Author
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MA, JINCAI - Jilin University |
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Ibekwe, Abasiofiok - Mark |
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YANG, CHING-HONG - University Of Wisconsin |
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CROWLEY, DAVID - University Of California |
Submitted to: Science of the Total Environment
Publication Type: Peer Reviewed Journal Publication Acceptance Date: 4/15/2016 Publication Date: 4/30/2016 Citation: Ma, J., Ibekwe, A.M., Yang, C., Crowley, D.E. 2016. Bacterial diversity and composition in major fresh produce growing soils affected by physiochemical properties and geographic locations. Science of the Total Environment. 563:199-209. doi: 10.1016/j.scitotenv.2016.04.122. Interpretive Summary: Microorganisms are numerous in soil, and they play crucial roles in in soil quality. In the current study, we selected the three major leafy green producing areas in California and Arizona as study sites, and investigated the bacterial community structure in soils from those sites using next generation sequencing technique. The objectives of this research were to understand the composition of bacterial communities in major leafy green soils under conventionally and organically managed systems, and identify factors affecting bacterial community structures in these soils. Our study showed that soil physical and chemical properties as well as geographic location have major influence on bacterial community structures in soils from California and Arizona. A better understanding of diversity and composition of microbial communities and their controlling factors may enable farmers to evaluate the soil quality and adjust their soil management strategies to boost microbial diversity and abundance toward a healthy and sustainable soil. The results of this research will be used by growers, researchers, FSIS, FDA, and different state agencies that are involved in leafy green production. Technical Abstract: Microbial diversity of agricultural soils is well documented, but information on leafy green producing soils is limited. Our goal was to assess bacterial composition and diversity in leafy green producing soils using pyrosequencing, and to identify factors affecting bacterial community structures. Canonical correspondence analysis (CCA) and Artificial neural network (ANN) analysis of bacterial community structures and soil variables showed that electrical conductivity (EC) , sand fraction, water holding capacity (WHC), pH, total nitrogen (TN), and organic carbon (OC) significantly (p <0.05) impacted microbial communities. CCA based variation partitioning analysis (VPA) showed that soil physical properties (sand fraction, EC, and WHC), soil chemical variables (pH, TN, and OC) and sampling location explained 16.3%, 12.5%, and 50.9%, respectively, of total variations of bacterial community structure, leaving 13% of total variation unexplained. Our current study showed that bacterial community composition and diversity in major fresh produce growing soils from California and Arizona is a function of soil physiochemical characteristics and geographic distances of sampling sites, with the best predictors being soil texture, EC, and pH. |