The numbers game of soybean breeding in the United States

Abstract

Soybean [Glycine max (L.) Merr.] represents one of the most essential crops to the world's economy and food security due to its unique seed composition. Public soybean breeding programs in the United States played an important role in developing the genetic basis of American soybean and discovering many economically important traits. After the passage of the Plant Variety Protection Act (PVP) in 1970 and the authorization to patent living matter in 1980, private companies have dominated the market share of commercial soybean varieties and public breeding programs shifted the efforts towards basic and applied research and education of the next generation of plant breeders. The short history of soybean breeding combined with a very narrow genetic basis derived from few ancestors can only make us reflect on all the innovations yet to be unveiled and the multiple possibilities to explore the unique traits that the golden miracle bean offers.

Differential responses of soybean genotypes to off‐target dicamba damage

“…Interestingly, the percentage of scores 3 and 4 (sensitivity to off‐target dicamba) decreased over the years (16–9.2% and 42.3–20%, respectively), whereas in the same period, scores 1 and 2 (tolerance to off‐target dicamba) increased 18–22% and 23.6–48.7%, respectively. This may be attributed to an indirect selection of genotypes with higher tolerance to off‐target dicamba damage throughout the breeding pipeline (progeny row stage, preliminary yield trial, and advanced yield trial) based on yield and overall favorable agronomic traits in environments under prolonged exposure to dicamba (Vieira & Chen, 2021). Indirect selection has been reported in soybean for multiple traits and breeding objectives, including seed size (LeRoy et al., 1991) and weight (Bravo et al., 1980), maturity‐based adaptation (Board et al., 1997), weed suppressive ability (Jannink et al., 2000), and yield performance (Board et al., 2003; Kahlon et al., 2011).…”

Incorporation of Soil-Derived Covariates in Progeny Testing and Line Selection to Enhance Genomic Prediction Accuracy in Soybean Breeding

“…Over the last two decades (2001/2002 to 2021/2022), soybean production has nearly doubled from 182,830 to 363,860 MT ( United States Department of Agriculture, 2002 ; United States Department of Agriculture, 2022 ). The substantial increase in soybean production can be attributed to advances in agronomical practices ( Specht et al, 1999 ; Mourtzinis et al, 2018 ), faster implementation of novel technologies in farming operations ( Liu et al, 2008 ; Ainsworth et al, 2012 ; Vieira and Chen, 2021 ), and the development of improved soybean cultivars ( Salado-Navarro et al, 1993 ; Voldeng et al, 1997 ; Specht et al, 1999 ; Specht and Williams, 2015 ; Vieira and Chen, 2021 ), of which the availability of high dimensional genomic ( Song et al, 2013 , 2020 ) and phenomic data ( Moreira et al, 2019 , 2020 ; Parmley et al, 2019 ; Zhou et al, 2022 ), as well as the integration of environmental covariates (ECs) through predictive analytics, have contributed to accelerated genetic gains ( Jarquin et al, 2014a ; Jarquin et al, 2014b ; Persa et al, 2020 ; Widener et al, 2021 ).…”

Improve Soybean Variety Selection Accuracy Using UAV-Based High-Throughput Phenotyping Technology

“…Conventional breeding programs still primarily make selection decisions through phenotypic observations that are time-consuming, labor-intensive, and subjective to the experience of breeders (Araus et al, 2018 ). For example, the development of a new soybean cultivar can take up to 8 years, given the many phases of crossing, selection, and field trials in multiple environments (Ahmar et al, 2020 ; Vieira et al, 2021 ). Genetic gains can be increased by enhancing selection intensity, shortening the breeding cycle, ensuring suitable genetic variation in the population, and obtaining accurate estimates of the genetic values (Xu et al, 2017 ; Araus et al, 2018 ; Moreira et al, 2019 ).…”