Paolo Menesatti

CRA Agricultural Research Council, Roma, Latium, Italy

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Publications (83)127.04 Total impact

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    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; · 1.86 Impact Factor
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    ABSTRACT: Proton Transfer Reaction-Mass Spectrometry (PTR-MS), in its recently developed implementation based on a time-of-flight mass spectrometer (PTR-TOFMS), was used to rapidly determine the volatile compounds present in fruits of Capsicum spp.
    Journal of the Science of Food and Agriculture 05/2014; · 1.88 Impact Factor
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    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).
    Food and Bioprocess Technology 05/2014; · 4.12 Impact Factor
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    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.
    Aerobiologia 03/2014; · 1.33 Impact Factor
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    Computers and Electronics in Agriculture 01/2014; 103:33–38. · 1.77 Impact Factor
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    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.
    Fuel. 01/2014; 137:70–76.
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    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.
    Food and Bioprocess Technology 12/2013; · 4.12 Impact Factor
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    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.
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    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.
    Aquacultural Engineering 11/2013; · 1.41 Impact Factor
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    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; · 3.71 Impact Factor
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    ABSTRACT: In this study, we present and test the functioning of a automated multi-flume actograph that is able to simulate concomitant geophysical cycles (day-night and hydrodynamic cycles) characterizing the benthic environment of continental margins. The burrowing Norway lobster (Nephrops norvegicus, L.) was used to test the functioning of the device. The system is endowed with pumps and a pipe system for periodical current flow generation. Monochromatic blue light cycle (472 nm) was provided by submergible LED's lighting strips. Locomotor activity of 8 individuals was tracked by 4 HD video cameras during a 10 days trial. A customized automated video-imaging protocol in MATLAB calculated displacement of animals (cm/min). The functioning of the system was tested simulating an Atlantic continental shelf scenario (i.e. light intensity of 4 · 10−3 μE/m2/s and current flow at 10 cm/s). Robust time series outputs of nocturnal phase were reported, with the first laboratory evidence of the influence of current flow on burrow emergence of the species. Water flow increase inhibited lobster movement generating a dual reaction in relation to their burrow emergence phase. The method presented here could be pivotal to study unknown aspects of Norway lobster ecology.
    Journal of Experimental Marine Biology and Ecology 06/2013; 446:177-185. · 2.26 Impact Factor
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    ABSTRACT: Constraints in sampling repeatability at statistically relevant frequencies are limiting the progress of marine ecology, especially in the vast and still largely unexplored deep sea. Within the framework of novel cabled observatory science, it is now possible to study and monitor the fauna of geologically different ecosystems at any depth of the continental margin and abyssal plains, at sampling frequencies and over temporal durations never attained before (i.e. from seconds to decades). New multiparametric platforms endowed with video cameras that are being progressively installed in different oceans, can be used not only for a broad faunal characterization but also to quantify the massive three-dimensional displacements of marine populations in response to cyclic oceanographic, chemical, and geologic fluctuations (also measured in a multiparametric fashion). Here, we will review how automated video-imaging protocols for animal classification and counting could be implemented to transform the video-camera into one of the first intelligent marine sensors for remote, autonomous and continuous monitoring of communities in relation to their diel (i.e. inertial, internal-tidal or day-night), seasonal, and inter-annual cycles of functioning. We will also discuss the possibility to study the responses of benthic species to other more stochastic habitat changes (e.g. those induced in the water column by the meteorology), through the measurement of modifications in water column properties by observatory vertical elongations. Studies of this kind may allow an efficient modeling of marine community modifications in view of future climate change scenarios, based on alterations of the benthopelagic coupling equilibrium. A special emphasis will also be given to the faunal monitoring prior and after catastrophic events (e-g-seismic activity or tsunamis), to initiate a critical discussion on the reliability of biologically-based early warning systems based on the continuous monitoring of the deep sea. The reliability of these systems should be evaluated by considering whether significant changes in automatically video-counted benthos occur prior to, or only after, the incoming catastrophe.
    International Symposium on Underwater Technology (UT13); 03/2013
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    ABSTRACT: Highlights ► Compare two VIS–NIR spectral based methods (laboratory vs. in-field). ► These methods early detect the Fusarium head blight infection in durum wheat. ► Two conditions are tested: diseased and healthy plants. ► Two multivariate statistical approaches are used: 50–50 MANOVA and PLSDA. ► Laboratory approach reports higher performance with respect to in-field ones.
    Biosystems Engineering. 03/2013; 114(3):289–293.
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    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.
    Sensors 01/2013; 13(11):14740-53. · 2.05 Impact Factor
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    ABSTRACT: The Norway lobster is a burrowing decapod of elevated commercial importance for the European fishery. Understand which factors affect its diel (24-h based) catchability is of importance for its stock assessment. Here we presented preliminary results on burrow emergence modulation on lobsters exposed to water flow cycles in the laboratory simulating internal tides.
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    ABSTRACT: BACKGROUND: The aim of this study was to extract a sorting rule for Tarocco orange fruit from several physicochemical and sensory tests performed on a marketable lot of 399 Tarocco orange fruits. RESULTS: The elastic tension at 5% strain (T(5) ) was found to be linearly correlated (r = 0.65) with the Magness-Taylor (MT) index. Thus T(5) was regarded as a non-destructive parameter quantifying fruit firmness and used to categorise the aforementioned lot in three different firmness classes, high (HF), medium (MF) and low (LF). Only the MT index, fruit rind thickness near the fruit peduncle, lightness coefficient and yellow/blue hue component of the orange flesh, as well as total soluble solid content, confirmed the validity of this discrimination at the significance level of 5%. Sensory professionals recognised the greater compactness (7 ± 2) but lower ease of peeling (4 ± 2) and segment separation (4 ± 2) of the HF oranges with respect to the corresponding sensory attributes of orange fruits grouped in the MF and LF classes. CONCLUSION: To limit the costly rejection of Tarocco orange fruit considered too soft, especially after long-term shipping, it would be reasonable to select only fruits characterised by a compressive force or tension at 5% strain in the range 23-41 N or 300-540 N m(-1) respectively. Copyright © 2012 Society of Chemical Industry.
    Journal of the Science of Food and Agriculture 10/2012; · 1.88 Impact Factor
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    ABSTRACT: The aim of this study is the integration of an electronic tracing system with a non-destructive quality analysis system for single product of a typical Italian cheese, prepared with buffalo milk and called “Caciottina massaggiata di Amaseno”, a typical diary product of Lazio Region. The tracing and quality information are combined on a web platform to obtain a complete procedure to develop what we define as an “infotracing system”. Quality analyses (chemical, sensorial and spectrophotometric) were carried out on a total of 23 cheese wheels (8 with TAGs) and for three cheese maturation classes (3, 6 or 9 months after production). Two typologies of RFID tags were tested. Results were screened by Partial Least Squares regressions (PLS) on reflectance values for the prediction of chemical content, while classification of cheese maturation classes (3, 6 or 9 months) was carried out by Partial Least Squares Discriminant Analysis (PLSDA) on reflectance values. The RFID system turned out as effective, reliable and compatible with the production process tool. A good estimation of maturation degree by spectral and chemical analysis was obtained. Moreover an infotracing web-based system was designed to acquire and link basic information that can be made available to the final consumer or to different food chain actors before or after purchasing, using the RFID code to identify the single and specific cheese product. The projected web-based tracing system could improve the products commerce by increasing the information transparency for the consumer.
    Food Control. 09/2012; 27(1):234–241.
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    ABSTRACT: The objective of this research was to develop a hyperspectral imaging system for estimating copper concentration in soils as an alternative to standard chemical analyses and to evaluate the analytical accuracy of the system using the visible–near-infrared and near-infrared regions. Hyperspectral imaging is a complex technology providing elevated information content. This work was carried out on air-dried <2-mm soil fraction contaminated by adding 20 mL of copper sulfate at concentrations ranging from 0 to 1000 mg of copper per kg of soil. The samples were scanned in random order and with orientation using visible–near-infrared and near-infrared spectrophotometers. A range of partial least squares regression models derived from the spectral arrays were tested on their ability to predict copper concentration. Significant correlations between predicted and known chemical concentrations were achieved with a correlation coefficient of 0.93 for the visible–near-infrared and 0.77 for the near infrared.
    Communications in Soil Science and Plant Analysis 05/2012; 43(10):1401-1411. · 0.42 Impact Factor

Publication Stats

309 Citations
127.04 Total Impact Points

Institutions

  • 2008–2014
    • CRA Agricultural Research Council
      • Research Unit for Agricultural Engineering (Roma) (CRA-ING)
      Roma, Latium, Italy
  • 2011
    • Tuscia University
      Viterbo, Latium, Italy
    • Università degli Studi di Perugia
      • Department of Environmental and Agricultural Sciences
      Terni, Umbria, Italy
  • 2009
    • Institut de Ciències del Mar
      Barcino, Catalonia, Spain
    • Spanish National Research Council
      Madrid, Madrid, Spain