Artificial neural network modelling to predict cuticle cracking in greenhouse peppers and tomatoes

Computers and Electronics in Agriculture

Volumn 61, Issue 2, 2008, Pages 108-116

  Ehret, David L ^a   Hill, Bernard D ^b   Raworth, David A ^a   Estergaard, Brad ^a  

^a SUMMERLAND RESEARCH AND DEVELOPMENT CENTRE   (Canada)

^b LETHBRIDGE RESEARCH CENTRE   (Canada)

Author keywords

Artificial neural networks; Cuticle cracking; Greenhouse; Pepper; Russeting; Tomato

Indexed keywords

ATMOSPHERIC HUMIDITY; CROPS; FRUITS; GROWTH RATE; MATHEMATICAL MODELS; MEAN SQUARE ERROR; SENSITIVITY ANALYSIS;

CUTICLE CRACKING; PEPPER; RUSSETING;

NEURAL NETWORKS;

AGRICULTURAL MODELING; ARTIFICIAL NEURAL NETWORK; BIOLOGICAL DEVELOPMENT; ENVIRONMENTAL FACTOR; FRUIT; GREENHOUSE ECOSYSTEM; GROWTH RATE; MODEL VALIDATION; SENSITIVITY ANALYSIS; SPICE;

BRITISH COLUMBIA; CANADA; NORTH AMERICA;

CAPSICUM; LYCOPERSICON ESCULENTUM;

EID: 38949143920     PISSN: 01681699     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.compag.2007.09.011     Document Type: Article

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