인문학
사회과학
자연과학
공학
의약학
농수해양학
예술체육학
복합학
DBpia AI
AI 에이전트
AI 아이디어
AI 리더
AI 뷰어
Citeasy
크롬 서지관리 다운로드
지원사업
학술연구/단체지원/교육 등 연구자 활동을 지속하도록 DBpia가 지원하고 있어요.
커뮤니티
연구자들이 자신의 연구와 전문성을 널리 알리고, 새로운 협력의 기회를 만들 수 있는 네트워킹 공간이에요.
학술저널
Full-text AI
오류 신고하기해당 페이지 내 제목·저자·목차·페이지정보가 잘못된 경우 알려주세요!
초록·키워드
Background: The leaf temperature (T<SUB>LEAF</SUB>) is one of the most important physical parameters governing water and carbon flux, including evapotranspiration, photosynthesis and respiration. Cnidium officinale is one of the important folk medicines for counteracting a variety of diseases, and is particularly used as a traditional medicinal crop in the treatment of female genital inflammatory diseases. In this study, we developed a model to estimate T<SUB>Leaf</SUB> of Cnidium officinale Makino based on black globe temperature (T<SUB>BGT</SUB>).
Methods and Results: This study was performed from April to July 2018 in field characterized by a valley and alluvial fan topography. Databases of TLEAF were curated by infrared thermometry, along with meteorological instruments, including a thermometer, a pyranometer, and an anemometer. Linear regression analysis and Student’s t-test were performed to evaluate the performance of the model and significance of the parameters. The correlation coefficient between observed T<SUB>LEAF</SUB> and calculated T<SUB>BGT</SUB> obtained using an equation, developed to predict T<SUB>LEAF</SUB> based on T<SUB>BGT</SUB> was very high (r² = 0.9500, p ＜ 0.0001). There was a positive relationship between T<SUB>BGT</SUB> and solar radiation (r² = 0.8556, p ＜ 0.0001), but a negative relationship between T<SUB>BGT</SUB> and wind speed (r² = 0.9707, p ＜ 0.0001). These results imply that heat exchange in leaves seems to be mainly controlled by solar radiation and wind speed. The correlation coefficient between actual and estimated T<SUB>BGT</SUB> was 0.9710 (p ＜ 0.0001).
Conclusions: The developed model can be used to accurately estimate the T<SUB>Leaf</SUB> of Cnidium officinale Makino and has the potential to become a practical alternative to assessing cold and heat stress.
Methods and Results: This study was performed from April to July 2018 in field characterized by a valley and alluvial fan topography. Databases of TLEAF were curated by infrared thermometry, along with meteorological instruments, including a thermometer, a pyranometer, and an anemometer. Linear regression analysis and Student’s t-test were performed to evaluate the performance of the model and significance of the parameters. The correlation coefficient between observed T<SUB>LEAF</SUB> and calculated T<SUB>BGT</SUB> obtained using an equation, developed to predict T<SUB>LEAF</SUB> based on T<SUB>BGT</SUB> was very high (r² = 0.9500, p ＜ 0.0001). There was a positive relationship between T<SUB>BGT</SUB> and solar radiation (r² = 0.8556, p ＜ 0.0001), but a negative relationship between T<SUB>BGT</SUB> and wind speed (r² = 0.9707, p ＜ 0.0001). These results imply that heat exchange in leaves seems to be mainly controlled by solar radiation and wind speed. The correlation coefficient between actual and estimated T<SUB>BGT</SUB> was 0.9710 (p ＜ 0.0001).
Conclusions: The developed model can be used to accurately estimate the T<SUB>Leaf</SUB> of Cnidium officinale Makino and has the potential to become a practical alternative to assessing cold and heat stress.
본문·목차
인공지능 문자 인식 모델을 통해 추출된 텍스트로, 일부 오타나 오류가 포함될 수 있으나 지속적으로 개선 중입니다.
오류를 발견하셨다면 해당 부분을 드래그한 후 ' 를 통해 신고해주세요.
오류를 발견하셨다면 해당 부분을 드래그한 후 ' 를 통해 신고해주세요.
최근 본 자료 전체보기
UCI(KEPA) : I410-ECN-0101-2019-480-000585972
