期刊
EUROPEAN JOURNAL OF AGRONOMY
卷 144, 期 -, 页码 -出版社
ELSEVIER
DOI: 10.1016/j.eja.2023.126744
关键词
Critical N concentration; Critical nitrogen dilution curve; Nitrogen nutrition index; Nitrogen use efficiency; Potato; Bayesian; Genotype-by-environment-by-management; interactions
类别
This study develops nitrogen dilution curves for potato using a partially-pooled Bayesian hierarchical method, which allows for a direct statistical comparison of %Nc differences across genotype, environment, and management interactions. It addresses the issues of non-uniform statistical methods, biased experimental data, and lack of uncertainty quantification in %Nc.
Multiple critical N dilution curves [CNDCs] have been previously developed for potato; however, attempts to directly compare differences in CNDCs across genotype [G], environment [E], and management [M] interactions have been confounded by non-uniform statistical methods, biased experimental data, and lack of proper quan-tification of uncertainty in the critical N concentration [%Nc]. This study implements a partially-pooled Bayesian hierarchical method to develop CNDCs for previously published and newly reported experimental data, sys-tematically evaluates the difference in %Nc [Delta%Nc] across G x E x M effects, and directly compare CNDCs from the Bayesian framework to CNDCs from conventional statistical methods. The partially-pooled Bayesian hier-archical method implemented in this study has the advantage of being less susceptible to inferential bias at the level of individual G x E x M interactions compared to alternative statistical methods that result from insuffi-cient quantity and quality of experimental datasets (e.g., unbalanced distribution of N limiting and non-N limiting observations). This method also allows for a direct statistical comparison of differences in %Nc across levels of the G x E x M interactions. Where found to be significant, Delta%Nc was hypothesized to be related to variation in the timing of tuber initiation (e.g., maturity class) and the relative rate of tuber bulking (e.g., planting density) across G x E x M interactions. In addition to using the median value for %Nc (i.e., CNDC), the lower and upper boundary values for the credible region (i.e., CNDClo and CNDCup) derived using the Bayesian framework should be used in calculation of N nutrition index (and other calculations) to account for uncertainty in %Nc. Overall, this study provides additional evidence that%Nc is dependent upon G x E x M interactions; therefore, evaluation of crop N status or N use efficiency must account for variation in %Nc across G x E x M interactions.
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