Non-destructive prediction of hazelnut and hazelnut kernel deformation energy using machine learning techniques-Reference-Cited by-同舟云学术

Non-destructive prediction of hazelnut and hazelnut kernel deformation energy using machine learning techniques

Published:2024-03-03 Issue:1 Volume:27 Page:326-340
ISSN:1094-2912
Container-title:International Journal of Food Properties
language:en
Short-container-title:International Journal of Food Properties

Author:

Kayakuş Mehmet¹,Kabas Onder²,Ünal İ̇lker³,Paçacı Serdar⁴,Dinca Mirela - Nicoleta⁵

Affiliation:

1. Department of Management Information Systems, Faculty of Social Sciences and Humanities, Akdeniz University, Antalya, Türkiye

2. Department of Machine, Technical Science Vocational School, Akdeniz University, Antalya, Türkiye

3. Department of Mechatronics, Technical Science Vocational School, Akdeniz University, Antalya, Türkiye

4. Department of Computer Engineering, Faculty of Technology, Isparta University of Applied Sciences, Isparta, Türkiye

5. Department of Biotechnical Systems, Faculty of Biotechnical Systems Engineering, National University of Science and Technology Politehnica Bucharest, Bucharest, Romania

Funder

The work was supported by the This research was funded by National University

Publisher

Informa UK Limited

Link

https://www.tandfonline.com/doi/pdf/10.1080/10942912.2024.2317749

Reference46 articles.

1. FAOSTAT. Food and Agriculture Organization of the United Natıons Crops And Livestock Product. 2021. Available online: https://www.fao.org/faostat/en/#data/QCL (accessed on December 23 2022).

2. Factors Influencing the Adoption of Pressurized Irrigation Systems in Hazelnut Production and Its Effect on the Water Footprint in the Çarşamba District of Samsun

3. N. N. Mohsenin: Physical Properties of Plant and Animal Materials. Structure, Physical Characteristics and Mechanical Properties. 2. Aufl. 891 Seiten, zahlr. Abb. und Tab. Gordon and Breach Science Publishers, New York u. a. 1986. Preis: 140.—£

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