设施蔬菜自动对靶喷药技术研究现状与分析

doi:10.6048/j.issn.1001-4330.2021.08.022

新疆农业科学 ›› 2021, Vol. 58 ›› Issue (8): 1547-1557.DOI: 10.6048/j.issn.1001-4330.2021.08.022

• 农产品加工工程·农产品分析检测 • 上一篇下一篇

设施蔬菜自动对靶喷药技术研究现状与分析

杨征鹤¹, 杨会民², 喻晨², 陈毅飞², 周欣², 马艳², 王学农²

1.新疆农业大学机电工程学院,乌鲁木齐 830052;
2.新疆农业科学院农业机械化研究所,乌鲁木齐 830091

收稿日期:2020-06-10 出版日期:2021-08-20 发布日期:2021-08-09
通信作者: 王学农(1964-),男,陕西汉中人,研究员,硕士生导师,研究方向为农业机械化技术装备,(E-mail)xjwxn2010@sina.com
作者简介:杨征鹤(1994-),男,山东菏泽人,研究生,研究方向为设施农业装备, (E-mail)247329956@qq.com
基金资助:
自治区重大专项“设施农业信息化智能化装备系统构建与集成示范”(20219860)

Research Status and Analysis of Automatic Target Spraying Technology for Facility Vegetables

YANG Zhenghe¹, YANG Huimin², YU Chen², CHEN Yifei², ZHOU Xin², MA Yan², WANG Xuenong²

1. College of Mechanical and Electrical Engineering, Xinjiang Agricultural University, Urumqi 830052, China;
2. Institute of Agricultural Mechanization, Xinjiang Academy of Agricultural Science, Urumqi 830091, China

Received:2020-06-10 Online:2021-08-20 Published:2021-08-09
Correspondence author: WANG Xuenong(1964-), male,from Hanzhong,Shanxi.research.research direction is agricultural mechanization technology and equipment, (E-mail) xjwxn2010@sina.com
Supported by:
Major Special Project of Autonomous Region "Construction and Integration Demonstration of Intelligent Equipment System for Facility Agriculture Informatization" (20219860)

摘要/Abstract

摘要： 【目的】回顾与总结国内外设施蔬菜自动对靶喷药技术的研究现状与进展,为该技术在设施蔬菜自动对靶喷药机器人的发展应用上提供理论和科学依据。【方法】采用相关文献资料、实地调研的方法,汇总、整理及分析。【结果】导航技术国外主要采用基于GPS、机器视觉、激光雷达等技术开发的路径识别及智能避障技术,国内主要采用电磁诱导、基于GPS、激光雷达和视觉技术的道路边缘获取与道路识别技术。病虫害检测现阶段国外主要采用图像识别、红外成像和高光谱及基于深度学习的病虫害识别技术,技术较为成熟,国内现阶段主要采用图像识别技术,利用作物颜色、纹理及形状特征进行识别。国外对靶喷药采用机器视觉、激光主动视觉和超声波技术并结合传感器对目标作物进行识别,利用变速喷药技术在生菜、番茄等作物上进行了应用,国内开发了温室自主喷药机器人,采用机器视觉技术获取靶标病虫害位置信息,对喷头进行单独控制,以达到精准对靶施药的效果。【结论】导航技术、病虫害识别技术及对靶喷药技术是自动对靶喷药技术的核心。导航方面在温室中利用机器视觉和激光雷达技术相比GPS技术更加可靠、灵活,精准度更高,高光谱与病虫害识别技术可提高病虫害识别的效率,对靶喷药技术中目标作物的识别与冠层稠密程度的判断是发展趋势。

关键词: 设施蔬菜; 温室; 导航技术; 病虫害识别; 对靶喷药; 趋势

Abstract: 【Objective】 This paper aims to review and summarize the research status and development direction of automatic target spraying technology in facility vegetables at home and abroad in the hope of providing theoretical and scientific basis for the development and application of the technology in automatic target spraying robot of vegetable in facility vegetables. 【Methods】 Relevant literatures at home and abroad were collected, field research conducted, and after that, they were systematically summarized and sorted out. 【Results】 Overseas navigation technology mainly adopts path recognition and intelligent obstacle avoidance technology based on GPS, machine vision, ladar and other technologies, and has been widely applied. In China, it mainly adopts electromagnetic induction, road edge acquisition and road identification technology based on GPS, ladar and vision technology. At the present stage, image recognition, infrared imaging, hyperspectrum and deep learn-based pest identification technologies are mainly used in foreign countries, which are relatively mature. At present, image recognition technology is mainly used in China to identify crops with color, texture and shape features. In the developed countries, machine vision, laser active vision and ultrasonic technology combined with sensor identification are employed to identify target crops, and variable speed spraying technology is applied in crops, such as lettuce, tomato and other crops, domestic scholars have developed greenhouse autonomous spraying robot, using machine vision technology to obtain target pest and disease location information, the nozzle is controlled separately to achieve the effect of accurate target application. 【Conclusion】 Navigation technology, pest and disease identification technology and target spraying technology are the core of automatic target spraying technology. Navigation in the greenhouse by using machine vision and laser radar technology compared with the GPS technology is more reliable, flexible, and accurate. In the aspect of pest and disease identification, we should develop pest and disease identification technology combined with hyperspectral and deep learning to improve the efficiency. The identification of target crops and the judgment of dense degree of branches and leaves need more in-depth study.

Key words: facility vegetables; greenhouse; navigation technology; identification of pests and diseases; target spraying; trend

中图分类号:

S224.3

杨征鹤, 杨会民, 喻晨, 陈毅飞, 周欣, 马艳, 王学农. 设施蔬菜自动对靶喷药技术研究现状与分析[J]. 新疆农业科学, 2021, 58(8): 1547-1557.

YANG Zhenghe, YANG Huimin, YU Chen, CHEN Yifei, ZHOU Xin, MA Yan, WANG Xuenong. Research Status and Analysis of Automatic Target Spraying Technology for Facility Vegetables[J]. Xinjiang Agricultural Sciences, 2021, 58(8): 1547-1557.

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设施蔬菜自动对靶喷药技术研究现状与分析

Research Status and Analysis of Automatic Target Spraying Technology for Facility Vegetables

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[1]	刘凯, 吴晓, 桑思语, 许红军, 高杰. 保温被揭盖方式对日光温室内部温度的影响[J]. 新疆农业科学, 2023, 60(3): 633-642.
[2]	张锦强, 苏学德, 李鹏程, 杨湘, 李铭, 郭绍杰. 一年两熟夏黑葡萄日光温室温度变化与果实品质差异性分析[J]. 新疆农业科学, 2022, 59(8): 1889-1895.
[3]	马永杰, 王星怡, 韩聪颖, 蔺玉红, 马慧, 张雪艳. 日光温室后墙自走式雾化降温机夏季降温效果评价[J]. 新疆农业科学, 2022, 59(4): 1016-1024.
[4]	韩坤林, 王钊英, 杨会民, 陈毅飞, 蒋永新, 张佳喜. 基于PCA-BPNN的温室番茄果实直径预测模型[J]. 新疆农业科学, 2022, 59(2): 485-492.
[5]	马月虹, 李保明, 李慧霜. 新疆砌块复合墙体和砖墙日光温室的传热数值模拟分析[J]. 新疆农业科学, 2022, 59(2): 493-501.
[6]	阮康, 王香茹, 贵会平, 董强, 李磊磊, 魏学文, 张西岭, 张恒恒, 宋美珍. 新疆“宽早优”模式下施氮量对棉田碳足迹的影响[J]. 新疆农业科学, 2021, 58(9): 1633-1641.
[7]	肖林刚, 宋兵伟, 曹新伟, 王瑞, 焦锐斌. 日光温室冬季加温热负荷的计算和热风炉补温试验验证[J]. 新疆农业科学, 2021, 58(5): 903-910.
[8]	宋羽, 蒋程瑶, 李玉姗. 不同叶背补光模式对戈壁温室番茄品质的影响[J]. 新疆农业科学, 2021, 58(2): 294-303.
[9]	杨征鹤, 喻晨, 杨会民, 陈毅飞, 周欣, 马艳, 王学农. 基于LiDAR的温室番茄冠层几何参数提取[J]. 新疆农业科学, 2021, 58(10): 1909-1917.
[10]	阿里甫·艾尔西, 朱家辉, 李进, 王为然, 宁新民, 刘志清, 孔杰. 新疆长绒棉育种现状、趋势及研究进展[J]. 新疆农业科学, 2020, 57(3): 393-400.
[11]	陈毅飞, 杨会民, 马艳, 张新伟, 喻晨, 王学农. 基于多层感知机的温室内番茄茎直径变化预测模型[J]. 新疆农业科学, 2020, 57(3): 562-571.
[12]	宋兵伟, 吴乐天, 慈军, 王亮. 不同固化剂对新疆非耕地戈壁土的力学性能影响[J]. 新疆农业科学, 2020, 57(3): 572-580.
[13]	马月虹, 李保明, 王国强, 宋兵伟, 刘娜. 新疆日光温室前屋面的风载数值模拟分析[J]. 新疆农业科学, 2020, 57(12): 2325-2331.
[14]	阿里甫·艾尔西, 朱家辉, 刘志清, 王为然, 宁新民, 肖丽, 孔杰. 新疆陆地棉纤维品质演进趋势与改良分析[J]. 新疆农业科学, 2020, 57(11): 2099-2107.
[15]	阿拉帕提·塔依尔江, 贾凯, 刘迁杰, 张妮, 刘玉, 高杰. 日光温室主动采光对不同种植密度番茄光合特性的影响[J]. 新疆农业科学, 2020, 57(1): 97-103.