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Interpretive Analysis for Forage Yield Trial Data
Author(s) -
Pedersen J. F.,
Moore K. J.,
Santen Edzard
Publication year - 1991
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/agronj1991.00021962008300040024x
Subject(s) - forage , cultivar , festuca arundinacea , yield (engineering) , agronomy , automatic summarization , regression analysis , mathematics , biology , statistics , poaceae , computer science , materials science , artificial intelligence , metallurgy
Forage cultivar evaluation is often done in small plots with multiple harvests throughout the growing season. Data is often summarized by presenting a yearly total yield for each cultivar in addition to the mean for each harvest date. Data summarization often becomes burdensome and difficult to interpret. Regressing yield against a growth index associated with harvest dates can be utilized to describe forage perfomrmance in a concise and easily interpreted format. Subsets of data from tall fescue ( Festuca arundinacea Schreb.) yield trials conducted in Alabama and Kentucky were used to demonstrate the technique. The analysis involves regressing yield of a cultivar against an index calculated as the mean of all entries at a harvest date minus the grand mean. The resulting regression coefficient (b) describes cultivar yield response over several harvest and is indicative of performance under variable growth conditions.