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- W2064254462 abstract "The design and economic evaluation of management systems for alfalfa (Medicago sativa L.) are facilitated by good estimates of the nutritional quality of the herbage produced. The objectives of this study were to calibrate and test prediction equations for crude protein, in vitro true digestibility (IVTD), neutral detergent fiber, acid detergent fiber, and acid detergent lignin (ADL) of leaf, stem, and total herbage components of alfalfa. Equations developed from New York data were tested for predictive accuracy with alfalfa samples collected in California, Georgia, Kentucky, New Mexico, New York, and Wisconsin. Prediction errors ranged from 0.9 to 4.7 percentage units of herbage dry matter for ADL and stem IVTD, respectively. New prediction equations based on age of the herbage in days, growing degree days (DD) with a 41 °F (5 °C) base temperature, mean morphological stage by weight (MSW), leaf proportion of the herbage (LP), latitude of the collection site, and hours of light received during growth were then calibrated from the national data set. Quadratic, cubic, and natural logarithms of various independent variables were considered. Weather and age data gave significant regressions, with calibration errors of 0.8 to 4.8 percentage units of dry matter for quality parameters of total herbage. Equations based on morphological properties generally gave better fits with corresponding error terms from 0.9 to 2.8. The best fitting equations found for the five components of total herbage quality included only two independent variables, one of which was always LP. The other variable was always ln (MSW + 1.), except for ADL, where it was ln (DD + 1.)." @default.
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- W2064254462 date "1988-04-01" @default.
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- W2064254462 title "Statistical Models for Predicting Alfalfa Herbage Quality from Morphological or Weather Data" @default.
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- W2064254462 doi "https://doi.org/10.2134/jpa1988.0160" @default.
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