scholarly journals Prediction of the chemical composition and nutritive value of lucerne (Medicago sativa L.) by Near Infrared Spectroscopy

2005 ◽  
Vol 4 (sup2) ◽  
pp. 141-143
Author(s):  
S. Colombini ◽  
M. Confalonieri ◽  
G. Borreani ◽  
E. Tabacco ◽  
P.G. Peiretti ◽  
...  
2000 ◽  
Vol 135 (4) ◽  
pp. 409-417 ◽  
Author(s):  
P. C. GARNSWORTHY ◽  
J. WISEMAN ◽  
K. FEGEROS

Near infrared spectroscopy (NIRS) is widely used in the flour milling industry for rapid determination of moisture and protein in wheat. However, these measurements give little indication of the nutritive value of wheat when fed to poultry or pigs. Accurate estimates of nutritive value require specialist facilities and are time-consuming and costly. Accordingly, prediction from chemical or NIRS measurements would be of some considerable benefit. In the current study 160 samples of wheat, representing 24 different varieties, were used to generate NIRS calibration equations for chemical, nutritive and agronomic characteristics. Predictions of chemical constituents in wheat were very accurate. Coefficients of determination (r2) were 0·94 for dry matter, 0·90 for crude protein, 0·97 for ash, 0·78 for starch and 0·98 for oil. True metabolizable energy in broiler chickens was predicted more accurately (r2 = 0·52 for adult birds, 0·74 for young birds) than apparent metabolizable energy (r2 = 0·45). Digestible energy (r2 = 0·17) and nitrogen digestibility (r = 0·22) in pigs were not predicted very accurately on a smaller subset (n = 33). Agronomic characteristics were predicted very accurately (r2 = 0·98 hardness, 0·80 bushel weight, 0·99 thousand-grain weight). Predictions of nutritive value of wheat from chemical or agronomic characteristics are very inaccurate, since coefficients of determination vary from zero to 0·25. It is concluded that NIRS can accurately estimate the chemical composition of wheat, but accurate prediction of nutritive value is reduced by animal variation. Nevertheless, NIRS is potentially more reliable for assessing nutritive value than chemical composition or agronomic characteristics.


2020 ◽  
Vol 28 (4) ◽  
pp. 214-223
Author(s):  
Junqian Mo ◽  
Wenbo Zhang ◽  
Xiaohui Fu ◽  
Wei Lu

This study investigated the feasibility of using near infrared spectroscopy technology to predict color and chemical composition in the heat-treated bamboo processing industry. The quantitative presentations of the changes in the chemical components were discussed using the difference spectra method of the 2nd derivative NIR spectra of the heat-treated bamboo samples. Then, the relationships between the color changes of the heat-treated bamboo and its near infrared spectra were constructed using the changes in the chemical components of the bamboo samples during the heating process. The prediction of color and chemical composition of both the outer and inner sides of the heat-treated bamboo surface were constructed using partial least squares regression method combined with a leave-one-out cross-validation process. Then, the results were validated by independent sample sets. The proposed prediction models were found to produce high r2P (above 0.93), RPD (above 3.13), and low RMSEP for both the outer and inner sides of the heat-treated bamboo samples. These studies’ results confirmed that the proposed models, especially outer side models, were perfectly suitable for the in-process inspections of the color and chemical content changes of heat-treated bamboo.


2010 ◽  
Vol 18 (1) ◽  
pp. 69-77 ◽  
Author(s):  
Denis Bastianelli ◽  
Laurent Bonnal ◽  
Hervé Juin ◽  
Sandrine Mignon-Grasteau ◽  
Fabrice Davrieux ◽  
...  

Aquaculture ◽  
2017 ◽  
Vol 476 ◽  
pp. 134-140 ◽  
Author(s):  
Helena Lopes Galasso ◽  
Myriam D. Callier ◽  
Denis Bastianelli ◽  
Jean-Paul Blancheton ◽  
Catherine Aliaume

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