Advances in Modern Agriculture

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Food Science

Submission deadline: 2023-12-16

Section Editors

Section Collection Information

Dear Colleagues,

Food science research involves developing technological solutions for improving the production of functional foods and food ingredients. This includes exploring processing technologies for functional food production, modifying crops to suit nutrient fortification, and utilizing crop biomass for both food and non-food applications. A cross-disciplinary approach and technical models are required to study the fundamental mechanisms of crops and their application as food and food ingredients. These efforts have significant implications for the development of sustainable, nutritious, and accessible food to all.

We welcome research and review articles related to food science research in our journal and look forward to receiving your contributions.

Dr. P. Suresh Kumar

Section Editor

Keywords

food science; functional foods; food ingredients; nutrient fortification; crop biomass; sustainable food; processing technologies; cross-disciplinary approach

Published Paper

Content creation or interpolation: AI generative digital art in the classroom

James Hutson;Martin Lang;

The integration of generative artificial intelligence (AI) tools in art and design has disrupted the traditional creative landscape, leading to debates on the legitimacy of AI-generated art and the emergence of new markets such as non-fungible tokens (NFTs). The US Copyright Office’s February 21, 2023, ruling withdrawing copyright protection for AI-generated comic artwork, while protecting the accompanying text and arrangement, highlights the contested nature of AI art and suggests that significant human intervention in the creative process will be required for monetization. Whether considered content interpolation or content creation, AI generative content for the creation of art and design is here with human-AI collaboration. To explore the potential of AI tools in creative practice, this study introduced students in a digital art course to Craiyon and Midjourney generative AI tools, with DALL-E 2 selected as the primary tool due to its varied output. The students were tasked with selecting a preferred prompt from one tool and then reproducing the output from both tools. The results revealed significant variations in replicating the outputs of different AI tools and limited exploration of prompt engineering, leading to restrictions in the iterative process of artmaking. The students agreed that generative AI tools are not a substitute for human creativity and should be used for final projects. The study demonstrates the potential and limitations of integrating AI tools in art and design and suggests the need for further research in developing effective prompt engineering strategies.