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作 者:王锐 王桂英[1] 吴文福 韩峰[1,2] 刘哲[1] 马昀钊 徐岩 张亚秋[1] WANG Rui;WANG Gui-ying;WU Wen-fu;HAN Feng;LIU Zhe;MA Yun-zhao;XU Yan;ZHANG Ya-qiu(College of Biological and Agricultural Engineering,Jilin University,Changchun,Jilin 130022,China;Weihai Biomimetic Research Institute of Jilin University,Jilin University,Weihai,Shandong 264402,China)
机构地区:[1]吉林大学生物与农业工程学院,吉林长春130022 [2]吉林大学,吉林大学威海仿生研究院,山东威海264402
出 处:《粮油食品科技》2023年第2期74-82,共9页Science and Technology of Cereals,Oils and Foods
基 金:吉林省科技发展计划项目(2019102003JH);国家重点研发计划(2017YFD0401402-04)。
摘 要:人工智能技术在解决传统农业难题方面表现出了无可比拟的优势。目前,粮食收购中对高水分玉米的水分含量和等级判定仍然以人工感官检测为主,存在工作量大、效率低、重复性差、主观性强等问题,影响企业效益和农民利益。针对玉米高水分快速检测的技术难题,采用机器视觉技术在挖掘玉米图像丰富信息的基础上,以互信息熵为耦合程度作为评价指标,研究了高水分玉米图像快速无损检测新方法及智能收购定等系统,并对系统进行了测试。结果表明,在实现“机器看水”仿生智能算法的基础上,进行高水分玉米收购定等是一条值得探索的技术路径。Artificial intelligence technology has shown incomparable advantages in solving traditional agricultural problems. At present, the determination of moisture content and grade of high moisture corn in grain purchase is still mainly based on artificial sensory detection. There are many problems such as heavy workload, low efficiency, poor repeatability, and strong subjectivity, which will cause the loss of grain quantity and quality, and this problems even affect the benefits of enterprises and farmers. Aiming at the technical difficulties in rapid detection of high moisture maize, this study obtains enlightenment from the experience of front line personnel in visual measurement of moisture. Based on mining the rich information in corn kernel images, a new bionic image rapid nondestructive measurement method using the mutual information entropy as the coupling degree evaluation index, were studied then a intelligent purchase grading system of high moisture corn were developed and tested. The test results show that on the basis of realization of the bionic intelligent algorithm of ‘watching moisture by machine’, the purchase of high moisture corn is a technical path worth exploring.
分 类 号:S-03[农业科学] TS205[轻工技术与工程—食品科学]
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