Pyrosequencing reveals the influence of organic and conventional farming systems on bacterial communities

Abstract

It has been debated how different farming systems influence the composition of soil bacterial communities, which are crucial for maintaining soil health. In this research, we applied high-throughput pyrosequencing of V1 to V3 regions of bacterial 16S rRNA genes to gain further insight into how organic and conventional farming systems and crop rotation influence bulk soil bacterial communities. A 2×2 factorial experiment consisted of two agriculture management systems (organic versus conventional) and two crop rotations (flax-oat-fababean-wheat versus flax-alfalfa-alfalfa-wheat) was conducted at the Glenlea Long-Term Crop Rotation and Management Station, which is Canada's oldest organic-conventional management study field. Results revealed that there is a significant difference in the composition of bacterial genera between organic and conventional management systems but crop rotation was not a discriminator factor. Organic farming was associated with higher relative abundance of Proteobacteria, while Actinobacteria and Chloroflexi were more abundant in conventional farming. The dominant genera including Blastococcus, Microlunatus, Pseudonocardia, Solirubrobacter, Brevundimonas, Pseudomonas, and Stenotrophomonas exhibited significant variation between the organic and conventional farming systems. The relative abundance of bacterial communities at the phylum and class level was correlated to soil pH rather than other edaphic properties. In addition, it was found that Proteobacteria and Actinobacteria were more sensitive to pH variation.

Figure 1. Partial least square discriminant score plot of soil bacteria under organic and conventional treatments.

GO: Grain-Only organic; GC: Grain-Only conventional; FO: Forage-Grain organic; FC: Forage-Grain conventional. Model indicated a significant difference in the composition of putative bacterial genera between organic and conventional managements (R²X = 0.427, R²Y = 0.882, Q² = 0.159). Only genera with VIP>0.35 is included in the model.

Figure 2. Partial least square discriminant analysis (PLS-DA) loading plot based on the relative abundance of the putative bacterial genera in soil microbiome and their association with organic or conventional treatments.

Bacterial genera closer to organic or conventional are highly correlated to either treatment. PLS1 (R²X = 0.27, R²Y = 0.525, Q² = 0.186) and PLS2 (R²X = 0.127, R²Y = 0.218, Q² = −0.081). Some sequences could only be affiliated to phylum (P) or family (F) levels.

Figure 3. Redundancy analysis ordination plots of abundant phyla for individual sample.