Water scarcity and unreliable weather conditions frequently cause smallholder farmers in Zimbabwe to plant maize (Zea mays L.) varieties outside the optimum planting timeframe. This challenge exacts the necessity to develop sowing management options for decision support. The study's objective was to use a hybrid approach to determine the best planting windows and maize varieties. The combination will guide farmers on planting dates, dry spell probability during critical stages of the crop growth cycle and rainfall cessation. To capture farmer's perception on agroclimatic information, a systematic random sampling of 438 smallholders was carried out. An analysis of climatic data during 1949-2012 was conducted using INSTAT to identify the best planting criterion. The best combination of planting criterion and maize varieties analysis was then achieved by optimizing planting dates and maize varieties in the DSSAT environment. It was found that 56.2% of farmers grew short-season varieties, 40.2% medium-season varieties and 3.6% long-season varieties. It was also established that the number of rain days and maize yield had a strong positive relationship (p = 0.0049). No significant association was found amongst maize yield (p > 0.05), and planting date criteria, Depth (40mm in 4 days), the AREX criterion- Agricultural Research Extension (25 mm rainfall in 7 days) and the MET Criterion-Department of Meteorological Services (40 mm in 15 days). Highest yields were simulated under the combination of medium-season maize variety and the AREX and MET criteria. The range of simulated yields from 0.0 t/ha to 2.8 t/ha formed the basis for the development of an operational decision support tool (cropping calendar) with (RMSE) (0.20). The methodology can be used to select the best suitable maize varieties and a range of planting time.
Keywords: Climate variability; Crop modelling; Cropping calendar; DSSAT; Maize varieties.
© 2021 The Authors.