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From crop specific to variety specific in crop modeling for the smart farm: A case study with blueberry
Facility cultivation has been evolved from greenhouses to smart farms using artificial intelligence (AI) that simulates big data to maximize production. However, the big data for AI in smart farm is not studied well; the effect of differences among varieties within a crop remains unclear. Therefore,...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9426892/ https://www.ncbi.nlm.nih.gov/pubmed/36040983 http://dx.doi.org/10.1371/journal.pone.0273845 |
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author | Han, Gyung Deok Choi, Jeong Min Choi, Inchan Kim, Yoonha Heo, Seong Chung, Yong Suk |
author_facet | Han, Gyung Deok Choi, Jeong Min Choi, Inchan Kim, Yoonha Heo, Seong Chung, Yong Suk |
author_sort | Han, Gyung Deok |
collection | PubMed |
description | Facility cultivation has been evolved from greenhouses to smart farms using artificial intelligence (AI) that simulates big data to maximize production. However, the big data for AI in smart farm is not studied well; the effect of differences among varieties within a crop remains unclear. Therefore, the response of two varieties of blueberry, ‘Suziblue’ and ‘Star’, to light was tested using SAPD meter in order to demonstrate the environmental responses could be different among varieties within the same species. The results showed that those two varieties had significant differences in SPAD values based on the leaf’s position and time, whereas ‘Star’ did not. This indicates that the effect of light depends on the variety, which implies that other traits and other crops may show similar differences. These results are based on a simple experiment. However, it is enough to elucidate that it is extremely important to characterize responses to the environment not only for each crop but also for each variety to collect data for smart farming to increase accuracy for modeling; consequently, to maximize the efficiency of these facilities. |
format | Online Article Text |
id | pubmed-9426892 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-94268922022-08-31 From crop specific to variety specific in crop modeling for the smart farm: A case study with blueberry Han, Gyung Deok Choi, Jeong Min Choi, Inchan Kim, Yoonha Heo, Seong Chung, Yong Suk PLoS One Research Article Facility cultivation has been evolved from greenhouses to smart farms using artificial intelligence (AI) that simulates big data to maximize production. However, the big data for AI in smart farm is not studied well; the effect of differences among varieties within a crop remains unclear. Therefore, the response of two varieties of blueberry, ‘Suziblue’ and ‘Star’, to light was tested using SAPD meter in order to demonstrate the environmental responses could be different among varieties within the same species. The results showed that those two varieties had significant differences in SPAD values based on the leaf’s position and time, whereas ‘Star’ did not. This indicates that the effect of light depends on the variety, which implies that other traits and other crops may show similar differences. These results are based on a simple experiment. However, it is enough to elucidate that it is extremely important to characterize responses to the environment not only for each crop but also for each variety to collect data for smart farming to increase accuracy for modeling; consequently, to maximize the efficiency of these facilities. Public Library of Science 2022-08-30 /pmc/articles/PMC9426892/ /pubmed/36040983 http://dx.doi.org/10.1371/journal.pone.0273845 Text en © 2022 Han et al https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Article Han, Gyung Deok Choi, Jeong Min Choi, Inchan Kim, Yoonha Heo, Seong Chung, Yong Suk From crop specific to variety specific in crop modeling for the smart farm: A case study with blueberry |
title | From crop specific to variety specific in crop modeling for the smart farm: A case study with blueberry |
title_full | From crop specific to variety specific in crop modeling for the smart farm: A case study with blueberry |
title_fullStr | From crop specific to variety specific in crop modeling for the smart farm: A case study with blueberry |
title_full_unstemmed | From crop specific to variety specific in crop modeling for the smart farm: A case study with blueberry |
title_short | From crop specific to variety specific in crop modeling for the smart farm: A case study with blueberry |
title_sort | from crop specific to variety specific in crop modeling for the smart farm: a case study with blueberry |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9426892/ https://www.ncbi.nlm.nih.gov/pubmed/36040983 http://dx.doi.org/10.1371/journal.pone.0273845 |
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