Prediction of the Chemical Composition of Poultry Excreta by near Infrared Spectroscopy

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

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 ◽  
...  
Keyword(s):  
Infrared Spectroscopy ◽  
Chemical Composition ◽  
Medicago Sativa ◽  
Near Infrared Spectroscopy ◽  
Nutritive Value ◽  
Near Infrared ◽  
Medicago Sativa L

Near infrared spectroscopy to evaluate change in color and chemical composition in heat-treated bamboo

2020 ◽  
Vol 28 (4) ◽  
pp. 214-223
Author(s):  
Junqian Mo ◽  
Wenbo Zhang ◽  
Xiaohui Fu ◽  
Wei Lu
Keyword(s):  
Infrared Spectroscopy ◽  
Chemical Composition ◽  
Near Infrared Spectroscopy ◽  
Near Infrared ◽  
Prediction Models ◽  
Chemical Components ◽  
Outer Side ◽  
Heating Process ◽  
Least Squares Regression ◽  
Heat Treated

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.

scholarly journals The potential of near infrared spectroscopy (NIRS) to measure the chemical composition of aquaculture solid waste

Aquaculture ◽  
2017 ◽  
Vol 476 ◽  
pp. 134-140 ◽  
Author(s):  
Helena Lopes Galasso ◽  
Myriam D. Callier ◽  
Denis Bastianelli ◽  
Jean-Paul Blancheton ◽  
Catherine Aliaume
Keyword(s):  
Infrared Spectroscopy ◽  
Chemical Composition ◽  
Solid Waste ◽  
Near Infrared Spectroscopy ◽  
Near Infrared
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