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181
Data Sheet 2_Phylogenetic analysis and genetic evolution of porcine respiratory coronavirus in Guangxi province, Southern China from 2022 to 2024.docx
Foilsithe / Cruthaithe 2025“…To analyze the genetic and evolutional characteristics of PRCV in Guangxi province, southern China, a total of 6,267 clinical samples were collected from different pig farms, harmless treatment plants and abattoirs in Guangxi province during 2022–2024. …”
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182
Table 1_Phylogenetic analysis and genetic evolution of porcine respiratory coronavirus in Guangxi province, Southern China from 2022 to 2024.docx
Foilsithe / Cruthaithe 2025“…To analyze the genetic and evolutional characteristics of PRCV in Guangxi province, southern China, a total of 6,267 clinical samples were collected from different pig farms, harmless treatment plants and abattoirs in Guangxi province during 2022–2024. …”
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183
Data Sheet 1_Phylogenetic analysis and genetic evolution of porcine respiratory coronavirus in Guangxi province, Southern China from 2022 to 2024.docx
Foilsithe / Cruthaithe 2025“…To analyze the genetic and evolutional characteristics of PRCV in Guangxi province, southern China, a total of 6,267 clinical samples were collected from different pig farms, harmless treatment plants and abattoirs in Guangxi province during 2022–2024. …”
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184
Table 4_Genome-wide association studies for identification of stripe rust resistance loci in diverse wheat genotypes.xlsx
Foilsithe / Cruthaithe 2025“…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.…”
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185
Table 5_Genome-wide association studies for identification of stripe rust resistance loci in diverse wheat genotypes.xlsx
Foilsithe / Cruthaithe 2025“…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.…”
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186
Table 3_Genome-wide association studies for identification of stripe rust resistance loci in diverse wheat genotypes.xlsx
Foilsithe / Cruthaithe 2025“…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.…”
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187
Table 1_Genome-wide association studies for identification of stripe rust resistance loci in diverse wheat genotypes.doc
Foilsithe / Cruthaithe 2025“…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.…”
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188
Table 2_Genome-wide association studies for identification of stripe rust resistance loci in diverse wheat genotypes.xlsx
Foilsithe / Cruthaithe 2025“…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.…”
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189
Image 1_Genome-wide association studies for identification of stripe rust resistance loci in diverse wheat genotypes.jpeg
Foilsithe / Cruthaithe 2025“…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.…”
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190
Image 1_Toxicological effects of sublethal microcystin-LR exposure in Labeo rohita: histopathological, ultrastructural, immunological, and biochemical impairments.jpeg
Foilsithe / Cruthaithe 2025“…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. …”
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191
Table 1_Strawberry-herb intercropping: a 2-year study toward sustainable intensification and diversification.docx
Foilsithe / Cruthaithe 2025“…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. …”
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192
Table 8_Dissecting adult plant resistance to stem rust through multi-model GWAS in a diverse barley germplasm panel.xlsx
Foilsithe / Cruthaithe 2025“…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. …”
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193
Table 6_Dissecting adult plant resistance to stem rust through multi-model GWAS in a diverse barley germplasm panel.xlsx
Foilsithe / Cruthaithe 2025“…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. …”
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194
Image 2_Dissecting adult plant resistance to stem rust through multi-model GWAS in a diverse barley germplasm panel.png
Foilsithe / Cruthaithe 2025“…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. …”
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195
Table 7_Dissecting adult plant resistance to stem rust through multi-model GWAS in a diverse barley germplasm panel.xlsx
Foilsithe / Cruthaithe 2025“…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. …”
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196
Table 3_Dissecting adult plant resistance to stem rust through multi-model GWAS in a diverse barley germplasm panel.xlsx
Foilsithe / Cruthaithe 2025“…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. …”
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197
Table 5_Dissecting adult plant resistance to stem rust through multi-model GWAS in a diverse barley germplasm panel.xlsx
Foilsithe / Cruthaithe 2025“…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. …”
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198
Table 1_Dissecting adult plant resistance to stem rust through multi-model GWAS in a diverse barley germplasm panel.xlsx
Foilsithe / Cruthaithe 2025“…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. …”
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199
Table 2_Dissecting adult plant resistance to stem rust through multi-model GWAS in a diverse barley germplasm panel.docx
Foilsithe / Cruthaithe 2025“…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. …”
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200
Table 4_Dissecting adult plant resistance to stem rust through multi-model GWAS in a diverse barley germplasm panel.xlsx
Foilsithe / Cruthaithe 2025“…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. …”