Fungal damage detection in wheat using short-wave near-infrared hyperspectral and digital colour imaging

International Journal of Food Properties

Volumn 15, Issue 1, 2012, Pages 11-24

  Singh, C B ^a   Jayas, D S ^a   Paliwal, J ^a   White, N D G ^b  

^a UNIVERSITY OF MANITOBA   (Canada)

^b Cereal Research Centre   (Canada)

Author keywords

Colour imaging; Fungal infection; Grain quality; Hyperspectral imaging; NIR

Indexed keywords

COLOUR IMAGE; DISCRIMINANT CLASSIFIERS; FIRST PRINCIPAL COMPONENTS; FUNGAL INFECTION; GRAIN QUALITY; HISTOGRAM FEATURES; HYPER-SPECTRAL IMAGES; HYPERSPECTRAL; HYPERSPECTRAL DATA; HYPERSPECTRAL IMAGING; LINEAR DISCRIMINANT ANALYSIS; MAHALANOBIS; MULTIVARIATE IMAGE ANALYSIS; NIGER; NIR; PENICILLIUM SPP; SHORT-WAVE NEAR-INFRARED; STATISTICAL CLASSIFIER; TEXTURAL FEATURE; WAVELENGTH RANGES; WHEAT KERNELS;

COLOR; DAMAGE DETECTION; DISCRIMINANT ANALYSIS; FUNGI; GRAIN (AGRICULTURAL PRODUCT); INFRARED DEVICES; MULTIVARIANT ANALYSIS; QUALITY CONTROL;

PRINCIPAL COMPONENT ANALYSIS;

ASPERGILLUS; ASPERGILLUS GLAUCUS; ASPERGILLUS NIGER; FUNGI; PENICILLIUM; TRITICUM AESTIVUM;

EID: 84856282742     PISSN: 10942912     EISSN: 15322386     Source Type: Journal    
DOI: 10.1080/10942911003687223     Document Type: Article

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