Mycobiome analysis for distinguishing the geographical origins of sesame seeds

  • Chun, Yoon Shik; 
  • Kim, Seok-Young; 
  • Kim, Minjoo; 
  • Lim, Jae Yoon; 
  • Shin, Byeong Kon; 
  • ... Choi, Hyung-Kyoon; 
  • 외 3명
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초록

Sesame (Sesamum indicum) is one of the most widely cultivated crops in Asia and Africa. The identification of the geographical origins of sesame seeds is important for the detection of fraudulent samples. This study was conducted to build a prediction model and suggest potential biomarkers for distinguishing the geographical origins of sesame seeds using mycobiome (fungal microbiome) analysis coupled with multivariate statistical analysis. Sesame seeds were collected from 25 cities in Korea, six cities in China, and five sites in other countries (Ethiopia, India, Nigeria, and Pakistan). According to the expression of fungal internal transcribed spacer (ITS) sequences in sesame seeds, 21 fungal genera were identified in sesame seeds from various countries. The optimal partial least squares-discriminant analysis model was established by applying two components with unit variance scaling. Based on seven-fold cross validation, the predictive model had 94.4% (Korea vs. China/other countries), 91.7% (China vs. Korea/other countries), and 88.9% (other countries vs. Korea/China) accuracy in determining the geographical origins of sesame seeds. Alternaria, Aspergillus, and Macrophomina were suggested as the potential fungal genera to differentiate the geographical origins of sesame seeds. This study demonstrated that mycobiome analysis could be used as a complementary method for distinguishing the geographical origins of raw sesame seeds. © 2021 Elsevier Ltd

키워드

Biomarker; Fungal ITS sequence; Geographical origin; Mycobiome analysis; Sesame seeds; Discriminant analysis; Fungi; Least squares approximations; Multivariant analysis; Cultivated crops; Fungal genera; Fungal internal transcribed spacer sequence; Geographical origins; Microbiome; Multivariate statistical analysis; Mycobiome analyse; Prediction model; Sesame seed; Sesamum indicum; Biomarkers
제목
Mycobiome analysis for distinguishing the geographical origins of sesame seeds
저자
Chun, Yoon Shik; Kim, Seok-Young; Kim, Minjoo; Lim, Jae Yoon; Shin, Byeong Kon; Kim, Young-Suk; Lee, Do Yup; Seo, Jeong-Ah; Choi, Hyung-Kyoon
DOI
10.1016/j.foodres.2021.110271
발행일
2021-05
유형
Article
저널명
Food Research International
권
143