ArticleFoods (Basel, Switzerland)2020
Metabolite Profiling and Chemometric Study for the Discrimination Analyses of Geographic Origin of Perilla (
Article in Foods (Basel, Switzerland), 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
What it found
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Who cites it
9 citing papers in PubMed, 22 citations in OpenAlex.
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- UV Fingerprinting Approaches for Quality Control Analyses of Food and Functional Food Coupled to Chemometrics: A Comprehensive Analysis of Novel Trends and Applications.Foods (Basel, Switzerland) · 2022Review
- Fatty Acid Profiling in Kernels Coupled with Chemometric Analyses as a Feasible Strategy for the Discrimination of Different Walnuts.Foods (Basel, Switzerland) · 2022Article
- Enhanced Production of Photosynthetic Pigments and Various Metabolites and Lipids in the CyanobacteriaBiomolecules · 2021Article
- Target and Non-Target Approaches for Food Authenticity and Traceability.Foods (Basel, Switzerland) · 2021Article
Corrections and comments
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Authors and funding
8 authors at 5 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Perilla and sesame are traditional sources of edible oils in Asian and African countries. In addition, perilla and sesame seeds are rich sources of health-promoting compounds, such as fatty acids, tocopherols, phytosterols and policosanols. Thus, developing a method to determine the geographic origin of these seeds is important for ensuring authenticity, safety and traceability and to prevent cheating. We aimed to develop a discriminatory predictive model for determining the geographic origin of perilla and sesame seeds using comprehensive metabolite profiling coupled with chemometrics. The orthogonal partial least squares-discriminant analysis models were well established with good validation values (
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Registered trials
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