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Maximizing Efficiency of Recurrent Phenotypic Selection for Neutral Detergent Fiber Concentration in Smooth Bromegrass
Author(s) -
Stendal C.,
Casler M. D.
Publication year - 2006
Publication title -
crop science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.76
H-Index - 147
eISSN - 1435-0653
pISSN - 0011-183X
DOI - 10.2135/cropsci2005.0083
Subject(s) - selection (genetic algorithm) , biology , replication (statistics) , bromus inermis , statistics , microbiology and biotechnology , livestock , poaceae , mathematics , agronomy , computer science , ecology , machine learning
Resources are always limited in plant breeding programs, limiting the number of plots or plants that can be utilized in recurrent selection. Replication of selection units in space or time provides a mechanism to improve the precision of measurements. For smooth bromegrass ( Bromus inermis L.), neutral detergent fiber (NDF) is the most effective and measurable predictor of animal intake, a major source of variation for livestock production. The objective of this experiment was to determine the potential benefits and costs of replication in time and space for divergent recurrent selection on NDF of smooth bromegrass. Phenotypic data was used to predict selection response and derive a benefit–cost ratio for a variety of selection criteria based on various numbers of blocks and harvests. Three of the 70 selection criteria examined had an expected selection response significantly greater than that predicted by a log‐linear regression of expected selection response as a function of cost. These selection criteria were based on two or three harvests and one or two blocks. Two of the selection criteria, emphasizing one harvest of unreplicated plants, had a benefit–cost ratio significantly above the mean. If financial resources are not a concern, selection based on the mean of multiple harvests in 1 yr results in the highest expected response per year. If financial resources are greatly limited, one harvest of unreplicated plants provides an adequate expected response per cycle but maximizes gain per unit cost.