Nutritional value of Cuba grass CT-115 (Pennisetum purpureum) based on NIRS and chemometry
DOI:
https://doi.org/10.19136/era.a13n2.4748Keywords:
Tropical forage, bromatological analysis, multiple regression (PLS)Abstract
In this work, visible and infrared (VIS-NIR) spectra and chemometrics were used to develop equations to estimate nutritional properties and in situ degradation of Cuba CT-115 grass (Pennisetum purpureum). 134 grass samples of five regrowth ages were collected and in each one the following were determined: crude protein (CP), neutral detergent fiber (NDF), acid detergent fiber (ADF), cell content (CC), hemicellulose (H), ash (A), in situ dry matter degradation (ISDM) and VIS-NIR-SWIR spectrum. With the measured properties and the spectra of each sample, the respective equations for their prediction were generated. The determination and correlation coefficients, from the internal and external validation, obtained for each model are excellent, close to unity (0.988 to 0.997); while the standard errors of calibration (SEC, 0282 to 1.292) and validation (SEV 0.317 to 1.383) are low; the SEC/SEV ratio is good (less than unity, from 0.766 to 0.938). Prediction deviation (PDR) ratios are acceptable for DIMS and FDA (1.41 and 1.71) and excellent for PC, NDF and ADF (1.41 and 1.71) and excellent for PC, NDF, CC, H, and C (2.33 to 7.88). Based on the statistics, it is concluded that the prediction equations, based on the VIS-NIR-SWIR spectral combinations, estimate each parameter with precision and accuracy. With the advantages that NIRS analysis non –destructive, does not generate chemical waste, requires less analytical time (minutes) and lower analysis cost; when compared to conventional methods.
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