Abstract
AbstractThe leaf area index (LAI) of a crop is an input in many agronomic models, but is time consuming to measure. An accurate method of estimating LAI is needed. Using measurements from 72 plots over 17 yr, a model was developed to predict corn (Zea mays L.) LAI based on a normalized thermal crop calendar (NC). The seasonal change in LAI was divided into three periods: 1) planting to silking; 2) silking to the start of rapid senescence; and 3) rapid senescence. The LAI data during the first period were fitted with a logistic function of NC and the maximum leaf area per plant (LAmax) using plot‐years with no moisture stress. The LAmax was predicted using the population density and a hybrid coefficient. The decline in LAI during the second period was predicted with NC, the maximum LAI, and a hybrid coefficient. During the third period, LAI prediction was based on the number of days past the beginning of rapid senescence. Leaf area measurements in plot‐years with moisture stress were used to develop a stress growth factor (SGF) to reduce the growth of LAI in the first period. The SGF was determined from the daily ratios of actual to potential evapotranspiration (ET/PET). Daily ET/PET values < 1.00 reduced LAI growth. Moisture stress did not affect LAI during Periods 2 and 3. The error of predicted LAI for independent plot‐years averaged 19% for the first period, 11% for the second, and 58% for the period of rapid senescence. The model is recommended for broader testing and use.
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