S. Fukuda, W. Spreer, W. Wiriya-Alongkorn, K. Spohrer, E. Yasunaga, C. Tiyayon
{"title":"随机森林作为龙眼根区CO2浓度分析局部干旱胁迫的工具。","authors":"S. Fukuda, W. Spreer, W. Wiriya-Alongkorn, K. Spohrer, E. Yasunaga, C. Tiyayon","doi":"10.2525/ECB.56.25","DOIUrl":null,"url":null,"abstract":"This study aims at establishing a relationship between water supply and CO 2 concentration in the rootzone, and to identify disturbing factors using data-driven modelling. In our previous study, 10 longan trees were planted in split-root technique and kept under controlled conditions. During six months, 5 trees were partially irrigated on one side of the root system, while the other side was kept non-irrigated. The sides were switched in a two-week interval. Five control trees received full irrigation on both sides. Monitoring results on CO 2 concentration in the rootzone, soil moisture and stomatal con-ductance indicated a weak correlation between the CO 2 concentration in the rootzone and the soil moisture, but without a statistically significant correlation, partially because air temperature was a main disturbing factor. In this study, Random Forests was applied to establish a CO 2 -water stress relationship based on air temperature, relative humidity, vapour pressure deficit and soil moisture. It was shown that the most important factor on CO 2 concentration in the rootzone was soil moisture, followed by air temperature. Together with the information retrieved, the results suggest a potential of CO 2 monitoring in the rootzone for assessing plant water status continuously and with a minimum level of invasion.","PeriodicalId":11762,"journal":{"name":"Environmental Control in Biology","volume":"56 1","pages":"25-31"},"PeriodicalIF":0.0000,"publicationDate":"2018-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Random forests as a tool for analyzing partial drought stress based on CO2 concentrations in the rootzone of longan trees.\",\"authors\":\"S. Fukuda, W. Spreer, W. Wiriya-Alongkorn, K. Spohrer, E. Yasunaga, C. Tiyayon\",\"doi\":\"10.2525/ECB.56.25\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This study aims at establishing a relationship between water supply and CO 2 concentration in the rootzone, and to identify disturbing factors using data-driven modelling. In our previous study, 10 longan trees were planted in split-root technique and kept under controlled conditions. During six months, 5 trees were partially irrigated on one side of the root system, while the other side was kept non-irrigated. The sides were switched in a two-week interval. Five control trees received full irrigation on both sides. Monitoring results on CO 2 concentration in the rootzone, soil moisture and stomatal con-ductance indicated a weak correlation between the CO 2 concentration in the rootzone and the soil moisture, but without a statistically significant correlation, partially because air temperature was a main disturbing factor. In this study, Random Forests was applied to establish a CO 2 -water stress relationship based on air temperature, relative humidity, vapour pressure deficit and soil moisture. It was shown that the most important factor on CO 2 concentration in the rootzone was soil moisture, followed by air temperature. Together with the information retrieved, the results suggest a potential of CO 2 monitoring in the rootzone for assessing plant water status continuously and with a minimum level of invasion.\",\"PeriodicalId\":11762,\"journal\":{\"name\":\"Environmental Control in Biology\",\"volume\":\"56 1\",\"pages\":\"25-31\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Environmental Control in Biology\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.2525/ECB.56.25\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"Agricultural and Biological Sciences\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Environmental Control in Biology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2525/ECB.56.25","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"Agricultural and Biological Sciences","Score":null,"Total":0}
Random forests as a tool for analyzing partial drought stress based on CO2 concentrations in the rootzone of longan trees.
This study aims at establishing a relationship between water supply and CO 2 concentration in the rootzone, and to identify disturbing factors using data-driven modelling. In our previous study, 10 longan trees were planted in split-root technique and kept under controlled conditions. During six months, 5 trees were partially irrigated on one side of the root system, while the other side was kept non-irrigated. The sides were switched in a two-week interval. Five control trees received full irrigation on both sides. Monitoring results on CO 2 concentration in the rootzone, soil moisture and stomatal con-ductance indicated a weak correlation between the CO 2 concentration in the rootzone and the soil moisture, but without a statistically significant correlation, partially because air temperature was a main disturbing factor. In this study, Random Forests was applied to establish a CO 2 -water stress relationship based on air temperature, relative humidity, vapour pressure deficit and soil moisture. It was shown that the most important factor on CO 2 concentration in the rootzone was soil moisture, followed by air temperature. Together with the information retrieved, the results suggest a potential of CO 2 monitoring in the rootzone for assessing plant water status continuously and with a minimum level of invasion.