Table 4_Genome-wide association studies for identification of stripe rust resistance loci in diverse wheat genotypes.xlsx por Vikesh Tanwar (22809038)

“...Marker–trait associations were identified using General Linear Model (GLM), Mixed Linear Model (MLM), and FarmCPU approaches, considering loci with –log₁₀(p) ≥ 3 as significant....”

Table 5_Genome-wide association studies for identification of stripe rust resistance loci in diverse wheat genotypes.xlsx por Vikesh Tanwar (22809038)

“...Marker–trait associations were identified using General Linear Model (GLM), Mixed Linear Model (MLM), and FarmCPU approaches, considering loci with –log₁₀(p) ≥ 3 as significant....”

Table 3_Genome-wide association studies for identification of stripe rust resistance loci in diverse wheat genotypes.xlsx por Vikesh Tanwar (22809038)

“...Marker–trait associations were identified using General Linear Model (GLM), Mixed Linear Model (MLM), and FarmCPU approaches, considering loci with –log₁₀(p) ≥ 3 as significant....”

Table 1_Genome-wide association studies for identification of stripe rust resistance loci in diverse wheat genotypes.doc por Vikesh Tanwar (22809038)

“...Marker–trait associations were identified using General Linear Model (GLM), Mixed Linear Model (MLM), and FarmCPU approaches, considering loci with –log₁₀(p) ≥ 3 as significant....”

Table 2_Genome-wide association studies for identification of stripe rust resistance loci in diverse wheat genotypes.xlsx por Vikesh Tanwar (22809038)

“...Marker–trait associations were identified using General Linear Model (GLM), Mixed Linear Model (MLM), and FarmCPU approaches, considering loci with –log₁₀(p) ≥ 3 as significant....”

Image 1_Genome-wide association studies for identification of stripe rust resistance loci in diverse wheat genotypes.jpeg por Vikesh Tanwar (22809038)

“...Marker–trait associations were identified using General Linear Model (GLM), Mixed Linear Model (MLM), and FarmCPU approaches, considering loci with –log₁₀(p) ≥ 3 as significant....”

Image 1_Toxicological effects of sublethal microcystin-LR exposure in Labeo rohita: histopathological, ultrastructural, immunological, and biochemical impairments.jpeg por Snatashree Mohanty (22459801)

“...Interestingly, the modulation in the expression of SOD, catalase, GST, CYP1A and CYP3A genes in different organs indicated their involvement in the antioxidant and detoxification process. ...”

Table 1_Strawberry-herb intercropping: a 2-year study toward sustainable intensification and diversification.docx por Sebastian Soppelsa (5776868)

“...Despite its ecological benefits, its adoption in specialized farming systems—such as strawberry monocultures—remains limited, as these systems typically focus on maximizing income from a single crop. ...”

Assessing the Effect of Undirected Forest Restoration and Flooding on the Soil Quality in an Agricultural Floodplain por Clayton Williams (10873518)

“...Two recently abandoned farm field sites (3.4 and 4.1 acres), now a mixture of young trees and prairie species, were selected near two forest sites....”

Table 8_Dissecting adult plant resistance to stem rust through multi-model GWAS in a diverse barley germplasm panel.xlsx por Yuliya Genievskaya (4725192)

“...Phenotypic data were combined with high-density SNP genotyping to perform GWAS using five statistical models (GLM, MLM, MLMM, FarmCPU, and BLINK). Population structure and kinship were accounted for to identify robust marker-trait associations (MTAs), followed by haplotype-based QTL delineation. ...”

Table 6_Dissecting adult plant resistance to stem rust through multi-model GWAS in a diverse barley germplasm panel.xlsx por Yuliya Genievskaya (4725192)

“...Phenotypic data were combined with high-density SNP genotyping to perform GWAS using five statistical models (GLM, MLM, MLMM, FarmCPU, and BLINK). Population structure and kinship were accounted for to identify robust marker-trait associations (MTAs), followed by haplotype-based QTL delineation. ...”

Image 2_Dissecting adult plant resistance to stem rust through multi-model GWAS in a diverse barley germplasm panel.png por Yuliya Genievskaya (4725192)

“...Phenotypic data were combined with high-density SNP genotyping to perform GWAS using five statistical models (GLM, MLM, MLMM, FarmCPU, and BLINK). Population structure and kinship were accounted for to identify robust marker-trait associations (MTAs), followed by haplotype-based QTL delineation. ...”

Table 7_Dissecting adult plant resistance to stem rust through multi-model GWAS in a diverse barley germplasm panel.xlsx por Yuliya Genievskaya (4725192)

“...Phenotypic data were combined with high-density SNP genotyping to perform GWAS using five statistical models (GLM, MLM, MLMM, FarmCPU, and BLINK). Population structure and kinship were accounted for to identify robust marker-trait associations (MTAs), followed by haplotype-based QTL delineation. ...”

Table 3_Dissecting adult plant resistance to stem rust through multi-model GWAS in a diverse barley germplasm panel.xlsx por Yuliya Genievskaya (4725192)

“...Phenotypic data were combined with high-density SNP genotyping to perform GWAS using five statistical models (GLM, MLM, MLMM, FarmCPU, and BLINK). Population structure and kinship were accounted for to identify robust marker-trait associations (MTAs), followed by haplotype-based QTL delineation. ...”

Table 5_Dissecting adult plant resistance to stem rust through multi-model GWAS in a diverse barley germplasm panel.xlsx por Yuliya Genievskaya (4725192)

“...Phenotypic data were combined with high-density SNP genotyping to perform GWAS using five statistical models (GLM, MLM, MLMM, FarmCPU, and BLINK). Population structure and kinship were accounted for to identify robust marker-trait associations (MTAs), followed by haplotype-based QTL delineation. ...”

Table 1_Dissecting adult plant resistance to stem rust through multi-model GWAS in a diverse barley germplasm panel.xlsx por Yuliya Genievskaya (4725192)

“...Phenotypic data were combined with high-density SNP genotyping to perform GWAS using five statistical models (GLM, MLM, MLMM, FarmCPU, and BLINK). Population structure and kinship were accounted for to identify robust marker-trait associations (MTAs), followed by haplotype-based QTL delineation. ...”

Table 2_Dissecting adult plant resistance to stem rust through multi-model GWAS in a diverse barley germplasm panel.docx por Yuliya Genievskaya (4725192)

“...Phenotypic data were combined with high-density SNP genotyping to perform GWAS using five statistical models (GLM, MLM, MLMM, FarmCPU, and BLINK). Population structure and kinship were accounted for to identify robust marker-trait associations (MTAs), followed by haplotype-based QTL delineation. ...”

Table 4_Dissecting adult plant resistance to stem rust through multi-model GWAS in a diverse barley germplasm panel.xlsx por Yuliya Genievskaya (4725192)

“...Phenotypic data were combined with high-density SNP genotyping to perform GWAS using five statistical models (GLM, MLM, MLMM, FarmCPU, and BLINK). Population structure and kinship were accounted for to identify robust marker-trait associations (MTAs), followed by haplotype-based QTL delineation. ...”

Image 1_Dissecting adult plant resistance to stem rust through multi-model GWAS in a diverse barley germplasm panel.png por Yuliya Genievskaya (4725192)

“...Phenotypic data were combined with high-density SNP genotyping to perform GWAS using five statistical models (GLM, MLM, MLMM, FarmCPU, and BLINK). Population structure and kinship were accounted for to identify robust marker-trait associations (MTAs), followed by haplotype-based QTL delineation. ...”

Table 1_Detection and risk factor analysis of avian colibacillosis associated with colistin-resistant Escherichia coli and Klebsiella pneumoniae.xlsx por Muhammad Adnan Saeed (21780770)

“...In total, 230 visceral organ samples were collected from 13 different chicken farms located in Sargodha, Jhang and Toba Tek Singh in Pakistan. ...”