Artificial intelligence in agriculture: Application trend analysis using a statistical approach

Abstract

To ensure food security and sustained production of crops, the traditional practices of agriculture should be replaced by modern artifacts. Artificial intelligence provides advanced methods and procedures that support domain-specific problem-solving and agricultural decision-making. They have immense successful applications for devising suitable solutions in agriculture. Several literature surveys have been reported worldwide regarding the applications of different artificial intelligence techniques in agriculture. However, none of them presented a complete scenario in a single nutshell. Moreover, a traditional and descriptive way of literature review with a limited number of papers is not sufficiently adequate to recognize the application trajectory of various artificial intelligence techniques in agriculture. Only a statistical study can emphasize the advancements and new frontiers of future applications prevailing in the field, compare the various aspects of different techniques and suggest the best one for a particular problem. Trend analysis provides a predictive guideline for forecasting any technique or approach prospect. However, no statistical study or application trend analysis of prevalent artificial intelligence techniques in the major subdomains of agriculture has been reported. This paper presents a statistical study to cover all multidimensional aspects of applications of various artificial intelligence techniques in agriculture concisely, based on a large number of articles published during the last three and a half decades.