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A survey of county extension agents was conducted in 1998 to determine the most troublesome weeds in corn, cotton, forages and pastures, peanut, small grains, soybean, tobacco, and vegetables in Georgia. The most troublesome weed statewide averaged over all crops was sicklepod. It was the most troublesome weed in cotton and soybean and among the four most troublesome weeds in corn, peanut, tobacco, and vegetables. Sicklepod was found in each of the nine climatological districts and in all the crops surveyed. Perennial nutsedge species were the second most troublesome weeds in Georgia. They ranked as the most troublesome weeds in tobacco and vegetables and were among the top five most troublesome weeds in corn, cotton, peanut, and soybean. Pigweed species were ranked third averaged over all the crops surveyed and were the second most troublesome weeds in cotton and vegetables and among the top five most troublesome species in corn, soybean, and tobacco. Morningglory species were listed as troublesome in six of the eight crops surveyed and ranked fourth overall. Similarly, Texas panicum was found in all districts and was the fifth most troublesome weed species. Texas panicum was the most troublesome weed in corn and among the top five most troublesome weeds in peanut, soybean, and tobacco. Florida beggarweed was the most troublesome weed in peanut, the second most troublesome weed in tobacco, and a top-10 weed species in corn, cotton, soybean, and vegetables, resulting in a ranking of sixth overall. Wild radish, large crabgrass, and tropic croton were the seventh through the ninth most troublesome weeds. Wild radish was the most troublesome weed of small grains and the sixth most troublesome weed of vegetables. Large crabgrass was the second most troublesome weed of forages and pastures and was reported in six other crops. Tropic croton was a troublesome weed in seven of the eight crops surveyed and was among the top five most troublesome weeds of cotton and peanut. The 10th most troublesome weed overall was bahiagrass, the most troublesome weed of forages and pastures.

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Background Due to the recent domestication of peanut from a single tetraploidization event, relatively little genetic diversity underlies the extensive morphological and agronomic diversity in peanut cultivars today. To broaden the genetic variation in future breeding programs, it is necessary to characterize germplasm accessions for new sources of variation and to leverage the power of genome-wide association studies (GWAS) to discover markers associated with traits of interest. We report an analysis of linkage disequilibrium (LD), population structure, and genetic diversity, and examine the ability of GWA to infer marker-trait associations in the U.S. peanut mini core collection genotyped with a 58 K SNP array. Results LD persists over long distances in the collection, decaying to r 2 = half decay distance at 3.78 Mb. Structure within the collection is best explained when separated into four or five groups (K = 4 and K = 5). At K = 4 and 5, accessions loosely clustered according to market type and subspecies, though with numerous exceptions. Out of 107 accessions, 43 clustered in correspondence to the main market type subgroup whereas 34 did not. The remaining 30 accessions had either missing taxonomic classification or were classified as mixed. Phylogenetic network analysis also clustered accessions into approximately five groups based on their genotypes, with loose correspondence to subspecies and market type. Genome wide association analysis was performed on these lines for 12 seed composition and quality traits. Significant marker associations were identified for arachidic and behenic fatty acid compositions, which despite having low bioavailability in peanut, have been reported to raise cholesterol levels in humans. Other traits such as blanchability showed consistent associations in multiple tests, with plausible candidate genes. Conclusions Based on GWA, population structure as well as additional simulation results, we find that the primary limitations of this collection for GWAS are a small collection size, significant remaining structure/genetic similarity and long LD blocks that limit the resolution of association mapping. These results can be used to improve GWAS in peanut in future studies – for example, by increasing the size and reducing structure in the collections used for GWAS. Electronic supplementary material The online version of this article (10.1186/s12864-019-5824-9) contains supplementary material, which is available to authorized users.

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