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

• Autores: Bohman, Brian J.; Culshaw-Maurer, Michael; Abdallah, Feriel Ben; Giletto, Claudia; Bélanger, Gilles; Fernández, Fabián G.; Miao, Yuxin; Mulla, David J.; Rosen, Carl J.
• Año de publicación: 2023
• Idioma: inglés
• Tipo de recurso: artículo
• Fuente: European Journal of Agronomy 144 : 126744 (March 2023)
• Materia: Nitrógeno; Papa; Eficiencia en el Uso de Nutrientes; Concentración; Métodos Estadísticos; Nitrogen; Potatoes; Nutrient Use Efficiency; Concentrating; Statistical Methods
• Institución: Instituto Nacional de Tecnología Agropecuaria

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.
EEA Balcarce
Fil: Bohman, Brian J. University of Minnesota. Department of Soil, Water, and Climate; Estados Unidos.
Fil: Culshaw-Maurer, Michael J. University of Arizona. CyVerse; Estados Unidos.
Fil: Abdallah, Feriel Ben. Walloon Agricultural Research Centre. Productions in Agriculture Department, Crop Production Unit, Bélgica.
Fil: Giletto, Claudia. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Balcarce; Argentina. Unidad Integrada Balcarce. Universidad Nacional de Mar del Plata. Facultad de Ciencias Agrarias; Argentina.
Fil: Bélanger, Gilles. Science and Technology Branch, Agriculture and Agri-Food Canada; Canadá.
Fil: Fernández, Fabián G. University of Minnesota. Department of Soil, Water, and Climate; Estados Unidos.
Fil: Miao, Yuxin. University of Minnesota. Department of Soil, Water, and Climate; Estados Unidos.
Fil: Mulla, David J. University of Minnesota. Department of Soil, Water, and Climate; Estados Unidos.
Fil: Rosen, Carl J. University of Minnesota. Department of Soil, Water, and Climate; Estados Unidos.