Data di Pubblicazione:
2018
Abstract:
Machine learning has emerged with big data technologies and high-performance computing
to create new opportunities for data intensive science in the multi-disciplinary agri-technologies
domain. In this paper, we present a comprehensive review of research dedicated to applications
of machine learning in agricultural production systems. The works analyzed were categorized in
(a) crop management, including applications on yield prediction, disease detection, weed detection
crop quality, and species recognition; (b) livestock management, including applications on animal
welfare and livestock production; (c) water management; and (d) soil management. The filtering
and classification of the presented articles demonstrate how agriculture will benefit from machine
learning technologies. By applying machine learning to sensor data, farm management systems are
evolving into real time artificial intelligence enabled programs that provide rich recommendations
and insights for farmer decision support and action.
Tipologia CRIS:
03B-Review in Rivista / Rassegna della Lett. in Riv. / Nota Critica
Keywords:
Artificial intelligence; Crop management; Livestock management; Planning; Precision agriculture; Soil management; Water management; Analytical Chemistry; Atomic and Molecular Physics, and Optics; Biochemistry; Instrumentation; Electrical and Electronic Engineering
Elenco autori:
Liakos, Konstantinos G.; Busato, Patrizia; Moshou, Dimitrios; Pearson, Simon; Bochtis, Dionysis*
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