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한빛사논문
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Nat. Commun., Feb 20 2024, 15 (1) | https://doi.org/10.1038/s41467-024-45725-x
An agricultural digital twin for mandarins demonstrates the potential for individualized agriculture
Steven Kim 1 & Seong Heo 2
1Department of Mathematics and Statistics, California State University, Monterey Bay, Seaside, CA 93955, USA.
2Department of Horticulture, Kongju National University, Yesan 32439, Republic of Korea.
Corresponding authors : Correspondence to Steven Kim or Seong Heo.
Abstract
A digital twin is a digital representation that closely resembles or replicates a real world object by combining interdisciplinary knowledge and advanced technologies. Digital twins have been applied to various fields, including to the agricultural field. Given big data and systematic data management, digital twins can be used for predicting future outcomes. In this study, we endeavor to create an agricultural digital twin using mandarins as a model crop. We employ an Open API to aggregate data from various sources across Jeju Island, covering an area of approximately 185,000 hectares. The collected data are visualized and analyzed at regional, inter-orchard, and intra-orchard scales. We observe that the intra-orchard analysis explains the variation of fruit quality substantially more than the inter-orchard analysis. Our data visualization and analysis, incorporating statistical models and machine learning algorithms, demonstrate the potential use of agricultural digital twins in the future, particularly in the context of micro-precision and individualized agriculture. This concept extends the current management practices based on data-driven decisions, and it offers a glimpse into the future of individualized agriculture by enabling customized treatment for plants, akin to personalized medicine for humans.
논문정보
- Research article
- 2024년 02월 (BRIC 등록일 2024-02-22)
- 국내(교신)+국외 연구진
- 생명과학 > 식량작물 및 원예작물
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