Abstract
Abstract Data from Oklahoma peanut (Arachis hypogaea L.) performance tests from 1969 through 1978 were used to estimate genotype X environment interaction variance components for pod yield, %TSMK, % SS, % OK, and gross return per unit area. The objectives of this study were to determine if it would be advantageous to select cultivars for specific regions, and to determine the most efficient combination of years, locations, and replications to use when evaluating peanut lines. Evidence was obtained that genotypes perform consistently between irrigated and nonirrigated locations for the traits studied. The variance of the difference between two cultivars or lines was calculated for % TSMK, pod yield, and gross return using various combinations of years, locations, and replications. Results indicate that, when testing for gross return, the time presently allotted for testing could be reduced without sacrificing accuracy.
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Claims 2
Claim · model-written summary
Peanut genotypes performed consistently between irrigated and nonirrigated locations for the traits studied.
- Taxon
- peanut
Arachis hypogaeat0 - Treatment
- irrigated and nonirrigated locationse1
- Outcome
- genotypes perform consistentlye1
- Direction
- consistentlye1
- Setting
- Oklahomat0
Organisms pictured · Representative pictures of the matched species, not figures from the paper.
Verbatim
t0“Peanut Lines in Oklahoma”
e1“Evidence was obtained that genotypes perform consistently between irrigated and nonirrigated locations for the traits studied”
Claim · model-written summary
The testing time presently allotted for gross return could be reduced without sacrificing accuracy in peanut line evaluation.
- Taxon
- peanutArachis hypogaeat0
- Outcome
- the time presently allotted for testing could be reducede2
- Qualifier
- without sacrificing accuracye2
Organisms pictured · Representative pictures of the matched species, not figures from the paper.
Verbatim
t0“Peanut Lines in Oklahoma”
e2“when testing for gross return, the time presently allotted for testing could be reduced without sacrificing accuracy”