Pubblicazione scientifica

Machine Learning in Agriculture: A Review

FILONE TECNOLOGICO	TEMA
produzione e raccolta	macchinari di ausilio alla produzione/raccolta metodi di allevamento: specie ittiche da allevamento metodi di riproduzione (micro alghe, molluschi, ecc.) sistemi di gestione/misura/monitoraggio ausiliari alla produzione e raccolta sistemi di produzione di acquacoltura biologica

RIASSUNTO

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.

DATA

Data di pubblicazione: 14/08/2018

AUTORI

LIAKOS KONSTANTINOS G
BUSATO PATRIZIA
MOSHOU DIMITRIOS
PEARSON SIMON
BOCHTIS DIONYSIS

ENTE DI AFFERENZA

Institute for Bio-Economy and Agri-Technology (IBO) Centre of Research and Technology—Hellas (CERTH) 6th km Charilaou-Thermi Rd GR 57001 Thessaloniki Greece; k.liakos@certh.gr (K.G.L.); dmoshou@auth.gr (D.M.)
DEPT AGRICULTURE FORESTRY & FOOD SCIENCES DISAFA FACULTY OF AGRICULTURE UNIV TURIN LARGO BRACCINI 2 10095 GRUGLIASCO ITALY PATRIZIA BUSATO UNITO IT
AGRICULTURAL ENG LAB FACULTY OF AGRICULTURE ARISTOTLE UNIV THESSALONIKI 54124 THESSALONIKI GREECE
LINCOLN INST AGRI FOOD TECH LIAT UNIV LINCOLN BRAYFORD WAY BRAYFORD POOL LINCOLN LN6 7TS UK SPEARSON LINCOLN AC UK

RIVISTA

Sensors (Basel, Switzerland), 18(8), 2674

IMPACT FACTOR

3,510

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