RESEARCH JOURNAL OF FOOD SCIENCE AND NUTRITION
Integrity Research Journals
ISSN: 2536-7080
Model: Open Access/Peer Reviewed
DOI: 10.31248/RJFSN
Start Year: 2016
Email: rjfsn@integrityresjournals.org
Application of artificial neural network for estimating the qualitative characteristics of cantaloupe melon and comparison with the regression model
https://doi.org/10.31248/RJFSN2017.023 | Article Number: ADE2B1481 | Vol.2 (1) - April 2017
Received Date: 20 February 2017 | Accepted Date: 08 March 2017 | Published Date: 30 April 2017
Authors: Mahdi Ghasemi-Varnamkhasti* , Davood Ghanbarian , Zahra Shojaei , Abbasali Yadollahi , Ayat Mohammad Razdari , Reza Goli and Seyedeh Hoda Yoosefian
Keywords: Quality, color, artificial neural network, cantaloupe melon.
APA STYLE
Ghasemi-Varnamkhasti, M., Ghanbarian, D., Shojaei, Z., Yadollahi, A., Razdari, A. M., Goli, R., & Yoosefian, S. H. (2017). Application of artificial neural network for estimating the qualitative characteristics of cantaloupe melon and comparison with the regression model. Research Journal of Food Science and Nutrition, 2(1), 1-8.
HARVARD STYLE
Orhevba, B. A. and Taiwo, A. D. 2017. Application of artificial neural network for estimating the qualitative characteristics of cantaloupe melon and comparison with the regression model. Research Journal of Food Science and Nutrition, 2(1), Pp. 1-8.
VANCOUVER STYLE
Ghasemi-Varnamkhasti M, Ghanbarian D, Shojaei Z, Yadollahi A, Razdari AM, Goli R & Yoosefian SH. Application of artificial neural network for estimating the qualitative characteristics of cantaloupe melon and comparison with the regression model. Research Journal of Food Science and Nutrition. 2017 Apr 30:2(1): 1-8.
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