Analysis of Andean blackberry (Rubus glaucus) production models obtained by means of artificial neural networks exploiting information collected by small-scale growers in Colombia and publicly available meteorological data

Computers and Electronics in Agriculture

Volumn 69, Issue 2, 2009, Pages 198-208

  Jiménez, Daniel ^a,c,d   Cock, James ^d,e   Satizábal, Héctor F ^b,c,d   Barreto S, Miguel A ^b,c,d   Pérez Uribe, Andrés ^c   Jarvis, Andy ^e,f   Van Damme, Patrick ^a  

^a GHENT UNIVERSITY   (Belgium)

^b UNIVERSITY OF LAUSANNE   (Switzerland)

^c UNIVERSITY OF APPLIED SCIENCES WESTERN SWITZERLAND   (Switzerland)

^d BIOTEC   (Colombia)

^e INTERNATIONAL CENTER FOR TROPICAL AGRICULTURE CIAT   (Colombia)

^f BIOVERSITY INTERNATIONAL   (Italy)

Author keywords

Andean blackberry; Artificial neural networks; Input relevance analysis; Multilayer perceptron; Publicly available meteorological data; Self Organizing Maps; Small scale growers

Indexed keywords

ANDEAN BLACKBERRY; ARTIFICIAL NEURAL NETWORKS; INPUT RELEVANCE ANALYSIS; MULTILAYER PERCEPTRON; PUBLICLY AVAILABLE METEOROLOGICAL DATA; SMALL-SCALE GROWERS;

BACKPROPAGATION; CONFORMAL MAPPING; CROPS; CYBERNETICS; ELECTRIC LOADS; GEOLOGIC MODELS; MULTILAYERS; PATTERN RECOGNITION SYSTEMS; PRODUCTION ENGINEERING; PRODUCTIVITY; SELF ORGANIZING MAPS; SOILS;

MULTILAYER NEURAL NETWORKS;

ACCURACY ASSESSMENT; ARTIFICIAL NEURAL NETWORK; CROP YIELD; ENVIRONMENTAL CONDITIONS; FRUIT; HILL; METEOROLOGY; PRECIPITATION (CLIMATOLOGY); SOIL DEPTH; SOIL DRAINAGE; SOIL TEMPERATURE;

COLOMBIA; SOUTH AMERICA;

RUBUS; RUBUS GLAUCUS;

EID: 70349569467     PISSN: 01681699     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.compag.2009.08.008     Document Type: Article

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