Electronic nose predicts high and low fumonisin contamination in maize cultures

Food Research International

Volumn 44, Issue 4, 2011, Pages 992-999

  Gobbi, Emanuela ^a,b   Falasconi, Matteo ^c   Torelli, Emanuela ^a   Sberveglieri, Giorgio ^c  

^a UNIVERSITY OF UDINE   (Italy)

^b Biodiversity spa   (Italy)

^c UNIVERSITY OF BRESCIA   (Italy)

Author keywords

Chemical sensors; Fungi; Fusarium; Volatiles; Zea mays

Indexed keywords

COVARIATES; ELECTRONIC NOSE; EXPLORATORY DATA ANALYSIS; FUMONISIN; FUNGAL COLONIES; FUNGAL CONTAMINATION; FUSARIUM; FUSARIUM VERTICILLIOIDES; IN-VITRO; MAIZE SAMPLE; METAL OXIDE SEMICONDUCTOR; MULTIVARIATE REGRESSION MODELS; PARTIAL LEAST SQUARES; QUANTITATIVE ESTIMATION; RAPID SCREENING; STATISTICAL ANALYSIS; UNIVARIATE; VOLATILES; ZEA MAYS;

ARTIFICIAL ORGANS; CHEMICAL SENSORS; DATA REDUCTION; FUNGI; METALLIC COMPOUNDS; MOS DEVICES; POLLUTION DETECTION; REGRESSION ANALYSIS; SENSOR ARRAYS;

GRAIN (AGRICULTURAL PRODUCT);

FUNGI; FUSARIUM; FUSARIUM OXYSPORUM; FUSARIUM PROLIFERATUM; FUSARIUM SOLANI; FUSARIUM SUBGLUTINANS; GIBBERELLA MONILIFORMIS; ZEA MAYS;

EID: 79955624755     PISSN: 09639969     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.foodres.2011.02.041     Document Type: Article

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