JOURNAL OF CHILEAN CHEMICAL SOCIETY

Vol 62 No 2 (2017): Journal of the Chilean Chemical Society
Original Research Papers

DETERMINATION OF BRACHIARIA SPP. FORAGE QUALITY BY NEAR-INFRARED SPECTROSCOPY AND PARTIAL LEAST SQUARES REGRESSION

Mariel Monrroy
Centro de investigación en Bioquímica y Química Aplicada, Universidad Autónoma de Chiriquí Departamento de Química, Facultad de Ciencias Naturales y Exactas, Universidad Autónoma de Chiriquí
Dehylis Gutiérrez
Centro de investigación en Bioquímica y Química Aplicada, Universidad Autónoma de Chiriquí Departamento de Química, Facultad de Ciencias Naturales y Exactas, Universidad Autónoma de Chiriquí
Marissa Miranda
Centro de investigación en Bioquímica y Química Aplicada, Universidad Autónoma de Chiriquí Departamento de Química, Facultad de Ciencias Naturales y Exactas, Universidad Autónoma de Chiriquí
José Renán GarcÍa
Centro de investigación en Bioquímica y Química Aplicada, Universidad Autónoma de Chiriquí Departamento de Química, Facultad de Ciencias Naturales y Exactas, Universidad Autónoma de Chiriquí
Published June 16, 2017
Keywords
  • Forage,
  • NIRS,
  • Partial least squares,
  • Chemical properties
How to Cite
Monrroy, M., Gutiérrez, D., Miranda, M., Hernández, K., & GarcÍa, J. R. (2017). DETERMINATION OF BRACHIARIA SPP. FORAGE QUALITY BY NEAR-INFRARED SPECTROSCOPY AND PARTIAL LEAST SQUARES REGRESSION. Journal of the Chilean Chemical Society, 62(2). Retrieved from https://jcchems.com/index.php/JCCHEMS/article/view/189

Abstract

Characterizing the chemical properties of forage is critical for the production of improved pastures and livestock development. Conventional analysis methods are very time- and material-consuming, whereas near-infrared spectroscopy (NIRS) and chemometric analyses allow a fast simultaneous determination of various chemical or physical properties without the use of solvents or large sample amounts. The present research involved the development of models based on NIRS and partial least squares regression (PLS) to estimate the neutral detergent fiber (NDF), acid detergent fiber (ADF), cellulose, and crude protein (CP) contents in

Brachiaria spp. forage samples. The models were constructed using spectral data in the range of 800 to 1850 nm. Different preprocessing methods were applied, such as standard normal variate and first-/second-derivative transformations. The obtained calibration models were internally cross-validated, displaying validation errors similar to those obtained for conventional methods. The predictive abilities of the developed models were evaluated for external set samples. NDF, ADF, cellulose, and CP contents were estimated with relative errors of prediction (REPs) of 1.8, 2.6, 4.1, and 8.5%, respectively. NIRS predictions are a useful and profitable tool for fast multi-sample chemical property analysis that is required for the assessment of forage quality. The obtained models are suitable for estimating the key chemical characteristics of forage quality. This research contributes a new approach to determining the quality of Brachiaria spp. forage and provides a new technological tool for the improvement of this crop.

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