LAUSR

This study aimed to identify possible relationships between corn productivity and its endosphere. The microbial sap communities were analyzed using TRFLP and identified using an internal reference database and BLAST. Diversity, richness, and normalized abundances of each bacterial population in corn sap samples were evaluated to link the microbiome of a specific field to its yield. A negative trend was observed where higher yielding fields had lower TRF richness. A PLS regression analysis of TRF intensity and binary data from 2014 identified ten TRFs (bacterial genera) that correlated to corn yields, when either absent or present at certain levels or ratios. Using these observations, a model was developed that accommodated criteria for each of the ten microbes and assigned a score for each field out of 10. Data collected in 2014 showed that sites with higher model scores were highly correlated with larger yields (r = 0.83). This correlation was also seen using the 2017 dataset (r = 0.87). We were able to conclude that a positive significant effect was seen with the model score and yield (adjusted R2 = 0.67, F1,22 = 46.7, p < 0.001) when combining 2014 and 2017 data. The results of this study are being expanded to identify the key microbes that potentially impact corn yield, regardless of corn variety, geographic, or edaphic factors.