Digital Twins: A Next‐Gen Solution for Agricultural Sustainability
2024; Wiley; Volume: 69; Issue: 9 Linguagem: Inglês
10.1002/csan.21374
ISSN2325-3584
AutoresAbhishek Panchadi, Bipin Bastakoti, Prathiksha Raghava, Prakash Kumar Jha,
Tópico(s)Smart Agriculture and AI
ResumoCSA NewsEarly View EARLY CAREER MEMBERS Digital Twins: A Next-Gen Solution for Agricultural Sustainability Abhishek Panchadi, Abhishek Panchadi Mississippi Agroclimatology Collaboratory, Department of Plant and Soil Sciences, Mississippi State UniversitySearch for more papers by this authorBipin Bastakoti, Bipin Bastakoti Mississippi Agroclimatology Collaboratory, Department of Plant and Soil Sciences, Mississippi State UniversitySearch for more papers by this authorPrathiksha Raghava, Prathiksha Raghava Mississippi Agroclimatology Collaboratory, Department of Plant and Soil Sciences, Mississippi State UniversitySearch for more papers by this authorPrakash Kumar Jha, Prakash Kumar Jha Mississippi Agroclimatology Collaboratory, Department of Plant and Soil Sciences, Mississippi State UniversitySearch for more papers by this author Abhishek Panchadi, Abhishek Panchadi Mississippi Agroclimatology Collaboratory, Department of Plant and Soil Sciences, Mississippi State UniversitySearch for more papers by this authorBipin Bastakoti, Bipin Bastakoti Mississippi Agroclimatology Collaboratory, Department of Plant and Soil Sciences, Mississippi State UniversitySearch for more papers by this authorPrathiksha Raghava, Prathiksha Raghava Mississippi Agroclimatology Collaboratory, Department of Plant and Soil Sciences, Mississippi State UniversitySearch for more papers by this authorPrakash Kumar Jha, Prakash Kumar Jha Mississippi Agroclimatology Collaboratory, Department of Plant and Soil Sciences, Mississippi State UniversitySearch for more papers by this author First published: 14 August 2024 https://doi.org/10.1002/csan.21374Read the full textAboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onEmailFacebookTwitterLinkedInRedditWechat References Alves, R.G., Souza, G., Maia, R.F., Tran, A.L.H., Kamienski, C., Soininen, J. P., Aquino Jr, P.T., Lima, F., (2019). A Digital Twin for Smart Farming. In IEEE Global Humanitarian Technology Conference (GHTC). IEEE. Google Scholar Attaran, M., Attaran, S., & Celik, B. G. (2023). Revolutionizing agriculture through digital twins. Encyclopedia of Information Science and Technology ( 6th ed.) (pp. 1–14). Google Scholar Attaran, M., & Celik, B. G. (2023). Digital Twin: Benefits, use cases, challenges, and opportunities. Decision Analytics Journal, 6. https://doi.org/10.1016/j.dajour.2023.100165 10.1016/j.dajour.2023.100165 Google Scholar Benos, L., Tagarakis, A. C., Dolias, G., Berruto, R., Kateris, D., & Bochtis, D. (2021). Machine learning in agriculture: A comprehensive updated review. Sensors, 21(11). https://doi.org/10.3390/s21113758 10.3390/s21113758 Google Scholar Brewster, C., Roussaki, I., Kalatzis, N., Doolin, K., & Ellis, K. (2017). IoT in agriculture: Designing a Europe-wide large-scale pilot. IEEE Communications Magazine, 55(9), 26–33. https://doi.org/10.1109/MCOM.2017.1600528 10.1109/MCOM.2017.1600528 Web of Science®Google Scholar Cesco, S., Sambo, P., Borin, M., Basso, B., Orzes, G., & Mazzetto, F. (2023). Smart agriculture and digital twins: Applications and challenges in a vision of sustainability. European Journal of Agronomy, 146. https://doi.org/10.1016/j.eja.2023.126809 10.1016/j.eja.2023.126809 Google Scholar El Saddik, A. (2018). Digital Twins: The Convergence of Multimedia Technologies. IEEE Multimedia, 25(2), 87–92. https://doi.org/10.1109/MMUL.2018.023121167 10.1109/MMUL.2018.023121167 Web of Science®Google Scholar Food and Agriculture Organization of the United Nations (FAO). (2011). The state of the world's land and water resources for food and agriculture (SOLAW) – Managing systems at risk. Food and Agriculture Organization of the United Nations. Google Scholar Fountas, S., Espejo-García, B., Kasimati, A., Gemtou, M., Panoutsopoulos, H., & Anastasiou, E. (2024). Agriculture 5.0: Cutting-edge technologies, trends, and challenges. IT Professional, 26(1), 40-47. https://doi.org/10.1109/MITP.2024.3358972 10.1109/MITP.2024.3358972 Google Scholar Fuller, A., Fan, Z., Day, C., & Barlow, C. (2020). Digital twin: Enabling technologies, challenges and open research. IEEE Access, 8, 108952–108971. https://doi.org/10.1109/ACCESS.2020.2998358 10.1109/ACCESS.2020.2998358 Web of Science®Google Scholar Guo, J., & Lv, Z. (2022). Application of digital twins in multiple fields. Multimedia Tools and Applications, 81(19), 26941–26967. https://doi.org/10.1007/s11042-022-12536-5 10.1007/s11042-022-12536-5 PubMedWeb of Science®Google Scholar Hearn, M., & Rix, S. (2019). Cybersecurity considerations for digital twin implementations. IIC Journal of Innovation, 10, 107–113. https://www.iiconsortium.org/news-pdf/joi-articles/2019-November-JoI-Cybersecurity-Considerations-for-Digital-Twin-Implementations.pdf Google Scholar IBM. (n.d.). What is a digital twin? IBM. https://www.ibm.com/topics/what-is-a-digital-twin Google Scholar Jo, S. K., Park, D. H., Park, H., & Kim, S. H. (2018). Smart livestock farms using digital twin: Feasibility study. In 2018 International Conference on Information and Communication Technology Convergence (ICTC) (pp. 1461–1463). IEEE. Google Scholar Kalyani, Y., Bermeo, N. V., & Collier, R. (2023). Digital twin deployment for smart agriculture in cloud-fog-edge infrastructure. International Journal of Parallel, Emergent and Distributed Systems, 38(6), 461-476. https://doi.org/10.1080/17445760.2023.2235653 10.1080/17445760.2023.2235653 Google Scholar Kampker, A., Stich, V., Jussen, P., Moser, B., & Kuntz, J. (2019). Business models for industrial smart services–the example of a digital twin for a product-service-system for potato harvesting. Procedia CIRP, 83, 534-540. https://doi.org/10.1016/j.procir.2019.04.114 10.1016/j.procir.2019.04.114 Google Scholar Kim, S., & Heo, S. (2024). An agricultural digital twin for mandarins demonstrates the potential for individualized agriculture. Nature Communications, 15(1), 1561. https://doi.org/10.1038/s41467-024-45725-x 10.1038/s41467-024-45725-x CASPubMedGoogle Scholar Mbow, C., Rosenzweig, C., Barioni, L.G., Benton, T.G., Herrero, M., Krishnapillai, M., Liwenga, E., … & Xu, Y. (2019). Food security. In P.R. Shukla, J. Skea, E. Calvo Buendia, V. Masson-Delmotte, H.-O. Pörtner, D.C. Roberts, P. Zhai, … & J. Malley, (Eds.) Climate Change and Land: an IPCC special report on climate change, desertification, land degradation, sustainable land management, food security, and greenhouse gas fluxes in terrestrial ecosystems (pp. 437–550). IPCC. https://doi.org/10.1017/9781009157988.007 10.1017/9781009157988.007 Google Scholar McFadden, J., Njuki, E., & Griffin, T. (2023). Precision agriculture in the digital era: Recent adoption on U.S. farms. U.S. Department of Agriculture, Economic Research Service. Google Scholar Monteiro, J., Barata, J., Veloso, M., Veloso, L., & Nunes, J. (2018). Towards sustainable digital twins for vertical farming. In 2018 Thirteenth International Conference on Digital Information Management (ICDIM) (pp. 234–239). IEEE. Google Scholar Peladarinos, N., Piromalis, D., Cheimaras, V., Tserepas, E., Munteanu, R. A., & Papageorgas, P. (2023). Enhancing smart agriculture by implementing digital twins: A comprehensive review. Sensors, 23(16). https://doi.org/10.3390/s23167128 10.3390/s23167128 Google Scholar Purcell, W., & Neubauer, T. (2023). Digital twins in agriculture: A state-of-the-art review. Smart Agricultural Technology, 3. https://doi.org/10.1109/ICDIM.2018.8847169 Google Scholar Resende, R. T., Hickey, L., Amaral, C. H., Peixoto, L. L., Marcatti, G. E., & Xu, Y. (2024). Satellite-enabled enviromics to enhance crop improvement. Molecular Plant, 17(6), 848-866. https://doi.org/10.1016/j.molp.2024.04.005 10.1016/j.molp.2024.04.005 CASPubMedGoogle Scholar Sands, R., Meade, B., Seale, Jr., J.L., Robinson, S., & Seeger, R. (2023). Scenarios of global food consumption: Implications for agriculture. U.S. Department of Agriculture, Economic Research Service. https://doi.org/10.32747/2023.8134356.ers 10.32747/2023.8134356.ers Google Scholar Sharma, A., Jain, A., Gupta, P., & Chowdary, V. (2020). Machine learning applications for precision agriculture: A comprehensive review. IEEE Access, 9, 4843-4873. https://doi.org/10.1109/ACCESS.2020.3048415 10.1109/ACCESS.2020.3048415 Web of Science®Google Scholar Skobelev, P., Laryukhin, V., Simonova, E., Goryanin, O., Yalovenko, V., & Yalovenko, O. (2020). Developing a smart cyber-physical system based on digital twins of plants. In 2020 Fourth World Conference on Smart Trends in Systems, Security and Sustainability (WorldS4) (pp. 522-527). IEEE. https://doi.org/10.1109/WorldS450073.2020.9210359 10.1109/WorldS450073.2020.9210359 Google Scholar Thilakarathne, N. N., Bakar, M. S. A., Abas, P. E., & Yassin, H. (2023). Towards making the fields talks: A real-time cloud enabled IoT crop management platform for smart agriculture. Frontiers in Plant Science, 13. https://doi.org/10.3389/fpls.2022.1030168 10.3389/fpls.2022.1030168 PubMedGoogle Scholar Verdouw, C. N., & Kruize, J. W. (2017). Digital twins in farm management: illustrations from the FIWARE accelerators SmartAgriFood and Fractals. In Proceedings of the 7th Asian-Australasian Conference on Precision Agriculture (pp. 16-18). https://doi.org/10.5281/zenodo.893662 10.5281/zenodo.893662 Google Scholar Verdouw, C., Tekinerdogan, B., Beulens, A., & Wolfert, S. (2021). Digital twins in smart farming. Agricultural Systems, 189. https://doi.org/10.1016/j.agsy.2020.103046 10.1016/j.agsy.2020.103046 Google Scholar Wakchaure, M., Patle, B. K., & Mahindrakar, A. K. (2023). Application of AI techniques and robotics in agriculture: A review. Artificial Intelligence in the Life Sciences, 3. https://doi.org/10.1016/j.ailsci.2023.100057 10.1016/j.ailsci.2023.100057 Google Scholar Walthall, C.L., Hatfield, J., Backlund, P., Lengnick, L., Marshall, E., Walsh, M., Adkins, S., … & Ziska, L.H. (2012). Climate change and agriculture in the United States: Effects and adaptation. USDA. Google Scholar Xu, Y., Zhang, X., Li, H., Zheng, H., Zhang, J., Olsen, M. S., … & Qian, Q. (2022). Smart breeding driven by big data, artificial intelligence, and integrated genomic-enviromic prediction. Molecular Plant, 15(11), 1664-1695. https://doi.org/10.1016/j.molp.2022.09.001 10.1016/j.molp.2022.09.001 CASPubMedWeb of Science®Google Scholar Early ViewOnline Version of Record before inclusion in an issue ReferencesRelatedInformation
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