Calibration and validation of a near-infrared spectroscopy equipment to predict crude protein and fibre of biodiverse pastures

Abstract

Pasture quality monitoring is a key element in the decision making process of the farm manager. The inter-annual variability of rainfall distribution has an important impact on the dryland pasture vegetative cycle, to the point that supplementation needs, normal in the critical summer period, can be anticipated by one to two months in years of reduced precipitation in the spring. Laboratory methods for assessing quality parameters such as crude protein (CP) or fibre (Neutral Detergent Fibre, NDF) require cutting, collection and analytical procedures involving technicians, time and reagents, making them laborious and expensive. In recent years, near infrared spectroscopy (NIRS) technology, which is based on the absorption of electromagnetic radiation at wavelengths between 780 and 2500 nm, has gained a wide range of agricultural applications. In this work, a combination of NIRS equipment and multivariate data analysis was used to estimate and monitor the evolution of CP and NDF of six biodiverse pastures during the 2018 and 2019 growing seasons. Regression equations with determination coefficients around 0.90-0.95 were established between predicted and laboratory reference measurements of CP and NDF. These equations were validated over the 2019 growing season in eight pastures. The results show the practical interest of portable spectrometry, associated with Global Navigation Satellite Systems (GNSS), as expeditious tools for monitoring pasture quality. Good prospects and opportunities open up for technology-based service providers to develop remote sensing-based computer applications from satellite imagery that enable dynamic management of animal grazing.