In a natural and cultivated system, plants usually interact with their neighboring plants either in a positive (facilitation) or in a negative (competition) way. Genome-wide association studies (GWAS) are one of the advanced approaches to reveal the underlying genetic mechanisms of given traits but are still unable to analyze the genotype by neighbor interactions in field conditions. This project aims to investigate the interactions between focal and neighboring genotypes considering different traits such as disease resistance, biomass gain, fruit quality, etc. For this purpose, a novel statistical method “Neighbor GWAS” (available in R packages) will be applied to analyze available datasets of different field crops such as barley, maize, rice, and apple. This analysis will lead us to quantify the phenotypic variations explained by the genotypic interactions along with the identification of specific loci associated with those phenotypic variations. Hypothetically, this study is expected to uncover the genetic factors of plant-plant interactions, enabling the improvement of plant breeding selection strategies based on marker-assisted selection, thus promising the optimized production of field crops under diverse environmental conditions. At present, we are analyzing barley data that is publicly available from the CAIGE project. To reveal genetic factors responsible for the spatial heterogeneity of disease damage, we applied SpATS (Spatial Analysis of Field Trials with Splines) and Neighbor GWAS to damage levels for NFNB (net form net blotch), SFNB (soft form net blotch) and scald. We will present preliminary results from the barley data analysis, including the spatial trends, heritability, and GWAS of disease damage.