(1) School of Mathematical Sciences, Queensland University of Technology, 2 George Street, Brisbane, 4000, Australia;(2) Department of Primary Industries (DPI), PO Box 102, Toowoomba, 4350 Queensland, Australia
Abstract:
Agronomists use overlaying protein and yield maps to identify factors limiting cereal crop growth and development. Management decisions can be derived from knowing what and where these limiting factors are. In using protein and yield in this manner, there is an assumption that a physiologically or biologically significant relationship exists between grain protein and grain yield at the local level. In this paper, we investigate whether within-field yield and protein data support this relationship. The protein-yield relationship was modelled using weighted regression with global and local neighbourhoods in both 1-D and 2-D spatial location frameworks. The results from both the 1-D and 2-D analyses showed that the relationships between protein and yield are significant at both the macro (field level) (r2=0.25) and the micro-scale (local within field level) (r2=0.69). The assumption of a significant local relationship between protein and yield is supported by these data, suggesting that management decisions may be determined using such a relationship.