Research Center for Digitization and Intelligent Robotics (CeDRI), 5300-253 Bragança, Portugal.
Robotics Group, Engineering School, University of León, Campus de Vegazana, 24071 León, Spain.
Sensors (Basel). 2023 Jan 15;23(2):1007. doi: 10.3390/s23021007.
This article presents the results regarding a systematic literature review procedure on digital twins applied to precision agriculture. In particular, research and development activities aimed at the use of digital twins, in the context of predictive control, with the purpose of improving soil quality. This study was carried out through an exhaustive search of scientific literature on five different databases. A total of 158 articles were extracted as a result of this search. After a first screening process, only 11 articles were considered to be aligned with the current topic. Subsequently, these articles were categorised to extract all relevant information, using the preferred reporting items for systematic reviews and meta-analyses methods. Based on the obtained results, there are two main conclusions to draw: First, when compared with industrial processes, there is only a very slight rising trend regarding the use of digital twins in agriculture. Second, within the time frame in which this work was carried out, it was not possible to find any published paper on the use of digital twins for soil quality improvement within a model predictive control context.
这篇文章介绍了一项关于数字孪生在精准农业中应用的系统文献综述的结果。具体而言,这项研究旨在探讨数字孪生在预测控制中的应用,以改善土壤质量。该研究通过对五个不同数据库中的科学文献进行全面搜索来进行。搜索共提取了 158 篇文章。经过初步筛选,只有 11 篇文章被认为与当前主题相关。随后,使用系统评价和荟萃分析方法的首选报告项目对这些文章进行了分类,以提取所有相关信息。根据获得的结果,可以得出两个主要结论:首先,与工业过程相比,数字孪生在农业中的应用仅呈现出非常微弱的上升趋势。其次,在开展这项工作的时间范围内,无法找到任何关于在模型预测控制环境中使用数字孪生来改善土壤质量的已发表论文。