Grade classification model tandem BpNN method with multi-metal sensor for rice eating quality evaluation-Reference-Cited by-同舟云学术

Grade classification model tandem BpNN method with multi-metal sensor for rice eating quality evaluation

Published:2019-02 Issue: Volume:281 Page:22-27
ISSN:0925-4005
Container-title:Sensors and Actuators B: Chemical
language:en
Short-container-title:Sensors and Actuators B: Chemical

Author:

Lu Lin,Fang Changyun,Hu Zhanqiang,Hu Xianqiao,Zhu Zhiwei

Funder

Analysis and Test Fund of Zhejiang Province, China

Special Fund of Chinese Central Government for Basic Scientific Research Operations in Commonweal Research Institutes

Science and Technology Innovation Program of Chinese Academy of Agriculture Science

Publisher

Elsevier BV

Subject

Materials Chemistry,Electrical and Electronic Engineering,Metals and Alloys,Surfaces, Coatings and Films,Condensed Matter Physics,Instrumentation,Electronic, Optical and Magnetic Materials

Reference20 articles.

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2. Instrumental methods (spectroscopy, electronic nose, and tongue) As tools to predict Taste and aroma in beverages: advantages and limitations;Smyth;Chem. Rev.,2013

3. Developments in understanding the basis of cooked-rice texture;Ramesh;Crit. Rev. Food Sci. Nutr.,2000

4. Study on rice sensory quality evaluation based on radar chart analysis method;Fang;China Rice,2017

5. Prediction model of rice eating quality using physicochemical properties and sensory quality evaluation;Kim;J. Sens. Stud.,2017

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