonstrate that the whole process is under control, e.g. in the industrial/productive context, or in the life science context by the emerging need of systems biology. Thus, the role of chemometrics is more and more increasing and the toolbox of chemometrics-like methods has been progressively enriched.In particular, deciphering signal-fingerprinting of complex matrix samples requires a deeper consideration on the nature of signals feature, and it has to be taken into account that the information pertinent to the problem is mixed with many uninformative sources of variations that may affect part or the whole signal domain. These issues from the data analysis point of view are reflected in a greater complexity of the preprocessing/pretreatment and variable selection steps.The main focus of this chapter will be on feature selection methodology; after a concise review of the main recently proposed feature selection methods, the specific case of feature selection in the wavelet (WT) domain will then be considered. In particular, it will deal with illustration of our recent developed tools for WT-feature selection in regression and classification tasks. The discussion of different applications will be the core of the work, to illustrate the effectiveness of the integration of both basic (simple) and more advanced methodologies together, with a complete strategy embracing data exploration, modelling, data display-interpretation and validation.
2007
- Caratterizzazione del Nocino tipico emiliano mediante indagini chimico-fisiche ed analisi chemiometriche
[Relazione in Atti di Convegno]
Foca, Giorgia; Franchini, Giancarlo; Grandi, Margherita; Marchetti, Andrea; Tassi, Lorenzo; Ulrici, Alessandro
abstract
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2007
- Caratterizzazione spettroscopica e tecnologica di miscele gluten-free formulate mediante disegno sperimentale
[Relazione in Atti di Convegno]
Ulrici, Alessandro; Foca, Giorgia; Cocchi, Marina; LI VIGNI, Mario; PAGANI M., A; Lucisano, M.
abstract
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2007
- Characterisation and optimisation of gluten-free formulations by multivariate analysis of technological parameters and nir spectra collected on d-optimal designed mixtures
[Relazione in Atti di Convegno]
Foca, Giorgia; Ulrici, Alessandro; Cocchi, Marina; PAGANI M., A; Lucisano, M.
abstract
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2007
- Chemical composition and characterisation of seeds from two varieties (pure and hybrid) of Aesculus hippocastanum
[Articolo su rivista]
Baraldi, Cecilia; Bodecchi, Lidia Maria; Cocchi, Marina; Durante, Caterina; Ferrari, Giorgia; Foca, Giorgia; Grandi, Margherita; Marchetti, Andrea; Tassi, Lorenzo; Ulrici, Alessandro
abstract
Investigations have been conducted on some samples of naturally desiccated horse-chestnuts (Aesculus hippocastanum), representativeof the two most common mediterranean varieties: the pure species (AHP, giving white flowers), and a hybrid (AHH, giving pink flowers).Different experimental techniques have been used to gain more information on morphological structure and chemical composition ofthese complex matrices. Surface analysis by SEM showed no differences in such floured samples (wild type), while thermal behaviour(DSC) outlines some significant differences between them. Chemical composition reveals some differences in residual moisture(AHP = 6.97%; AHH = 6.59%), proteins (AHP = 2.64%; AHH = 1.82%), lipids (AHP = 4.13%; AHH = 5.10%), glucides (AHP =15.2%; AHH = 14.3%), and ashes (AHP = 2.51%; AHH = 2.19%). Most likely, these characters modulate other undifferentiated chemicalparameters, such as cold water solubility (CWS:AHP = 53.9%; AHH = 48.6%), and total inorganic soluble salts (TISS:AHP = 2.18%; AHH = 1.92%). Principal component analysis was applied to differentiate the two horse-chestnuts varieties. In particular,the first principal component effectively distinguish and discriminates AHH and AHP samples in two well-separated categories, giving, atthe same time, some information on the influence of the whole set of chemical compositional parameters.
2007
- Colourgrams: an alternative, fast and inexpensive way for characterising inhomogeneous food matrices through multivariate image analysis
[Relazione in Atti di Convegno]
Ulrici, Alessandro; Foca, Giorgia
abstract
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2007
- Determinazione di acidi e zuccheri presenti negli impasti per la produzione industriale di pane a diversi stadi della lavorazione
[Relazione in Atti di Convegno]
Cocchi, Marina; Foca, Giorgia; LI VIGNI, Mario; Marchetti, Andrea; Tassi, Lorenzo; Ulrici, Alessandro
abstract
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2007
- Efficient variables selection in multivariate analysis of signals by coupling fast wavelet transform and genetic algorithms
[Relazione in Atti di Convegno]
Cocchi, Marina; Durante, Caterina; Foca, Giorgia; LI VIGNI, Mario; Leardi, R; Ulrici, Alessandro
abstract
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2007
- Elaboration and Application of Algorithms Performing Feature Selection in the Wavelet Domain for Analysis of NIR based data
[Relazione in Atti di Convegno]
Cocchi, Marina; Durante, Caterina; LI VIGNI, Mario; Foca, Giorgia; Ulrici, Alessandro
abstract
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2007
- End-use classification of wheat flours after feature selection on NIR spectra
[Relazione in Atti di Convegno]
Foca, Giorgia; Ulrici, Alessandro; Cocchi, Marina; Corbellini, M; Tassi, Lorenzo
abstract
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2007
- Monitoraggio multivariato di un processo industriale di panificazione
[Relazione in Atti di Convegno]
Belloni, P; Brettagna, B; Cocchi, Marina; DE MARCO, T; Foca, Giorgia; LI VIGNI, Mario; Marchetti, Andrea; Ulrici, Alessandro
abstract
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2007
- Monitoring an industrial bread making process by means of Near Infrared Spectroscopy and chemometric methods
[Relazione in Atti di Convegno]
P., Belloni; B., Brettagna; Cocchi, Marina; T., De Marco; Durante, Caterina; Foca, Giorgia; LI VIGNI, Mario; Marchetti, Andrea; Ulrici, Alessandro
abstract
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2007
- Monitoring of the leavening process in industrial bread making
[Relazione in Atti di Convegno]
Belloni, P; Brettagna, B; Cocchi, Marina; DE MARCO, T; Foca, Giorgia; LI VIGNI, Mario; Marchetti, Andrea; Ulrici, Alessandro
abstract
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2007
- Multivariate analysis of NIR spectra collected on D-optimal designed gluten-free doughs
[Relazione in Atti di Convegno]
Ulrici, Alessandro; Foca, Giorgia; Cocchi, Marina; PAGANI M., A; Lucisano, M.
abstract
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2007
- Reproducibility of the Italian ISQ method for quality classification of bread wheats: An evaluation by expert assessors
[Articolo su rivista]
Foca, Giorgia; Ulrici, Alessandro; M., Corbellini; Ma, Pagani; M., Lucisano; Franchini, Giancarlo; Tassi, Lorenzo
abstract
The great variety of different bakery products in Italy has led to the development of a method, the Synthetic Index of Quality (Indice Sintetico, di Qualita, ISQ), for the classification of bread wheats in different quality categories. Based on chemical and rheological properties, each wheat sample is assigned to the most suitable class by an expert assessor. In many cases this procedure is not straightforward, making the class assignation uncertain, thus leading to the possibility of controversies during the trading phase. In the present study, in order to have a quantitative estimate of the validity and reliability of this procedure, a panel composed of nine expert assessors was utilised for the repeated evaluation of 100 samples of bread wheats of various qualities. The results suggest that the proposed approach can be used both to monitor the reliability of the single assessors, and to identify samples whose class assignation is reasonably indubitable, e.g. to be used for the development of automated classification methods. Moreover, the analysis of the most uncertain assignation cases can be useful in order to enhance the ISQ classification method itself. (c) 2007 Society of Chemical Industry.
2006
- Applicazione di algoritmi per la selezione di variabili nell’analisi di spettri NIR di prodotti alimentari
[Relazione in Atti di Convegno]
Cocchi, Marina; Ulrici, Alessandro; Foca, Giorgia; Durante, Caterina
abstract
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2006
- Classificazione chemiometrica di spettri NIR di frammenti ossei di specie animali diverse
[Relazione in Atti di Convegno]
Cocchi, Marina; Pavino, D; Ulrici, Alessandro; Foca, Giorgia; Durante, Caterina; Martra, G; Abete, M. C.
abstract
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2006
- Classificazione multivariata sulla base di spettri NIR dei risultati di un panel test per il riconoscimento della classe qualitativa del grano tenero
[Relazione in Atti di Convegno]
Ulrici, Alessandro; Foca, Giorgia; Cocchi, Marina; Corbellini, M; Franchini, Giancarlo; Tassi, Lorenzo
abstract
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2006
- Controllo at-line di impasti per la produzione industriale di pane mediante tecniche analitiche e chemiometriche
[Relazione in Atti di Convegno]
Foca, Giorgia; Ulrici, Alessandro; Cocchi, Marina; Marchetti, Andrea; LI VIGNI, Mario
abstract
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2006
- Determinazione di pigmenti e attributi sensoriali mediante analisi multivariata del colore di immagini digitali
[Abstract in Atti di Convegno]
Ulrici, Alessandro; Foca, Giorgia; Masino, Francesca
abstract
Recentemente è stato presentato un nuovo metodo automatizzato per la classificazione di matrici alimentari disomogenee sulla base delle comuni fotografie digitali RGB che, rappresentando il contenuto in colore di ogni immagine digitale sotto forma di un segnale (colorigramma) dato dalla sequenza di curve di distribuzione di vari descrittori del colore dei pixel, permette di selezionare le regioni più significative con opportuni algoritmi di feature selection/classificazione. I risultati ottenuti su una serie di campioni di pesto alla genovese, ci hanno spinto a valutare la possibilità di impiegare lo stesso approccio a scopi di calibrazione, utilizzando i colorigrammi ottenuti da fotografie di campioni di pesto per prevederne il contenuto in pigmenti (clorofille, feofitine, caroteni) ed alcune caratteristiche legate all’aspetto, valutate per mezzo di un panel test. Per molte delle proprietà studiate sono stati ottenuti modelli di calibrazione PLS con soddisfacente capacità predittiva, e risultati ancora migliori sono stati raggiunti impiegando un algoritmo di feature selection/calibrazione basato sulla Trasformata Wavelet.
2006
- Durum wheat adulteration detection by NIR spectroscopy multivariate calibration
[Articolo su rivista]
Cocchi, Marina; Durante, Caterina; Foca, Giorgia; Marchetti, Andrea; Tassi, Lorenzo; Ulrici, Alessandro
abstract
In the present work, we explored the possibility of using near-infrared spectroscopy in order to quantify the degree of adulteration of durum wheat flour with common bread wheat flour. The multivariate calibration techniques adopted to this aim were PLS and a wavelet-based calibration algorithm, recently developed by some of us, called WILMA. Both techniques provided satisfactory results, the percentage of adulterant present in the samples being quantified with an uncertainty lower than that associated to the Italian official method. In particular the WILMA algorithm, by performing feature selection, allowed the signal pretreatment to be avoided and obtaining more parsimonious models.
2006
- Elaboration and Application of Algorithms Performing Feature Selection in the Wavelet Domain
[Relazione in Atti di Convegno]
Ulrici, Alessandro; Cocchi, Marina; Foca, Giorgia
abstract
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2006
- Feature selection e classificazione multivariata nel dominio wavelet per la classificazione di spettri NIR di grani di diversa qualità
[Relazione in Atti di Convegno]
Foca, Giorgia; Ulrici, Alessandro; Cocchi, Marina
abstract
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2006
- Investigation on a Roman copper alloy artefact from Pompeii (Italy)
[Articolo su rivista]
Baraldi, Pietro; Baraldi, Cecilia; Ferrari, Giorgia; Foca, Giorgia; Marchetti, Andrea; Tassi, Lorenzo
abstract
A selection of samples, obtained from a particular copper-alloy domestic artefact of Roman style from Pompeii, has been analysed by using different techniques (IR, Raman, SEM-EDX, FAAS), in order to investigate the chemical nature and composition of the metals utilised for such manufacturing pieces. The surface analysis of the bright red metallic microfragments conducted by different analytical techniques, emphasises the presence of pure unalloyed copper and confirms the absence of other metallic species on the upper layers. On the contrary, the mapping analysis of the section of the laminar metal of the investigated sample shows a consistent enrichment in tin content. Finally, destructive analysis by FAAS confirms that the artefact looks like a bronze metal alloy, with a medium Sn content of about 6.5%
2006
- Monitoraggio at-line del processo di lievitazione di impasti per la produzione industriale di pane
[Relazione in Atti di Convegno]
Ulrici, Alessandro; Cocchi, Marina; Marchetti, Andrea; Foca, Giorgia; Durante, Caterina; DE MARCO, T; Brettagna, B; Belloni, P.
abstract
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2006
- Study of the dependence on temperature and composition of the volumic properties of ethane-1,2-diol+2-methoxyethanol+1,2-dimethoxyethane plus water solvent system and graphical representation in the quaternary domain
[Articolo su rivista]
Ulrici, Alessandro; Cocchi, Marina; Foca, Giorgia; M., Manfredini; Marchetti, Andrea; D., Manzini; Tassi, Lorenzo; S., Sighinolfi
abstract
In this paper, the temperature and composition dependencies of the volumetric behavior are studied for the ethane-1,2-diol + 2-methoxyethanol + 1,2-dimethoxyethane + water quaternary system. Density data were collected at different temperatures ranging from -10 to 80 degrees C and at atmospheric pressure over the whole composition range, 0 :5 x(i)(i = 1, 2, 3,4) <= 1. Moreover, we also made use of the results on the six binary (ij) and four ternary (kij) subsystems studied previously. The excess molar volume (V-E) data have been fitted to an equation derived from the well-known Redlich-Kister equation and some interesting correlations were found. Furthermore, in order to represent in an effective way the behavior of the V-E = V-E(x(i)) function (and of the derived partial molar quantities) in the quaternary domain, a new algorithm has been developed, which gives 3D plots where the dependent function is depicted by means of '' colored slices '' of the tetrahedron corresponding to the investigated composition quaternary domain.
2005
- Analisi multivariata di dati storici chimico-fisici e microbiologici delle acque potabili reggiane
[Relazione in Atti di Convegno]
Ulrici, Alessandro; Foca, Giorgia; Manzini, Daniela; Masino, Francesca; N., Fontani; Franchini, Giancarlo; G., Carapezzi
abstract
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2005
- Analisi multivariata di immagini digitali per la valutazione di matrici alimentari eterogenee
[Articolo su rivista]
Ulrici, Alessandro; Manzini, Daniela; Masino, Francesca; Franchini, Giancarlo; Antonelli, Andrea; Foca, Giorgia
abstract
Questo lavoro descrive un nuovo metodo automatizzato per la classificazione di matricialimentari eterogenee sulla base delle comunifotografie digitali a colori. La caratteristica piùinnovativa di questo approccio consiste nellacapacità di identificare autonomamente gliaspetti che risultano essere maggiormente utiliper la classificazione degli alimenti esaminati. Ciòsignifica individuare le variabili più significativeper la classificazione dei campioni analizzatiin maniera cieca, ovvero senza la necessità dieffettuare alcuna assunzione a priori sulla naturadella matrice alimentare considerata. L’approccioprevede di rappresentare il contenuto in colore diogni immagine digitale sotto forma di un segnale,che noi abbiamo chiamato colorigramma, il qualeconsiste essenzialmente nella sequenza delle curvedi distribuzione dei tre valori di colore Rosso, Verdee Blu, nonché di vari parametri da essi derivati. Icolorigrammi così ottenuti possono quindi essereanalizzati mediante un algoritmo di classificazionee selezione di variabili chiamato WPTER. In questolavoro si presenta l’applicazione di tale approcciosu una serie di campioni di pesto alla genovese.Questo tipo di condimento, soprattutto a causa delladegradazione della clorofilla, tende a presentare unagrande variabilità di colore, che risulta però difficileda quantificare con metodi tradizionali di analisi acausa dell’aspetto eterogeneo.
2005
- Classification of bread wheat flours in different quality categories by a wavelet-based feature selection/classification algorithm on NIR spectra
[Articolo su rivista]
Cocchi, Marina; M., Corbellini; Foca, Giorgia; M., Lucisano; Ma, Pagani; Tassi, Lorenzo; Ulrici, Alessandro
abstract
In the Italian context, bread wheat flour is commercially classified in different quality categories on the basis of a Synthetic Index of Quality (Indice Sintetico di Qualit, ISQ), which is defined by means of specific parameters, i.e., hectolitric weight, falling number, protein content, alveographic indexes (W, P/L) and farinograph stability. The analyses involved in the determination of these parameters are expensive, time consuming and require specialized personnel, thus there is concern to develop alternative methods to be applied during the commercial transactions, when the products need to be characterized in very short times. For this reason, a fast technique such as an automated classification on the basis of NIR spectra acquired on the wheat flour samples could be a very useful tool. In this work, various wheat flour samples belonging to four different ISQ classes have been analysed by means of NIR spectroscopy, and the obtained spectra have been classified both by SIMCA applied to the signals subjected to different pretreatment methods, and by using a wavelet-based feature selection/classification algorithm, called WPTER. Due to the high overlap of the two intermediate quality classes, it was not possible to classify all the data set signals. However, when considering only the two extreme categories, an acceptable degree of class separation can be gained after feature selection by WPTER. Moreover, this approach allowed us to locate the NIR spectral regions that are mainly involved in the assignment of the wheat flour samples to these two quality categories.
2005
- Studio sensoriale sulle acque: approccio sperimentale
[Relazione in Atti di Convegno]
Masino, Francesca; Antonelli, Andrea; Ulrici, Alessandro; Foca, Giorgia; Franchini, Giancarlo
abstract
Le caratteristiche sensoriali assumono un ruolo di fondamentale importanza nella determinazione della qualità alimentare. Per questi motivi, l’analisi sensoriale è uno strumento valido che, abbinata ad altre metodiche, consente d’individuare, sviluppare e migliorare le caratteristiche di un prodotto, oltre che a studiare le preferenze dei consumatori.L’acqua è, per definizione, priva di gusto ed odore e, proprio per questo motivo, le sue caratteristiche sensoriali sono difficili da valutare. In questo lavoro si descrive l’addestramento di un gruppo di persone (panel) per la valutazione sensoriale dell’acqua, ed alcune applicazioni a campioni reali
2005
- Use of multivariate analysis of MIR spectra to study bread staling
[Articolo su rivista]
Cocchi, Marina; Foca, Giorgia; Marchetti, Andrea; Sighinolfi, Simona; Tassi, Lorenzo; Ulrici, Alessandro
abstract
Different kinds of bread, stored at constant temperature and at controlled humidity conditions for a week since their manufacturing date, were analysed by Attenuated Total Reflectance-Fourier Transform InfraRed (ATR-FTIR) spectroscopy. The collected spectra were processed by Principal Component Analysis (PCA), in order to evaluate the changes occurring during bread ageing. For the sake of comparison, the 1060-950 cm(-1) spectral window has been also investigated by curve-fitting methods. It was observed that the first PC increases monotonically with ageing of samples. Furthermore, the more influential variables on PCl correspond to spectral regions where are located stretching and bending bands, which are mainly attributed to typical starch bonds vibrations.
2004
- Analysis of the temperature and composition dependence of viscosimetric properties of 2-butanone+2-butanol solvent mixtures
[Articolo su rivista]
S., Faranda; Foca, Giorgia; Marchetti, Andrea; Tassi, Lorenzo; Ulrici, Alessandro; Zucchi, Claudia
abstract
Kinematic viscosities were measured for 2-butanone + 2-butanol binary liquid mixtures with a capillary Ubbelohde routine viscometer in the temperature range from 273.15 to 353.15 K at atmospheric pressure, and covering the whole miscibility field (0 less than or equal to x(i) less than or equal to 1). Experimental data have been correlated by means of different empirical or semiempirical relationships, such as nu = nu(T), nu = nu(x(i)), and nu = nu(T, x(i)). Viscosity deviations, Deltanu, from ideal behavior are negative at all experimental conditions, confirming that structure breaking effects prevail in the liquids. Furthermore, the thermodynamics of viscous flow and excess Gibbs energy of activation of viscous flow, G*(E), have been calculated. As an alternative and complementary approach to such investigations, the fluidity (phi) of this binary system has been analyzed by the modified-Batschinski theory. The results are discussed in terms of the specific molecular interactions between the mixture components.
2004
- Application of NIR spectroscopy multivariate calibration to the quantification of durum wheat semolina adulteration with bread wheat flour
[Relazione in Atti di Convegno]
Cocchi, Marina; Foca, Giorgia; Marchetti, Andrea; Tassi, Lorenzo; Ulrici, Alessandro
abstract
-
2004
- Application of a wavelet-based algorithm on HS-SPME/GC signals for the classification of balsamic vinegars
[Articolo su rivista]
Cocchi, Marina; Durante, Caterina; Foca, Giorgia; Manzini, Daniela; Marchetti, Andrea; Ulrici, Alessandro
abstract
A novel feature selection and classification algorithm (WPTER) based on the wavelet packet transform has been applied to the discrimination of balsamic vinegars, namely the typical made Aceto Balsamico Tradizionale di Modena, which gained the PDO denomination on the year 2000, from the industrial made Aceto Balsamico of the Modena district. All the samples have been characterized on the basis of the gas chromatographic (GC) profiles of the headspace (HS) volatile fraction, sampled by solid phase microextraction (SPME). Good discrimination between the two categories has been obtained both for the calibration and for the test set samples. GC-MS analysis allowed the identification of the peaks lying in the chromatographic regions selected by the algorithm, giving useful suggestions about the compounds which may be worth of further investigation in order to rationalize the chemical transformation occurring during the traditional making procedure. The proposed methodology seems very promising in authentication tasks, coupling some of the advantages of blind analysis with the possibility of acquiring chemical information, and giving, at the same time, very parsimonious multivariate classification models, which can be particularly suitable for data storage and handling.
2004
- Applicazione della calibrazione multivariata su spettri NIR per la quantificazione dell’adulterazione di semola di grano duro con farina di grano tenero
[Relazione in Atti di Convegno]
Cocchi, Marina; Foca, Giorgia; Marchetti, Andrea; Tassi, Lorenzo; Ulrici, Alessandro
abstract
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2004
- Applicazione dell’algoritmo WPTER su spettri NIR di farine di frumento tenero per la classificazione nelle diverse classi di qualità
[Relazione in Atti di Convegno]
Cocchi, Marina; Corbellini, M; Foca, Giorgia; Tassi, Lorenzo; Ulrici, Alessandro
abstract
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2004
- Automated evaluation of food colour by means of multivariate image analysis coupled to a wavelet-based classification algorithm
[Articolo su rivista]
Antonelli, Andrea; Cocchi, Marina; Fava, Patrizia; Foca, Giorgia; Franchini, Giancarlo; Manzini, Daniela; Ulrici, Alessandro
abstract
This paper describes an approach for the colour-based classification of RGB images, taken with a common digital CCD camera oninhomogeneous food matrices. The aimwas that of elaborating a feature selection/classification method independent of the specific food matrixthat is analysed, in the sense that the variables that are the most relevant ones for the classification of the analysed samples are selected in a blindway, with no a priori assumptions on the basis of the nature of the considered food matrix.Aone-dimensional signal describing the colour contentof each acquired digital image, which we have called colourgram, is created as the contiguous sequence of the frequency distribution curves ofthe three red, green and blue colours values, of related parameters (also including hue, saturation and intensity) and of the scores values derivingfrom the PCA analysis of the unfolded 3D image array, together with the corresponding loadings values and eigenvalues. Once a sufficientnumber of digital images has been acquired, the corresponding colourgrams are then analysed by means of a feature selection/classificationalgorithm based on the wavelet transform, wavelet packet transform for efficient pattern recognition (WPTER). This approach was tested ona series of samples of “pesto”, a typical Italian vegetable pasta sauce, which presents high colour variability, mainly due to technologicalvariables (raw materials, processes) and to the degradation of chlorophylls during storage. Good classification results (100% of correctlyclassified objects with very parsimonious models) have been obtained, also in comparison with the visual evaluation results of a panel test.
2004
- Caratterizzazione chimico-fisica di amidi di varia origine
[Relazione in Atti di Convegno]
Cocchi, Marina; Foca, Giorgia; Franchini, Giancarlo; Marchetti, Andrea; Sighinolfi, Simona; Tassi, Lorenzo; Ulrici, Alessandro
abstract
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2004
- Classification of bread wheats in different baking categories by application of a wavelet-based feature selection/classification algorithm on NIR spectra
[Relazione in Atti di Convegno]
Cocchi, Marina; Corbellini, M; Foca, Giorgia; PAGANI M., A; Lucisano, M; Ulrici, Alessandro
abstract
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2004
- Classification of cereal flours by chemometric analysis of MIR spectra
[Articolo su rivista]
Cocchi, Marina; Foca, Giorgia; M., Lucisano; Marchetti, Andrea; Ma, Pagani; Tassi, Lorenzo; Ulrici, Alessandro
abstract
Different kinds of cereal flours submitted to various technological treatments were classified on the basis of their mid-infrared spectra by pattern recognition techniques. Classification in the wavelet domain was achieved by using the wavelet packet transform for efficient pattern recognition (WPTER) algorithm, which allowed singling out the most discriminant spectral regions. Principal component analysis (PCA) on the selected features showed an effective clustering of the analyzed flours. Satisfactory classification models were obtained both on training and test samples. Furthermore, mixtures of varying composition of the studied flours were distributed in the PCA space according to their composition.
2004
- Classificazione di frumenti teneri in diverse classi di qualità mediante applicazione sugli spettri NIR di un algoritmo di classificazione/selezione di variabili basato sulla trasformata wavelet
[Relazione in Atti di Convegno]
Cocchi, Marina; Corbellini, M; Foca, Giorgia; PAGANI M., A; Lucisano, M; Ulrici, Alessandro
abstract
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2004
- Density measurements of the binary mixtures of 2-butanone and 2-butanol at temperatures from –10 to 80 °C
[Articolo su rivista]
S., Faranda; Foca, Giorgia; Marchetti, Andrea; Palyi, Gyula; Tassi, Lorenzo; Zucchi, Claudia
abstract
Densities of methyl-ethyl-ketone + 2-butanol were measured at temperatures between -10 and 80 degreesC, working with the pure species and nine binary mixtures. At each experimental condition, the data were correlated by means of some empirical equations and according to well-established literature models. The estimated excess molar volumes (and some related quantities) were also evaluated by applying the Redlich-Kister equation. The results related to specific intermolecular interactions have been interpreted in terms of structural and geometrical effects.
2004
- Dielectric properties in ternary mixtures of ethane-1,2-diol+1,2-dimethoxyethane + water
[Articolo su rivista]
Foca, Giorgia; Manfredini, Matteo; Manzini, Daniela; Marchetti, Andrea; Pigani, Laura; Sighinolfi, Simona; Tassi, Lorenzo; Ulrici, Alessandro
abstract
The static dielectric constant (epsilon) of ethane-1,2-diol + 1,2-dimethoxyethane + water ternary mixtures was measured as a function of temperature (263.15 less than or equal to T (K) less than or equal to 353.15) and composition, over the complete mole fraction range 0 less than or equal to x(1), x(2), x(3) less than or equal to 1. The experimental values were analyzed by empirical relationships that accounted for the dependence epsilon = epsilon(T) and Y = Y(x(i)). A comparison between calculated and experimental data shows that these fitting relationships can be reliably used to predict epsilon values, along with other related properties, in areas of experimental data gaps. Starting from the experimental measurements, some derived quantities such as molar orientational polarization (P), dipolar interaction free energy (Fmu) and the relevant thermodynamic excess mixing properties (F-mu(E), (F) over bar (E)(mu,i)), were obtained. The values of the excess quantities are indicative of the presence of specific interactions between different components in the mixtures. A discussion of data in terms of the Kirkwood theory also provides information on the short-range intermolecular interactions, suggesting the formation of stable two-component adducts rather than of more complex moieties involving all three molecular species.
2004
- Spettroscopia NIR, un metodo di analisi veloce e promettente
[Articolo su rivista]
M., Lucisano; Cocchi, Marina; M., Corbellini; Ma, Pagani; Ulrici, Alessandro; Foca, Giorgia
abstract
La spettroscopia NIR accoppiata all'analisi chemiometrica dei tracciati spettrali è illustarta com emetodica rapida, efficace e non distruttiva nel controllo di routine di alimenti cerealicoli
2003
- Applicazione dell’Algoritmo WPTER per la Classificazione di Spettri MIR di Farine Provenienti da Diversi Careali
[Relazione in Atti di Convegno]
Cocchi, M.; Foca, G.; Marchetti, Andrea; Sighinolfi, S.; Tassi, L.; Ulrici, A.
abstract
l’Algoritmo WPTER è stato utilizzato per la Classificazione di prodotti da forno ottenuti impiegando cereali diversi mediante spettri MIR i
2003
- Applicazione dell’algoritmo WPTER per la classificazione di spettri MIR di farine provenienti da diversi cereali
[Relazione in Atti di Convegno]
Cocchi, Marina; Foca, Giorgia; Marchetti, Andrea; Sighinolfi, Simona; Tassi, Lorenzo; Ulrici, Alessandro
abstract
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2003
- Density and volume properties of the 2-chloroethanol+2-methoxyethanol+1,2-dimethoxyethane ternary solvent system at different temperatures
[Articolo su rivista]
Ferrari, Giorgia; Foca, Giorgia; M., Manfredini; Manzini, Daniela; Marchetti, Andrea; Tassi, Lorenzo; Ulrici, Alessandro
abstract
The density of the 2-chloroethanol (CE) + 2-methoxyethanol (ME) + 1,2-dimethoxyethane (DME) ternary mixtures has been measured at different temperatures ranging from -10 to 80degreesC, and over the entire composition range. The experimental data have been used to check the validity of some relationships accounting for the dependence of the density on temperature and composition domains. Starting from the primary data, some derived quantities, such as excess molar volumes V-E, partial molar volumes (V) over bar (i) and partial excess molar volumes (V) over bar (E)(i), have been obtained. In these mixtures, V-E is always positive for the [CE(1) + ME(2)] binaries, while it is generally negative at all other experimental conditions, showing the greatest deviations along the binary axes corresponding to the binary subsystems in the sequence [CE(1) + DME(2)] < [CE(1) + ME(2)] < [ME(1) + DME(2)]. The results are compared and discussed to in terms of changes in molecular association and structural effects in these solvent systems.
2003
- Evaluation of the Colour of “Pesto” by means of Digital Image Analysis coupled to a Wavelet-Based Classification Algorithm
[Relazione in Atti di Convegno]
Antonelli, Andrea; Fava, Patrizia; Foca, Giorgia; Franchini, Giancarlo; Ulrici, Alessandro
abstract
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2003
- Il sistema solvente ternario 1,2-etandiolo + 1,2-dimetossietano + acqua: proprietà dielettriche a diverse temperature
[Relazione in Atti di Convegno]
Foca, Giorgia; Franchini, Giancarlo; Manfredini, Matteo; Manzini, Daniela; Tassi, Lorenzo; Ulrici, Alessandro; Zannini, Paolo
abstract
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2003
- Selective solvation of chiral compounds in binary mixtures of 2-butanone + 2-butanol
[Relazione in Atti di Convegno]
Faranda, S; Foca, Giorgia; Manfredini, Matteo; Marchetti, Andrea; Sighinolfi, Simona; Tassi, Lorenzo
abstract
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2003
- Solvatazione selettiva di biomolecole in miscele binarie 2-butanone + 2-butanolo
[Relazione in Atti di Convegno]
Foca, Giorgia; Manfredini, Matteo; Manzini, Daniela; Marchetti, Andrea; Sighinolfi, Simona; Tassi, Lorenzo; Zucchi, Claudia
abstract
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2003
- Valutazione del colore del “pesto” mediante analisi di immagini digitali e successiva classificazione utilizzando l’algoritmo WPTER
[Relazione in Atti di Convegno]
Antonelli, Andrea; Fava, Patrizia; Foca, Giorgia; Franchini, Giancarlo; Ulrici, Alessandro
abstract
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2002
- Caratterizzazione di farine di frumento mediante analisi PCA di spettri infrarossi
[Articolo su rivista]
Cocchi, Marina; Foca, Giorgia; Marchetti, Andrea; Tassi, Lorenzo; Ulrici, Alessandro
abstract
La qualità risulta essere un criterio fondamentale per la scelta dei prodotti alimentari da parte dei consumatori, pertanto le tecniche anaitiche che si occupano del controllo della composizione chimica degli alimenti e dell'individuazione di eventuali adulterazioni sono in continuo aumento.
2002
- Classificazione di mosti varietali rossi mediante PCA applicata a cromatogrammi HPLC di antociani
[Relazione in Atti di Convegno]
Camurali, M; Foca, Giorgia; Franchini, Giancarlo; TARANTINO E., M; Tassi, Lorenzo; Vignali, M.
abstract
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2002
- Classificazione di spettri MIR acquisiti su matrici di origine cerealicola mediante l’utilizzo dell’algoritmo WPTER
[Relazione in Atti di Convegno]
Cocchi, Marina; Foca, Giorgia; Marchetti, Andrea; Tassi, Lorenzo; Ulrici, Alessandro
abstract
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2002
- Il sistema ternario metanolo + etanolo + 1-propanolo: proprietà volumiche e disegno sperimentale di miscele solventi
[Relazione in Atti di Convegno]
Cocchi, Marina; Foca, Giorgia; Franchini, Giancarlo; Manfredini, Matteo; Manzini, Daniela; Marchetti, Andrea; Tassi, Lorenzo; Ulrici, Alessandro; Vignali, M.
abstract
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