New developments and opportunities for AI in viticulture, pomology, and soft-fruit research: a mini-review and invitation to contribute articles

Sigfredo Fuentes, Eden Tongson, Claudia Gonzalez Viejo
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Abstract

Climate change constraints on horticultural production and emerging consumer requirements for fresh and processed horticultural products with an increased number of quality traits have pressured the industry to increase the efficiency, sustainability, productivity, and quality of horticultural products. The implementation of Agriculture 4.0 using new and emerging digital technologies has increased the amount of data available from the soil–plant–atmosphere continuum to support decision-making in these agrosystems. However, to date, there has not been a unified effort to work with these novel digital technologies and gather data for precision farming. In general, artificial intelligence (AI), including machine/deep learning for data modeling, is considered the best approach for analyzing big data within the horticulture and agrifood sectors. Hence, the terms Agriculture/AgriFood 5.0 are starting to be used to identify the integration of digital technologies from precision agriculture and data handling and analysis using AI for automation. This mini-review focuses on the latest published work with a soil–plant–atmosphere approach, especially those published works implementing AI technologies and modeling strategies.
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人工智能在葡萄栽培、果学和软果研究中的新发展和机遇:一篇小型综述和投稿文章邀请
气候变化对园艺生产的限制,以及消费者对新鲜和加工的园艺产品质量要求的增加,迫使该行业提高园艺产品的效率、可持续性、生产力和质量。利用新兴数字技术实施的农业4.0增加了土壤-植物-大气连续体的可用数据量,以支持这些农业系统的决策。然而,到目前为止,还没有一个统一的努力来使用这些新颖的数字技术并为精准农业收集数据。一般来说,人工智能(AI),包括用于数据建模的机器/深度学习,被认为是分析园艺和农业食品部门大数据的最佳方法。因此,术语“农业/农业食品5.0”开始被用于识别来自精准农业的数字技术的集成以及使用人工智能进行自动化的数据处理和分析。这篇迷你综述的重点是最新发表的土壤-植物-大气方法的作品,特别是那些发表的实施人工智能技术和建模策略的作品。
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