Agronomic Traits In Soybean Research Articles

Integrating targeted genetic markers to genotyping-by-sequencing for an ultimate genotyping tool.

New selection methods, using trait-specific markers (marker-assisted selection (MAS)) and/or genome-wide markers (genomic selection (GS)), are becoming increasingly widespread in breeding programs. This new era requires innovative and cost-efficient solutions for genotyping. Reduction in sequencing cost has enhanced the use of high-throughput low-cost genotyping methods such as genotyping-by-sequencing (GBS) for genome-wide single-nucleotide polymorphism (SNP) profiling in large breeding populations. However, the major weakness of GBS methodologies is their inability to genotype targeted markers. Conversely, targeted methods, such as amplicon sequencing (AmpSeq), often face cost constraints, hindering genome-wide genotyping across a large cohort. Although GBS and AmpSeq data can be generated from the same sample, an efficient method to achieve this is lacking. In this study, we present the Genome-wide & Targeted Amplicon (GTA) genotyping platform, an innovative way to integrate multiplex targeted amplicons into the GBS library preparation to provide an all-in-one cost-effective genotyping solution to breeders and research communities. Custom primers were designed to target 23 and 36 high-value markers associated with key agronomical traits in soybean and barley, respectively. The resulting multiplex amplicons were compatible with the GBS library preparation enabling both GBS and targeted genotyping data to be produced efficiently and cost-effectively. To facilitate data analysis, we have introduced Fast-GBS.v3, a user-friendly bioinformatic pipeline that generates comprehensive outputs from data obtained following sequencing of GTA libraries. This high-throughput low-cost approach will greatly facilitate the application of DNA markers as it provides required markers for both MAS and GS in a single assay.

Identification of quantitative trait loci for lodging and related agronomic traits in soybean (Glycine max [L.] Merr.)

BackgroundLodging, a crucial agronomic trait linked to soybean yield, poses a significant challenge in soybean production. Nevertheless, there has been less research on soybean lodging compared to other important agronomic traits, hindering progress in breeding high-yield soybeans. Our goals were to investigate lodging, pinpoint quantitative trait loci (QTL) linked to lodging, and forecast potential candidate genes linked to this trait. To achieve this, we employed a recombinant inbred line (RIL) population derived from a cross between Guizao 1 and B13 (GB) across various environments.ResultsThe lodging score of the RIL population was found to be significantly positively correlated with flowering time, maturity time, plant height, number of main stem nodes, stem diameter, and internode length, with correlation coefficients ranging from 0.457 to 0.783. A total of 84 QTLs associated with soybean lodging and related traits were identified using the GB population. The contribution of phenotypic variance ranged from 1.26 to 66.87%, with LOD scores ranging from 2.52 to 69.22. Additionally, within these QTLs, a stable major QTL associated with lodging was newly discovered in the GB population. Out of the ten major QTLs associated with other related traits, nine of them were situated within the qLD-4-1 interval of the major lodging score locus, displaying phenotypic variations ranging from 12.10 to 66.87%. Specific alterations in gene expression were revealed through the analysis of resequencing data from the two parental lines, potentially indicating their significant roles in lodging. Subsequently, it was determined through qRT-PCR that four genes are likely to be the major genes controlling soybean lodging.ConclusionsThis study’s findings offer valuable insights into the genetic underpinnings of soybean lodging resistance traits. By comprehending the potential genetic factors associated with lodging, this research lays the groundwork for breeding high-yield soybeans with improved lodging resistance.

Use of Phenomics in the Selection of UAV-Based Vegetation Indices and Prediction of Agronomic Traits in Soybean Subjected to Flooding

Flooding is a frequent environmental stress that reduces soybean growth and grain yield in many producing areas in the world, such as the United States, Southeast Asia, and Southern Brazil. In these regions, soybean is frequently cultivated in lowland areas in crop rotation with rice, which provides numerous technical, economic, and environmental benefits. In this context, the identification of the most important spectral variables for the selection of more flooding-tolerant soybean genotypes is a primary demand within plant phenomics, with faster and more reliable results enabled using multispectral sensors mounted on unmanned aerial vehicles (UAVs). Accordingly, this research aimed to identify the optimal UAV-based multispectral vegetation indices for characterizing the response of soybean genotypes subjected to flooding and to test the best linear model fit in predicting tolerance scores, relative maturity group, biomass, and grain yield based on phenomics analysis. Forty-eight soybean cultivars were sown in two environments (flooded and non-flooded). Ground evaluations and UAV-image acquisition were conducted at 13, 38, and 69 days after flooding and at grain harvest, corresponding to the phenological stages V8, R1, R3, and R8, respectively. Data were subjected to variance component analysis and genetic parameters were estimated, with stepwise regression applied for each agronomic variable of interest. Our results showed that vegetation indices behave differently in their suitability for more tolerant genotype selection. Using this approach, phenomics analysis efficiently identified indices with high heritability, accuracy, and genetic variation (>80%), as observed for MSAVI, NDVI, OSAVI, SAVI, VEG, MGRVI, EVI2, NDRE, GRVI, BNDVI, and RGB index. Additionally, variables predicted based on estimated genetic data via phenomics had determination coefficients above 0.90, enabling the reduction in the number of important variables within the linear model.

Genome-wide association studies reveal novel QTLs for agronomic traits in soybean.

Soybean, as a globally significant crop, has garnered substantial attention due to its agricultural importance. The utilization of molecular approaches to enhance grain yield in soybean has gained popularity. In this study, we conducted a genome-wide association study (GWAS) using 156 Chinese soybean accessions over a two-year period. We employed the general linear model (GLM) and the mixed linear model (MLM) to analyze three agronomic traits: pod number, grain number, and grain weight. Our findings revealed significant associations between qgPNpP-98, qgGNpP-89 and qgHGW-85 QTLs and pod number, grain number, and grain weight, respectively. These QTLs were identified on chromosome 16, a region spanning 413171bp exhibited associations with all three traits. These QTL markers identified in this study hold potential for improving yield and agronomic traits through marker-assisted selection and genomic selection in breeding programs.

A multi-trait GWAS-based genetic association network controlling soybean architecture and seed traits.

Ideal plant architecture is essential for enhancing crop yields. Ideal soybean (Glycine max) architecture encompasses an appropriate plant height, increased node number, moderate seed weight, and compact architecture with smaller branch angles for growth under high-density planting. However, the functional genes regulating plant architecture are far not fully understood in soybean. In this study, we investigated the genetic basis of 12 agronomic traits in a panel of 496 soybean accessions with a wide geographical distribution in China. Analysis of phenotypic changes in 148 historical elite soybean varieties indicated that seed-related traits have mainly been improved over the past 60 years, with targeting plant architecture traits having the potential to further improve yields in future soybean breeding programs. In a genome-wide association study (GWAS) of 12 traits, we detected 169 significantly associated loci, of which 61 overlapped with previously reported loci and 108 new loci. By integrating the GWAS loci for different traits, we constructed a genetic association network and identified 90 loci that were associated with a single trait and 79 loci with pleiotropic effects. Of these 79 loci, 7 hub-nodes were strongly linked to at least three related agronomic traits. qHub_5, containing the previously characterized Determinate 1 (Dt1) locus, was associated not only with plant height and node number (as determined previously), but also with internode length and pod range. Furthermore, we identified qHub_7, which controls three branch angle-related traits; the candidate genes in this locus may be beneficial for breeding soybean with compact architecture. These findings provide insights into the genetic relationships among 12 important agronomic traits in soybean. In addition, these studies uncover valuable loci for further functional gene studies and will facilitate molecular design breeding of soybean architecture.

Study of the soybean varieties quantitative traits variability in the Central Non-Chernozem Earth Region conditions

In the experiments, the formation of the yield of new early-ripening soybean varieties Georgiy, Slavyanka and Snezhana under the conditions of the Central Non-Chernozem Region was studied and an assessment was made of the influence of hydrothermal conditions on the variability and conjugation of soybean agronomic traits. Field experiments were carried out in 2020-2022. at the Institute of Seed Production and Agrotechnologies, a branch of the FGBNU FNAC VIM (Ryazan region), located in the forest-steppe agro-climatic zone of the Non-Chernozem zone of the Russian Federation. The soil is dark gray forest, heavy loamy in granulometric composition, of medium fertility (humus content - 4.54%), with an average content of exchangeable potassium and mobile phosphorus. Through correlation analysis, a significant positive relationship was established between the duration of the growing season and the HTC (r = 0.916 + 0.09), with the average daily temperature in August (r = 0.896 + 0.04). The height of plants and the height of attachment of the lower bean in the varietal section changed to an average degree (V = 7.96-21.38%). The greatest variability over the years was noted for the number of beans (V=31.92%) and the weight of seeds per plant (V=38.03%). The weight of 1000 seeds changed the least during the years of the study (V = 8.54-13.38%). The yield of the studied varieties is directly related to the number of beans and seeds per plant, and has no significant relationship with the height of the plant. The results of the research were used in the development of varietal technologies for the cultivation of soybeans in the conditions of the Ryazan region.

Genetic diversity analysis in soybean (Glycine max L.)

Using Mahalanobis D2 Statistics, genetic diversity research was carried out on 321 different genotypes of Soybean (Glycine max L.) at All India Coordinated Research Project on Soybean, Vasantrao Naik Marathwada Krishi Vidyapeeth, Parbhani, Maharashtra. Total 321 genotypes were classified into ten clusters based on D2 values. Cluster II, cluster VII, cluster VI, cluster V and cluster IX had 74, 15, 9, 3 and 2 genotypes, respectively, whereas, cluster I had the maximum genotypes of 214. One genotype was present in clusters III, IV, VIII and X. Cluster VII (1230.69) had the greatest intra-cluster distance, followed by Cluster VI (1104.13), Cluster II (604.39), Cluster I (478.57), Cluster IX (209.08) and Cluster V (96.3). D2 Values across the clusters ranged from 128.81 to 15699.76.The maximum inter-cluster distance was noticed between cluster X and cluster III (15699.76); followed by cluster X and cluster V (15568.61); cluster X and cluster VI (12020.02) and cluster X and cluster I (11083.56). Plant height (37.1%), number of pod clusters/plant (28.83%), total number of pods/plant (21.48%) and number of nods/plant (5.95%) contributed the most to diversity. Genotypes included in Cluster X & Cluster III; Cluster X & Cluster V and Cluster X & Cluster VI were identified for diverse source in the hybridization programme for identification of desirable transgressive segregants for important Agronomic traits in soybean.

Progress and future impacts on genomic dissection of soybean domestication and improvement

Soybean (Glycine max [L.] Merr.) was domesticated from the wild annual progenitor Glycine soja (Sieb. & Zucc.) in the temperate zone of China. Through domestication and improvement, soybean agronomic traits and adaptability have been significantly altered. In this review, we discuss the ways in which genetic changes were selected in soybean to enable adaptation to diverse environmental conditions. Challenges and strategies are discussed for breeding new elite varieties from existing elite varieties. Finally, we propose a strategy to break the current genetic bottleneck in soybean breeding: de novo domestication, which utilizes the excellent genetic resources available in wild soybean and provides a feasible strategy for accelerating the soybean improvement process. Overall, this review serves as a guide to understand the genetic factors that have driven soybean domestication and improvement over thousands of years, promoting future generation of soybean cultivars that are optimized for high yield under stressful environmental conditions.

QTL mapping reveals key factors related to the isoflavone contents and agronomic traits of soybean (Glycine max)

BackgroundSoybean is a valuable source of edible protein and oil, as well as secondary metabolites that can be used in food products, cosmetics, and medicines. However, because soybean isoflavone content is a quantitative trait influenced by polygenes and environmental interactions, its genetic basis remains unclear.ResultsThis study was conducted to identify causal quantitative trait loci (QTLs) associated with soybean isoflavone contents. A mutant-based F2 population (190 individuals) was created by crossing the Korean cultivar Hwanggeum with low isoflavone contents (1,558 µg g−1) and the soybean mutant DB-088 with high isoflavone contents (6,393 µg g−1). A linkage map (3,049 cM) with an average chromosome length of 152 cM was constructed using the 180K AXIOM® SoyaSNP array. Thirteen QTLs related to agronomic traits were mapped to chromosomes 2, 3, 11, 13, 19, and 20, whereas 29 QTLs associated with isoflavone contents were mapped to chromosomes 1, 3, 8, 11, 14, 15, and 17. Notably, the qMGLI11, qMGNI11, qADZI11, and qTI11, which located Gm11_9877690 to Gm11_9955924 interval on chromosome 11, contributed to the high isoflavone contents and explained 11.9% to 20.1% of the phenotypic variation. This QTL region included four candidate genes, encoding β-glucosidases 13, 14, 17–1, and 17–2. We observed significant differences in the expression levels of these genes at various seed developmental stages. Candidate genes within the causal QTLs were functionally characterized based on enriched GO terms and KEGG pathways, as well as the results of a co-expression network analysis. A correlation analysis indicated that certain agronomic traits (e.g., days to flowering, days to maturity, and plant height) are positively correlated with isoflavone content.ConclusionsHerein, we reported that the major QTL associated with isoflavone contents was located in the interval from Gm11_9877690 to Gm11_9955924 (78 kb) on chromosome 11. Four β-glucosidase genes were identified that may be involved in high isoflavone contents of soybean DB-088. Thus, the mutant alleles from soybean DB-088 may be useful for marker-assisted selection in developing soybean lines with high isoflavone contents and superior agronomic traits.

Potential interaction of soybean-grass intercropping with residual nitrogen for a no-tillage system implementation

Combinations between crop intercropping and forage production in a no-tillage system are not well established for environments under low water retention and soil fertility conditions. Our study aimed to evaluate the potential interactions between soybean-grass intercropping with residual nitrogen in a no-tillage system. The experimental design was a randomized block with four replications in a subdivided plot scheme. The main plots in the summer season were: 1) soybean monoculture; 2) soybean - Aruana Guinea grass (Megathyrsus maximus cv. Aruana) intercropping, and 3) soybean - Congo grass (Urochloa ruziziensis cv. Comum) intercropping. The subplots were the nitrogen rates of 0, 50, 100, and 150 kg ha-1, applied as side-dressing in maize and grasses during the autumn-winter season. Here, the results of the summer seasons are shown. To do so, the parameters evaluated were soybean agronomic traits, dry biomass production, and macronutrient concentrations of plants intercropped. The main effects and interactions were studied. Our findings showed that soybean-Aruana Guinea grass intercropping is an alternative to no-tillage system implementation. Moreover, residual nitrogen from the autumn-winter season directly interfered with the dry biomass production of grasses intercropped with soybeans in the summer season. In short, the systems studied seem suitable for implementing a no-tillage system, which aims to neutralize degraded pastures and produce forage for ensilage. Despite the changes in macronutrient concentrations within the intercropping system and residual nitrogen, and among intercropped crops over the years, Congo grass intercropped with soybeans in the summer season showed great capacity for phosphorus, potassium, and magnesium cycling.

Genome-Wide Association Study for Agronomic Traits in Wild Soybean (Glycine soja)

The agronomic traits of soybean are important because they are directly or indirectly related to its yield. Cultivated soybean (Glycine max (L.) Merr) has lost genetic diversity during domestication and selective breeding. However, wild soybean (G. soja) represents a useful breeding material because it has a diverse gene pool. In this study, a total of 96,432 single-nucleotide polymorphisms (SNPs) across 203 wild soybean accessions from the 180K Axiom® Soya SNP array were employed in the association analysis. Wild soybean accessions were divided into four clusters based on their genetic distance using ADMIXTURE, principal component analysis, and neighbor-joining clusters. The linkage disequilibrium decayed rapidly in wild soybean. A genome-wide association study was conducted for days to flowering (DtF), days to maturity (DtM), the number of pods (NoP), and the 100-seed weight (100SW), which are major agronomic traits for wild soybean accessions. A total of 22 significant SNPs were found to be associated with DtF, DtM, and the 100SW. Based on the detected SNP markers, Glyma.12g210400, a gene related to DtF, Glyma.17g115300, a gene related to DtM, and Glyma.14g140200, a gene related to the 100SW, were selected as candidate genes. The SNP markers related to agronomic traits identified in this study are expected to help improve the quality of soybean cultivars through selective breeding.

ECONOMIC AND AGRONOMIC POSITIONING OF FUNGICIDES IN CONDITIONS OF WATER DEFICIT IN SOYBEAN CULTURES

<p><strong>Background. </strong>The management of diseases in soybean crops demands a great economic cost with fungicide applications. Therefore, unnecessary or excessive applications can promote negative environmental results. Therefore, understanding the weather conditions and the development of diseases in the crop is essential to avoid the unnecessary use of fungicides, consequently reducing costs and ensuring the sustainability of the activity. <strong>Aim.</strong> The aim is to identify which yield components are quantitatively affected, and which aspects of the chemical composition of the grains are qualitatively influenced by fungicide management, in addition to relating the cost-benefit rate of sequential applications or previously stipulated management in the soybean crop, as well as their economic effects under water deficit conditions. <strong>Methodology. </strong>The trial was carried out using a randomized block design composed of 4 replications. The trial consisted of 5 kinds of fungicide management, defined by the time and number of applications, during the development cycle of the Lança cultivar, in the 2019/2020 crop season. Soybean agronomic traits and nutritional attributes were evaluated. <strong>Results. </strong>Unfavorable climate conditions contributed to the low rate of Asian rust infection during the soybean development cycle. The different kinds of fungicide management influenced soybean performance for the main agronomic variables studied. For the chemical composition of the grains, there was no statistical difference in relation to the different kinds of fungicide management. <strong>Implications. </strong>The results indicate that the management of fungicides must be carried out according to the meteorological conditions of the year of cultivation. <strong>Conclusion.</strong> Management without fungicide application maximized grain yield and promoted the highest economic return.</p>

Identification and characterization of long-InDels through whole genome resequencing to facilitate fine-mapping of a QTL for plant height in soybean (Glycine max L. Merr.)

With the development of sequencing technology, insertions-deletions (InDels) have been increasingly reported to be involved in the genetic determination of agronomical traits. However, most studies have focused on the identification and application of short-InDels (1–15 bp) for genetic analysis. The objective of this study was to deeply deploy long-InDels (>15 bp) for the genetic analysis of important agronomic traits in soybean. A total of 13 573 polymorphic long-InDels were identified between parents Zhongpin 03-5373 (ZP) and Zhonghuang 13 (ZH), which were unevenly distributed on 20 chromosomes of soybean, varying from 321 in Chr11 to 1 246 in Chr18. Consistent with the distribution pattern of annotated genes, the average density of long-InDels in arm regions was significantly higher than that in pericentromeric regions at the P=0.01 level. A total of 2 704 (19.9% of total) long-InDels were located in genic regions, including 319 large-effect long-InDels, which resulted in truncated or elongated protein sequences. A previously identified QTL (qPH16) underlying plant height was further analyzed, and it was found that 26 out of 35 (74.3%) long-InDel markers located in the qPH16 region showed clear polymorphisms between parents ZP and ZH. Seven markers, including three long-InDels and four previously reported SNP markers, were used to genotype 242 recombinant inbred lines derived from ZP×ZH. As a result, the qPH16 locus was narrowed from a 960-kb region to a 477.55-kb region, containing 65 annotated genes. Therefore, these long-InDels are a complementary genetic resource of SNPs and short-InDels for plant height and can facilitate genetic studies and molecular assisted selection breeding in soybean.

Erratum to: Improvement of key agronomical traits in soybean through genomic prediction of superior crosses

Erratum to: Improvement of key agronomical traits in soybean through genomic prediction of superior crosses

Effects of Drought Stress on Key Enzymes of Carbon Metabolism, Photosynthetic Characteristics and Agronomic Traits of Soybean at the Flowering Stage under Different Soil Substrates

Soybean is an important legume food crop, and its seeds are rich in nutrients, providing humans and animals with edible oil and protein feed. However, soybean is sensitive to water requirements, and drought is an important factor limiting soybean yield and quality. This study used Heinong 84 (drought resistant variety) and Hefeng 46 (intermediate variety) as tested varieties planted in chernozem, albic, and black soils. The effects of drought stress on the activities of key enzymes in carbon metabolism and photosynthetic characteristics of soybean were studied during the flowering stage, most sensitive to water. (1) The activities of SS-1, 6PGDH, and G6PDH enzymes in soybean leaves first increased and then decreased under drought stress. The enzyme activity was the highest under moderate drought stress and weakest in the blank group. (2) Drought stress increased Phi2, PhiNO, and Fm in soybean leaves and reached the highest value under severe drought; with the increase in drought stress, PhiNPQ and Fv/Fm of soybean leaves gradually decreased, reaching the lowest under severe drought. (3) With the increase in drought stress, F0 and Fs of soybean leaves showed a single peak curve, and the maximum was at moderate drought. (4) Correlation analysis showed that F0 was greatly affected by varieties and soil types; Fs, F0, and Fm soil varieties had a great influence, and chlorophyll fluorescence parameters were affected differently under drought stress with different drought degrees. (5) Drought stress changed the agronomic traits and yield of soybean. With the increase of drought degree, plant height, node number of main stem, effective pod number, 100-seed weight and total yield decreased continuously. (6) Drought stress affected the dry matter accumulation of soybean. With the increase of drought degree, the dry matter accumulation gradually decreased. Among them, the leaf was most seriously affected by drought, and SD decreased by about 55% compared with CK. Under the condition of black soil, the dry matter accumulation of soybean was least affected by drought.

Características agronômicas de cultivares de soja com aplicação tardia de nitrogênio em suplementação à inoculação de Bradyrhizobium spp.

ABSTRACT Late season nitrogen (N) applications may serve as cultural practices to increase soybean yield and grain protein concentration in modern high-yielding cultivars. A study to evaluate the response of soybean cultivars to late N application in supplementation to Bradyrhizobium spp. inoculation was conducted in two Brazilian Cerrado agricultural soils with medium and high fertility during the 2019/2020 growing season. Treatments were arranged in a randomized block design in a 2×2×5 factorial scheme: two agricultural production environments [UFMS 1 (medium fertility) and UFMS 2 (high fertility)], two soybean cultivars (TMG 7067 IPRO and BMX Bônus IPRO), and five late N application rates (0, 50, 100, 150 and 200 kg N ha-1), with four replicates. Canonical correlation analysis (CCA) was used to investigate the interrelationships between the groups of independent (agricultural production environments, soybean cultivars, and N application rates) and dependent (soybean agronomic traits) variables. Nitrogen rates were applied in topdressing at the R5.3 soybean growth stage. Late N applications did not affect soybean agronomic traits (plant height, first pod height, pod number per plant, grain number per pod, and 1,000-grain mass) and did not increase the grain protein concentration or yield of the soybean cultivars, regardless of the fertility level of the agricultural area. We conclude that when efficient strains of Bradyrhizobium spp. are used in soybean cropping in medium- and high-fertility Cerrado soils, there is no need to apply late rates of N fertilizer.

What are the effects of irrigation rates and cropping systems on the soybean agronomic traits?

The irregularity and uneven distribution of rainfall may restrict the potential productive development of soybeans, causing numerous losses to farmers. The use of irrigation systems in hydrically heterogeneous areas are important measures that should be adopted during the crop cycle. Furthermore, the implementation of conservationist strategies, such as crop rotation or intercropping and no-till (NT) farming systems, can minimize the damage caused by water deficit. Therefore, the present study aimed to evaluate the soybean yield under different irrigation sheets and cropping systems in the extreme west of São Paulo. A completely randomized design was used, with 10 repetitions, in a subdivided plot scheme. The treatments were composed of different cropping systems in the plots, with four levels (conventional system; NT, using Urochloa brizantha cv Paiaguás; U. brizantha cv Piatã; and U. ruziziensis cv Ruziziensis), and different irrigation scheduling in the subplots, with three levels of irrigation scheduling (0%, 70% and 100%) based on reference evapotranspiration (ETo). Irrigation rates of 70% and 100% ETo in the conventional system provided higher grain yields under the climatic conditions in which the experiment was conducted. However, the continuity of long-term research is necessary, since NT is incipient, and have been implemented only two years ago. This is a relatively short period to observe the advantages of this cultivation system and for its consolidation process. Thus, the Brachiaria residual dry mass showed similar behavior in NT at the irrigation levels evaluated.

Improvement of key agronomical traits in soybean through genomic prediction of superior crosses

AbstractMaximizing yield is very important when developing new cultivars. However, yield must usually be improved jointly with other key traits, which can prove challenging when they are unfavorably correlated. Genomic predictions can facilitate the selection of promising lines among the progeny of crosses, but it may also help in selecting crosses that are more likely to produce improved lines by predicting progeny performance for the various key traits considered jointly. To assess whether genomic predictions of cross performance could help breeders simultaneously improve multiple traits, yield and maturity were predicted for 60,000 soybean [Glycine max (L.) Merr.] crosses. These predictions were then compared with the persistence of 101 biparental crosses throughout the selection process measured as the success in advancing progeny lines through to registration and commercialization. All but 2 of the 22 superior crosses retained by breeders had been predicted to display above‐average mean yield within different maturity windows. At the opposite end of the spectrum, 96.2% of all crosses predicted to produce progeny with a below‐average mean yield within a specific maturity window were eliminated during selection. Our results therefore suggest that by making crosses predicted to produce progeny meeting target requirements for multiple key traits, breeders could either achieve the same genetic gains with fewer resources or invest the same resources on a more promising set of crosses and thereby achieve greater gains.

Seed Longevity and Its Association with Agronomic Traits in Soybean [Glycine max (L.) Merrill

Background: Soybean is an important oilseed crop but it has poor seed longevity. Studies on seed longevity are very complex and hence, an indirect selection criterion should be identified. In this study, seed longevity and its association with agronomic traits of seven soybean varieties was evaluated in the year 2019-2020.Methods: Seed were kept for storage under ambient conditions for a period of 16 months (January 2019 to May 2020). Their germination was recorded at bimonthly intervals and seed longevity was inferred as the time period in months up to which the seed maintains its germination percentage above IMSCS.Result: Accordingly, Palam Early Soya 1 and Him Palam Hara Soya were classified as having short seed longevity (12 months). Hara Soya, Shivalik, Him Soya and Palam Soya were classified as having medium seed longevity (14 months). Whereas, PS 1556 was classified as having long seed longevity ( greater than 16 months). Further, it was found that seed longevity was positively associated with number of pods per plant and seed yield, and negatively associated with number of branches per plant and 100-seed weight. This study presents an indirect selection criterion based on some easily accessible parameters which have strong association with seed longevity.

Efficacy of Magnetic Water and Methanol on Agronomic Traits of Soybean (Glycine max L.)

Background: The major part of the edible oil used in Iran is supplied through imports. It is important to increase the yield of oilseed crops, especially soybeans, in non-chemical and environmentally friendly ways, along with its easy availability and low cost. The use of magnetic water as a new method, increases the yield of plants by improving solubility and access the nutrients. On the other hand, in recent years, methanol spraying as a source of carbon dioxide, which increases the concentration of this gas around the plant, enhancing the photosynthesis and plant yield. This study was conducted to study the efficacy of different intensities of magnetic water and various concentrations of methanol foliar application on agronomic traits of soybean. Methods: This experiment was carried out as split plot in a randomized complete block design with 3 replications during two consecutive years 2016-17. The main plot was irrigated with magnetic water in 4 intensity (0: control, 4, 8, 12mTesla) and a subplot was methanol spraying in 4 volumetric percentage (distilled water: control, 10, 20 and 30% v/v). Result: Photosynthetic pigments viz. (Chlorophyll a, b, carotenoid), yield attributes, seed yield, biological yield, seed protein and soybean economics were significantly affected by the magnetic water and methanol spraying. Seed yield and net return, as the most important traits increased by magnetic irrigated with 8 and 12mTesla intensities, compared to control, by 70.05-72.19% and 122.37-126.05%, respectively. Furthermore the maximum biological, stover yields and protein obtained by 8mTesla magnetic irrigation, compared to control, it showed 59.54, 54.9 and 10.07% superiority, respectively. Also, methanol foliar application at 20% concentration increased seed yield, biological yield, seed protein and net return by 19.01, 13.73, 5.24 and 26.43%, respectively.