Discriminating the origin of basil seeds (Ocimum basilicum L.) using hyperspectral imaging analysis. (January 2020)

• Record Type: Journal Article
• Authors: Choi, Ji-Young; Heo, Suhyeon; Bae, Suin; Kim, Jiyoon; Moon, Kwang-Deog
• Is Part Of: Lebensmittel-Wissenschaft + Technologie =. Volume 118(2020)
• Publication Date: 2020-01
• Subjects: Hyperspectral imaging -- Basil (Ocimum basilicum L.) -- Discrimination -- Crude lipid content; Food industry and trade -- Periodicals; Food -- Composition -- Periodicals; Microbiology -- Periodicals; Nutrition -- Periodicals; 664.005
• DOI: 10.1016/j.lwt.2019.108715
• Languages: English
• ISSNs: 0023-6438

Abstract

Abstract: Hyperspectral imaging was used to study basil seeds and discriminate their origins (Singapore, India, Pakistan, or Vietnam). Normalization was the most effective method of preprocessing. The dominant wavelengths that were useful in classifying the basil seeds were approximately 1449–1457 nm, 1242–1254 nm, 1380 nm and 1696 nm (associated with moisture content, crude lipid content, total phenolic compounds, and fatty acids). Colour values were very similar between seeds of different origins and did not provide a good basis for discrimination. However, the moisture content and crude lipid content values significantly differed between groups, with predicted R 2 values of 0.9888 and 0.9753, respectively, from the partial least squares regression model. Therefore, it is possible to discriminate among basil seeds using hyperspectral imaging analysis. This approach can be applied to discrimination technology to identify other agricultural products in the future. Highlights: Basil seeds have different components according to their origin. Approximately 1380 nm was the most powerful wavelength to classify basil seeds. Hyperpsectral image can be used to classify basil seeds from various origin.