Identification of tomato maturity based on multinomial logistic regression with kernel clustering by integrating color moments and physicochemical indices-Reference-Cited by-同舟云学术

Identification of tomato maturity based on multinomial logistic regression with kernel clustering by integrating color moments and physicochemical indices

Published:2020-08-17 Issue:10 Volume:43 Page:
ISSN:0145-8876
Container-title:Journal of Food Process Engineering
language:en
Short-container-title:J Food Process Eng

Author:

Jiang Yiping¹^ORCID,Bian Bei¹,Wang Xiaochan¹,Chen Sifan¹,Li Yuhua¹,Sun Ye¹

Affiliation:

1. College of Engineering, Nanjing Agricultural University Nanjing China

Funder

Fundamental Research Funds for the Central Universities

Publisher

Wiley

Subject

General Chemical Engineering,Food Science

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1111/jfpe.13504

Reference47 articles.

1. Quantification of sugars and organic acids in tomato fruits

2. Characterization of textural failure mechanics of strawberry fruit

3. A new proposal for automatic identification of multiple soybean diseases

4. A method to construct fruit maturity color scales based on support machines for regression: Application to olives and grape seeds

5. Evaluation of the ripening stages of apple (Golden Delicious) by means of computer vision system

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