The Experts below are selected from a list of 252 Experts worldwide ranked by ideXlab platform
Yong He - One of the best experts on this subject based on the ideXlab platform.
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determination of Calcium Content in powdered milk using near and mid infrared spectroscopy with variable selection and chemometrics
Food and Bioprocess Technology, 2012Co-Authors: Di Wu, Yong HeAbstract:Near infrared (NIR) and mid-infrared (MIR) spectroscopy techniques were evaluated to determine Calcium Content in powdered milk. A hybrid spectral variable selection algorithm combined with uninformation variable elimination (UVE) and successive projections algorithm (SPA) selected 11 NIR and 15 MIR variables from full 2,756 NIR and 3,727 MIR variables, respectively. Predicted results of least-squares support vector machine models for the samples in the prediction set show that the 15 MIR variables obtained much better results (0.930 for coefficient of determination (r 2), 3.703 for residual predictive deviation (RPD), 30.162 for root mean square error of prediction set (RMSEP) and 5.22% for relative errors of prediction (RSEP)) than 11 NIR variables did (0.636 for r 2, 1.587 for RPD, 78.815 for RMSEP, and 13.40% for RSEP). The overall results indicate that MIR spectroscopy could be applied as a precision and rapid method to determine Calcium Content in powdered milk. The good performance shows a potential application using UVE-SPA to select NIR and MIR effective variables.
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Determination of Calcium Content in Powdered Milk Using Near and Mid-Infrared Spectroscopy with Variable Selection and Chemometrics
Food and Bioprocess Technology, 2012Co-Authors: Di Wu, Yong He, Pengcheng Nie, Yidan BaoAbstract:Near infrared (NIR) and mid-infrared (MIR) spectroscopy techniques were evaluated to determine Calcium Content in powdered milk. A hybrid spectral variable selection algorithm combined with uninformation variable elimination (UVE) and successive projections algorithm (SPA) selected 11 NIR and 15 MIR variables from full 2,756 NIR and 3,727 MIR variables, respectively. Predicted results of least-squares support vector machine models for the samples in the prediction set show that the 15 MIR variables obtained much better results (0. 930 for coefficient of determination (r 2 ), 3. 703 for residual predictive deviation (RPD), 30. 162 for root mean square error of prediction set (RMSEP) and 5. 22% for relative errors of prediction (RSEP)) than 11 NIR variables did (0. 636 for r 2 , 1. 587 for RPD, 78. 815 for RMSEP, and 13. 40% for RSEP). The overall results indicate that MIR spectroscopy could be applied as a precision and rapid method to determine Calcium Content in powdered milk. The good performance shows a potential application using UVE-SPA to select NIR and MIR effective variables. © 2011 Springer Science + Business Media, LLC.
Di Wu - One of the best experts on this subject based on the ideXlab platform.
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determination of Calcium Content in powdered milk using near and mid infrared spectroscopy with variable selection and chemometrics
Food and Bioprocess Technology, 2012Co-Authors: Di Wu, Yong HeAbstract:Near infrared (NIR) and mid-infrared (MIR) spectroscopy techniques were evaluated to determine Calcium Content in powdered milk. A hybrid spectral variable selection algorithm combined with uninformation variable elimination (UVE) and successive projections algorithm (SPA) selected 11 NIR and 15 MIR variables from full 2,756 NIR and 3,727 MIR variables, respectively. Predicted results of least-squares support vector machine models for the samples in the prediction set show that the 15 MIR variables obtained much better results (0.930 for coefficient of determination (r 2), 3.703 for residual predictive deviation (RPD), 30.162 for root mean square error of prediction set (RMSEP) and 5.22% for relative errors of prediction (RSEP)) than 11 NIR variables did (0.636 for r 2, 1.587 for RPD, 78.815 for RMSEP, and 13.40% for RSEP). The overall results indicate that MIR spectroscopy could be applied as a precision and rapid method to determine Calcium Content in powdered milk. The good performance shows a potential application using UVE-SPA to select NIR and MIR effective variables.
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Determination of Calcium Content in Powdered Milk Using Near and Mid-Infrared Spectroscopy with Variable Selection and Chemometrics
Food and Bioprocess Technology, 2012Co-Authors: Di Wu, Yong He, Pengcheng Nie, Yidan BaoAbstract:Near infrared (NIR) and mid-infrared (MIR) spectroscopy techniques were evaluated to determine Calcium Content in powdered milk. A hybrid spectral variable selection algorithm combined with uninformation variable elimination (UVE) and successive projections algorithm (SPA) selected 11 NIR and 15 MIR variables from full 2,756 NIR and 3,727 MIR variables, respectively. Predicted results of least-squares support vector machine models for the samples in the prediction set show that the 15 MIR variables obtained much better results (0. 930 for coefficient of determination (r 2 ), 3. 703 for residual predictive deviation (RPD), 30. 162 for root mean square error of prediction set (RMSEP) and 5. 22% for relative errors of prediction (RSEP)) than 11 NIR variables did (0. 636 for r 2 , 1. 587 for RPD, 78. 815 for RMSEP, and 13. 40% for RSEP). The overall results indicate that MIR spectroscopy could be applied as a precision and rapid method to determine Calcium Content in powdered milk. The good performance shows a potential application using UVE-SPA to select NIR and MIR effective variables. © 2011 Springer Science + Business Media, LLC.
Yidan Bao - One of the best experts on this subject based on the ideXlab platform.
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Determination of Calcium Content in Powdered Milk Using Near and Mid-Infrared Spectroscopy with Variable Selection and Chemometrics
Food and Bioprocess Technology, 2012Co-Authors: Di Wu, Yong He, Pengcheng Nie, Yidan BaoAbstract:Near infrared (NIR) and mid-infrared (MIR) spectroscopy techniques were evaluated to determine Calcium Content in powdered milk. A hybrid spectral variable selection algorithm combined with uninformation variable elimination (UVE) and successive projections algorithm (SPA) selected 11 NIR and 15 MIR variables from full 2,756 NIR and 3,727 MIR variables, respectively. Predicted results of least-squares support vector machine models for the samples in the prediction set show that the 15 MIR variables obtained much better results (0. 930 for coefficient of determination (r 2 ), 3. 703 for residual predictive deviation (RPD), 30. 162 for root mean square error of prediction set (RMSEP) and 5. 22% for relative errors of prediction (RSEP)) than 11 NIR variables did (0. 636 for r 2 , 1. 587 for RPD, 78. 815 for RMSEP, and 13. 40% for RSEP). The overall results indicate that MIR spectroscopy could be applied as a precision and rapid method to determine Calcium Content in powdered milk. The good performance shows a potential application using UVE-SPA to select NIR and MIR effective variables. © 2011 Springer Science + Business Media, LLC.
Luc Delaby - One of the best experts on this subject based on the ideXlab platform.
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Evolution of milk Calcium Content during the year
Journal of Animal Science, 2013Co-Authors: C. Hurtaud, Muriel Johan, Ségolène Leurent, Yves Gallard, Luc DelabyAbstract:Calcium Content is regarded as being relatively stable in cows’ milk during lactation. However, results from commercial herds, have suggested that changes in milk Calcium (Ca) Content can occur. The objective of this experiment was to compare the characteristics of milk (especially milk Ca Content) based on low input grass based systems compared with corn silage based systems, across 2 breeds of dairy cows (Holstein, HO vs. Normande, NO).The experiment took place on the INRA experimental farm of Le Pin-au-Haras. Sixty dairy cows were observed from calving to drying off. Two feeding systems were compared. The Intensive system (IS) was designed to maximize individual performance, with a high energy diet (in winter, corn silage with 30% concentrate; in spring, summer and autumn periods, pasture with 4 kg/d of concentrate supplemented with corn silage from July). The Grass system (GS) was designed to decrease inputs (in winter, conserved grass with no concentrate; in spring, summer and autumn, pasture with no concentrate). The experimental design was a continuous design. No significant interaction was detected between feeding system and breed for milk yield and composition. During the whole year, GS treatment reduced milk yield (−5 kg/d), with no significant effect on protein and total Ca Contents. The NO cows produced less milk, but with higher protein and total Ca Contents. During winter, GS treatment reduced milk yield, protein and total Ca Contents. Milk Ca Content decreased from January to June and rapidly increased after July irrespective of breed. During May and June, HO milk had a Ca concentration below the French limit of 1.2 g/L of the European health allegation of milk for consumption. There was a significant effect of stage of lactation and month on Ca Content. Month included numerous significant factors such as maximum daily temperature, day length and radiance duration. This study clearly showed that both cow genotype and lactation stage affects milk Ca Content. However, the lactation stage did not explain all the seasonal variations of milk Calcium Content observed in this trial.
C. Hurtaud - One of the best experts on this subject based on the ideXlab platform.
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Dietary anion-cation difference and day length affect milk Calcium Content
Journal of Animal Science, 2013Co-Authors: Anne Boudon, Muriel Johan, Agnès Narcy, C. HurtaudAbstract:Milk and dairy products are an important source of Calcium for humans but recent studies in France have shown a clear decrease in milk Calcium Content during May and June and with grass diets compared with corn silage diets. The aim of this study was to identify the reasons of this seasonal drop of milk Calcium Content by testing the effect of 2 levels of dietary anion-cation differences (DCAD; 0 mEq/kg DM for D0 and 400 mEq/kg for D400) and 2 d lengths (8 h of light/d for short days and 16 h/d for long days) on Calcium balances of dairy cows. The DCAD treatments were conceive to mimic diets based either on maize silage or on herbage. The cows were only lightened by solarium lights providing UVA and UVB. The trial was carried out according to a Latin square design using 8 dairy cows averaging 103 ± 44 DIM with 4 periods of 14 d. Data were analyzed accordingly using Mixed procedure. The significance threshold was set at P ≤ 0.05. There was no significant interaction between day length and DCAD level. With D400 compared with D0, blood pH increased and plasma ionized Calcium Content decreased, while the plasma total Calcium Content was not different between treatments. However, milk Calcium Content increased, in relation with a decrease of the amount of Calcium excreted in urine. DCAD had no significant effect on protein and casein Contents and D400 tended to decrease milk yield. This illustrates that the udder did not decrease Ca uptake from the blood at high DCAD even though high DACA decreased the availability of Ca by decreasing the proportion of blood ionized Ca. Milk Calcium and casein Contents were significantly lower with long compared with short days, whereas day length had no effect on milk yield. This work highlights that long and sunny days can explain a part of the seasonal decrease of milk Calcium Content in summer and refutes the hypothesis that low milk Calcium Contents at grazing could be due to the high DCAD of herbage.
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Evolution of milk Calcium Content during the year
Journal of Animal Science, 2013Co-Authors: C. Hurtaud, Muriel Johan, Ségolène Leurent, Yves Gallard, Luc DelabyAbstract:Calcium Content is regarded as being relatively stable in cows’ milk during lactation. However, results from commercial herds, have suggested that changes in milk Calcium (Ca) Content can occur. The objective of this experiment was to compare the characteristics of milk (especially milk Ca Content) based on low input grass based systems compared with corn silage based systems, across 2 breeds of dairy cows (Holstein, HO vs. Normande, NO).The experiment took place on the INRA experimental farm of Le Pin-au-Haras. Sixty dairy cows were observed from calving to drying off. Two feeding systems were compared. The Intensive system (IS) was designed to maximize individual performance, with a high energy diet (in winter, corn silage with 30% concentrate; in spring, summer and autumn periods, pasture with 4 kg/d of concentrate supplemented with corn silage from July). The Grass system (GS) was designed to decrease inputs (in winter, conserved grass with no concentrate; in spring, summer and autumn, pasture with no concentrate). The experimental design was a continuous design. No significant interaction was detected between feeding system and breed for milk yield and composition. During the whole year, GS treatment reduced milk yield (−5 kg/d), with no significant effect on protein and total Ca Contents. The NO cows produced less milk, but with higher protein and total Ca Contents. During winter, GS treatment reduced milk yield, protein and total Ca Contents. Milk Ca Content decreased from January to June and rapidly increased after July irrespective of breed. During May and June, HO milk had a Ca concentration below the French limit of 1.2 g/L of the European health allegation of milk for consumption. There was a significant effect of stage of lactation and month on Ca Content. Month included numerous significant factors such as maximum daily temperature, day length and radiance duration. This study clearly showed that both cow genotype and lactation stage affects milk Ca Content. However, the lactation stage did not explain all the seasonal variations of milk Calcium Content observed in this trial.
