Quantifying critical N dilution curves across G × E × M effects for potato using a partially-pooled Bayesian hierarchical method

• Published in: European journal of agronomy Vol. 144; p. 126744
• Main Authors: Bohman, Brian J., Culshaw-Maurer, Michael J., Ben Abdallah, Feriel, Giletto, Claudia, Bélanger, Gilles, Fernández, Fabián G., Miao, Yuxin, Mulla, David J., Rosen, Carl J.
• Format: Journal Article
• Language: English
• Published: Elsevier B.V 01.03.2023
• Subjects: agronomy; Bayesian; Bayesian theory; class; Critical N concentration; Critical nitrogen dilution curve; data collection; genotype; Genotype-by-environment-by-management interactions; nitrogen content; Nitrogen nutrition index; Nitrogen use efficiency; nutrient use efficiency; nutrition; Potato; potatoes; uncertainty; CNUtEC; E; G; NNI; Critical N concentration; NNIup; M; NPlant; EONR; Nitrogen use efficiency; Potato; CNDClo; Nc; W; Genotype-by-environment-by-management interactions; NUE; NNIlo; CNUC; Critical nitrogen dilution curve; Bayesian; CNDC; Nitrogen nutrition index; NUpE; NUtEc; CNDCup; NUtE
• ISSN: 1161-0301; 1873-7331
• DOI: 10.1016/j.eja.2023.126744

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 quantification 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, systematically evaluates the difference in %Nc [∆%Nc] across G × E × M effects, and directly compare CNDCs from the Bayesian framework to CNDCs from conventional statistical methods. The partially-pooled Bayesian hierarchical method implemented in this study has the advantage of being less susceptible to inferential bias at the level of individual G × E × M interactions compared to alternative statistical methods that result from insufficient 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 × E × M interactions. Where found to be significant, ∆%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 × 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 × E × M interactions; therefore, evaluation of crop N status or N use efficiency must account for variation in %Nc across G × E × M interactions. •Critical N dilution curves [CNDCs] for potato are subject to G x E x M effects.•Bayesian methods can quantify uncertainty in critical N concentration [%Nc].•Partial pooling Bayesian method enables direct comparison of G x E x M effects.•Variation in %Nc for potato due to tuber initiation timing and tuber bulking rate.•N use efficiency and N nutrition index depend on %Nc variability and uncertainty.