Plant factories have a great potential for mitigating the contradiction between the world’sgrowing population and food scarcity. During the process of its automatic production,machine vision plays a significant role....Plant factories have a great potential for mitigating the contradiction between the world’sgrowing population and food scarcity. During the process of its automatic production,machine vision plays a significant role. This technique almost covers every production linkfrom raising seedlings, transplanting, management, and harvesting to fruit grading. To provide references and a starting point for those who are committed to studying this issue. Inthis paper, the application prospects of machine vision in plant factories were analyzed,and the present researches were summarized from the fields of plant growth monitoring,robot operation assistance, and fruit grading. The results found that although the existingmethods have solved some practical problems at low cost, high efficiency and precision,some challenges still are faced by machine vision. Firstly, the changing lighting, complexbackgrounds, and color similarity within plant different parts cause the commonly usedimage segmentation algorithms to fail. The shortage of standard agricultural datasets alsokeeps deep learning and unsupervised classification algorithms from making progress.Secondly, there are some theoretical knowledge gaps for machine vision application in aparticular environment of plant factories, which seriously contains its application effect.Thirdly, the lack of special image acquisition devices and supporting facilities resulted inpoor image quality. All these factors hinder machine vision application in plant factories.Nevertheless, it is still a powerful tool and irreplaceable at present. We believed that thistechnique would promote plant factory development greatly with more robust, efficient,and reliable algorithms are developed in the future.展开更多
文摘Plant factories have a great potential for mitigating the contradiction between the world’sgrowing population and food scarcity. During the process of its automatic production,machine vision plays a significant role. This technique almost covers every production linkfrom raising seedlings, transplanting, management, and harvesting to fruit grading. To provide references and a starting point for those who are committed to studying this issue. Inthis paper, the application prospects of machine vision in plant factories were analyzed,and the present researches were summarized from the fields of plant growth monitoring,robot operation assistance, and fruit grading. The results found that although the existingmethods have solved some practical problems at low cost, high efficiency and precision,some challenges still are faced by machine vision. Firstly, the changing lighting, complexbackgrounds, and color similarity within plant different parts cause the commonly usedimage segmentation algorithms to fail. The shortage of standard agricultural datasets alsokeeps deep learning and unsupervised classification algorithms from making progress.Secondly, there are some theoretical knowledge gaps for machine vision application in aparticular environment of plant factories, which seriously contains its application effect.Thirdly, the lack of special image acquisition devices and supporting facilities resulted inpoor image quality. All these factors hinder machine vision application in plant factories.Nevertheless, it is still a powerful tool and irreplaceable at present. We believed that thistechnique would promote plant factory development greatly with more robust, efficient,and reliable algorithms are developed in the future.
