Abstract
The occurrence of high- (H) and low- (L) yielding field sites within a farm is a commonly observed phenomenon in soybean cultivation. Site topography, soil physical and chemical attributes, and soil/root-associated microbial composition can contribute to this phenomenon. In order to better understand the microbial dynamics associated with each site type (H/L), we collected bulk soil (BS), rhizosphere soil (RS), and soybean root (R) samples from historically high and low yield sites across eight Pennsylvania farms at V1 (first trifoliate) and R8 (maturity) soybean growth stages (SGS). We extracted DNA extracted from collected samples and performed high-throughput sequencing of PCR amplicons from both the fungal ITS and prokaryotic 16S rRNA gene regions. Sequences were then grouped into amplicon sequence variants (ASVs) and subjected to network analysis. Based on both ITS and 16S rRNA gene data, a greater network size and edges were observed for all sample types from H-sites compared to L-sites at both SGS. Network analysis suggested that the number of potential microbial interactions/associations were greater in samples from H-sites compared to L-sites. Diversity analyses indicated that site-type was not a main driver of alpha and beta diversity in soybean-associated microbial communities. L-sites contained a greater percentage of fungal phytopathogens (ex: Fusarium, Macrophomina, Septoria), while H-sites contained a greater percentage of mycoparasitic (ex: Trichoderma) and entomopathogenic (ex: Metarhizium) fungal genera. Furthermore, roots from H-sites possessed a greater percentage of Bradyrhizobium and genera known to contain plant growth promoting bacteria (ex: Flavobacterium, Duganella). Overall, our results revealed that there were differences in microbial composition in soil and roots from H- and L-sites across a variety of soybean farms. Based on our findings, we hypothesize that differences in microbial composition could have a causative relationship with observed within-farm variability in soybean yield.
Highlights
Spatial heterogeneity in soil characteristics within agricultural fields is a frequently observed phenomenon that can influence yield and other crop traits (Khakural et al, 1996; Jaynes and Colvin, 1997; Paz et al, 1998; Kravchenko and Bullock, 2000; Vollmann et al, 2000; Batchelor et al, 2002; Shahandeh et al, 2005)
Microbial networks constructed for three sample types from high and low yield sites at two SGS differed in their network statistics (Table 1)
Analyses performed with three sample types showed greater network size and total/positive/negative edges for high yield sites compared to low yield sites at both V1 and R8 growth stages, with the exception of rhizosphere soil at V1 stage (Table 1 and Figures 2A–D)
Summary
Spatial heterogeneity in soil characteristics within agricultural fields is a frequently observed phenomenon that can influence yield and other crop traits (Khakural et al, 1996; Jaynes and Colvin, 1997; Paz et al, 1998; Kravchenko and Bullock, 2000; Vollmann et al, 2000; Batchelor et al, 2002; Shahandeh et al, 2005). The site-scale spatial heterogeneity of various soil characteristics and their relationships with soybean yields have been previously reported in several locations including Iowa (Kaspar et al, 2004; Rogovska et al, 2007), Mississippi (Cox et al, 2003), and Michigan (Jiang and Thelen, 2004). These studies indicated that site-scale heterogeneity in soil factors, such as pH, P, K, slope of the site, site elevation, and soil texture explained the observed variability in soybean yield. The authors found that farmer-identified good sites contained significantly greater levels of B, Ca, Mg, and higher pH, compared to poor sites
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