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Testing Taylor’s Power Law association of winter wheat variation with mean yield at two contrasting soils
European Journal of Agronomy ( IF 5.2 ) Pub Date : 2021-03-11 , DOI: 10.1016/j.eja.2021.126268
Pavlina Smutná , Ioannis S. Tokatlidis

Previous research has found that, based on Taylor’s Power Law (TPL), the coefficient of variation (CV) of yield data may functionally be related to the mean, with an exponential mean yield decline with increasing CV. Recent proposals have been made how this scale-dependency can be removed in order to allow a scale-independent assessment of stability. The theoretical background of the hypothesis was studied in wheat (Triticum aestivum L.) throughout data obtained from two fields of the farm of the Mendel University of Brno, Czech Republic. Soils of the two fields were of the contrasting loamy and sandy textures. Yield variation was intense in the sandy field representing a low-input agro-ecosystem. TPL became more obvious when the two fields were considered together, so as to enlarge the range of means and CVs. On the simple correlation between logarithms of variances and respective means, there was a systematic dependence of yield variance on mean yield when the within-block CV was considered. Conversion of variance to remove dependence on mean did not validate the CV ∼ yield negative relationship meaning that caution is needed when interpreting the CV of yield as a stability index. On the other hand, when the genotype CV for yield was considered variance was independent of the mean indicating agronomic essence in the CV∼ yield relationship, and coupled with the POLAR statistic, based on the negative residuals from the linear TPL regression that reflect low variability, revealed genotype cases exhibiting both high yield and stability. The findings corroborated that TPL is not always valid depending on scales and factors structuring the data. Interpreting crop variation via CV may entail a risk of bias due to variance dependence on mean, whereas the POLAR index offers an alternative stability measure that allows straight-forward interpretation providing the basis for developing more stable cropping systems. A trade-off between yield and stability does not exclude genotype cases of simultaneous occurrence of both, pinpointing realism in the pursuit of stable varieties without compromising yield.



中文翻译:

用两种对比土壤上的平均产量测试冬小麦变异的泰勒幂定律关联

先前的研究发现,基于泰勒幂定律(TPL),收益数据的变异系数(CV)在功能上可能与均值相关,随着CV的增加,指数平均收益率下降。最近提出了如何消除这种尺度依赖性的提议,以便进行与尺度无关的稳定性评估。在小麦(Triticum aestivum)中研究了该假设的理论背景。L.)从捷克布尔诺的孟德尔大学农场两个场获得的数据。这两个田地的土壤具有对比鲜明的壤土和沙质质地。沙地的产量变化剧烈,代表着低投入的农业生态系统。当同时考虑这两个领域时,TPL变得更加明显,从而扩大了均值和CV的范围。关于方差对数与相应均值之间的简单相关性,当考虑块内CV时,产量方差对平均产量的系统依赖性。方差转换以消除对均值的依赖性并不能验证CV〜产生负相关,这意味着在解释CV时需要谨慎收率作为稳定性指标。在另一方面,当基因型CV为产量被认为方差是独立的在平均指示农艺本质CV〜产量的关系,以及与所述POLAR统计量,基于从线性TPL回归反映低变异负残差,揭示了表现出高产量和稳定性的基因型病例。该发现证实了TPL并不总是有效的,这取决于构成数据的规模和因素。通过简历解释农作物变异由于方差对均值的依赖性,可能会带来偏差的风险,而POLAR指数提供了另一种稳定性测度,可以进行直接解释,从而为开发更稳定的种植系统提供基础。在产量和稳定性之间进行权衡并不能排除同时出现两者的基因型情况,这在追求稳定品种而不损害产量的前提下明确了现实性。

更新日期:2021-03-11
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