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Advancement in artificial intelligence for on-farm fruit sorting and transportation

On-farm sorting and transportation of postharvest fruit include sorting out defective products, grading them into categories based on quality, distributing them into bins, and carrying bins to field collecting stations. Advances in artificial intelligence (AI) can speed up on-farm sorting and transp...

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Autores principales: Zhou, Zheng, Zahid, Umair, Majeed, Yaqoob, Nisha, Mustafa, Sadaf, Sajjad, Muhammad Muzzammil, Butt, Hafiz Danish, Fu, Longsheng
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10117807/
https://www.ncbi.nlm.nih.gov/pubmed/37089654
http://dx.doi.org/10.3389/fpls.2023.1082860
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author Zhou, Zheng
Zahid, Umair
Majeed, Yaqoob
Nisha,
Mustafa, Sadaf
Sajjad, Muhammad Muzzammil
Butt, Hafiz Danish
Fu, Longsheng
author_facet Zhou, Zheng
Zahid, Umair
Majeed, Yaqoob
Nisha,
Mustafa, Sadaf
Sajjad, Muhammad Muzzammil
Butt, Hafiz Danish
Fu, Longsheng
author_sort Zhou, Zheng
collection PubMed
description On-farm sorting and transportation of postharvest fruit include sorting out defective products, grading them into categories based on quality, distributing them into bins, and carrying bins to field collecting stations. Advances in artificial intelligence (AI) can speed up on-farm sorting and transportation with high accuracy and robustness and significantly reduce postharvest losses. The primary objective of this literature review is to provide an overview to present a critical analysis and identify the challenges and opportunities of AI applications for on-farm sorting and transportation, with a focus on fruit. The challenges of on-farm sorting and transportation were discussed to specify the role of AI. Sensors and techniques for data acquisition were investigated to illustrate the tasks that AI models have addressed for on-farm sorting and transportation. AI models proposed in previous studies were compared to investigate the adequate approaches for on-farm sorting and transportation. Finally, the advantages and limitations of utilizing AI have been discussed, and in-depth analysis has been provided to identify future research directions. We anticipate that this survey will pave the way for further studies on the implementation of automated systems for on-farm fruit sorting and transportation.
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spelling pubmed-101178072023-04-21 Advancement in artificial intelligence for on-farm fruit sorting and transportation Zhou, Zheng Zahid, Umair Majeed, Yaqoob Nisha, Mustafa, Sadaf Sajjad, Muhammad Muzzammil Butt, Hafiz Danish Fu, Longsheng Front Plant Sci Plant Science On-farm sorting and transportation of postharvest fruit include sorting out defective products, grading them into categories based on quality, distributing them into bins, and carrying bins to field collecting stations. Advances in artificial intelligence (AI) can speed up on-farm sorting and transportation with high accuracy and robustness and significantly reduce postharvest losses. The primary objective of this literature review is to provide an overview to present a critical analysis and identify the challenges and opportunities of AI applications for on-farm sorting and transportation, with a focus on fruit. The challenges of on-farm sorting and transportation were discussed to specify the role of AI. Sensors and techniques for data acquisition were investigated to illustrate the tasks that AI models have addressed for on-farm sorting and transportation. AI models proposed in previous studies were compared to investigate the adequate approaches for on-farm sorting and transportation. Finally, the advantages and limitations of utilizing AI have been discussed, and in-depth analysis has been provided to identify future research directions. We anticipate that this survey will pave the way for further studies on the implementation of automated systems for on-farm fruit sorting and transportation. Frontiers Media S.A. 2023-04-06 /pmc/articles/PMC10117807/ /pubmed/37089654 http://dx.doi.org/10.3389/fpls.2023.1082860 Text en Copyright © 2023 Zhou, Zahid, Majeed, Nisha, Mustafa, Sajjad, Butt and Fu https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Plant Science
Zhou, Zheng
Zahid, Umair
Majeed, Yaqoob
Nisha,
Mustafa, Sadaf
Sajjad, Muhammad Muzzammil
Butt, Hafiz Danish
Fu, Longsheng
Advancement in artificial intelligence for on-farm fruit sorting and transportation
title Advancement in artificial intelligence for on-farm fruit sorting and transportation
title_full Advancement in artificial intelligence for on-farm fruit sorting and transportation
title_fullStr Advancement in artificial intelligence for on-farm fruit sorting and transportation
title_full_unstemmed Advancement in artificial intelligence for on-farm fruit sorting and transportation
title_short Advancement in artificial intelligence for on-farm fruit sorting and transportation
title_sort advancement in artificial intelligence for on-farm fruit sorting and transportation
topic Plant Science
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10117807/
https://www.ncbi.nlm.nih.gov/pubmed/37089654
http://dx.doi.org/10.3389/fpls.2023.1082860
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