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A Classification System for Factors Affecting Crop Response to Nitrogen Fertilization
Author(s) -
Lory John A.,
Russelle Michael P.,
Randall Gyles W.
Publication year - 1995
Publication title -
agronomy journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.752
H-Index - 131
eISSN - 1435-0645
pISSN - 0002-1962
DOI - 10.2134/agronj1995.00021962008700050015x
Subject(s) - crop , mathematics , agronomy , response factor , yield (engineering) , nitrogen , fertilizer , crop yield , cropping system , chemistry , biology , physics , organic chemistry , chromatography , thermodynamics
Crop response to N fertilizer ( N f ) is influenced by factors such as N f management, soil type, crop sequence, and supply of residual and mineralized N, but there is no framework to define the best strategy to account for a given factor in an N f recommendation. This paper describes a three‐component classification system for evaluating the effect of any factor on yield response to N f . This system provides (i) a vocabulary to describe clearly the effect of a factor on N f recommendations, and (ii) insight on how to adjust N f recommendations for the effect. Factors that affect yield response to N f but not to N supply ( N s ) were classified as shift effects (i.e., movement of a response curve in the x and/or y direction, with no change in coefficients of curvature). Factors that interact with N f and N s response were classified as interaction effects. Nitrogen supply was defined as the sum of aboveground plant N content of the control (0 N applied) plot, postharvest fall NO ‐ 3 in the surface 1.5 m of the control plot, and N f applied. Two 2‐yr experiments were conducted at Rosemount and Waseca, MN, to compare N f response of continuous corn ( Zea mays L.) with that of first‐ and then second‐year corn following alfalfa ( Medicago sativa L.). We used the classification system to evaluate effects of crop sequence, year, and location on corn yield response to N f . Year and crop sequence effects at Rosemount were primarily shift effects, implying that quantifying the effect on N s would be sufficient to account for these effects on N f recommendations. In contrast, the interaction model predominated at Waseca. Consequently, at this location simple adjustments of N s were not sufficient to account for the complexity of crop sequence effects on N f recommendations. This classification system facilitates the organization, evaluation, and communication of the many factors that influence crop yield.