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Stahl V.,Technical Institute for Food Industry | Ndoye F.T.,IRSTEA | El Jabri M.,Technical Institute for Food Industry | Le Page J.F.,Technical Institute for Food Industry | And 5 more authors.
Journal of Food Engineering | Year: 2015

It is of crucial importance for Ready-To-Eat (RTE) foodstuffs producers to guarantee the quality and safety of their products under the cold chain variations related to different time-temperature profiles. Experimental designs were used to investigate and model the effects of temperature on safety and quality attributes of selected RTE meat products. Three types of RTE sliced pork products (cooked ham, cooked paté and smoked ham) were stored at different temperatures (5, 8, 12 and 15 °C) up to 6 weeks. Microbiological and physico-chemical attributes were followed. Growth parameters of Listeria monocytogenes were investigated by challenge testing for the three RTE products at the four temperatures. Two lactic acid bacteria (Lactobacillus sakei and Leuconostoc mesenteroïdes) were also investigated by challenge testing but only for cooked ham and cooked paté at 8°C. Changes in quality indicators including colour, texture and water content, water activity and water dripping were evaluated over storage time for the three RTE products. Spoilage experiments were conducted (at 2, 8, 12, 15°C for 48 days) on cooked ham and the production of ethanol, as a representative volatile deriving from bacterial metabolism, was correlated to bacterial outgrowth. Growth parameters of the three strains for the given food were mathematically modelled and validation tests were performed for L. monocytogenes in cooked ham and cooked paté. Physico-chemical attributes were not significantly affected by time-temperature storage. The production of ethanol on spoiled cooked ham was related to growth of lactic acid bacteria, especially Leuconostoc. A threshold value of ethanol concentration was defined in relation with a threshold count numbers of LAB under the conditions studied. © 2014 Elsevier Ltd. All rights reserved. Source

Mao D.,Hunan Normal University | Yu F.,Hunan Normal University | Li J.,Hunan Normal University | Van De Poel B.,Biostatistics and Sensors MeBioS | And 7 more authors.
Plant, Cell and Environment | Year: 2015

Environmental inputs such as stress can modulate plant cell metabolism, but the detailed mechanism remains unclear. We report here that FERONIA (FER), a plasma membrane receptor-like kinase, may negatively regulate the S-adenosylmethionine (SAM) synthesis by interacting with two S-adenosylmethionine synthases (SAM1 and SAM2). SAM participates in ethylene, nicotianamine and polyamine biosynthetic pathways and provides the methyl group for protein and DNA methylation reactions. The Arabidopsis fer mutants contained a higher level of SAM and ethylene in plant tissues and displayed a dwarf phenotype. Such phenotype in the fer mutants was mimicked by over-expressing the S-adenosylmethionine synthetase in transgenic plants, whereas sam1/2 double mutant showed an opposite phenotype. We propose that FER receptor kinase, in response to environmental stress and plant hormones such as auxin and BR, interacts with SAM synthases and down-regulates ethylene biosynthesis. © 2015 John Wiley & Sons Ltd. Source

Bravo E.L.,Biostatistics and Sensors MeBioS | Tijskens E.,University "Marta Abreu" of Las Villas | Suarez M.H.,Biostatistics and Sensors MeBioS | Ramon H.,Biostatistics and Sensors MeBioS
Particle-Based Methods II - Fundamentals and Applications | Year: 2011

High pressures on the soil surface by action of heavy machinery and tillage process cause soil compaction and hardpan layers formation. De-compaction is a energy demanding operation applied to break deeply compacted soil for agricultural uses. Three dimensional simulations of soil decompaction are presented based on a soil-tool interaction model implemented in DEMeter software. Formulation of soil-soil and soil-tool interaction are combined into an elastic-plastic particle based model for soil deformation and evaluated in different tension states among soil particles; The macromechanical input parameters include: adhesion, friction, Young's modulus, Poisson's coefficient, elastic limit, plastic limit and soil density. Compression triaxial tests and shear box tests were carried out in order to obtain the required mechanical properties for a tropical clay soil. Simulations of unconfined compression tests using different particle sizes and inter-particle tension were used to calibrate the model to experimental stress-strain curves. The performance of complex tillage tools geometries is tested with 3D simulations and evaluated based on the reaction force on the tool as a function of time and displacement. The results show qualitative and quantitative adjusts of real patter of soil behaviour. Source

Mouazen A.M.,Cranfield University | Kuang B.,Cranfield University | De Baerdemaeker J.,Biostatistics and Sensors MeBioS | Ramon H.,Biostatistics and Sensors MeBioS
Geoderma | Year: 2010

The selection of calibration method is one of the main factors influencing the measurement accuracy with visible (vis) and near infrared (NIR) spectroscopy. This paper compared the performance of three calibration methods, namely, principal component regression (PCR), partial least squares regression (PLSR) and back propagation neural network (BPNN) analyses for the accuracy of measurement of selected soil properties, namely, organic carbon (OC) and extractable forms of potassium (K), sodium (Na), magnesium (Mg) and phosphorous (P). A total of 168 soil samples collected from Belgium and Northern France were used as the data set for the calibration-validation procedure. Optical scanning was carried out on fresh soil samples with a fibre-type, vis-NIR (LabSpec®Pro Near Infrared Analyzer, Analytical Spectral Devices, Inc, USA) with a measurement range of 350-2500 nm. The entire data set was split randomly into 3 replicates of 90% and 10% for the cross-validation set and prediction set, respectively. The input of BPNN was the first 5 principal components (PCs) resulted from the principal component analysis (PCA) and the optimal number of latent variables (LVs) obtained from PLSR. Both the leave-one-out cross validation and prediction for the three replicates showed that all BPNN-LV models outperformed PCR, PLSR and BPNN-PCs models. Furthermore, BPNN-PCs and PLSR provided, respectively, better performance than PCR. The best predictions were obtained with BPNN-LVs modelling for OC (Rpre2 = 0.84 and residual prediction deviation (RPD) = 2.54) and Mg (Rpre2 = 0.82 and RPD = 2.54), which were classified as excellent model predictions. The prediction of K, P and Na was classified as good (Rpre2 = 0.68-0.74 and RPD = 1.77-1.94), where quantitative predictions were considered possible. It is recommended to adopt BPNN-LVs modelling technique for higher accuracy measurement of the selected soil properties with vis-NIR spectroscopy, in comparison with PCR, PLS and BPNN-PCs modelling techniques. © 2010 Elsevier B.V. All rights reserved. Source

Bravo E.L.,University "Marta Abreu" of Las Villas | Tijskens E.,Biostatistics and Sensors MeBioS | Suarez M.H.,University "Marta Abreu" of Las Villas | Gonzalez Cueto O.,University "Marta Abreu" of Las Villas | Ramon H.,Biostatistics and Sensors MeBioS
Computers and Electronics in Agriculture | Year: 2014

In the present study the discrete element method is used for predicting forces reactions and soil behavior during non-inversion tillage. The numerical model at particle level works with a force system integrated by normal, shear, cohesion and friction forces. Macro parameters are defined as the soil mechanical properties obtained by soil mechanical tests. The behavior of soil-soil and soil-metal interface at different dry bulk densities and gravimetric water contents were determined by modified direct shear box and triaxial compression tests. A set of statistical regression equations feasible to estimate the macro values of Young's modulus, shear strength, soil friction and soil cohesion were obtained. The relationship between macro and micro behavior of soil friction was investigated by means of the simulation of direct shear tests. The discrete soil model was used to simulate soil tillage at conditions called hard- dry, soft- wet and friable state. To calibrate the model, a soil-bin was filled with the soil previously characterized and equipped with a tool similar to the one used for the simulation. A National Instrument Data Logger system was configured aimed at measuring vertical and horizontal reaction forces. The comparison between draft forces from simulation and soil-bin tests showed a small under-predicted behavior of the model for loose soil with high moisture; this behavior was fixed toward compacted and dry soil conditions. Para-plough and moldboard were the tools used for non-inversion tillage simulation at different physical states of the soil. The result shows the pattern of movement and force distribution related with the geometry of the tool. © 2014 Elsevier B.V. Source

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