Emerging Technologies in Agriculture and Food Science

Machine Learning for Precision Agriculture: Methods and Applications

Author(s): Ennio Ottaviani, Enrico Barelli and Karim Ennouri

Pp: 91-107 (17)

Doi: 10.2174/9789811470004120010007

* (Excluding Mailing and Handling)

Abstract

Agriculture plays a critical role in the global economy, and pressure on agricultural systems will continue to increase as the world’s population grows. Modern agricultural techniques should take into account both the increased need for efficiency and the challenges posed by climate change, which together define the competing needs for sustainable farming and increased food production. Precision agriculture (PA) refers to the use of both advanced sensor technologies and state-of-the-art data analysis techniques in order to develop data-driven decision support systems. PA can help farmers to optimize crop management through accurate yield prediction and the timely detection of plant diseases and pests. Similar techniques and sensors to those used in precision agriculture can be used in the management and monitoring of livestock or fish farms, which this paper will introduce for completeness. A survey of machine learning methods will be presented in order to provide researchers and endusers with an up-to-date starting point for their projects and use-cases.


Keywords: Artificial Intelligence, Crop Management, Data Analysis, Livestock Management, Machine Learning, Precision Agriculture, Smart Farms, Soil Management, Statistical Prediction.

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