TY - JOUR

T1 - Methods of yield stability analysis in long-term field experiments

T2 - A review

AU - Reckling, Moritz

AU - Ahrends, Hella

AU - Chen, Tsu Wei

AU - Eugster, Werner

AU - Hadasch, Steffen

AU - Knapp, Samuel

AU - Laidig, Friedrich

AU - Linstädter, Anja

AU - Macholdt, Janna

AU - Piepho, Hans Peter

AU - Schiffers, Katja

AU - Döring, Thomas F.

N1 - Funding Information: Open Access funding enabled and organized by Projekt DEAL. The research leading to these results received funding from the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) under Grant Agreement numbers 420661662, 420210236, 419973621, and 324840916, provided to MR, JM, TWC, and HPP, respectively. We also thank the DFG for funding the young scientist academy on Agroecosystem Research and Plant Production 2018–2019 that supported MR, JM, and TWC and initiated the collaboration between projects. Additional financial support was received from the Ekhaga Foundation, Stockholm (project RESTOR, 2015-65), and the SusCrop/FACCE-JPI project LegumeGap (Grant 031B0807B). Funding Information: This article is a result of a workshop on ?Methods for analyzing yield stability in long-term field experiments? on November 19?20, 2019, at the University of Bonn, Institute of Crop Science and Resource Conservation, Department of Agroecology and Organic Farming. We thank the Swedish University of Agricultural Sciences, the University of Bonn, Rothamsted Research, and the German Federal Office of Plant Varieties for providing the data from their long-term field experiments and variety trials. The code for analysing the data can be obtained from the authors of the individual sections.

PY - 2021/4

Y1 - 2021/4

N2 - In the face of a changing climate, yield stability is becoming increasingly important for farmers and breeders. Long-term field experiments (LTEs) generate data sets that allow the quantification of stability for different agronomic treatments. However, there are no commonly accepted guidelines for assessing yield stability in LTEs. The large diversity of options impedes comparability of results and reduces confidence in conclusions. Here, we review and provide guidance for the most commonly encountered methodological issues when analysing yield stability in LTEs. The major points we recommend and discuss in individual sections are the following: researchers should (1) make data quality and methodological approaches in the analysis of yield stability from LTEs as transparent as possible; (2) test for and deal with outliers; (3) investigate and include, if present, potentially confounding factors in the statistical model; (4) explore the need for detrending of yield data; (5) account for temporal autocorrelation if necessary; (6) make explicit choice for the stability measures and consider the correlation between some of the measures; (7) consider and account for dependence of stability measures on the mean yield; (8) explore temporal trends of stability; and (9) report standard errors and statistical inference of stability measures where possible. For these issues, we discuss the pros and cons of the various methodological approaches and provide solutions and examples for illustration. We conclude to make ample use of linking up data sets, and to publish data, so that different approaches can be compared by other authors and, finally, consider the impacts of the choice of methods on the results when interpreting results of yield stability analyses. Consistent use of the suggested guidelines and recommendations may provide a basis for robust analyses of yield stability in LTEs and to subsequently design stable cropping systems that are better adapted to a changing climate.

AB - In the face of a changing climate, yield stability is becoming increasingly important for farmers and breeders. Long-term field experiments (LTEs) generate data sets that allow the quantification of stability for different agronomic treatments. However, there are no commonly accepted guidelines for assessing yield stability in LTEs. The large diversity of options impedes comparability of results and reduces confidence in conclusions. Here, we review and provide guidance for the most commonly encountered methodological issues when analysing yield stability in LTEs. The major points we recommend and discuss in individual sections are the following: researchers should (1) make data quality and methodological approaches in the analysis of yield stability from LTEs as transparent as possible; (2) test for and deal with outliers; (3) investigate and include, if present, potentially confounding factors in the statistical model; (4) explore the need for detrending of yield data; (5) account for temporal autocorrelation if necessary; (6) make explicit choice for the stability measures and consider the correlation between some of the measures; (7) consider and account for dependence of stability measures on the mean yield; (8) explore temporal trends of stability; and (9) report standard errors and statistical inference of stability measures where possible. For these issues, we discuss the pros and cons of the various methodological approaches and provide solutions and examples for illustration. We conclude to make ample use of linking up data sets, and to publish data, so that different approaches can be compared by other authors and, finally, consider the impacts of the choice of methods on the results when interpreting results of yield stability analyses. Consistent use of the suggested guidelines and recommendations may provide a basis for robust analyses of yield stability in LTEs and to subsequently design stable cropping systems that are better adapted to a changing climate.

KW - Coefficient of variation

KW - Cropping systems

KW - Mixed models

KW - Statistics

KW - Taylor’s power law

KW - Variability

UR - http://www.scopus.com/inward/record.url?scp=85103500492&partnerID=8YFLogxK

U2 - 10.1007/s13593-021-00681-4

DO - 10.1007/s13593-021-00681-4

M3 - Review article

AN - SCOPUS:85103500492

VL - 41

JO - Agronomy for Sustainable Development

JF - Agronomy for Sustainable Development

SN - 1774-0746

IS - 2

M1 - 27

ER -