The Application of Machine Learning in Agriculture Sustainability: A Review

Abstract

The major challenge arises from social issues such as overpopulation and the competition over food resources and groundwater overused poses the main threat to food security. Sustainable development is becoming increasingly important in the agricultural sector, considering the environmental pressures from climate change, soil management, crop yield management, water consumption, and irrigation management, as well as disease management. This paper presents the finding of the literature review analysis to establish the modern evidence regarding the application of Machine Learning in Agriculture Sustainability. Published papers are reviewed within the period from 2018 to 2022. Advanced computer algorithm techniques have been learned and explored to improvise the challenges faced by agriculture sector, to ensure the efficiency of yields and sustainability, and to increase the level of quality of agriculture products in society generally. Meanwhile, the methods of Machine Learning have also been deeply explored recently to develop advanced techniques for agriculture to increase data-driven decision-making for farmers.