Inbreeding coefficient modeling, BLUP genetic value estimation, genetic gain calculation, genomic selection analysis, and selection index optimization β grounded in USDA ARS plant genetics research.
Published heritability (h²) estimates and effective population size benchmarks from USDA-ARS germplasm research programs. Auto-populates heritability across all five SF2 science calculators (BLUP, Genetic Gain, Genomic Selection, Selection Index) and effective population size (N€).
Source: USDA-ARS Crop Improvement Programs. Published h² estimates from USDA germplasm and breeding program literature. Reference values; actual h² is population- and environment-specific.
USDA NASS national average yields for use as population mean benchmarks in BLUP and Genetic Gain calculations. Auto-populates population mean (μ) in the BLUP EBV calculator (SF2-S.002) and provides phenotypic standard deviation context for the Genetic Gain calculator (SF2-S.003).
Source: USDA NASS QuickStats. National average yield, annual. Live API attempted; reference data used as fallback.
Compares expected genetic gain per cycle under phenotypic selection vs genomic selection, based on loaded h² benchmarks. Shows years to achieve a target yield improvement and the cycle-time advantage of GS over conventional breeding.
Tip: Use the GS advantage output to justify genomic selection investment in the Genomic Selection Accuracy calculator (SF2-S.004).
Model SF2-S.001
Calculate Wright's coefficient of inbreeding from pedigree data. Measures the probability that two alleles at any locus are identical by descent.
Model SF2-S.002
Estimate Best Linear Unbiased Prediction (BLUP) breeding values using phenotypic records, heritability, and population parameters.
Model SF2-S.003
Predict response to selection using the Breeder's Equation. Calculate expected genetic gain per cycle based on heritability, selection intensity, and genetic variance.
Model SF2-S.004
Predict genomic selection accuracy based on training population size, heritability, effective number of loci, and marker density. Uses Daetwyler et al. (2008) framework.
Model SF2-S.005
Construct a multi-trait selection index combining 2β4 traits with economic weights. Calculates optimal index weights and expected genetic gains per trait.
From inbreeding assessment to multi-trait selection indices, our calculators bring research-grade quantitative genetics tools to breeders at every level. All models are based on peer-reviewed methods with full scientific citations.