[Show abstract][Hide abstract] ABSTRACT: Deoxynivalenol (DON) is the most common Fusarium-mycotoxin among the type B group of trichothecenes found at high concentration in cereals mainly produced by F. graminearum and F. culmorum. Analytical methods for the rapid evaluation of mycotoxins contamination of grains are highly needed in order to prevent the food chain contamination. The synthesis of mycotoxins is often associated with the production of volatile organic compounds (VOCs). These, when detectable through the use of suitable methods of analysis, represent a “fingerprint” of the contaminated samples. PTR-TOFMS technology was used for a rapid and efficient detection of DON in naturally contaminated durum wheat grain samples, by evaluating the correlations between selected patterns of volatile organic compounds with DON concentration. A partial least square (PLS) regression was used to efficiently quantify the DON value (r= 0.94 in the test set). A partial least squares discriminant analysis (PLSDA) was used to classify the samples above or below the fixed DON value of 1,750 μg/kg (91.9% of correct classification in the test set). Eight VOCs have been proven as good indicators in discriminating wheat samples, with DON concentration values above/below the legal limit 1,750 μg/kg, using both class-modeling approaches, partial least square (PLS) analysis and partial least squares discriminant analysis (PLSDA). The obtained results show a promising use of the PTR-TOFMS for the application of rapid, non-destructive, and massive screening of DON contaminated durum wheat samples.
Food Control 04/2015; 57. DOI:10.1016/j.foodcont.2015.03.047 · 2.81 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: The pellet market has experienced a continuous development and increase in recent years due to a number of positive properties of this enhanced biomass. However the supply chain has not been entirely able to follow the same trend, causing some issues, often related to the quality of traded products. These problems can be partially solved by ensuring a continuous and reliable flow of information regarding the quality parameters of wood pellets from the producers to the final users. The aim of this work is to define a metric index for quality parameters that can detect the certifiability of analyzed samples compared with those on the market. The model is built on measured quality parameters of certified and non-certified wood pellet samples taken from products on the market applying a multivariate class modelling methodology (soft independent modelling of class analogy, SIMCA). Results showed that the model can predict the general quality of some test samples and that its precision, already fairly high, can be constantly improved by adding new model samples. The output of the model is also the relative influence (modelling power) of each variable in the prediction of certifiability. The SIMCA model could be easily integrated and implemented on the most common digital platforms where users (private, laboratories, agencies, etc.) could test their samples and verify if the index of their pellet falls within the area defined by the model for certified samples.
Renewable Energy 04/2015; 76:258-263. DOI:10.1016/j.renene.2014.11.041 · 3.48 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: The trade of fresh fruits from tropical countries has steadily increased over the past decades, but limited familiarity of consumers with these products has limited their introduction in worldwide markets. The increasing competition in European and international fruit markets is generating the need for improved ripeness evaluation techniques to assess fruit quality standards. As tropical fruits produce a wide range of volatile organic compounds (VOCs), PTR-ToF-MS was used to fingerprint the volatile profile of four tropical fruits (avocado, banana, mango and mangosteen) and determine whether this instrument could be used to assess fruit ripening stages, which was measured with traditional methods. Data were subsequently subjected to partial least squares discriminant analysis. By pooling the entire dataset together, it emerges that VOCs and chemical analyses enabled the separation of the two different ripening stages of all fruits, while skin color and fruit firmness did not always enable that separation. For avocado, banana and mangosteen, it was possible to observe the process of maturation during the shelf life, via physicochemical parameters and VOC analysis, whereas for mango, the constant production of methanol and acetaldehyde detected at both stages, together with the unchanged of evolution of the physicochemical parameters (TSS, pH and color), indicated a lack of maturation. Given the rapidity and the potential to use this analysis method on a large scale, the PTR-ToF-MS has a high potential to become a commercial standard tool for monitoring food quality from entering the storage chain up to the ‘ready to eat’ labeling.
European Food Research and Technology 02/2015; 241(1). DOI:10.1007/s00217-015-2438-6 · 1.56 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: The European technical standard EN 14961 on solid biofuels determines the fuel quality
classes and specifications for wood chips. Sieving methods are currently used for the determination of
particle size distribution. Some authors suggested that image analysis tools could provide methods for
a more accurate measure of size integrated with shape. This work for the first time analyzes how image
analysis combined with multivariate modeling methods could be used to construct cumulative size
distribution curves based on chip mass (or weight). This has been done through a Partial Least Squares
Regression model for the weight prediction of poplar chips and Partial Least Squares Discriminant
Analysis models for estimation of chips size classification. Images of 7583 poplar chips were analyzed
to extract size and shape descriptors (area, major and minor axis lengths, perimeter, eccentricity,
equivalent diameter, fractal dimension index, Feret diameters and Fourier descriptors). The weight
prediction model showed an high accuracy (r = 0.94). The chip classification based on three size
fractions (8-16 mm, 16-45 mm and 45-63 mm), with or without Fourier descriptors, showed
accuracies equal to 92.9% of correct classification for both models in the independent test. The
combination of image analysis with multivariate modeling approaches allow a better conversion of
image analysis results to sieve results using the esteemed weight. The proposed method will allow to
standardize processes applicable by biofuels laboratories and machinery certifiers.
Biomass and Bioenergy 12/2014; 73. DOI:10.1016/j.biombioe.2014.12.001 · 3.39 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: Color of wood pellets is mainly affected by the feedstock material used for their production and which composition and characteristic affect the final product quality. Pellets made from pure wood are light in color and have low ash content, while pellets made from different mixtures of wood and bark or foliage are generally darker and richer in minerals. This study aims to verify the correlation between color and quality parameters of wood pellets available on the Italian market. All the samples were analyzed following the procedures laid down by the European Norms (EN) on solid biofuels for moisture, ash, calorific value, durability, bulk and solid density. The acquisition of the images was done with two techniques: the CIE L∗a∗b∗ color space and RGB-HSV color spaces. Canonical correlation analysis (CCA) was performed with CIE-L∗a∗b, RGB and HSV separately showing for all the color components good degree of correlation with ash content of pellets. The PCA analysis on two principal components (total explained variance: 64.2%) showed a clear color gradient moving form good to medium or low quality parameters. This pattern is confirmed by the clustering of certified pellets in the region of lightest samples. The calculation of ΔE and ΔRGB showed a good discrimination level between whole pellets samples and their sawdust, and between ones with high and low ash content. The visual predictability of pellets quality on the basis of their color is however not so sharp when considering samples with similar colors. The industrial applicability of such methods for the evaluation of pellets quality is desirable for RGB methodologies that are less expensive and more reliable in working condition, given that specific color calibration is performed.
[Show abstract][Hide abstract] ABSTRACT: Forecasting symptoms of pollen-related allergic rhinoconjunctivitis at the level of individual patients would be useful to improve disease control and plan pharmacological intervention. Information Technology nowadays facilitates a more efficient and easier monitoring of patients with chronic diseases. We aimed this study at testing the efficiency of a model to short-term forecast symptoms of pollen-AR at the "individual" patient level. We analysed the data prospectively acquired from a group of 21 Italian children affected by pollen-related allergic rhinoconjunctivitis and recorded their symptoms and medication "Average Combined Score" (ACS) on a daily basis during April-June 2010-2011 through an informatics platform (Allergymonitor™). The dataset used for prediction included 15 variables in four categories: (A) date, (B) meteo-climatic, (C) atmospheric concentration of 5 pollen taxa, and (D) intensity of the patient's IgE sensitization. A Partial Least Squares Discriminant Analysis approach was used in order to predict ACS values above a fixed threshold value (0.5). The best performing predicting model correctly classified 77.8% ± 10.3% and 75.5% ± 13.2% of the recorded days in the model and test years, respectively. In this model, 9/21 patients showed ≥ 80% correct classification of the recorded days in both years. A better performance was associated with a higher degree of patient's atopic sensitization and a time lag > 1. Symptom forecasts of seasonal allergic rhinitis are possible in highly polysensitised patients in areas with complex pollen exposure. However, only predictive models tailored to the individual patient's allergic susceptibility are accurate enough. Multicenter studies in large population samples adopting the same acquisition data system on smart phones are now needed to confirm this encouraging outcome.
European annals of allergy and clinical immunology 11/2014; 46(6):216-225.
[Show abstract][Hide abstract] ABSTRACT: The field measurements of swimming activity rhythms of fishes are scant for the difficulty of counting individuals at a high frequency over a large period of time. Cabled observatory video monitoring allows such a sampling at a high frequency. Unfortunately, automated animal visual counting is still a major bottleneck. We developed a new automated video-imaging protocol for the 24-h continuous counting of fishes in calorimetrically calibrated time-lapse photographic outputs, taken by a shallow water (20 m depth) cabled video-platform, the OBSEA. All the images were acquired within a standardized Region Of Interest, represented by a 2 x 2 m methacrylate panel, endowed with a 9-colour calibration chart, and calibrated using the recently implemented “3D Thin-Plate Spline” warping approach.
[Show abstract][Hide abstract] ABSTRACT: A two-year study was conducted in an organic vineyard to evaluate the phytochemical content and antioxidant capacity of grapes treated with low-rate copper quantities for downy mildew control, in comparison with an untreated test and to a standard fungicide. The metabolic profile and antioxidant capacity were analyzed in relationship with the results of downy mildew incidence and severity. The maturity level of grapes appeared an important parameter in determining the potential risk for the spread of fungal disease, as suggested by the results of PCA analysis that showed a positive relationship between the tartaric acid content with both incidence and severity of downy mildew disease. Polyphenols and thiols amounts resulted higher in grape berries with lower disease levels. The thiols were highly correlated with the antioxidant capacity, indicating an important role of these metabolites in determining the antioxidant potential of grape berries. Moreover, the fact that in PCA both the antioxidant indexes and thiols were plotted at the opposite of the disease severity and incidence, suggests that an higher antioxidant potential may be responsible for a better capacity of grapes to counteract the disease. Finally, the present findings showed that low-copper formulations were able to control grape downy mildew in the field with a similar effectiveness compared to the standard reference fungicide, without affecting the phytochemical profile and the antioxidant potential of grapes. Low-copper formulations may be thus considered alternative formulates to be used in organic agriculture in order to minimize costs as well as copper accumulation in the soil, so ensuring the most possible grape quality in a sustainable crop management.
American Journal of Enology and Viticulture 07/2014; 65(4). DOI:10.5344/ajev.2014.14028 · 1.39 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: Wheat durum pasta represents one of the most typical Italian food products. Many factories realize different class products regarding the use of organic wheat or not and the application of traditional or industrial production parameters. Being not subordinate to regulations, these classifications are only indicative of the real processes representing different quantitative levels for the same class. Aim of this study is to set up a rapid and nondestructive method to distinguish between different declared production parameters of pasta brands (spaghetti) such as industrial (high temperature, short-time drying, Teflon drawn) and traditional (low temperature, long-time drying, bronze drawn) processes and the use of organic wheat or not. A hyperspectral system operating within visible and near-infrared spectra was used to acquire images of spaghetti bundles (of two different years). Hyperspectral information was statistically analyzed by multivariate provisional soft independent modeling of class analogy (SIMCA). The results report a percentage of correct classification equal to 75.3 % for the first year and to 73.9 % for the second year. For both sampling years, all the traditional brands are the most distant from the origin (i.e., full industrial model). The Spearman's cross-correlation test performed on the SIMCA distances indicates a statistically significant correlation between the 2 years of analysis confirming the system repeatability. The results demonstrate that the differentiation of pasta does not depend only on the raw material (i.e., organic and not) but also on the times and types of processing (i.e., short- and long-time drying, bronze or Teflon wire drawing).
[Show abstract][Hide abstract] ABSTRACT: A low-cost dual web-camera high-resolution system was developed to obtain three-dimensional position of homologous points in a scene. Two different softwares have been developed in Matlab environment. The first to acquire couples of frames by the two web-cameras, the second to process the images and obtain the points position in the space and so the distances between points. Distances between points have been corrected using a Partial Least Square regression. The efficiency of the system has been evaluated on a calibration setup experiment and then on 27 live Alpagota sheep. In the calibration phase, at a distance lower than 10 m, mean size errors were always lower than 2%. Measures on the Alpagota sheeps showed lower errors for withers height and chest depth (around 3.5%) and higher for body length (around 5.0%). These higher errors, with respect to the ones in the calibration phase, are partially due to the precision of the manual measurements on the animals. Sheep weight estimation using a PLS model on log transformed biometries showed SEP values on the data manually measured and on the stereovision extracted equal to 3.6 kg and 4.4 kg respectively. Being so inexpensive, ready-to-use and easily transportable this system could find application in other biosystems fields such as forestry, agriculture and environment.
Computers and Electronics in Agriculture 04/2014; 103:33–38. DOI:10.1016/j.compag.2014.01.018 · 1.76 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: Forecasting pollen concentrations in the short term is a topic of major importance in aerobiology. Forecasting models proposed in the literature are numerous and increasingly complex, but they fail in at least 25 % of cases and are not available for all botanical species. This work makes it possible to build a forecast model from meteorological data for estimating pollen concentration over a certain threshold of Poaceae, an allergenic family. In Italy, about 25 % of the population suffer from allergies, these in 80 % of cases being caused by airborne allergens, including taxa of agricultural interest such as Poaceae. The pollen dispersion in air is determined by both the phenological stage of plants and the meteorological conditions; the pollen presence varies according to the year, month and even the time of the day. There is a correlation between environmental factors, pollen concentrations and pollinosis. A partial least squares discriminant analysis approach was used in order to predict the presence of Poaceae pollen in the atmosphere with a time lag of 3, 5, 7 days, on the basis of a data set of 14 meteorological and pollen variables over a period of 14 years (1997–2010). The results show a high accuracy in predicting pollen critical concentrations, with values ranging from 85.4 to 88.0 %. This study is hopefully a positive first step in the use of a statistical approach that in the next future could have clinical applications.
[Show abstract][Hide abstract] ABSTRACT: The shape of an object can be described by a finite
number of points called landmarks. Nowadays, there are no
systems available for the automated landmarks detection.
However, the implementation of such method would be of
elevated interest in the food industrial processing. The evaluation
of cattle carcass and fish quality requires the timeconsuming
and manual positioning of landmarks, with still
too subjective results. The aim of this work is the application
of an innovative algorithm, called backwarping, for the automated
positioning of landmarks onto the beef carcass and sea
bass profiles. This algorithm combines the automated extraction
of the outlines with the thin-plate spline interpolation
algorithm. The proposed approach is applied to two very
different cases in order to stress the high performing versatility
of the procedure. We firstly carried out a calibration phase
where the landmarks were manually placed. Then we applied
the automated procedure for comparison. The errors in the
automated landmarks positioning has been always lower than
3 % and the percentage standard error of prediction was
always lower than 1.5 %. The approach for both study cases
showed its feasibility in being easily extended to the processing
of a diversified variety of food products, such as poultry,
bakery or “pasta.” Moreover, due to its versatility, the technique
could be also applied within the zoological and biomedical
fields, given the obtained high levels of accuracy in the
automated landmark positioning.
[Show abstract][Hide abstract] ABSTRACT: NEMO-SN1 is the cabled node in the Western Ionian Sea of EMSO Research Infrastructure (European Multidisciplinary Seafloor and water-column Observatory; www.emso-eu.org). EMSO is aimed at establishing, implementing and operating ocean observatories from the Arctic, the Atlantic Ocean and to the Mediterranean, for long-term observations and studies of geo-hazards, climate change and marine ecosystems. In this scenario, we describe the next implementation of the NEMO-SN1 node within the framework of the CREEP-2 project, led by the Rock & Ice Physics Laboratory at University College London) and funded by NERC. A video-camera system will be deployed at 2100 m depth, with the major objective of monitoring the local benthic community and its temporal changes at high frequency over a very large period of time. Briefly, the camera system (Luxus Colour Zoom) will be installed onto the frame of a multi-sample rock deformation apparatus, assembled for geophysical experiments devoted to the monitoring of ultra-long-term brittle creep in crustal rocks (including acoustic emission output as a proxy for crustal seismicity). Here, we will describe the system architecture in terms of hardware equipment and software requirements, considering the needs of time-lapse video image acquisition for the high frequency monitoring of the community. The use of that video-imaging will be discussed in relation to potential ecological research scenarios related to the behaviourally sustained benthopelagic coupling, the study of which is of relevance to understand the dynamism of deep-sea communities.
[Show abstract][Hide abstract] ABSTRACT: Field measurements of the swimming activity rhythms of fishes are scant due to the difficulty of counting individuals at a high frequency over a long period of time. Cabled observatory video monitoring allows such a sampling at a high frequency over unlimited periods of time. Unfortunately, automation for the extraction of biological information (i.e., animals' visual counts per unit of time) is still a major bottleneck. In this study, we describe a new automated video-imaging protocol for the 24-h continuous counting of fishes in colorimetrically calibrated time-lapse photographic outputs, taken by a shallow water (20 m depth) cabled video-platform, the OBSEA. The spectral reflectance value for each patch was measured between 400 to 700 nm and then converted into standard RGB, used as a reference for all subsequent calibrations. All the images were acquired within a standardized Region Of Interest (ROI), represented by a 2 × 2 m methacrylate panel, endowed with a 9-colour calibration chart, and calibrated using the recently implemented "3D Thin-Plate Spline" warping approach in order to numerically define color by its coordinates in n-dimensional space. That operation was repeated on a subset of images, 500 images as a training set, manually selected since acquired under optimum visibility conditions. All images plus those for the training set were ordered together through Principal Component Analysis allowing the selection of 614 images (67.6%) out of 908 as a total corresponding to 18 days (at 30 min frequency). The Roberts operator (used in image processing and computer vision for edge detection) was used to highlights regions of high spatial colour gradient corresponding to fishes' bodies. Time series in manual and visual counts were compared together for efficiency evaluation. Periodogram and waveform analysis outputs provided very similar results, although quantified parameters in relation to the strength of respective rhythms were different. Results indicate that automation efficiency is limited by optimum visibility conditions. Data sets from manual counting present the larger day-night fluctuations in comparison to those derived from automation. This comparison indicates that the automation protocol subestimate fish numbers but it is anyway suitable for the study of community activity rhythms.
[Show abstract][Hide abstract] ABSTRACT: Product diversification, among which organic farming, is an important issue in modern aquaculture activities. Discriminating organic vs. conventional products is complex, but appearance may help in tracing different batches of produce. To test this fact, sea basses were fed a commercial or an organic diet, and fishes of each different group were photographed before and during the experiment. Body landmarks were digitized on each colour-calibrated (using the TPS-3D algorithm) image; on the basis of landmarks configuration, the RGB matrices were warped using a geometric morphometrics procedure. The calibrated colour matrix of each warped individual (195 × 135,225) was analyzed with a 50–50 MANOVA, followed by a partial least squares discriminant analysis. Finally, a cluster analysis on the diet/time groups was performed. Growth and changes in condition factor over time are not dependent on the rearing method. Colour (as represented by the pixel vector) does depend on time and on rearing method, based on the MANOVA method used. Standard length and condition factor were not good predictors of colour. The partial least square discriminant analysis was highly effective in detecting colour differences on the basis of the fish diet. The 9-group dendrogram showed that the wild sample and the organic fish cluster together. The head, darker in fishes raised conventionally, is the part showing the greatest difference; the longer the life spent under the 2 regimens, the stronger the differences. In conclusion, these preliminary results demonstrate that a colorimetric analysis is able to distinguish 2 batches of fishes fed different diets in different environmental conditions and – in the present instance – to certify the organically grown sea basses.
[Show abstract][Hide abstract] ABSTRACT: The levels of environmental light experienced by organisms during the behavioral activity phase deeply influence the performance of important ecological tasks. As a result, their shape and coloring may experience a light-driven selection process via the day-night rhythmic behavior. In this study, we tested the phenotypic and genetic variability of the western Mediterranean squat lobster (Munida tenuimana). We sampled at depths with different photic conditions and potentially, different burrow emergence rhythms. We performed day-night hauling at different depths, above and below the twilight zone end (i.e., 700 m, 1200 m, 1350 m, and 1500 m), to portray the occurrence of any burrow emergence rhythmicity. Collected animals were screened for shape and size (by geometric morphometry), spectrum and color variation (by photometric analysis), as well as for sequence variation at the mitochondrial DNA gene encoding for the NADH dehydrogenase subunit I. We found that a weak genetic structuring and shape homogeneity occurred together with significant variations in size, with the smaller individuals living at the twilight zone inferior limit and the larger individuals above and below. The infra-red wavelengths of spectral reflectance varied significantly with depth while the blue-green ones were size-dependent and expressed in smaller animals, which has a very small spectral reflectance. The effects of solar and bioluminescence lighting are discussed as depth-dependent evolutionary forces likely influencing the behavioral rhythms and coloring of Munida tenuimana.
Progress In Oceanography 09/2013; 118. DOI:10.1016/j.pocean.2013.07.011 · 3.03 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: In food science, colour is a fundamental property for the evaluation of freshness, quality and conformity. One of the most important attributes indicating sweet cherry freshness is stem colour and shape. Fruit post-harvest cool storage retards respiration and colour ripening changes. The common technology of refrigeration is based on active cooling determining high evapotranspiration for the passage of air over the products surface. An innovative preservation system, such as the Passive Refrigeration System (PRS™), could guarantee perfect shelf-life preservation maintaining optimal temperature and relative humidity close to 100%, minimizing colour changes in medium-long storage range. There is the need to numerically quantify cherry stem thickness and colour changes to compare fruit postharvest conditions under the two systems. The use of the Thin-Plate Spline 3D warping (TPS3D) in the 3-dimensional-RGB colour space allowed an efficient colour calibration. Sweet cherry stem images belonging to the two different storage systems (active and passive refrigeration) were acquired before and after 7 days to preservation through a professional high resolution scanner. Thickness and colour (after calibration) were measured. Results indicate, in terms of sweet cherry quality of preservation, that the ones preserved in passive refrigerator after 7 days appears similar to the fruits at the beginning of the experiment.