Real-Time and Rapid Food Quality Monitoring Using Smart Sensory Films with Image Analysis and Machine Learning-Reference-Cited by-同舟云学术

Real-Time and Rapid Food Quality Monitoring Using Smart Sensory Films with Image Analysis and Machine Learning

Published:2022-06-24 Issue:7 Volume:2 Page:1123-1134
ISSN:2692-1944
Container-title:ACS Food Science & Technology
language:en
Short-container-title:ACS Food Sci. Technol.

Author:

Pounds Karyn¹,Bao Hanxi¹,Luo Yifei²,De Jaysankar³,Schneider Keith³,Correll Melanie¹,Tong Zhaohui⁴^ORCID

Affiliation:

1. Department of Agricultural and Biological Engineering, University of Florida, P.O. Box 110570, Gainesville, Florida 32611, United States

2. School of Industrial and Systems Engineering, Georgia Institute of Technology, Atlanta, Georgia 30332, United States

3. Department of Food Science and Human Nutrition, Aquatic Food Products Lab, P.O. Box 110370, Gainesville, Florida 32611, United States

4. School of Chemical and Biomolecular Engineering, Georgia Institute of Technology, Atlanta, Georgia 30332, United States

Funder

National Institute of Food and Agriculture

U.S. Department of Agriculture

GEM National Consortium Fellowship Program

Publisher

American Chemical Society (ACS)

Subject

Organic Chemistry,Chemistry (miscellaneous),Food Science,Analytical Chemistry

Link

https://pubs.acs.org/doi/pdf/10.1021/acsfoodscitech.2c00124

Reference48 articles.

1. Lonergan, S. Pork Quality: pH Decline and Pork Quality. Animal Science White Papers, Technical Reports, & Fact Sheets 7, 2012. https://lib.dr.iastate.edu/ans_whitepapers/7.

2. The significance of pre-slaughter stress and diet on colour and colour stability of pork

3. Machine learning approaches for large scale classification of produce

4. A Machine Vision Technique for Grading of Harvested Mangoes Based on Maturity and Quality

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