Testing mean stage as a predictor of alfalfa forage quality with growth chamber trials

Estimation of alfalfa (Medicago sativa L.) forage quality as the crop grows in the field provides useful management information. The quantified morphological stage of development defined by mean stage by weight (MSW) can be used to estimate crude protein (CP), in vitro true digestibility (IVTD), neu...

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Bibliographic Details
Published inCrop science Vol. 30; no. 3
Main Authors Fick, G.W. (Cornell Univ., Ithaca, NY), Janson, C.G
Format Journal Article
LanguageEnglish
Published 01.05.1990
Subjects
ALIMENT POUR ANIMAUX
CALIDAD
COMPOSICION
COMPOSITION
CONTENIDO DE FIBRAS
CONTENIDO DE MATERIA SECA
CULTIVO IN VITRO
CULTURE IN VITRO
DIGESTIBILIDAD
DIGESTIBILITE
LIGNINAS
LIGNINE
MEDICAGO SATIVA
MODELE
MODELOS
NORMALISATION
NORMALIZACION
PESO
PIENSOS
POIDS
PREVISION
PRONOSTICO
PROTEINA BRUTA
PROTEINE BRUTE
QUALITE
TENEUR EN FIBRES
TENEUR EN MATIERE SECHE
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Summary:Estimation of alfalfa (Medicago sativa L.) forage quality as the crop grows in the field provides useful management information. The quantified morphological stage of development defined by mean stage by weight (MSW) can be used to estimate crude protein (CP), in vitro true digestibility (IVTD), neutral-detergent fiber (NDF), acid-detergent fiber (ADF), and acid-detergent lignin (ADL) of the standing crop. The purpose of this study was to validate previously published prediction equations for CP, IVTD, NDF, ADF, and ADL based on MSW, including evaluation of general robustness and potential bias in prediction equations. Nine combinations of growth-chamber environment and plant age were used to develop a data set independent of the prediction equations to be tested. The tests consisted of linear regression of growth-chamber observations on predicted values. Prediction errors were less than or equal to 39 g kg-1 of dry matter for all parameters, and all coefficients of determination were greater than or equal to 0.61. These compare favorably to calibration statistics for the prediction equations and indicate that MSW is a robust basis for predicting alfalfa forage quality. However, most intercepts and slopes of the linear regressions deviated from 0.0 and 1.0, respectively, indicating bias in model predictions. Therefore, prediction equations should be recalibrated so that the calibration data and the predictive domain overlap as much as possible
Bibliography:F60
Q54
9044913
ISSN:0011-183X
1435-0653
DOI:10.2135/cropsci1990.0011183X003000030040x