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Effects of systematic data reduction on trend estimation from German registration trials
KEY MESSAGE: VCU trials can provide unbiased estimates of post-breeding trends given that all data is used. Dropping data of genotypes tested for up to two years may result in biased post-breeding trend estimates. ABSTRACT: Increasing yield trends are seen on-farm in Germany. The increase is based o...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer Berlin Heidelberg
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9870826/ https://www.ncbi.nlm.nih.gov/pubmed/36688966 http://dx.doi.org/10.1007/s00122-023-04266-5 |
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author | Hartung, Jens Laidig, Friedrich Piepho, Hans-Peter |
author_facet | Hartung, Jens Laidig, Friedrich Piepho, Hans-Peter |
author_sort | Hartung, Jens |
collection | PubMed |
description | KEY MESSAGE: VCU trials can provide unbiased estimates of post-breeding trends given that all data is used. Dropping data of genotypes tested for up to two years may result in biased post-breeding trend estimates. ABSTRACT: Increasing yield trends are seen on-farm in Germany. The increase is based on genetic trend in registered genotypes and changes in agronomic practices and climate. To estimate both genetic and non-genetic trends, historical wheat data from variety trials evaluating a varieties’ value for cultivation und use (VCU) were analyzed. VCU datasets include information on varieties as well as on genotypes that were submitted by breeders and tested in trials but could not make it to registration. Therefore, the population of registered varieties (post-registration population) is a subset of the population of genotypes tested in VCU trials (post-breeding population). To assess post-registration genetic trend, historical VCU trial datasets are often reduced, e.g. to registered varieties only. This kind of drop-out mechanism is statistically informative which affects variance component estimates and which can affect trend estimates. To investigate the effect of this informative drop-out on trend estimates, a simulation study was conducted mimicking the structure of German winter wheat VCU trials. Zero post-breeding trends were simulated. Results showed unbiased estimates of post-breeding trends when using all data. When restricting data to genotypes tested for at least three years, a positive genetic trend of 0.11 dt ha(−1) year(−1) and a negative non-genetic trend (− 0.11 dt ha(−1) year(−1)) were observed. Bias increased with increasing genotype-by-year variance and disappeared with random selection. We simulated single-trait selection, whereas decisions in VCU trials consider multiple traits, so selection intensity per trait is considerably lower. Hence, our results provide an upper bound for the bias expected in practice. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s00122-023-04266-5. |
format | Online Article Text |
id | pubmed-9870826 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Springer Berlin Heidelberg |
record_format | MEDLINE/PubMed |
spelling | pubmed-98708262023-01-25 Effects of systematic data reduction on trend estimation from German registration trials Hartung, Jens Laidig, Friedrich Piepho, Hans-Peter Theor Appl Genet Original Article KEY MESSAGE: VCU trials can provide unbiased estimates of post-breeding trends given that all data is used. Dropping data of genotypes tested for up to two years may result in biased post-breeding trend estimates. ABSTRACT: Increasing yield trends are seen on-farm in Germany. The increase is based on genetic trend in registered genotypes and changes in agronomic practices and climate. To estimate both genetic and non-genetic trends, historical wheat data from variety trials evaluating a varieties’ value for cultivation und use (VCU) were analyzed. VCU datasets include information on varieties as well as on genotypes that were submitted by breeders and tested in trials but could not make it to registration. Therefore, the population of registered varieties (post-registration population) is a subset of the population of genotypes tested in VCU trials (post-breeding population). To assess post-registration genetic trend, historical VCU trial datasets are often reduced, e.g. to registered varieties only. This kind of drop-out mechanism is statistically informative which affects variance component estimates and which can affect trend estimates. To investigate the effect of this informative drop-out on trend estimates, a simulation study was conducted mimicking the structure of German winter wheat VCU trials. Zero post-breeding trends were simulated. Results showed unbiased estimates of post-breeding trends when using all data. When restricting data to genotypes tested for at least three years, a positive genetic trend of 0.11 dt ha(−1) year(−1) and a negative non-genetic trend (− 0.11 dt ha(−1) year(−1)) were observed. Bias increased with increasing genotype-by-year variance and disappeared with random selection. We simulated single-trait selection, whereas decisions in VCU trials consider multiple traits, so selection intensity per trait is considerably lower. Hence, our results provide an upper bound for the bias expected in practice. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s00122-023-04266-5. Springer Berlin Heidelberg 2023-01-23 2023 /pmc/articles/PMC9870826/ /pubmed/36688966 http://dx.doi.org/10.1007/s00122-023-04266-5 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Original Article Hartung, Jens Laidig, Friedrich Piepho, Hans-Peter Effects of systematic data reduction on trend estimation from German registration trials |
title | Effects of systematic data reduction on trend estimation from German registration trials |
title_full | Effects of systematic data reduction on trend estimation from German registration trials |
title_fullStr | Effects of systematic data reduction on trend estimation from German registration trials |
title_full_unstemmed | Effects of systematic data reduction on trend estimation from German registration trials |
title_short | Effects of systematic data reduction on trend estimation from German registration trials |
title_sort | effects of systematic data reduction on trend estimation from german registration trials |
topic | Original Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9870826/ https://www.ncbi.nlm.nih.gov/pubmed/36688966 http://dx.doi.org/10.1007/s00122-023-04266-5 |
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