Research Hub

대학 자원

대학 인프라와 자원을 공유해 공동 연구와 기술 활용을 지원합니다.

Loading...

논문 리스트

2024
Search Using Text Mining in R on Botrytis cinerea in Horticulture
한국화훼학회
이영분
논문정보
Publisher
화훼연구
Issue Date
2024-03-29
Keywords
-
Citation
-
Source
-
Journal Title
-
Volume
32
Number
1
Start Page
14
End Page
20
DOI
https://doi.org/10.11623/frj.2024.32.1.02
ISSN
12255009
Abstract
This study utilized text mining analysis to identify keywords used in the research of gray mold (Botrytis cinerea), taking into account horticultural crops, environmental or physical treatments, and chemical or material factors. Data spanning from 1980 to 2021 was gathered from ScienceON and interpreted using word cloud visualization analysis following post-processing. Morphological analysis and coding were conducted using the text mining packages library tm provided by the R program. Our review of B. cinerea included and analyzed 7,342 papers. Among the extracted words, those related to crops and ranking in the top 10 were tomato, strawberry, grape, apple, cucumber, bean, kiwifruit, rose, pepper, and pear. roses were the only flower in the top 10 horticultural crops. Research has explored environmental or physical treatment factors such as storage, temperature, cold, seasons, humidity, heat/hot UV-C, sprays, films, and coatings. Chemical or material words included fungicide, chitosan, ethylene, oil, ROS, ABA, VOC, glucose, carbon, and ethanol.

저자 정보

이름 소속
이영분 원예생명공학과