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Articles by Haohan Ding
Integration of Distributed Technologies for Intelligent Food Quality and Safety Management: Blockchain, IoT, and Federated Learning
ABSTRACT Against the backdrop of intensified globalization and complex supply chains, food quality management faces three major challenges: insufficient real-time monitoring capabilities, information silos and traceability difficulties, and weak data collaboration and risk prediction capabilities. This article focuses on the practical applications and impact of distributed technologies such as blockchain, Internet of Things, and federated learning in food quality and safety management.
Application of Convolutional Neural Networks and Recurrent Neural Networks in Food Safety
All articles published by MDPI are made immediately available worldwide under an open access license. No special permission is required to reuse all or part of the article published by MDPI, including figures and tables. For articles published under an open access Creative Common CC BY license, any part of the article may be reused without permission provided that the original article is clearly cited. For more information, please refer to https://www.mdpi.com/openaccess.
Applications of Big Data and Blockchain Technology in Food Testing and Their Exploration on Educational Reform
All articles published by MDPI are made immediately available worldwide under an open access license. No special permission is required to reuse all or part of the article published by MDPI, including figures and tables. For articles published under an open access Creative Common CC BY license, any part of the article may be reused without permission provided that the original article is clearly cited. For more information, please refer to https://www.mdpi.com/openaccess.
The Application of Artificial Intelligence and Big Data in the Food Industry
All articles published by MDPI are made immediately available worldwide under an open access license. No special permission is required to reuse all or part of the article published by MDPI, including figures and tables. For articles published under an open access Creative Common CC BY license, any part of the article may be reused without permission provided that the original article is clearly cited. For more information, please refer to https://www.mdpi.com/openaccess.
Application of Three-Dimensional Digital Photogrammetry to Quantify the Surface Roughness of Milk Powder
1. Introduction Quality control and product consistency are key properties for any food industry, and especially for the dairy industry [1]. Experience shows that the surface appearance usually influences consumers’ assumptions about the organoleptic and functional performance of milk powders, particularly for those consumers who use the product regularly and have become accustomed to the surface appearance of the product [2].
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