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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...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2020
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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 |
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. |
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