Multi-Environment Evaluation of Soybean Variety Heike 88: Transgressive Segregation and Regional Adaptation in Northern China

Heike 88, a new soybean variety developed through strategic hybridization of Heijiao 08-1611 × Heihe 43 followed by pedigree selection, was evaluated across seven locations in Heilongjiang Province from 2019 to 2022. The variety demonstrated stable performance with a 10.3% average yield advantage over regional check varieties and mean yields of 3188 kg ha −1 . Principal component analysis revealed that genetic variation accounted for 43.4% and 32.6% of performance variance in the first two components, indicating successful transgressive segregation where the pure line exceeded both parental lines through complementary gene action. Performance relative to parental averages ranged from −20% to +40% across the temperature gradient, demonstrating strong genotype-environment interaction effects. Machine learning analysis identified year effect (13% importance), accumulated temperature (7.6% importance), and oil content (4% importance) as primary yield drivers. Complete resistance to soybean mosaic virous (SMV) and cyst nematode attack was observed across all locations, with excellent gray leaf spot resistance (grades 0–1) maintained under natural pathogen pressure. Seed quality parameters remained stable across environments, with protein content ranging from 41.69% to 42.25% and oil content from 19.74% to 20.13%, indicating minimal environmental effects on compositional traits. Yield stability improved progressively over the evaluation period, with the coefficient of variation decreasing from 18.7% in 2019 to 6.7% in 2022, while absolute yields increased from 2550 to 3200 kg ha −1 . These results demonstrate successful exploitation of transgressive segregation for regional adaptation through strategic parent selection and pedigree breeding, supporting commercial deployment in northern China’s challenging production environments while providing methodological guidance for future breeding programs targeting environmental specificity.