%A Qiuzi Wen‑Han, Yongqiang Zheng, Yang Liu %T Research and Application of Citrus Big Data %0 Journal Article %D 2021 %J Journal of Agricultural Big Data %R 10.19788/j.issn.2096-6369.210104 %P 33-44 %V 3 %N 1 %U {http://agbigdata.aiijournal.com/CN/abstract/article_19690.shtml} %8 2021-03-26 %X

Using the citrus industry chain model as the basic framework, this paper proposes an explicit definition of Citrus Big Data. For each of the four main parts of the citrus industry chain, i.e., production resources, planting operations, processing, storage and transportation, and marketing, the composition of data, acquisition methods and challenges in applications of its core data resources are analyzed, respectively. Applications of typical data technologies such as product standardization, image recognition, meteorology forecasting, data visualization, and digital traceability in the citrus industry are systematically reviewed. Cases studies on Coca Cola orange juice, Chongqing citrus and Gannan umbilical orange are presented, demonstrating that big data technology is playing a more and more important role in the citrus industry, aiding green farming, disease and insect pest control, production increase, and improvement of fruit commodity rates. In China, research on citrus has entered a stage of rapid development since 2007, and has made great progresses in talent training, fundamental research, and transformation and application of scientific research results, but research on the application of the new generation information technologies such as big data and artificial intelligence, is still limited. Major citrus production regions in southern China are actively exploring the feasibility route of digital transformation for citrus industry. As a core resource for industrial upgrading and digital transformation, Citrus Big Data has a wide range of applications and great potential for growth. Application of Citrus Big Data in China is still in its infancy, facing many challenges such as equality in science and technology, data sharing, development of key models and algorithms, etc.