Literature DB >> 24232712

Accuracy and selection success in yield trial analyses.

H G Gauch1, R W Zobel.   

Abstract

Yield trials serve research purposes of estimation and selection. Order statistics are used here to quantify the successes or problems to be expected in selection tasks commonly encountered in breeding and agronomy. Greater accuracy of yield estimates implies greater selection success. A New York soybean yield trial serves as a specific example. The Additive Main effects and Multiplicative Interaction (AMMI) statistical model is used to increase the accuracy of these soybean yield estimates, thereby increasing the probability of successfully selecting, on the basis of the empirical yield data, that genotype which has the maximum true mean. The statistical strategy for increasing accuracy is extremely cost effective relative to the alternative strategy of increasing the number of replications. Better selections increase the speed and effectiveness of breeding programs, and increase the reliability of variety recommendations. Selection tasks are frequently more difficult than may be suspected.

Entities:  

Year:  1989        PMID: 24232712     DOI: 10.1007/BF00274266

Source DB:  PubMed          Journal:  Theor Appl Genet        ISSN: 0040-5752            Impact factor:   5.699


  1 in total

1.  Predictive and postdictive success of statistical analyses of yield trials.

Authors:  H G Gauch; R W Zobel
Journal:  Theor Appl Genet       Date:  1988-07       Impact factor: 5.699

  1 in total
  7 in total

1.  Imputing missing yield trial data.

Authors:  H G Gauch; R W Zobel
Journal:  Theor Appl Genet       Date:  1990-06       Impact factor: 5.699

2.  Interpreting genotype-by-environment interaction using redundancy analysis.

Authors:  F A van Eeuwijk
Journal:  Theor Appl Genet       Date:  1992-10       Impact factor: 5.699

3.  Use of AMMI and linear regression models to analyze genotype-environment interaction in durum wheat.

Authors:  M M Nachit; G Nachit; H Ketata; H G Gauch; R W Zobel
Journal:  Theor Appl Genet       Date:  1992-03       Impact factor: 5.699

Review 4.  Use of genotype x environment interactions to understand rooting depth and the ability of wheat to penetrate hard soils.

Authors:  Tina L Botwright Acuña; Len J Wade
Journal:  Ann Bot       Date:  2012-11-29       Impact factor: 4.357

5.  Full and reduced models for yield trials.

Authors:  H G Gauch
Journal:  Theor Appl Genet       Date:  1990-08       Impact factor: 5.699

6.  AMMI adjustment for statistical analysis of an international wheat yield trial.

Authors:  J Crossa; P N Fox; W H Pfeiffer; S Rajaram; H G Gauch
Journal:  Theor Appl Genet       Date:  1991-01       Impact factor: 5.699

7.  Assessing community variation and randomness in public health indicators.

Authors:  Stephan Arndt; Laura Acion; Kristin Caspers; Ousmane Diallo
Journal:  Popul Health Metr       Date:  2011-02-02
  7 in total

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