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A Peanut Simulation Model: II. Assessing Regional Production Potential
Author(s) -
Meinke Holger,
Hammer Graeme L.
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/agronj1995.00021962008700060010x
Subject(s) - production (economics) , sowing , simulation modeling , yield (engineering) , agricultural engineering , environmental science , agronomy , engineering , mathematics , materials science , macroeconomics , mathematical economics , metallurgy , economics , biology
An assessment of production potential over a broad geographical region is useful in industry planning. In this study, we present a method for combining crop simulation with spatial analysis to assess regional production potential. The Australian peanut industry, and its plan to expand production to new areas, is used as a case study to demonstrate the method. Using a peanut simulation model and historical climate records, irrigated potential peanut yields were simulated for a range of sowing dates at 53 locations throughout eastern Australia. The simulated median potential yield and feasible planting period at each location were used in a spatial interpolation routine to generate maps of regional production potential. The results were consistent with industry experience in traditional production areas and highlighted new areas with good potential for irrigated production. The analysis also showed the change in feasible planting period and optimal sowing date throughout the broad geographical region covered. The analysis considered only temperature and radiation effects on potential production. Other factors, such as disease incidence and water availability, must be considered in conjunction with these results when using them for industry planning. However, the methodology presented demonstrates how combining simulation analysis with simple spatial analysis can provide useful information to support industry planning.