LAUSR

ABSTRACT The knowledge of Sowing Dates (SD), Maximum Vegetative Development Dates (MVDD), and Harvest Dates (HD) of crops is important for estimating and forecasting large-scale productivity. Prior information on harvest date of crops is also useful in optimizing grain reception logistics and improving business decision-making in agro-industrial companies. This study aimed to develop a method to predict the HD of soybeans from MVDD, which was obtained from crop maps in the state of Paraná between 2011/2012 and 2013/2014 crop years. TIMESAT software was used to perform a seasonal trend analysis of enhanced vegetation index (EVI) time series from Moderate Resolution Imaging Spectroradiometer (MODIS) satellite imagery. After estimating time intervals between MVDD and HD (MH), applied to each mapped pixel, we calculated the 3 year MH average (average of the interval between MVDD and HD for the 3 crop years) for mesoregion and state levels, respectively. The MH by mesoregion was added to MVDD at a regional level, generating HDFORECAST, which is a prediction of the HD. Our results were compared with information from 44 monitored farms in the state in the 2013/2014 crop year. The findings showed that, for soybeans, MH by mesoregion can be used to predict HD with a Mean Error (ME) of 4.84 days, Mean Absolute Error (MAE) of 6.84 days, Root Mean Square Error (RMSE) of 8.12 days, Willmott modified coefficient (d) of 0.9, and Pearson correlation coefficient (r) of 0.88. Our study has produced valuable information for crop productivity models, as well as for logistics of grain transportation and storage in agro-companies, which can anticipate operations knowing when grains will be harvested and delivered to the centres.