The Power of Indicators in Agriculture Decision Support Systems: Integrating Climate, Remote Sensing, and Crop Phenology.

Agricultural production must deal with many challenges to feed the nine billion people predicted by the mid-century. The climate variability and change has been one of the main factors which affect the crop productivity being variable in space and time, and which impact can highly vary according to physical landscape, agricultural management practices, and along the crop growing season. Assessing and monitoring the state of the vegetation condition by integrating indicators of Climate and remote sensing-based Vegetation Indices (C+VI) on critical phenological stages is key information that can improve agricultural decision support systems. In this study, we evaluated the use of (C+VI) under phenological stages over maize areas in Nebraska-USA. Spatial and time variability as well as under irrigated and rainfed fields were considered. Indicators of heat stress were given by Killing Degree Days (KDD) and Accumulated Night Temperature Index (NT), and the water stress determined by the Agricultural Reference Index for Drought (ARID). Canopy properties and condition were evaluated using vegetation indices of NDVI and EVI2 from MODIS Terra satellite 16-days product. Crop phenology was estimated using a gridded layer of maize phenology simulated using minimum and maximum temperature records in an adaptation of the CERES-Maize model. The indicators presented a potential to evaluate crop response to climate-driven stresses. In the resulting of that, a decision support system (DSS) has been developed to customize AgroClimate web system for the National Agricultural Statistics Service (USDA-NASS) allowing a better assessment to identify, measure, and monitor the effect of climate variability and extreme events on crops.