Canopy Visible and Near‐infrared Reflectance Data to Estimate Alfalfa Nutritive Attributes Before Harvest

Abstract

ABSTRACTCanopy reflectance (i.e., remotely sensed) data may allow rapid assessment of nutritive values, such as total N, neutral detergent fiber (NDF), and acid detergent fiber (ADF), as well as nutritive quality indicators such as relative feed value (RFV) and a forage energy/protein ratio of alfalfa (Medicago sativa L.). Remotely sensed data were acquired over seven alfalfa cultivars in the 2005 to 2008 growing seasons (n = 580) to develop and test calibration equations to predict concentrations of total N, NDF, and ADF. About 31% of the canopy reflectance dataset and corresponding measured values of total N, NDF, and ADF were used in calibration equation development while the remaining samples (69%) were used to validate the calibration equations. The remote sensing based values of NDF, ADF, and crude protein (CP = total N × 6.25) were used to calculate RFV and the total digestible nutrients/crude protein (TDN/CP) ratio. Measured total N, NDF, ADF, RFV, and the TDN/CP ratio were used to assess the accuracy of the corresponding predicted values from the remotely sensed canopy reflectance data. The remotely sensed based prediction equations explained from 78 to 83% of the variation in measured total N, NDF, and ADF, correctly predicted about 80% of the RFV‐based hay grade classifications, and about 78% of the measured TDN/CP ratios. This technology could help improve profit margins by timing the cutting or harvesting of alfalfa, in rapid assessment of nutritive values over large areas devoted to growing alfalfa, and assessing nutritive quality in real time.