Abstract
Understanding crop yield formation is important for agronomists to make a contribution to improved cropmanagement. An analytical procedure, referred to here as Sp-method, is presented as a way to evaluatealternative ways to achieve yield advances, based on ecological theory and using regression techniques. Therationale of Sp-method is that the crop yield is the result of genetic potential performance under ecologicalpressure within field environments. Yield and its components are expressed as mathematical equationsrepresenting interacting ecological and management factors. Partial differentials of yield components andgradients for the factors assessed reveal which management tactics can best be exploited for higher crop yield.The application of this routine is illustrated with two examples, and some directions are pointed out for betterapplying and improving this method.
Highlights
Higher crop yield is farmers’ aspiration, and something that most governments seek to promote
High yield is the focus of much agricultural research, especially in countries with large populations to feed such as China
Thresholds for super- high yield have previously been considered as 12 tons per hectare for rice, 9 tons per hectare for wheat, and 13.5-18 tons per hectare for maize, and various impressive achievements have been achieved in high-yield contests (Yang, 1987; Wang et al, 1990; Wang et al, 2000)
Summary
Higher crop yield is farmers’ aspiration, and something that most governments seek to promote. Some researchers seeking a more analytical route have used multiple-regression statistical analysis in their experimental design to explore various mathematic relationships between crop yield and crop management method. Their aim is to find optimum combinations of crop management measures. Several studies have employed (e.g., Lu et al, 1990; Wang et al, 1993; Akihito et al, 1993; Wang et al, 2000) They still have some systematic weaknesses on the physiological side and some mechanistic shortcomings in their regression designs. We elaborate on those results and outline further this new approach
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
