Relação entre índices espectrais e parâmetros de qualidade da forrageira tifton 85

Jhiorranni Freitas Souza; Anderson Gomide Costa; João Célio Luna de Carvalho; Lucas Andrade dos Santos; Vinícius Pimentel Silva; Murilo Machado de Barros

doi:10.1590/1983-21252024v3712139rc

Authors

Jhiorranni Freitas Souza Engineering Department, Technology Institute, Universidade Federal Rural do Rio de Janeiro, Seropédica, RJ, Brazil https://orcid.org/0009-0001-6295-9415
Anderson Gomide Costa Engineering Department, Technology Institute, Universidade Federal Rural do Rio de Janeiro, Seropédica, RJ, Brazil https://orcid.org/0000-0003-0594-8514
João Célio Luna de Carvalho Engineering Department, Technology Institute, Universidade Federal Rural do Rio de Janeiro, Seropédica, RJ, Brazil https://orcid.org/0000-0003-1676-4577
Lucas Andrade dos Santos Engineering Department, Technology Institute, Universidade Federal Rural do Rio de Janeiro, Seropédica, RJ, Brazil https://orcid.org/0000-0002-4910-4324
Vinícius Pimentel Silva Department of Animal Nutrition and Pastures – Animal Science Institute, Universidade Federal Rural do Rio de Janeiro, Seropédica, RJ, Brazil https://orcid.org/0000-0002-5424-2094
Murilo Machado de Barros Engineering Department, Technology Institute, Universidade Federal Rural do Rio de Janeiro, Seropédica, RJ, Brazil https://orcid.org/0000-0003-0378-4800

DOI:

https://doi.org/10.1590/1983-21252024v3712139rc

Keywords:

Cynodon spp. Pastures. Computer vision. Digital images.

Abstract

Computer vision systems can be an alternative to traditional methods of analyzing the quality of forage crops, allowing the instantaneous, non-destructive monitoring of the crop, with cost reduction. This study aimed to evaluate the quality parameters of Tifton 85 (Cynodon spp.) using digital images, relating spectral indices to the quality parameters of this forage. In the experimental area, four levels of nitrogen fertilization were applied and the analyses were made at different times after the standardization cut (14, 28, 42, and 56 days). The quality parameters evaluated were mineral matter, crude protein, and neutral detergent fiber. From images obtained in the visible (RGB) and near-infrared (RGNIR) spectral regions, spectral indices were generated. Principal component analysis was applied to summarize the information obtained by spectral indices into a single principal component (PC1). PC1 associated with spectral indices was related to forage quality parameters for each cutting time using simple quadratic regression models. The relationships between mineral matter and spectral indices were variable over time. Crude protein and neutral detergent fiber showed the highest relationships with the spectral indices obtained by RGNIR images already at the initial times. Thus, although the RGB images have shown satisfactory results to obtain information about the quality of Tifton 85, the NIR band tends to increase the reliability of the relationships at early times.

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