Abstract

Regression equations can be used to estimate the neutral! detergent fiber (NDF) of alfalfa (Medicago sativa L.), assisting producers in decision making at harvest time. In New York State, where most alfalfa is grown in mixed stands with grass, there are no available models to estimate NDF. The objectives of this experiment were to develop equations for estimating total mixed stand NDF with an emphasis on producer useable equations based on easily obtainable data.. Stands of first-cut alfalfa and grass (0.1-0.9 fraction grass) were sampled at two experimental sites and producers' fields in 19 New York counties during May and June 2004 and 2005. A range of plant measurements and environmental characteristics were recorded and used to develop prediction equations. For selection of two to five variable models using 899 data points, R-2 ranged from 0.89 to 0.94 and root mean square error (RMSE) ranged from 21.2 to 30.1 g kg(-1) dry matter (DM). The most important explanatory variables were the fraction of grass and alfalfa height. Growing degree days and day of the year improved goodness of fit but were biased between years. Categorization of the grass fraction into 0.2, 0.4, 0.6, or 0.8 allows estimation without requiring species separations. Categorization decreased R-2 and increased RMSE but is a variable that could be more easily used by producers. Model validation found significant biases with some model estimates; however biases and prediction errors were small enough to suggest that the results are practically applicable to New York farms.

Published in

Agronomy Journal
2006, Volume: 98, number: 4, pages: 1081-1089

UKÄ Subject classification

Agricultural Science


Publication identifier

DOI: https://doi.org/10.2134/agronj2005.0326

Permanent link to this page (URI)

https://res.slu.se/id/publ/89170