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Plant Mortality and Natural Selection May Increase Biomass Yield in Switchgrass Swards
Author(s) -
Casler Michael D.,
Smart Alexander J.
Publication year - 2013
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/cropsci2012.07.0434
Subject(s) - panicum virgatum , biology , biomass (ecology) , cultivar , agronomy , selection (genetic algorithm) , survivorship curve , population , bioenergy , yield (engineering) , microbiology and biotechnology , biofuel , demography , genetics , materials science , cancer , artificial intelligence , sociology , computer science , metallurgy
Switchgrass ( Panicum virgatum L.) is an important candidate for bioenergy feedstock production, prompting significant efforts to increase the number of breeding programs and the output of those programs. The objective of this experiment was to determine the potential utility of natural selection for survivorship in switchgrass swards as a tool for improving efficiency of progeny‐test‐based recurrent selection programs in switchgrass. One hundred random surviving plants were selected from 5‐yr‐old plots of six cultivars grown at five locations. Progeny of each population were grown in a four‐location field experiment in Illinois and Wisconsin in direct comparison to their parent populations. On average, natural selection for survivorship increased biomass yield by 6.7%. The northernmost (i.e., coldest) selection location had the greatest response among the five locations (13.2%) while the most genetically diverse cultivar had the greatest response among the cultivars (23.5%). Results were highly variable among cultivars and selection locations, but there were no significant negative responses, suggesting that the genetic correlation between survivorship and biomass yield in switchgrass ranges from zero to some positive value. Selection for survivorship within switchgrass sward plots has the potential to improve efficiency of family‐based selection methods designed to improve biomass yieldpotential.