Premium
Validation of Predictive Equations of Pre‐Harvest Forage Nutritive Value for Alfalfa–Grass Mixtures
Author(s) -
Wood Shane,
Seguin Philippe,
Tremblay Gaëtan F.,
Bélanger Gilles,
Lajeunesse Julie,
Martel Huguette,
Berthiaume Robert,
Claessens Annie
Publication year - 2018
Publication title -
agronomy journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.752
H-Index - 131
eISSN - 1435-0645
pISSN - 0002-1962
DOI - 10.2134/agronj2017.09.0542
Subject(s) - forage , mathematics , predictive value , neutral detergent fiber , agronomy , regression analysis , linear regression , zoology , statistics , environmental science , biology , medicine
Core Ideas Predictive equations can help producers determine when to harvest their forage fields. Equations developed in New York State could be used to predict aNDFom, ADFom, RFV, and RFQ in Quebec. Equations developed in New York State cannot be used to predict NDFdom in Quebec.Predictive equations of pre‐harvest nutritive attributes of alfalfa ( Medicago sativa L.)–grass mixtures using simple plant or climate data were developed in New York State for the spring growth, but they must be validated before being used outside their development area. Our objective was to validate these predictive equations for their use in Quebec, Canada. Samples ( n = 679) of alfalfa–grass mixtures were collected during spring growth at three sites for 2 consecutive years and analyzed for several nutritive attributes. Alfalfa maximum height, the most mature stage of development of alfalfa, growing degree days, grass proportion, and grass maximum height were also measured and used as input in several existing predictive equations. Predicted values were then compared with laboratory‐determined values using several validation statistics. The most promising predictive equations of neutral detergent fiber (NDF) and acid detergent fiber concentrations, relative feed value, and relative forage quality had coefficients of determination ( r 2 ) of the linear regression between observed and predicted values between 0.74 and 0.81, and an index of agreement ( d ) between 0.87 and 0.93. Several equations were, however, significantly biased as indicated by slopes and intercepts of the regressions. The NDF digestibility was not predicted satisfactorily with the New York State equations. Among all equations evaluated, an equation for NDF concentration has the most potential for use to predict the spring growth pre‐harvest nutritive value of alfalfa–grass mixtures in Quebec.