Combing machine learning and elemental profiling for geographical authentication of Chinese Geographical Indication (GI) rice
Abstract Identification of geographical origin is of great importance for protecting the authenticity of valuable agri-food products with designated origins. In this study, a robust and accurate analytical method that could authenticate the geographical origin of Geographical Indication (GI) product...
Saved in:
Main Authors: | Fei Xu, Fanzhou Kong, Hong Peng, Shuofei Dong, Weiyu Gao, Guangtao Zhang |
---|---|
Format: | article |
Language: | EN |
Published: |
Nature Portfolio
2021
|
Subjects: | |
Online Access: | https://doaj.org/article/b65f6fbe740d4dac912a39d4c09b304e |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Oral intake of rice overexpressing ubiquitin ligase inhibitory pentapeptide prevents atrophy in denervated skeletal muscle
by: Reiko Nakao, et al.
Published: (2021) -
Tracing geographical origin of Lambrusco PDO wines using isotope ratios of oxygen, boron, strontium, lead and their elemental concentration
by: Lisa Lancellotti, et al.
Published: (2021) -
Monitoring the microbiome for food safety and quality using deep shotgun sequencing
by: Kristen L. Beck, et al.
Published: (2021) -
Author Correction: Advances in 3D peptide hydrogel models in cancer research
by: Jingwen Xu, et al.
Published: (2021) -
White button mushroom interrupts tissue AR-mediated TMPRSS2 expression and attenuates pro-inflammatory cytokines in C57BL/6 mice
by: Xiaoqiang Wang, et al.
Published: (2021)