Abstract
Simple equations to predict alfalfa (Medicago sativa L.) herbage quality are needed for economic analysis of management alternatives. In this study, regression analysis was used to formulate and test prediction equations for leaf proportion (LP), for crude protein (CP), and in vitro true digestibility (IVTD) levels of leaf and stem fractions of standing herbage with canopy age, heat sums with a 5°C base temperature, and daylength sums as independent variables. All data were for pure alfalfa samples collected in central New York State between 1972 and 1980 from established stands with canopies ranging in age from 7 to 66 days. Separate equations were needed to predict LP in first growth and regrowth, but a corresponding distinction was not necessary for leaf and stem CP and IVTD. Heat‐sum‐based equations gave good fits (R2 from 0.75 to 0.97) for all predicted variables. In few cases, equations with both heat and daylength sums fit equally as well. Canopy age adequately predicted only leaf CP and IVTD. Equation form varied from simple linear to polynomial and logarithmic. Thirteen equations were selected for testing by regressing independent field observations on model predictions of those observations. The r2 values in these tests for the various herbage components were as follows: LP in regrowth, 0.81 to 0.87; leaf CP, 0.55 to 0.59; leaf IVTD, 0.44 to 0.46; stem CP, 0.72 to 0.76; and stem IVTD, 0.89 to 0.92. In general, predicting standing alfalfa herbage quality from heat summation is a promising approach.
Published Version
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