Evaluation of a NIR camera for monitoring yield and nitrogen effect in sugarcane
Evaluación de una cámara NIR para el monitoreo de productividad y efecto del nitrógeno en caña de azúcar
DOI:
https://doi.org/10.15446/agron.colomb.v35n1.60852Palabras clave:
Nitrogen, yield, near infrared, precision agriculture, vegetation index, RPAS (en)Nitrógeno, productividad, infrarrojo cercano, agricultura de precisión, índice de vegetación, RPAS (es)
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The main objective of the research carried out in the sugar productive sector in Colombia is to improve crop productivity of sugarcane. The rise of RPAS, together with the use of multispectral cameras, which allows for high spatial resolution images and spectral information outside the visible spectrum, has generated an alternative nondestructive technological approach to monitoring crop sugarcane that must be evaluated and adapted to the specific conditions of Colombia's sugar productive sector. In this context, this paper assesses the potential of a modified camera (NIR) to discriminate three varieties of sugarcane, as well as three doses of fertilization and estimating the sugarcane yield at an early stage, for the three varieties through multiple vegetation indices. In this study, no significant differences were found by vegetation index between fertilization doses, and only significant differences between varieties were found when the fertilization was normal or high. Likewise, multiple regressions between scores derived from vegetation indices after applying PCA and productivity produced determinations of up to 56%.
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1. Fatemeh Mousabeygi, Yousef Rezaei, Samira Akhavan. (2021). Assessment of maize water status using a consumer-grade camera and thermal imagery. Water Supply, 21(6), p.2543. https://doi.org/10.2166/ws.2020.270.
2. L. A. S. Cardoso, P. R. S. Farias, J. A. C. Soares, C. R. T. Caldeira, F. J. de Oliveira. (2024). Use of a UAV for statistical-spectral analysis of vegetation indices in sugarcane plants in the Eastern Amazon. International Journal of Environmental Science and Technology, 21(10), p.6947. https://doi.org/10.1007/s13762-024-05477-z.
3. Fatemeh Mousabeygi, Samira Akhavan, Yousef Rezaei. (2022). Assessment of consumer-grade camera-derived vegetation indices for monitoring nitrogen and leaf relative water content of maize. Spanish Journal of Agricultural Research, 20(1), p.e0203. https://doi.org/10.5424/sjar/2022201-17138.
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