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Assessment of crop development provides important information for agricultural management and yield prediction. Accurate estimates of crop phenology require information about actual planting dates and hydrometeorological variables such as soil moisture and temperature. In 2019, an unseasonably wet spring across Illinois due to persistent flood events delayed or prevented normal planting, ultimately reducing crop production. A study was conducted to develop a novel approach to determine day of planting for corn using remotely sensed soil moisture and temperature. Planting dates were determined based on soil moisture conditions and soil temperature suitable for corn germination. Estimated planting dates were then used to initiate accumulating growth degree days derived from air temperature to estimate the crop progress stages. Results were evaluated by comparing the estimated planting schedule and timelines of crop phenology to those obtained from USDA’s Crop Progress Report. The estimated planting schedule shows that more than 90 % of the fields were planted by June 2 in normal seasons, while only about 45 % of fields were planted by that date in 2019, similar to that observed from the USDA’s report. Overall, estimates of accumulative planted areas over the planting season for both normal seasons and for 2019 match up well to USDA’s report. Nearly two weeks of average planting delay for 2019, as compared to normal seasons, resulted in 20-30 days of delays for all growth stages through the season, which can also be observed from both estimated and reported timelines of crop phenology. The RMSDs between estimated and reported crop progress timelines over the growing seasons for 2015-2020 and 2019 are 6.0 and 4.8 days, respectively. These results demonstrate the feasibility of utilizing soil moisture and temperature to estimate the planting schedule and crop phenology for agricultural management. This proposed approach is particularly applicable for assessment of planting schedule during extremely wet soil conditions. In addition, the study provides an opportunity to estimate planting dates along with the sowing season that can be further applied with weather forecasting data for crop yield prediction and assessment in the early stage of the growing season.
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