Contract Farming Optimization Through Leveraging Artificial Intelligence to Combat Side Marketing Practices

Abstract

Contract farming has become the main financing strategy for most cash crops grown in developing countries in general and Africa in particular. The serendipitous emergence of artificial intelligence brings forth a wide array of possibilities for minimising the incidences of side marketing. A qualitative study was conducted through interviewing a purposive sample of 30 agricultural extension officers directly involved with contract farming of cash crops such as cotton and tobacco, and the data was thematically analysed. The results indicated that artificial intelligence can be deployed to minimize side marketing practices through analysing historical delivery patterns for detecting anomalies, using predictive analytics leveraging past delivery patterns to identify the farmers with a propensity to indulge in side marketing behaviours, and predicting the expected harvest through AI powered drone technology. The study suggested that AI algorithm developers incorporate the above suggested applications in developing tailor made modules for combating side marketing practices.