Predicting Pre‐harvest Forage Nutritive Value of Spring and Summer Growth of Alfalfa–Grass Mixtures

Abstract

Currently available regression equations developed to predict pre‐harvest nutritive attributes from simple field measurements taken in alfalfa (Medicago sativa L.)–grass mixtures can help producers determine when to best harvest their forages but they are applicable to only spring growth. Our objective was to develop and validate predictive equations of pre‐harvest forage nutritive attributes of mixed alfalfa–grass stands for the spring and first summer growth cycles. Forage samples (n = 1856) were collected in 2015 and 2016 from three research sites in Quebec, Canada, and used to develop predictive equations that were then validated using samples (n = 315) collected on commercial farms across Quebec and compared to equations previously developed in New York State for use during spring growth. For newly developed equations with two to four field measurements, R2 ranged from 0.70 to 0.84. The best equation developed to estimate a neutral detergent fiber assayed with a heat stable α‐amylase and corrected for the ash content of the residue (aNDFom) had an R2 of 0.82 and a root mean square error (RMSE) of 29.3 g kg−1 dry matter (DM). Some equations can be used to predict aNDFom concentration and the relative feed value of samples from commercial farms, but only if alfalfa proportion can be precisely determined. Locally developed equations resulted in better predictions than equations developed only for spring growth in New York State. Forage producers now have access to a tool to predict the pre‐harvest nutritive value of their forages for two growth cycles.Core Ideas Predictive equations can help producers determine when to harvest their forage fields. Equations developed can predict nutritive value of alfalfa‐grass stands for the spring and first summer growth cycles. Alfalfa proportion must be precisely determined for equations to yield reliable results.