Effectiveness of the WOFOST simulation model to predict maize

  • S M Wokabi


The World Food Studies (WOFOST) model was applied to predict 3 production levels of maize on the eastern slopes of Mt Kenya in Embu District. Production level 1 used location, temperature, cloudiness and crop characteristic data to calculate the  production potential level of a crop, all other factors remaining optimal. At this production situation only temperature and radiation were limiting factors. This is the crop-time and site-specific maximum obtainable yield under ideal conditions of water and nutrient availability as well as optimum management and input levels. Environment requirements of climate, soil and water for optimum growth and yield vary with crop and crop variety. Production situation 2 analysed the crop production when an additional land quality, the availability of moisture, was limiting. This production situation uses temperature, radiation and moisture as the main limiting factors. Production situation 3 analysed crop production when an additional variable, the nutrient availability is limiting. This situation uses temperature, radiation, water availability and availability of plant nutrients as determining variables. A medium maturity maize (Zea mays L.) variety H 511 was used as the test crop during two cropping seasons in 1992-93. Triple superphosphate (TSP) at the rate of 75 kg P/ha and 75 kg N/ha were applied during planting and when the crop was knee high, respectively. Maize yield was also obtained from farmers' fields. Four yield levels were selected for yield gap analysis, namely potential yield, water limited, experimental and farmers' yields. Potential and water-limited grain yield of maize obtained via the application of WOFOST model compared relatively well with the yield obtained from the experimental plots. This means that if soil and climate conditions of a given area are known, the maize production of the area can be determined accurately using WOFOST model.

How to Cite
Wokabi, S. (2008). Effectiveness of the WOFOST simulation model to predict maize. East African Agricultural and Forestry Journal, 69(1&2). Retrieved from https://www.kalro.org/www.eaafj.or.ke/index.php/path/article/view/57