An agricultural digital twin for mandarins demonstrates the potential for individualized agriculture
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...
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| Format: | Article |
| Language: | English |
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Nature Portfolio
2024-02-01
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| Series: | Nature Communications |
| Online Access: | https://doi.org/10.1038/s41467-024-45725-x |
| _version_ | 1797274019135750144 |
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| author | Steven Kim Seong Heo |
| author_facet | Steven Kim Seong Heo |
| author_sort | Steven Kim |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-03-07T14:52:24Z |
| format | Article |
| id | doaj.art-40611ba7c9014081a1c0afc847a4a6fd |
| institution | Directory Open Access Journal |
| issn | 2041-1723 |
| language | English |
| last_indexed | 2024-03-07T14:52:24Z |
| publishDate | 2024-02-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Nature Communications |
| spelling | doaj.art-40611ba7c9014081a1c0afc847a4a6fd2024-03-05T19:35:41ZengNature PortfolioNature Communications2041-17232024-02-0115111510.1038/s41467-024-45725-xAn agricultural digital twin for mandarins demonstrates the potential for individualized agricultureSteven Kim0Seong Heo1Department of Mathematics and Statistics, California State University, Monterey BayDepartment of Horticulture, Kongju National UniversityAbstract 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.https://doi.org/10.1038/s41467-024-45725-x |
| spellingShingle | Steven Kim Seong Heo An agricultural digital twin for mandarins demonstrates the potential for individualized agriculture Nature Communications |
| title | An agricultural digital twin for mandarins demonstrates the potential for individualized agriculture |
| title_full | An agricultural digital twin for mandarins demonstrates the potential for individualized agriculture |
| title_fullStr | An agricultural digital twin for mandarins demonstrates the potential for individualized agriculture |
| title_full_unstemmed | An agricultural digital twin for mandarins demonstrates the potential for individualized agriculture |
| title_short | An agricultural digital twin for mandarins demonstrates the potential for individualized agriculture |
| title_sort | agricultural digital twin for mandarins demonstrates the potential for individualized agriculture |
| url | https://doi.org/10.1038/s41467-024-45725-x |
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