{"title":"茶包指数(TBI)对比较土壤分解速率有用吗?","authors":"Taiki Mori","doi":"10.3390/ecologies3040038","DOIUrl":null,"url":null,"abstract":"The Bag Index (TBI) is a novel approach using standardized materials (i.e., commercial tea bags) to evaluate organic matter decomposition by determining two indexes: the early stage decomposition constant k (k_TBI) and litter stabilization factor S (S_TBI). k_TBI is defined as the decomposition constant of an asymptote model describing the decomposition curve of rooibos tea, whereas S is the ratio of the stabilized to total hydrolysable fractions of green tea. However, it was recently revealed that both k_TBI and S_TBI deviate from the actual S and k values accurately determined by fitting an asymptote model to the time series mass of green and rooibos teas remaining (k_fitting and S_fitting, respectively). Nevertheless, k_TBI and S_TBI, which can be determined in a cost- and labor-effective manner, might indicate the relative values of k_fitting and S_fitting across different soils and be useful for comparative analyses. Therefore, this study investigated the positive correlations of k_TBI and S_TBI with k_fitting and S_fitting, respectively, in which case these indexes are useful for comparative analyses. However, the result showed that k_TBI was negatively correlated with k_fitting. This study underscores the importance of obtaining time-series data for accurately determining the decomposition constant of an asymptote model describing the decomposition curve of rooibos tea. S_TBI was positively correlated with S_fitting, implying that S_TBI can be used as an indicator of S.","PeriodicalId":72866,"journal":{"name":"Ecologies","volume":" ","pages":""},"PeriodicalIF":1.7000,"publicationDate":"2022-11-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"Is the Tea Bag Index (TBI) Useful for Comparing Decomposition Rates among Soils?\",\"authors\":\"Taiki Mori\",\"doi\":\"10.3390/ecologies3040038\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The Bag Index (TBI) is a novel approach using standardized materials (i.e., commercial tea bags) to evaluate organic matter decomposition by determining two indexes: the early stage decomposition constant k (k_TBI) and litter stabilization factor S (S_TBI). k_TBI is defined as the decomposition constant of an asymptote model describing the decomposition curve of rooibos tea, whereas S is the ratio of the stabilized to total hydrolysable fractions of green tea. However, it was recently revealed that both k_TBI and S_TBI deviate from the actual S and k values accurately determined by fitting an asymptote model to the time series mass of green and rooibos teas remaining (k_fitting and S_fitting, respectively). Nevertheless, k_TBI and S_TBI, which can be determined in a cost- and labor-effective manner, might indicate the relative values of k_fitting and S_fitting across different soils and be useful for comparative analyses. Therefore, this study investigated the positive correlations of k_TBI and S_TBI with k_fitting and S_fitting, respectively, in which case these indexes are useful for comparative analyses. However, the result showed that k_TBI was negatively correlated with k_fitting. This study underscores the importance of obtaining time-series data for accurately determining the decomposition constant of an asymptote model describing the decomposition curve of rooibos tea. S_TBI was positively correlated with S_fitting, implying that S_TBI can be used as an indicator of S.\",\"PeriodicalId\":72866,\"journal\":{\"name\":\"Ecologies\",\"volume\":\" \",\"pages\":\"\"},\"PeriodicalIF\":1.7000,\"publicationDate\":\"2022-11-15\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Ecologies\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.3390/ecologies3040038\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"ECOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Ecologies","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.3390/ecologies3040038","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"ECOLOGY","Score":null,"Total":0}
Is the Tea Bag Index (TBI) Useful for Comparing Decomposition Rates among Soils?
The Bag Index (TBI) is a novel approach using standardized materials (i.e., commercial tea bags) to evaluate organic matter decomposition by determining two indexes: the early stage decomposition constant k (k_TBI) and litter stabilization factor S (S_TBI). k_TBI is defined as the decomposition constant of an asymptote model describing the decomposition curve of rooibos tea, whereas S is the ratio of the stabilized to total hydrolysable fractions of green tea. However, it was recently revealed that both k_TBI and S_TBI deviate from the actual S and k values accurately determined by fitting an asymptote model to the time series mass of green and rooibos teas remaining (k_fitting and S_fitting, respectively). Nevertheless, k_TBI and S_TBI, which can be determined in a cost- and labor-effective manner, might indicate the relative values of k_fitting and S_fitting across different soils and be useful for comparative analyses. Therefore, this study investigated the positive correlations of k_TBI and S_TBI with k_fitting and S_fitting, respectively, in which case these indexes are useful for comparative analyses. However, the result showed that k_TBI was negatively correlated with k_fitting. This study underscores the importance of obtaining time-series data for accurately determining the decomposition constant of an asymptote model describing the decomposition curve of rooibos tea. S_TBI was positively correlated with S_fitting, implying that S_TBI can be used as an indicator of S.