The maturity date of soybean (Glycine max (L.) Merr.) is sensitive to photoperiod, which varies with latitude and growing seasons. The maturity group (MG) system, composed of 13 MGs, is a major approach in characterizing varieties’ ecological properties and adaptable areas. A total of 512 world soybean varieties, including 48 MG checks, were tested at a major site (Nanjing, 32.04°N) with portions tested in supplementary sites (Heihe, 50.22°N; Mudanjiang, 44.60°N; Jining, 35.38°N and Nanning, 22.84°N) in China to explore the world-wide MG distribution. The maturity date of the world soybean varied greatly (75–201 d) in Nanjing. Along with soybeans disseminated to new areas, the MGs further expanded during the last 70 years from MG I–VII to the early MG 0–000 in the north continents and to the late MG VIII–X in the south continents with the growth period structure differentiated into two subgroups in each MG 0–VIII except V. The cluster analysis among MGs and subgroups using genome-wide markers validated the MG sequential emergence order and the subgroup differentiation in eight MGs. For future evaluation, in addition to one major site (Nanjing), one supplementary southern site (Nanning) and one supplementary northern site (Heihe) are sufficient.

Yield evaluation of breeding lines is the key to successful release of cultivars, which is becoming a serious issue due to soil heterogeneity in enlarged field tests. This study aimed at establishing plot-yield prediction models using unmanned aerial vehicle (UAV)-based hyperspectral remote sensing for yield-selection in large-scale soybean breeding programs. Three sets of soybean breeding lines (1103 in total) were tested in blocks-in-replication experiments for plot yield and canopy spectral reflectance on 454~950 nm bands at different growth stages using a UAV-based hyperspectral spectrometer (Cubert UHD185 Firefly). The four elements for plot-yield prediction model construction were studied respectively and concluded as: the suitable reflectance-sampling unit-size in a plot was its 20%–80% central part; normalized difference vegetation index (NDVI) and ration vegetation index (RVI) were the best combination of vegetation indices; the initial seed-filling stage (R5) was the best for a single stage prediction, while another was the best combination for a two growth-stage prediction; and multi-variate linear regression was suitable for plot-yield prediction. In model establishment for each material-set, a random half was used for modelling and another half for verification. Twenty-one two growth-stage two vegetation-index prediction models were established and compared for their modelling coefficient of determination (RM2) and root mean square error of the model (RMSEM), verification RV2 and RMSEV, and their sum RS2 and RMSES. Integrated with the coincidence rate between the model predicted and the practical yield-selection results, the models, MA1-2, MA4-2 and MA6-2, with coincidence rates of 56.8%, 58.5% and 52.4%, respectively, were chosen for yield-prediction in yield-test nurseries. The established model construction elements and methods can be used as local models for pre-harvest yield-selection and post-harvest integrated yield-selection in advanced breeding nurseries as well as yield potential prediction in plant-derived-line nurseries. Furthermore, multiple models can be used jointly for plot-yield prediction in soybean breeding programs.

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Summary Soybean (Glycine max (L.) Merr.) has been disseminated globally as a photoperiod/temperature‐sensitive crop with extremely diverse days to flowering (DTF) and days to maturity (DTM) values. A population with 371 global varieties covering 13 geographic regions and 13 maturity groups (MGs) was analyzed for its DTF and DTM QTL‐allele constitution using restricted two‐stage multi‐locus genome‐wide association study (RTM‐GWAS). Genotypes with 20 701 genome‐wide SNPLDBs (single‐nucleotide polymorphism linkage disequilibrium blocks) containing 55 404 haplotypes were observed, and 52 DTF QTLs and 59 DTM QTLs (including 29 and 21 new ones) with 241 and 246 alleles (two to 13 per locus) were detected, explaining 84.8% and 74.4% of the phenotypic variance, respectively. The QTL‐allele matrix characterized with all QTL‐allele information of each variety in the global population was established and subsequently separated into geographic and MG set submatrices. Direct comparisons among them revealed that the genetic adaptation from the origin to geographic subpopulations was characterized by new allele/new locus emergence (mutation) but little allele exclusion (selection), while that from the primary MG set to emerged early and late MG sets was characterized by allele exclusion without allele emergence. The evolutionary changes involved mainly 72 DTF and 71 DTM alleles on 28 respective loci, 10–12 loci each with three to six alleles being most active. Further recombination potential for faster maturation (12–21 days) or slower maturation (14–56 days) supported allele convergence (recombination) as a constant genetic factor in addition to migration (inheritance). From the QTLs, 44 DTF and 36 DTM candidate genes were annotated and grouped respectively into nine biological processes, indicating multi‐functional DTF/DTM genes are involved in a complex gene network. In summary, we identified QTL‐alleles relatively thoroughly using RTM‐GWAS for direct matrix comparisons and subsequent analysis.

Soybean is a native crop in China for ≈ 5,000 years. The 560 cultivars released in 2006–2015, commercialized with seeds available publicly, were collected (designated modern Chinese soybean cultivars, MCSCs), as a part of 2,371 ones released during ~100 years' breeding history. The MCSCs with their parental pedigrees were gathered, including 279, 155, and 126 cultivars from Northeast and Northwest China (NNC), Huang-Huai-Hai Valleys (HHH), and Southern China (SC), respectively. The MCSCs were tested in the field, genotyped with sequencing, and analyzed for their germplasm sources, genetic richness, and population differentiation based on pedigree integrated with genomic-marker analysis. The main results were as follows: (i) The MCSCs covering 12 of the global 13 MGs (maturity groups) showing different ecoregions with different cropping systems caused their different MG constitutions. (ii) Parental pedigree analysis showed 718 immediate parents and 604 terminal ancestors involved in MCSCs, from which 41 core-terminal ancestors were identified. (iii) NNC was richer in allele number and specific present/deficient alleles, and genetically distant from HHH and SC. (iv) The geographic grouping of MCSCs was partially consistent with marker-based clustering, indicating multiple genetic backgrounds in three eco-subpopulations. (v) Eleven major core-terminal ancestor-derived families were identified, including four derived from ancestors in NNC, four from HHH, and three from SC, containing 463 (82.68%) MCSCs with some cross-distribution among ecoregions. (vi) CGS (coefficient of genetic similarity) calculated from genomic markers showed more precision than COP (coefficient of parentage) using pedigree information in evaluating genetic relationship/differentiation. Overall, through pedigree and genomic-marker analyses, the germplasm constitutions of the three eco-subpopulations were relatively self-sufficient, and germplasm exchange is seriously required for further improvement.