The recently developed Cosmic-ray Neutron Probe (CRNP) for estimating soil water content (SWC) fills a critical measurement gap between point scale methods and large scale measurements collected from remote sensing. CRNP works by measuring the change in low-energy neutron intensity over time. However, the accuracy of CRNP to measure SWC is well known to be affected by other hydrogen sources (e.g. soil organic content, atmospheric water vapor, vegetation and surface water). This study focuses on the influence of rapidly growing vegetation in agricultural fields on the accuracy of the CRNP method. Our results indicate that biomass data determined from remote sensing (GrWDRVI) closely follows in-situ sampling of biomass (R2=0.677 for Maize and R2=0.567 for Soybean). We found that local correction factors using bare to moderated ratio removing the influence of vegetation changes can be derived, thus removing bias in the CRNP SWC observations. The improved algorithm for estimating SWC from CRNP will be beneficial for long-term monitoring as well as validating remote sensing SWC products.