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Is foliar spectrum predictive of belowground bacterial diversity ? A case study in a peach orchard

文献类型： 外文期刊

作者： Sun, Na 1 ; Zhang, Weiwei 2 ; Liao, Shangqiang 1 ; Li, Hong 1 ;

作者机构： 1.Beijing Acad Agr & Forestry Sci, Inst Plant Nutr Resources & Environm, Beijing, Peoples R China

2.Beijing Acad Agr & Forestry Sci, Inst Grassland Flowers & Ecol, Beijing, Peoples R China

关键词： foliar spectral traits; plant productivity; fruit quality; bacterial diversity; soil conditioner

期刊名称：FRONTIERS IN MICROBIOLOGY （ 影响因子：5.2； 五年影响因子：6.2 ）

ISSN：

年卷期： 2023 年 14 卷

页码：

收录情况： SCI

摘要： Rhizosphere bacteria can have wide-ranging effects on their host plants, influencing plant biochemical and structural characteristics, and overall productivity. The implications of plant-microbe interactions provides an opportunity to interfere agriculture ecosystem with exogenous regulation of soil microbial community. Therefore, how to efficiently predict soil bacterial community at low cost is becoming a practical demand. Here, we hypothesize that foliar spectral traits can predict the diversity of bacterial community in orchard ecosystem. We tested this hypothesis by studying the ecological linkages between foliar spectral traits and soil bacterial community in a peach orchard in Yanqing, Beijing in 2020. Foliar spectral indexes were strongly correlated with alpha bacterial diversity and abundant genera that can promote soil nutrient conversion and utilization, such as Blastococcus, Solirubrobacter, and Sphingomonas at fruit mature stage. Certain unidentified or relative abundance < 1% genera were also associated with foliar spectral traits. We selected specific indicators (photochemical reflectance index, normalized difference vegetable index, greenness index, and optimized soil-adjusted vegetation index) of foliar spectral indexes, alpha and beta diversities of bacterial community, and quantified the relations between foliar spectral traits and belowground bacterial community via SEM. The results of this study indicated that foliar spectral traits could powerfully predict belowground bacterial diversity. Characterizing plant attributes with easy-accessed foliar spectral indexes provides a new thinking in untangling the complex plant-microbe relationship, which could better cope with the decreased functional attributes (physiological, ecological, and productive traits) in orchard ecosystem.

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