Author:
Ortega Monsalve Manuela,Rodríguez Monroy Tatiana,Galeano-Vasco Luis,Medina-Sierra Marisol,Cerón-Muñoz Mario
Abstract
Spectroscopy is a promising technique for determining nutrients in grasses and may be a valuable tool for future research. This chapter reviews research carried out in recent years, focusing on determining the quality of grasses using spectroscopy techniques, specifically, spectrophotometry. The chemical methods used to determine the nutritional quality of grasses produce chemical residues, are time-consuming, and are costly to use when analyzing large crop extensions. Spectroscopy is a non-destructive technique that can establish the nutritional quality of grass easily and accurately. This chapter aims to describe the techniques focused on the use of spectroscopy and machine learning models to predict and determine the quality of grasses. A bibliographic review was conducted and recent research articles were selected that showed spectroscopic techniques applied to grasses. Different methods and results focusing on the quality of the grasses were compiled. In general, this review showed that the most commonly used spectroscopic method is near-infrared analysis. Spectroscopy is a very effective tool that opens the way to new types of technologies that can be applied to obtain results in determining the quality of pastures, leaving behind the use of traditional methods that represent higher costs and disadvantages compared to traditional methods based on precision agriculture.
Reference82 articles.
1. Silveira ML, Kohmann MM. Maintaining soil fertility and health for sustainable pastures. In: Management Strategies for Sustainable Cattle Production in Southern Pastures. Cambridge, Massachusetts: Academic Press; 2020. pp. 35-58. DOI: 10.1016/b978-0-12-814474-9.00003-7
2. Westerman RL. Soil Testing and Plant Analysis. 3rd ed. Vol. 152, No. 2. Madison: Soil Science; 1991. p. 137
3. Molano ML. Caracterización nutricional de forrajes tropicales usando espectroscopía de infrarrojo cercano (nirs). Bogotá, Colombia: Universidad Nacional de Colombia; 2013
4. Teye E, Amuah CL, Atiah K, Darko RO, Abindaw T, Amoah KK, et al. Quick determination of soil quality using portable spectroscopy and efficient multivariate techniques. Journal of Spectroscopy. 2023;2023:11. DOI:10.1155/2023/2024318
5. Serrano J, Shahidian S, Carreira E, Nogales-Bueno J, Rato AE. Predicting the evolution of pasture quality by NIRS: Perspectives for real-time pasture and grazing management. In: Online AgEng2021 Conference, 5–8 July 2021. Évora, Portugal; 2021. pp. 1-8