Use of near-infrared spectroscopy for prediction of chemical composition of Tifton 85 grass

Authors

DOI:

https://doi.org/10.5433/1679-0359.2021v42n3p1287

Keywords:

Cynodon spp, Hay. Leaf blade, NIRS, Protein.

Abstract

The reduction in the quality, consumption, and digestibility of forage can cause a decrease in animal performance, resulting in losses to the rural producer. Thus, it is important to monitor these characteristics in forage plants to devise strategies or practices that optimize production systems. The aim of this study was to develop and validate prediction models using near-infrared spectroscopy (NIRS) to determine the chemical composition of Tifton 85 grass. Samples of green grass, its morphological structures (whole plant, leaf blade, stem + sheath, and senescent material) and hay, totaling 105 samples were used. Conventional chemical analysis was performed to determine the content of oven-dried samples (ODS), mineral matter (MM), crude protein (CP), neutral detergent fiber (NDF), acid detergent fiber (ADF), acid detergent lignin (ADL), cellulose (CEL), hemicellulose (HEM), and in vitro dry matter digestibility (IVDMD). Subsequently, all the samples were scanned using a Vis-NIR spectrometer to collect spectral data. Principal component analysis (PCA) was applied to the data set, and modified partial least squares was used to correlate reference values to spectral data. The coefficients of determination (R2) were 0.74, 0.85, 0.98, 0.75, 0.85, 0.71, 0.82, 0.77, and 0.93, and the ratio of performance deviations (RPD) obtained were 1.99, 2.71, 6.46, 2.05, 2.58, 3.84, 1.86, 2.35, 2.09, and 3.84 for ODS, MM, CP, NDF, ADF, ADL, CEL, HEM, and IVDMD, respectively. The prediction models obtained, in general, were considered to be of excellent quality, and demonstrated that the determination of the chemical composition of Tifton 85 grass can be performed using NIRS technology, replacing conventional analysis.

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Author Biographies

Camila Cano Serafim, State University of Londrina

Student, Doctoral Course of the Graduate Program in Animal Science, State University of Londrina, UEL, Londrina, PR, Brazil.

Geisi Loures Guerra, State University of Londrina

PhD in Animal Science, UEL, Londrina, PR, Brazil.

Ivone Yurika Mizubuti, State University of Londrina

Professor Senior, PhD, Graduate Program in Animal Science, UEL, Londrina, PR, Brazil.

Filipe Alexandre Boscaro de Castro, State University of Londrina

Prof., PhD’s, Zootechnical Department, UEL, PR, Brazil.

Odimári Pricila Prado-Calixto, State University of Londrina

Profa., PhD’s, Graduate Program in Animal Science, UEL, Londrina, PR, Brazil.

Sandra Galbeiro, State University of Londrina

Profa, PhD’s, Zootechnical Department, UEL, PR, Brazil.

Angela Rocio Poveda Parra, State University of Londrina

Profa, PhD’s, Zootechnical Department, UEL, PR, Brazil.

Valter Harry Bumbieris Junior, State University of Londrina

Prof., PhD’s, Graduate Program in Animal Science, UEL, Londrina, PR, Brazil.

Simone Fernanda Nedel Pértile, University North of Parana

Profa., PhD’s, Master’s Degree in Animal Health and Production, Pitagoras University North of Parana, UNOPAR, Arapongas, PR, Brazil.

Fabíola Cristine de Almeida Rego, University North of Parana

Profa., PhD’s, Master’s Degree in Animal Health and Production, Pitagoras University North of Parana, UNOPAR, Arapongas, PR, Brazil.

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Published

2021-03-19

How to Cite

Serafim, C. C., Guerra, G. L., Mizubuti, I. Y., Castro, F. A. B. de, Prado-Calixto, O. P., Galbeiro, S., … Rego, F. C. de A. (2021). Use of near-infrared spectroscopy for prediction of chemical composition of Tifton 85 grass. Semina: Ciências Agrárias, 42(3), 1287–1302. https://doi.org/10.5433/1679-0359.2021v42n3p1287

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