Research progress in mechanized and intelligentized pollination technologies for fruit and vegetable crops

Panliang Wu, Xiaohui Lei, Jin Zeng, Yannan Qi, Quanchun Yuan, Wanxi Huang, Zhengbao Ma, Qiyang Shen, Xiaolan Lyu

Abstract


With the rapid advancement of modern agriculture, mechanized and intelligent pollination has emerged as a crucial focus for enhancing agricultural efficiency and minimizing labor expenses. Traditional pollination methods, limited by environmental factors and high labor costs, fail to adequately address the production demands of large-scale orchards and vegetable gardens. Consequently, researchers have integrated mechanized equipment, drone technology, robotics, and deep learning algorithms to achieve accurate identification and precise pollination on inflorescences. The research on mechanized and intelligent pollination has not only injected new momentum into the field of fruit and vegetable pollination but also provided key technological support for addressing global agricultural labor shortages and increasing crop yields. This review summarizes recent advances in mechanized and intelligent pollination, focusing on deep learning’s role in object recognition, improvements in pollination equipment, and the effectiveness of intelligent pollination across various fruits or vegetables. Studies indicate that mechanized and intelligent pollination significantly enhances working efficiency and fruit yields, though it continues to face challenges such as technical complexity and high implementation costs. Looking ahead, as robotics and artificial intelligence algorithms continue to advance, mechanized and intelligent pollination is poised for broader adoption in agricultural management practices. This review systematically summarizes the research progress in mechanized and intelligent pollination technologies for fruit and vegetable crops, providing significant theoretical support and reference value for future studies in crop pollination techniques.
Key words: fruit and vegetable pollination, mechanization, deep learning, drone technology, object recognition
DOI: 10.25165/j.ijabe.20241706.9403

Citation: Wu P L, Lei X H, Zeng J, Qi Y N, Yuan Q C, Huang W X, et al. Research progress in mechanized and intelligentizedpollination technologies for fruit and vegetable crops. Int J Agric & Biol Eng, 2024; 17(6): 11–21.

Keywords


fruit and vegetable pollination, mechanization, deep learning, drone technology, object recognition

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References


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