Using a soil bacterial species balance index to estimate potato crop productivity

Abstract

The development of 'molecular-omic' tools and computing analysis platforms have greatly enhanced our ability to assess the impacts of agricultural practices and crop management protocols on soil microbial diversity. However, biotic factors are rarely factored into agricultural management models. Today it is possible to identify specific microbiomes and define biotic components that contribute to soil quality. We assessed the bacterial diversity of soils in 51 potato production plots. We describe a strategy for identifying a potato-crop-productivity bacterial species balance index based on amplicon sequence variants. We observed a significant impact of soil texture balances on potato yields; however, the Shannon and Chao1 richness indices and Pielou's evenness index poorly correlated with these yields. Nonetheless, we were able to estimate the portion of the total bacterial microbiome related to potato yield using an integrated species balances index derived from the elements of the bacterial microbiome that positively or negatively correlate with residual potato yields. This innovative strategy based on a microbiome selection procedure greatly enhances our ability to interpret the impact of agricultural practices and cropping system management choices on microbial diversity and potato yield. This strategy provides an additional tool that will aid growers and the broader agricultural sector in their decision-making processes concerning the soil quality and crop productivity.

Fig 1. Balance structure used to compute soil isometric log-ratios.

Fig 2. Statistical analysis workflow applied to soil microbiome and potato crop productivity.

Fig 3. Slope coefficients and their 95% confidence intervals from a linear model linking environmental and physico-chemical features to potato yield.

Fig 4. (A) Counts of ASVs per bacterial phyla (bacteria and archaea) detected in soil samples and (B) counts of ASVs per bacterial phyla that significantly correlated, either positively or negatively, with residual yields at the 0.05 level of significance.

Fig 5. Relationships between alpha diversity metrics and the SBI-py index with residual potato yield.

Fig 6. Triplot of a redundancy analysis showing ecological niches of ASVs that exhibit a significant positive (+) or negative (-) correlation with potato yield residual, as well as those ASVs with no significant correlation (translucid points) in distance scaling (scaling 1).