Prediction of some quality properties of rice and its flour by near‐infrared spectroscopy (NIRS) analysis-Reference-Cited by-同舟云学术

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Prediction of some quality properties of rice and its flour by near‐infrared spectroscopy (NIRS) analysis

Published:2020-12-25 Issue:2 Volume:9 Page:1099-1105
ISSN:2048-7177
Container-title:Food Science & Nutrition
language:en
Short-container-title:Food Sci Nutr

Author:

Fazeli Burestan Nasrollah¹,Afkari Sayyah Amir Hossein²^ORCID,Taghinezhad Ebrahim³^ORCID

Affiliation:

1. College of Agriculture and Natural ResourcesUniversity of Mohaghegh Ardabili Ardabil Iran

2. Faculty of Agriculture and Natural ResourcesUniversity of Mohaghegh Ardabili Ardabil Iran

3. Moghan College of Agriculture and Natural ResourcesUniversity of Mohaghegh Ardabili Ardabil Iran

Funder

University of Mohaghegh Ardabili

Publisher

Wiley

Subject

Food Science

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/fsn3.2086

Reference24 articles.

1. Relationship between rice grain amylose and pasting properties for breeding better quality rice varieties

2. Starch physicochemical properties of rice accessions and their association with molecular markers

3. Prediction of Rice Starch Quality Parameters by Near-Infrared Reflectance Spectroscopy

4. Determination of apparent amylose content, pasting properties and gel texture of rice starch by near-infrared spectroscopy

5. Authenticity detection of black rice by near‐infrared spectroscopy and support vector data description;Chen H.;International Journal of Analytical Chemistry,2018

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1. Prediction of protein content in paddy rice (Oryza sativa L.) combining near-infrared spectroscopy and deep-learning algorithm;Frontiers in Plant Science;2024-07-31

2. An effective moisture interference correction method for maize powder NIR spectra analysis;Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy;2024-05

3. Geographical Origin Identification of Red Chili Powder Using NIR Spectroscopy Combined with SIMCA and Machine Learning Algorithms;Food Analytical Methods;2024-04-26

4. Rapid identification of adulterated rice based on data fusion of near-infrared spectroscopy and machine vision;Journal of Food Measurement and Characterization;2024-03-25

5. Application of spectroscopic techniques combined with chemometrics to the authenticity and quality attributes of rice;Critical Reviews in Food Science and Nutrition;2023-11-27

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