E-nose based rapid prediction of early mouldy grain using probabilistic neural networks

Bioengineered

Volumn 6, Issue 4, 2015, Pages 222-226

  Ying, Xiaoguo ^a   Liu, Wei ^a   Hui, Guohua ^a   Fu, Jun ^a  

^a ZHEJIANG A F UNIVERSITY   (China)

Author keywords

Early mouldy grain; Electronic nose; Non linear; Probabilistic neural network; Rapid prediction

Indexed keywords

ARTICLE; ARTIFICIAL NEURAL NETWORK; ELECTRONIC NOSE; GRAIN; MOULD; NONHUMAN; OAT; PHASEOLUS VULGARIS; PREDICTION; PRINCIPAL COMPONENT ANALYSIS; PROBABILISTIC NEURAL NETWORK; RICE; AVENA; CHEMISTRY; DEVICES; FOOD ANALYSIS; FOOD GRAIN; FUNGUS; GENETIC PROCEDURES; HUMAN; MICROBIOLOGY; ORYZA; PHASEOLUS; PROCEDURES; SENSITIVITY AND SPECIFICITY; STATISTICAL MODEL;

AVENA; BIOSENSING TECHNIQUES; EDIBLE GRAIN; ELECTRONIC NOSE; FOOD ANALYSIS; FUNGI; HUMANS; MODELS, STATISTICAL; NEURAL NETWORKS (COMPUTER); ORYZA; PHASEOLUS; PRINCIPAL COMPONENT ANALYSIS; SENSITIVITY AND SPECIFICITY;

EID: 84948165692     PISSN: 21655979     EISSN: 21655987     Source Type: Journal    
DOI: 10.1080/21655979.2015.1022304     Document Type: Article

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