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Advancement in artificial intelligence for on-farm fruit sorting and transportation
Zheng Zhou1, Umair Zahid2, Yaqoob Majeed2
1College of Engineering, Heilongjiang Bayi Agricultural University, Daqing, China.
Frontiers in Plant Science
|April 24, 2023
Summary
Artificial intelligence (AI) can enhance on-farm fruit sorting and transportation, reducing postharvest losses. This review analyzes AI applications, challenges, and opportunities for automated systems in agriculture.
Area of Science:
- Agricultural Engineering
- Computer Science
- Food Science
Background:
- On-farm fruit handling involves sorting, grading, binning, and transport.
- Postharvest losses remain a significant challenge in fruit production.
- Automation can improve efficiency and reduce waste in fruit supply chains.
Purpose of the Study:
- To review and critically analyze artificial intelligence (AI) applications for on-farm fruit sorting and transportation.
- To identify challenges and opportunities associated with AI implementation in postharvest logistics.
- To guide future research in automated fruit handling systems.
Main Methods:
- Literature review focusing on AI applications in on-farm fruit sorting and transportation.
- Investigation of sensors and data acquisition techniques for AI models.
- Comparative analysis of AI models used in previous studies.
- Discussion of challenges, opportunities, advantages, and limitations of AI.
Main Results:
- AI offers high accuracy and robustness in on-farm sorting and transportation.
- Various AI models have been applied to tasks like defect detection and quality grading.
- Key challenges include sensor integration, environmental variability, and cost-effectiveness.
- Opportunities lie in developing sophisticated AI algorithms for real-time decision-making.
Conclusions:
- AI holds significant potential to revolutionize on-farm fruit sorting and transportation.
- Addressing identified challenges is crucial for successful AI adoption.
- Further research is needed to optimize AI algorithms and system integration for widespread implementation.
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