Abstract：In order to establish new multispectral indexes for automatic identification of strawberry ripeness, hyperspectral imaging technology was applied in this paper. Eight indexes: Ind1=R730+R640-2×R680, Ind2=R680/(R640+R730), Ind3=R675/R800, IAD=log10(R720/R670), I1=R650/R550, I2=R650/R450, I3=R650/(R450+R550), I4=2×R650-(R550+R450) were calculated by extracting average spectral of strawberry samples and their identification effects of strawberry samples in three ripening stages(mature, nearly mature and immature) were judged with Fisher linear discriminant(FLD). The result showed that the identification effects of linear discriminant analysis model based on index I4 was the best among 8 indexes and the identification accuracy of modeling and prediction set was 90% and 91. 67% respectively. Three wavelengths (535, 675, 980 nm) related to strawberry ripeness were extracted based on average spectral of strawberry samples and 4 new indexes were established based on these three wavelengths: i1=2×R675- (R980+R535), i2=R675/(R980+R535), i3= (R675-R535)/(R675+R535), i4=[R675- (R535+R980)]/[R675+(R535+R980)]. The identification effects was judged with FLD and the results showed that the effects of linear discriminant analysis models based on i1, i2, i4 were better than index I4 and the identification accuracy of modeling and prediction set was 95.83%，95.83%，95.83% and 95%，95%，96.67% respectively. In conclusion, new established indexes i1, i2, i4 could be used in automatic identification of strawberry ripeness.
Key words：Strawberry;Identification of strawberry ripeness;Multispectral index;Hyperspectral image;Fisher linear discriminant
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