[논문]Review: Application of Artificial Intelligence in Phenomics

Nabwire, Shona; Suh, Hyun-Kwon; Kim, Moon S.; Baek, Insuck; Cho, Byoung-Kwan

doi:10.3390/s21134363

[해외논문] Review: Application of Artificial Intelligence in Phenomics 원문보기

Sensors, v.21 no.13, 2021년, pp.4363 -

Nabwire, Shona (Department of Biosystems Engineering, Chungnam National University, Daejeon 34134, Korea) , Suh, Hyun-Kwon (nabwireshona@o.cnu.ac.kr) , Kim, Moon S. (Department of Life Resources Industry, Dong-A University, Busan 49315, Korea) , Baek, Insuck (Environmental Microbial and Food Safety Laboratory, Agricultural Research Service, United States Department of Agriculture, Powder Mill Road, BARC-East, Bldg 303, Beltsville, MD 20705, USA) , Cho, Byoung-Kwan (moon.kim@usda.gov (M.S.K.))

Abstract ▼ AI-Helper

Plant phenomics has been rapidly advancing over the past few years. This advancement is attributed to the increased innovation and availability of new technologies which can enable the high-throughput phenotyping of complex plant traits. The application of artificial intelligence in various domains of science has also grown exponentially in recent years. Notably, the computer vision, machine learning, and deep learning aspects of artificial intelligence have been successfully integrated into non-invasive imaging techniques. This integration is gradually improving the efficiency of data collection and analysis through the application of machine and deep learning for robust image analysis. In addition, artificial intelligence has fostered the development of software and tools applied in field phenotyping for data collection and management. These include open-source devices and tools which are enabling community driven research and data-sharing, thereby availing the large amounts of data required for the accurate study of phenotypes. This paper reviews more than one hundred current state-of-the-art papers concerning AI-applied plant phenotyping published between 2010 and 2020. It provides an overview of current phenotyping technologies and the ongoing integration of artificial intelligence into plant phenotyping. Lastly, the limitations of the current approaches/methods and future directions are discussed.

Keyword

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용어 설명: PCR은 세균 특이성이 있는 primer를 이용하여 적은 수의 세균이 있을지라도 쉽게 검출할 수 있는 유용한 방법이며, 이를 이용하여 구강 내 치면세균막이나 타액에서 직접 세균을 검출할 수 있게 되었다[8].

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