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.

面对气候变化，单产稳定对农民和育种者变得越来越重要。长期野外实验（LTE）生成的数据集可以量化不同农艺处理方法的稳定性。但是，目前尚没有公认的评估LTE良率稳定性的指南。选项的多样性极大地阻碍了结果的可比性，并降低了对结论的信心。在此，我们将分析LTE中的良率稳定性时，对最常遇到的方法问题进行回顾并提供指导。我们在各个部分中建议和讨论的要点如下：研究人员应（1）在分析LTE的产量稳定性时，使数据质量和方法学方法尽可能透明。（2）测试和处理异常值；（3）调查并在统计模型中包括潜在的混杂因素；（4）探索降低收益数据趋势的必要性；（5）必要时考虑时间自相关；（6）为稳定性措施做出明确选择，并考虑其中一些措施之间的相关性；（7）考虑并考虑稳定措施对平均产量的依赖；（8）探索稳定的时间趋势；（9）尽可能报告标准差和稳定性测度的统计推断。对于这些问题，我们讨论了各种方法论方法的利弊，并提供了说明性的解决方案和示例。我们的结论是充分利用链接数据集并发布数据，以便其他作者可以比较不同的方法，最后，在解释产量稳定性分析结果时，应考虑方法选择对结果的影响。一致使用建议的指南和建议可以为LTE的产量稳定性的稳健分析提供基础，并为随后设计更适合气候变化的稳定种植系统提供基础。