English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

In this paper, principal component analysis (PCA), linear discriminant analysis (LDAp, artificial neural networks (ANN), and support vector machine (SVM) were applied to discriminate the geographical origin of Chinese red peppers ( Zanthoxylum bungeanum Maxim.). The models based on color, smell and taste may discriminate quickly and effectively the geographical origin of Chinese red peppers from different regions, but the successful identification rates may vary with different kinds of parameters and chemometric methods. Among them, all models based on taste indexes showed an excellent ability to discriminate the geographical origin of Chinese red peppers with correct classifications of 100% for the training set and the 100% for test set. The present study provided a simple, efficient, inexpensive, practical and fast method to discriminate the geographical origin of Chinese red peppers from different regions, which was of great importance for both consumers and producers.

molecules/molecules online/molecules annual

Rapid Determination of the Geographical Origin of Chinese Red Peppers (Zanthoxylum Bungeanum Maxim.) Based on Sensory Characteristics and Chemometric Techniques