AUTHOR=Kaur Mandeep , Li Ji , Zhang Ping , Yang He-fa , Wang Lin , Xu Ming TITLE=Agricultural soil physico-chemical parameters and microbial abundance and diversity under long-run farming practices: A greenhouse study JOURNAL=Frontiers in Ecology and Evolution VOLUME=10 YEAR=2022 URL=https://www.frontiersin.org/journals/ecology-and-evolution/articles/10.3389/fevo.2022.1026771 DOI=10.3389/fevo.2022.1026771 ISSN=2296-701X ABSTRACT=

The growth of agriculture led to indiscriminate use of synthetic pesticides or fertilizers and unsustainable crop management farming practices which can aggravate harmful impacts on the microbial population and physical and chemical characteristics of soil ecosystem. Based on this fact, the present study was planned to evaluate the effect of long run farming practices on different soil physico-chemical parameters and soil microbial abundance and diversity within different soil depth (0–20 cm and 20–40 cm) at Quzhou Experimental Station of China Agricultural University, Hebei, China during October and December, 2016. The effect of farming practices on soil microbial abundance and diversity was studied by phospho-lipid fatty acid (PLFA) and DNA high-throughput sequencing methods. The findings revealed that soil is neutral to slightly alkaline in nature with highest water content under organic farming (ORF) at 0–20 cm and least under conventional farming at 20–40 cm depth. It was found that the ORF significantly increased the contents of total organic carbon (TOC), total carbon (TC), ammonium nitrogen, available nitrogen (AN), total nitrogen (TN), total phosphorus (TP), and available phosphorus (AP) followed by low input and conventional farming modes in both October and December soil samples. The correlation analysis showed significantly (at p ≤ 0.05 and 0.01) strong positive relationship within different physical and chemical properties of the soil under study. ANOVA and MANOVA analysis indicated significant effect of interaction between soil depth and farming modes on soil parameters. PCA analysis showed the most significant correlation between most of the bacterial types (G + bacteria, G− bacteria, actinomycetes) and soil AP, total available nitrogen, TOC and soil WC. Pearson correlation analysis revealed a significant correlation between microbial phylum groups (Proteobacteria, Bacteroidetes, and Latescibacteria) and microbial class group (Alphaproteobacteria, Sphingobacteriia, Flavobacteriia) with most of the soil physicochemical properties.