Abstract
Near infrared spectroscopy (NIRS) is a staple in laboratories used to determine forage quality in an affordable and efficient manner compared with standard wet chemistry analysis. The use of hand-held, portable NIRS technology in the field has not been thoroughly developed but could potentially be a tool to measure forage quality at harvest. The objectives of this research were to formulate and validate NIRS predictive equations for in-field use on wet alfalfa ( Medicago sativa L.) using a hand-held NIRS device (NIR4 Farm, AB Vista, Marlborough, England). In 2019, alfalfa was hand-harvested from an existing stand, sorted by maturity, and chopped to 2.5-cm lengths (n = 100 samples). Alfalfa was scanned as-is by the NIRS device in a climate-controlled room to obtain spectral data. Samples were then ground to 1-mm lengths and thoroughly mixed before performing wet chemistry analysis. Predictive equations were developed using the data gathered through wet chemistry analysis. In 2020, alfalfa was hand-harvested from different existing stands, sorted by maturity, and chopped to 2.5-cm lengths (n = 102 samples). Samples were scanned in the field immediately after harvesting using the NIRS device containing the previously developed equations. Samples were then analyzed using wet chemistry. Data were analyzed using R (version 3.6.2) and significance was set at P < 0.05. Calibration statistics were generated based on the developed prediction equation for crude protein (CP). A linear model and an ANOVA were then used to determine differences between the wet chemistry and NIRS values for CP. Calibration statistics showed that the developed predictive equation for CP could predict results with acceptable accuracy (R 2 = 0.84; Standard Error of Calibration = 1.45). There was no significant difference between wet chemistry and NIRS values for CP ( P = 0.86; R 2 = 0.89; Standard Error of Prediction = 0.77). These findings suggests that the hand-held NIRS could accurately estimate the CP concentration of wet alfalfa. The ability to predict CP indicates that other forage quality parameters may also be predicted by the hand-held NIRS device.
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