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Near infrared spectroscopy (NIRS) data analysis for a rapid and simultaneous prediction of feed nutritive parameters

Presented paper described dataset on near infrared spectroscopy (NIRS) used as a rapid and robust method to predict and determine several nutritive parameters of animal feed simultaneously. Near spectra data were acquired and recorded in wavelength range from 1000 to 2500 nm with co-added of 64 scan...

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Detalles Bibliográficos
Autores principales: Samadi, Wajizah, Sitti, Munawar, Agus Arip
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7015983/
https://www.ncbi.nlm.nih.gov/pubmed/32071986
http://dx.doi.org/10.1016/j.dib.2020.105211
Descripción
Sumario:Presented paper described dataset on near infrared spectroscopy (NIRS) used as a rapid and robust method to predict and determine several nutritive parameters of animal feed simultaneously. Near spectra data were acquired and recorded in wavelength range from 1000 to 2500 nm with co-added of 64 scans per sample measurement. On the other hand, actual reference nutritive parameters: in vitro organic matter digestibility (IVOMD), in vitro dry matter digestibility (IVDMD), neutral detergent fibre (NDF) and acid detergent fibre (ADF) of animal feed were measured using proximate laboratory procedures. Near infrared datasets can be enhanced using several spectra correction methods to improve prediction accuracy and robustness. Animal feed nutritive parameters can be determined simultaneously and rapidly by establishing prediction models by means of principal component regression (PCR), partial least squares regression (PLSR) and other regression approaches.