A Method for Rapid Identification of Rice Origin by Hyperspectral Imaging Technology. Issue 1 (16th October 2015)

• Record Type: Journal Article
• Authors: Sun, Jun; Lu, Xinzi; Mao, Hanping; Jin, Xiaming; Wu, Xiaohong
• Is Part Of: Journal of food process engineering. Volume 40:Issue 1(2017:Feb.)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2015-10-16
• Subjects: Food industry and trade -- Periodicals; Food -- Analysis -- Periodicals; 664.005
• DOI: 10.1111/jfpe.12297
• Languages: English
• ISSNs: 0145-8876

Abstract

Abstract: The potential of hyperspectral imaging system was evaluated for the rapid identification of rice origin. 240 samples from four different regions of China were imaged by a hyperspectral imaging system. Hyperspectral images were studied from the three principal aspects (spectral, morphological and texture features). Support vector machine was used for developing the identification models. Seven models based on spectral, morphological, texture, combined spectral and morphological, combined spectral and texture, combined morphological and texture and combined spectral, morphological and texture features were developed for seeking the optimal feature combination. Nine important wavelengths were determined by principal component analysis. The results showed that the highest accuracy (91.67%) was obtained from combined spectral, morphological and texture features. This study demonstrated that hyperspectral imaging could provide a rapid identification of rice origin and the method of feature combination could be very helpful to improve the performance of identification models. Practical Applications: The price and quality of rice mainly depends on its geographical origin in the food market. Traditional methods for identification of rice origin mainly focus on the appearance of rice and depend on the feelings of professionals, which are tedious, time‐consuming, expensive and greatly influenced by subjective factors. Therefore, the results in our paper can provide a foundational basis to develop a real‐time inspection system for the rapid, precise and non‐destructive identification of rice origin.