Development of Reliable Decision Support for Precision Agricultural Farming

Abstract

Decision Support Systems are becoming increasingly valuable for precision agriculture with direct applications in predicting crop productivity and disease outbreaks. This review article provides an introduction to decision support systems, along with use case examples of decision support tools being developed and marketed by various companies. We discuss the different types of decision support systems based on farm data, communication, knowledge, and predictions made by historical data, farmers or producers. Use case examples are presented by company products in the areas of managing the breadth and depth of resources, knowledge, and data within various types of sensing (soil sensing, remote sensing etc.) and farm management (nutrients, water etc.) while detecting and preventing disease outbreaks (integrated pest management and disease resistance) in crops and livestock. There is a significant increase in the levels of investment for agricultural decision support systems which suggests a growing level of farm-level acceptance of such technologies which deploy state-of-art data computation and data management tools. At the same time, there are several challenges and considerations in developing, testing, and implementing decision support systems that are also discussed here, including costs, data quality, data management, model development, reliability testing, reluctance of new technologies, and ethical considerations.  We hope this article will provide a comprehensive summary of decision support tools in precision agriculture which will inspire future use cases that add value to our society.