Optimizing the spatial distribution of plants under normal conditions of water and fertilizer is widely used by farmers to improve soybean yield. However, the relationship between soybean yield and spatial plant distribution in the field has not been well studied. This study examined the effect of planting density and plant distribution pattern on soybean plant growth, yield components, canopy light interception, and dry matter accumulation. We also analyzed the relationship between photosynthetic rate, dry matter accumulation, and yield under different planting densities and plant distribution. A two year field experiment was conducted during the 2018 and 2019 soybean planting seasons. Two planting densities (1.8 × 10⁵ and 2.7 × 10⁵ plants ha⁻¹) and two plant distribution patterns (uniform and non-uniform plant spacing) were tested. Higher planting density significantly increased the canopy light interception and dry matter accumulation during soybean growth, leading to increased soybean productivity. The seed yield of soybean under higher planting density was 22.8% higher than under normal planting density. Soybean planted under uniform spacing significantly reduced the differences plant-to-plant. Uniform plant spacing significantly increased the canopy light interception and dry matter accumulation of the soybean population. In addition, the coefficient of variation of seed weight per plant between individual plants under uniform plant distribution decreased by 71.5% compared with non-uniform plant distribution. Furthermore, uniform plant distribution increased soybean seed yield by 9.5% over non-uniform plant distribution. This study demonstrates that increasing planting density under uniform plant distribution can be useful to obtain higher seed yield without increasing other farm inputs.

Increasing planting density is one of the key management practices to enhance soybean yield. A 2-yr field experiment was conducted in 2018 and 2019 including six planting densities and two soybean cultivars to determine the effects of planting density on branch number and yield, and analyze the contribution of branches to yield. The yield of ZZXA12938 was 4389 kg ha⁻¹, which was significantly higher than that of ZH13 (+22.4%). In combination with planting year and cultivar, the soybean yield increased significantly by 16.2%, 31.4%, 41.4%, and 46.7% for every increase in density of 45,000 plants ha⁻¹. Yield will not increase when planting density exceeds 315,000 plants ha⁻¹. A correlation analysis showed that pod number per plant increased with the increased branch number, while pod number per unit area decreased; thus, soybean yield decreased. With the increase of branch number, the branch contribution to yield increased first, and then plateaued. ZH13 could produce a high yield under a lower planting density due to more branches, while ZZXA12938 had a higher yield potential under a higher planting density due to the smaller branch number and higher tolerance to close planting. Therefore, seed yield can be increased by selecting cultivars with a little branching capacity under moderately close planting.

Flowering time and maturity are among the most important adaptive traits in soybean (Glycine max (L.) Merill). Flowering Locus T (FT) family genes function as key flowering integrators, with flowering-promoting members GmFT2a/GmFT5a and flowering-inhibiting members GmFT4/GmFT1a antagonistically regulating vegetative and reproductive growth. However, to date, the relations between natural variations of FT family genes and the diversity of flowering time and maturity in soybean are not clear. Therefore, we conducted this study to discover natural variations in FT family genes in association with flowering time and maturity. Ten FT family genes, GmFT1a, GmFT1b, GmFT2a, GmFT2b, GmFT3a, GmFT3b, GmFT4, GmFT5a, GmFT5b and GmFT6, were cloned and sequenced in the 127 varieties evenly covering all 14 known maturity groups (MG0000-MGX). They were diversified at the genome sequence polymorphism level. GmFT3b and GmFT5b might have experienced breeding selection in the process of soybean domestication and breeding. Haplotype analysis showed that a total of 17 haplotypes had correlative relationships with flowering time and maturity among the 10 FT genes, namely, 1a-H3, 1b-H1, 1b-H6, 1b-H7, 2a-H1, 2a-H3, 2a-H4, 2a-H9, 2b-H3, 2b-H4, 2b-H6, 2b-H7, 3b-H4, 5a-H1, 5a-H2, 5a-H4 and 5b-H1. Based on the association analysis, 38 polymorphic sites had a significant association with flowering time at the level of p < 0.01. Some natural variations exist within the 10 FT family genes, which might be involved in soybean adaptation to different environments and have an influence on diverse flowering time and maturity. This study will facilitate the understanding of the roles of FTs in flowering and maturity.

Increasing soybean production and ensuring greater access to soybean protein and lipids is critical for global food security and human health. Seed size (i.e., seed weight) is one of the most important agronomic traits of soybean, which not only determines the seed yield, but can also affect the yield of protein and lipids. In China, farmers favor soybean cultivars with large seeds, which they believe produce more protein and lipids; however, experimental evidence supporting this belief is lacking. Therefore, we conducted field experiments from 2017 to 2020 at 35 locations across the Huang-Huai-Hai region (HHH) of China with 64 soybean cultivars. The seed yield, seed protein content, and seed lipids content of soybean, and their relationship with seed size were investigated. The highest seed yield (i.e., seed weight per unit area) was 2996.5 kg ha⁻¹ in the north of HHH. However, the highest seed protein content was found in the south of HHH (42.5%) for the higher temperature, which was significantly higher than that of the middle (41.7%) and north of HHH (40.2%). In contrast, the highest seed lipids content was 20.7% in the north of HHH. Temperature, which had a path coefficient on seed yield of 0.519, can promote soybean seed yield. The correlation analysis indicated that the selection of the large seed size cultivar did not increase seed yield, and even led to a reduction of seed yield under high-yield environmental conditions. The seed protein content of soybean was not increased in the cultivars with large seed sizes. In addition, under different levels of seed lipids content (20.30%), a significantly negative relationship was found between seed lipids content and hundred seed weight. Therefore, it is recommended that farmers choose to plant cultivars with smaller soybean seed sizes, so as to ensure high and stable soybean seed yield and obtain more vegetable protein and lipids per unit area.

Soybean is planted in a wide span of the world, and flowering and maturity time is an important trait determining soybean yield formation and adaptation. Maturity loci E1, E2, E3 and E4 were frequently reported as the most influential genetic loci for soybean flowering and maturity. To understand the allelic variation and assess the phenological traits of cultivars with different E allelic combinations in natural environments, 251 cultivars of maturity group (MG) I–V were field tested in 42 locations across four sub-regions in the Huang-Huai-Hai and Northwest region of China and genotyped with KASP markers for E1–E4 loci. The results indicated that mutant alleles were only found in the E1 and E2 locus, all of the cultivars carried functional alleles in the E3 and E4 loci in this area, with the frequency of mutant allele to be higher in early maturity groups (MGs) than late MGs. Among nine E allelic combinations in this area, one photoperiodic insensitive mutation in E2 loci (E1/e2-ns/E3-Ha/E4 and E1/e2-ns/E3-Mi/E4) made up the largest proportion (25.10 and 18.33%), while two photoperiodic insensitive mutations in both E1 and E2 loci (e1-as/e2-ns/E3-Ha/E4) (1.20%) occupied the lowest proportion in this panel. The major combinations of E locus for MGI, MGII and MG III in this area were E1/E2-dl/E3-Mi/E4, E1/e2-ns/E3-Mi/E4 and E1/e2-ns/E3-Ha/E4, respectively. Cultivars carrying e1-as/e2-ns/E3-Ha/E4 genotype flowered earliest (34 days) on average, 7.6 days earlier than the latest-flowering E haplotype (E1/e2-ns/E3-Ha/E4). This study provided an opportunity to detect the E allelic combinations in the Huang-Huai-Hai River Valley and the Northwest China, which would facilitate the improvement of soybean adaptation in the future.

Crop heat units (CHU) and ≥10 °C active accumulated temperature (≥10 °C AAT) are important indexes to quantify the effects of temperature on soybean development. The relative maturity group (RMG) is widely used in the classification of different soybean varieties. However, CHU and ≥10 °C AAT (AAT) were applied in Canada and northeastern China, respectively, and the relationships among CHU, AAT and RMG are poorly documented. The objective of this study is to analyze the conversion function among CHU, AAT and RMG based on two datasets. The first dataset was obtained to analyze the relationship between RMG and AAT in 395 varieties in Northeast China. The second dataset was obtained to calculate the relationship between CHU and AAT at 95 weather stations based on 30-year climatic data (1990–2019). The results showed that both relationships were significantly and positively correlated, and the R-square of these relationships were 0.90 and 0.98, respectively. The distribution of CHU or AAT in the Northeast is proposed. These results can be extensively used for predicting the CHU or AAT of soybean cultivars given the known RMG, thus determining the adaptation zone as well as the growth stage of agricultural practices and responses to heat accumulation. The conclusion of the current study is expected to be widely adopted by soybean regionalization and germplasm exchanges throughout the world.