Nonoy Bandillo

Abstract Soybean [Glycine max (L.) Merr.] is a critical crop globally, valued for its protein and oil content. However, historical bottlenecks have constrained genetic diversity in soybean, particularly in high-latitude regions such as North Dakota, where environmental conditions necessitate maturity group (MG) 00 and 0 cultivars.

1 Introduction Drought limits soybean [Glycine max (L.) Merr.] productivity by affecting diverse processes during reproductive (Sinha et al., 2021) and vegetative growth, including photosynthesis and biological nitrogen fixation (Kunert et al., 2016; Martynenko et al., 2016; Zhu et al., 2016; Dubey et al., 2019).

Abstract The major drawback to the implementation of genomic selection in a breeding program is the reduction of additive genetic variance in the long term, primarily due to the Bulmer effect. Increasing genetic gain and retaining additive genetic variance requires optimizing the trade-off between the two competing factors. Our approach integrated index selection in the genomic infer cross-selection (GCS) methods.