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      KCI등재 SCOPUS

      Development of a Low-Cost Plant Growth Chamber for Improved Phenotyping Research

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      https://www.riss.kr/link?id=A108820160

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      다국어 초록 (Multilingual Abstract)

      Purpose This study aimed to develop a research-use plant growth chamber from which plant researchers can easily acquire data and in which plants can be effectively grown by improving the sealing and control performance of the plant grower. Methods The...

      Purpose This study aimed to develop a research-use plant growth chamber from which plant researchers can easily acquire data and in which plants can be effectively grown by improving the sealing and control performance of the plant grower.
      Methods The low-cost plant growth chamber presented in this paper enables control of internal temperature, LED lighting, and aeroponics and features easy remote operation using open-source technology. Furthermore, it can apply a prediction model for the area and fresh weight using canopy images. We also demonstrated that the small enclosed plant grower could provide the opportunity to improve the efficiency and reproducibility of plant growth for various research aims.
      Results When used in plant-growth tests, the manufactured prototype achieved over 600 μmol m−2 s−1 photosynthetic photon flux densities (PPFD) and internal temperatures satisfying day/night temperature of 21/17 °C, demonstrating its applicability to grow various plants. Moreover, we confirmed that the sensor and image data storage, download functionality, and image analysis operated normally.
      Conclusion This prototype is advantageous for researchers who have difficulty investing in commercial phenotype equipment and facilitates access to phenotype data processing through a programming approach using canopy images. In the future, as hardware manufacturing costs continue to drop and performance improves, the proposed prototype provides the potential for plant science researchers to utilize creative application programs, systematic experimental design, and shared datasets and code.

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