High-Oil Soybean for More Efficient Energy Conversion to Soy-Based Biodiesel

The relatively low genomic variation of current U.S. soybean [Glycine max (L.) Merill] cultivars constrains the improvement of grain yield, seed quality, and other agronomic traits within soybean breeding programs. Recently, a substantial effort has been undertaken to introduce novel genetic diversity present in wild soybean (Glycine soja Siebold and Zucc.) into new elite cultivars, in both public and private applied soybean breeding programs. The objectives of this research were to evaluate the phenotypic diversity within a core collection of 80 G. soja plant introductions (PIs) in the United States Department of Agriculture National Genetic Resources Program that were collected in China, Japan, Russia, and South Korea, and to analyze the correlations between agronomic and seed composition traits. Field tests were conducted in Missouri and North Carolina during three years, 2013, 2014, and 2015, in a randomized complete block design (n=3). The phenotypic data collected included plant maturity date, seed weight, and the seed concentration of protein, oil, essential amino acid, fatty acid, and soluble carbohydrates. Analyzing the data from six environments, we found genotype was a significant (p less than 0.0001) source of variation for maturity date, seed weight, seed protein and amino acids, seed oil and fatty acids, and seed carbohydrates. Significant correlations were observed between numerous traits. The core collection had lower seed weight, higher seed content of protein, linolenic acid, raffinose and stachyose but lower seed content of oil and oleic acid than those of the cultivated soybean lines that were used as checks. The amino acid profile of the core collection was significantly different from that of the checks. An association analysis revealed 19 SNP that were significantly associated with maturity, seed weight, and seed contents of aspartic acid, glutamine, palmitic acid, oleic acid, and linoleic acid. The information and data collected in this study will be invaluable in guiding soybean breeders and geneticists in selecting promising Glycine soja plant introductions for research and cultivar improvement. In addition the identification of quantitative trait loci (QTLs) associated with the contents of seed protein and oil, maturity, branching traits, height, lodging, and yield in a recombinant inbred line (RIL) population developed from one single F2 plant from the cross between Osage and PI593983 was carried out. The mapping population in this study included 164 F4:6 recombinant inbred lines (RILs) derived from a cross between Osage, a cultivated soybean variety, and PI593983, a wild soybean accession. Field tests were carried out in Missouri for two years during 2016 and 2017, in a randomized complete block design (n=2). Both protein and oil contents showed high heritabilities. Seed protein and seed oil were negatively correlated (-0.77). A total of 4,374 polymorphic markers were used to construct a genetic linkage map, and nine QTLs for protein content, explained 7.6 to 36.7% of variance, and seven QTLs for oil content, explained for 7.8 to 29.7% of variance, were detected using composite interval mapping. addition we identified eight novel QTLs and confirmed sixteen QTLs associated with maturity (R2 = 6.4 to 26.3%), plant height (R2 = 7.4 to 15.5%), and total branch length (R2 = 9.3% and 14.5%) in individual and across environments, and the ratio of total branch length to plant height (R2 = 11.8%), yield (R2 =12.8 and 15.7), and lodging (R2 = 12.1 and 13.4) in individual studied environments. Sixteen QTLs for maturity, yield, and plant height confirmed previously reported QTLs, and eight QTLs have not been reported before. The results of this study will facilitate the identification of the causative genes for seed protein and oil, maturity, height, lodging, and branching traits, and will help soybean breeder improve soybean performance by developing markers for marker-assisted selection.

Peanut is a world-renowned oilseed and food crop. Improving its biochemical quality is of great significance not only for meeting the demand for edible oil and food, but also for producing clean renewable energy. Identification of peanut genotypes with high and stable oil content in coastal areas is of economic importance, as the high oil trait of peanut bred in inland areas is difficult to fully express in coastal areas. Two peanut genotypes were grown at two sites in the coastal area. One of the genotypes was identified as having high oil and low carbohydrate, while the other had low oil and high carbohydrate. We noticed that number and total area of oil bodies were higher in high oil peanut than in low oil peanut, and that peanut with higher protein content had larger total protein body area. A novel finding of the present study was that number and area of starch grains were higher in peanut with high total soluble sugar (TSS) and sucrose contents than in peanut with low TSS and sucrose. Regarding the ultrastructural properties associated with oil, protein and TSS/sucrose contents, significant and highly positive correlations were detected between total oil body area and number of oil bodies, between total protein area and maximum protein body area, and between total starch grain area and number of starch grains. This study laid the foundation for further exploration of the mechanisms shaping peanut seed biochemical quality.

Combined genome-wide association analysis and transcriptome sequencing to identify candidate genes for flax seed fatty acid metabolism

Soybean oil plays crucial roles in both food and biodiesel industries. Increasing oil content and improving the fatty acid composition are critical objectives in soybean breeding programs. In this study, we performed high-resolution QTL mapping for oil content and fatty acid composition using 192 F2:7−8 recombinant inbred lines (RILs) based on a high-density genetic map. We detected a total of 66 QTL, including 14 for oil content and 52 for individual fatty acids. Among these, seven QTL were stable across multiple environments, with qPA-05 and qLA-06 being novel loci for palmitic and linoleic acids, respectively. A total of 34 QTL were grouped into seven clusters. Through candidate gene mining for Cluster05-2 and qLNA-14 using single-locus ANOVA in 1025 soybean accessions, combined with gene expression profiling and annotation, we identified the MOTHER OF FT AND TFL1 (MFT) gene (Glyma.05G244100), the 2-acylglycerol O-acyltransferase (MGAT) gene (Glyma.05G248100), and three ubiquitination-related genes (Glyma.05g237500, Glyma.05G238500, and Glyma.05G238900) in Cluster05-2 as strong candidate genes for oil content, and the ω-3 fatty acid desaturase (FAD3A) gene (Glyma.14G194300) in qLNA-14 as strong candidate gene for linolenic acid. Haplotype analyses of these candidate genes revealed significant influence of specific haplotypes on oil and linolenic acid content, respectively. Notably, for MGAT, the frequency of the high-oil haplotype (Hap1-TA) exhibited a clear decreasing trend from north to south in China among the soybean accessions, which is consistent with the distribution trend of soybean oil content across China. The discovery of stable QTL and candidate genes associated with oil and fatty acid contents will enhance the efficiency of molecular breeding programs aimed at improving soybean quality.

ABSTRACTMacadamia nut butter is a value‐added product, promoting lower‐grade nuts to premium products. The commercial grade of macadamia nuts includes the kernel quality (i.e., maturity and oil content) and style (i.e., size). However, whether immature nuts are suitable for nut butter production remains under‐explored. The study aimed to determine the influence of macadamia nut qualities and styles on the sensory profile of macadamia nut butter. Individual butters from two high oil, mature qualities (Style 1, Style 8) and two low oil, immature qualities (Style 2, Style 4) were compared to a commercial control. Descriptive sensory analysis was performed with an experienced panel (n = 13), a combination of ballot and consensus training, and reference standards. A sensory lexicon of 40 descriptors was developed, where 35 attributes differed (p < 0.050) between treatments. Principal component analysis (70.42% explained variance) confirmed variability in the sensory profiles of commercial control batches. High oil, mature kernels produced more replicable butter quality. Low oil, immature kernels produced inconsistent quality butters, with higher association with positive attributes (e.g., nutty aroma/flavor), but also with off‐notes (e.g., fruity aroma/flavor). The results suggest that kernel quality (maturity and oil content), rather than style, has the greatest influence on the final sensory quality of nut butter. These findings provide practical guidance for manufacturers in the procurement of macadamia kernel grades for butter production and the implications on product sensory quality. Further investigation is needed to customize roasting and grinding times based on kernel quality, which may improve product consistency.

A study was undertaken on oil-protein content and their relation with yield and evaluation of resistance for aerial blight and frog eye leaf spot diseases in soybean during kharif (July−December, 2019) at J.N.K.V.V., Jabalpur, Madhya Pradesh, India. The experiment was laid out using augmented block design with 154 genotypes of soybean including four check varieties namely JS 20-34, JS 20-98, JS 335 and NRC 86. Per cent disease severity was measured at peak of disease during seed formation stage (R5-R6). Yield and 100 seed weight were recorded at time of harvesting. Oil and protein content from harvested yield was estimated by using standard methods of association of official analytical chemists (AOAC). The results revealed that oil content varied from 16.8−20.2% and protein content from 36.1−41.2% in all 154 genotypes. Per plant average seed yield (3.9-15.1 g) and hundred seed weight (6.7−14.7 g) were also varied from genotypes to genotypes. The correlation between oil and protein was highly negative (r=-0.620**, p=0.01). This investigation identified ten genotypes with high oil (&gt;20%) and fourteen genotypes with high protein (&gt;40%) content. Among which JS 20-104, Cat 473B and RKS 24 were higher in protein, and Cat 48, Cat 330 and JS 20−69 were higher in oil content. In disease evaluation, eleven genotypes namely Cat 473B, Cat 60, Cat 642, JS 20−76, JSM 122, JSM 126A, JSM 126B, JSM 203, JSM 287, RKS 66 and SQL 89 exhibited dual resistance for aerial blight as well as frog eye leaf spot were screened out. The result showed that variation in oil-protein content and disease resistance depends on the genotype.

Availability of adapted cultivars is needed for the development of soybean cultivation in upland soil in Lampung, Sumatra. Twelve advanced soybean breeding lines and two check varieties (Tanggamus and Wilis) were tested on upland soils of Lampung Province. The trials were conducted in the District of Tulangbawang, Central Lampung, East Lampung and South Lampung during the late rainy season of 2003/2004. Two sites were selected per district for a total of eight sites for the four districts. A split plot design with three replications was used within each location. Plot size was 2.4 m x 4.5 m, plant spacing of 40 cm between rows and 15 cm within a row, and two plants per hill. The mainplot was fertilizer: A= Low inputs (22.5 kg N, 27 kg P2O5, and 40 kg K2O per ha), and B=Medium inputs (22.5 kg N, 36 kg P2O5, 53 kg K2O and 0.56 t CaO per ha). The fertilizers were applied before planting. The subplots were 12 soybean breeding lines together with two check soybean varieties. Results showed that soybean yields were affected significantly by locations, fertilizers, breeding lines, location x fertilizer and location x breeding line interactions. Plant height was affected siginificantly by locations, fertilizers, breeding lines and location x breeding interaction. Pods per plant were affected by locations, fertilizers, location x fertilizer and location x breeding line interactions. All breeding lines and varieties were responsive to changing environments. Based on the smallest Pi parameter (the distance mean square between the cultivar’s response and the maximum response averaged over all locations), and the highest frequency of rank, three breeding lines, namely W3465-27-2 (released in 2004 as cv. Ratai), cv. Tanggamus and D3578- 3/K3911-66-3 were identified as wide adaptability genotypes with the yield potential of more than 2.4 t/ha with an average of 1.6 t/ha.

Factors affecting the bioconversion of Philippine tung seed by black soldier fly larvae for the production of protein and oil-rich biomass

Soybean [Glycine max (L.) Merr.] has been studied and enhanced for most of its economically important traits. Previous research has studied the association among them and the effect of the genotype × environment interaction; however, less is known about their correlation considering absolute maturity, as well as the use of multiple selection indices to study the genotype × environment interaction and select superior cultivars. Regarding this, the aim of the present study was to identify lines that associate precocity, good yield performance, and high oil and protein contents in the grains, as well as to estimate the correlation among these traits and study the effect of genotype × environment interaction using a standardized multiple selection index. Trials were conducted in two crop seasons in the state of Minas Gerais, Brazil, with 39 lines in 13 evaluation environments. The experiments were conducted in a randomized complete block design with four replications, and the grain yield, absolute maturity, and oil and protein contents in the grains were evaluated. The results indicated high experimental precision and accuracy, with significant differences among lines for all traits. High‐magnitude correlations between evaluated traits were found, highlighting the negative correlation between absolute maturity and protein content in the grains. The genotype × environment interaction was also significant, and the use of the multiple selection index was efficient to identify superior and stable inbred lines by the genotype + genotype × environment (GGE) biplot method, which explained 82.23% of the genotype × environment interaction effect. Lines 27 and 31 stood out from the others because they associated stability and good performance for all evaluated traits.

Soybean is the most important legumes crop and source of protein for Indonesia society. The aim of the research was to evaluate the morpho-chemical characters of soybean genotypes across environments. A total of 16 soybean genotypes were evaluated in four different agro-ecosystems from February to May 2015. The experiment at each agro-ecosystem was arranged in a randomized block design with 16 treatments and four replicates. . The result showed that the morpho-chemical characters of 16 genotypes were significantly affected by genotype by environment interaction. The average of protein contents in four locations were 39.30%, 38.76%, 39.06%, and 38.14%, respectively; and the oil contents were 19.52%, 19.66%, 19.15%, and 20.54%, respectively. There was an indication that a higher protein content resulted in a lower oil content. The highest protein content was GRRR-12-15 (39.96%), and followed by Anjasmoro (39.84%) and GA-1-4 (39.46%). Genotypes with high oil content were GAAA-6-3 (21.36%), GAA-5-1 (20.72%), and GRRRR-19-7 (20.38%). A drier agro-ecosystem affected to the decrease in protein content. Stability analysis of protein content showed that GA-1-6 as the most stable genotype, followed by Anjasmoro and GA-1-4. Meanwhile, the most stable genotype for its oil content was Grobogan, and followed by GAAA-6-3 and GA-1-6. The high yield productivities were showed by GAAA-6-7 (3.06 t/ha), GA-1-4-2 (2.91 t/ha), and GA-1-4 (2.82 t/ha). The two top yielding genotypes, GAAA-6-7 and GA-1-4, were showed specific adaption, hence they can be recommended to be developed at relatively dry environment to obtain high yield, protein and oil contents.

Groundnut is currently a major industrial oilseed crop with good commercial significance. 20 advanced Groundnut lines were planted in Randomized Complete Block Design along with parental lines and two checks and they were evaluated for 13 traits. The analysis of variance showed significant differences among all the traits studied. The genotypes were grouped into five clusters. Among the clusters, cluster I had 14 lines (PP-19, PP-12, PP-6, PP-13, PP-14, PP-11, PP-18, PP-20, PP-17, PP-5, PP-8, PP-10, PP-9, PP-4) followed by cluster II had one line (PP-2), cluster III had one line (PP-16) and cluster IV had one lines (PP-1) and cluster V had three lines (PP-7, PP-15, PP-3). Clusters II and V had the long stand best inter-cluster distance (635.60), followed by clusters II and III (367.54), clusters IV and V (304.12), clusters I and V (302.11) and clusters I and III (235.79) indicating that these cluster pairs were most divergent. The relative contribution of individual character towards the divergence revealed that Protein content (5098.81%), was the highest contributor to the total genetic divergence followed by Oil content (2055.34%) (7.35%) and pod yield per plant (1976.28%). Thus, on the basis of inter-cluster distance, cluster means, characters with high contribution to D2 values and by comparing the mean values of the all the genotypes, this study revealed that the genotypes, belong to the cluster II, V and III will be used for further breeding programme. In the present study, four lines viz., PP-1, PP-2, PP-5 and PP-14 developed through marker assisted backcross breeding programme showed resistance to late leaf spot, improved oil quality features like high oil and oleic acid content and were also superior or equivalent in yield compared with the recurrent parent, K6, further forward to yield evaluation trails and promising lines with LLS resistance and high yield will be released as superior variety/varieties.

Soybean Glycine max (L.) Merr. production trends have increased throughout the past century due to its versatile use in food, feed, and fuel industries. The selection of soybean cultivars with higher yields coupled with consumer-preferred seed quality has become a priority to sustain economic advantage. In this study, eighteen popular soybean cultivars from different maturity groups (MG III to V) were phenotyped for yield and quality traits under optimum water and nutrient conditions. Significant phenotypic variability was observed for days to flowering, yield, and seed quality traits. The late flowering soybean cultivars (MG V) recorded 14% lower seed weight than the early flowering (MG IV). Under optimum growing conditions, protein content increased with the MGs, but oil content decreased. Further, significant negative correlations between protein and yield, oil, and sucrose were observed. In contrast, the oil content was positively correlated with yield. Cultivars 539-T3 and GT-477CR2 were classified as high-yielding short-duration soybean cultivars. Based on the cultivar performance index, MS 4616 RXT and 7547XT were found to have a combination of desirable industry traits such as high protein, and oil content with high yield compared to other cultivars. The current research provides prospective benchmark seed weight and quality parameters under sunlit and temperature conditions with optimum water and nutrient conditions for many soybean cultivars grown in the US Mid-South. Furthermore, it can assist growers and breeders in selecting soybean cultivars with high protein and oil specific to their regional demand.

Soybean [Glycine max (L.) Merr.] is a valuable and nutritious crop in part due to the high protein meal and vegetable oil produced from its seed. Soybean producers desire cultivars with both elevated seed protein and oil concentrations as well as specific amino acid and fatty acid profiles. Numerous studies have identified quantitative trait loci (QTLs) associated with seed composition traits, but validation of these QTLs has rarely been carried out. In this study, we have collected information, including genetic location and additive effects, on each QTL for seed contents of protein and oil, as well as amino acid and fatty acid compositions from over 80 studies. Using BioMercator V. 4.2, a meta-QTL analysis was performed with genetic information comprised of 175 QTLs for protein, 205 QTLs for oil, 156 QTLs for amino acids, and 113 QTLs for fatty acids. A total of 55 meta-QTL for seed composition were detected on 6 out of 20 chromosomes. Meta-QTL possessed narrower confidence intervals than the original QTL and candidate genes were identified within each meta-QTL. These candidate genes elucidate potential natural genetic variation in genes contributing to protein and oil biosynthesis and accumulation, providing meaningful information to further soybean breeding programs.

Protein and sugar content are important seed quality traits in soybean because they improve the value and sustainability of soy food and feed products. Thus, identifying Quantitative Trait Loci (QTL) for soybean seed protein and sugar content can benefit plant breeders and the soybean market by accelerating the breeding process via marker-assisted selection. For this study, a population of recombinant inbred lines (RILs) was developed from a cross between R08-3221 (high protein and low sucrose) and R07-2000 (high sucrose and low protein). Phenotypic data for protein content were taken from the F2:4 and F2:5 generations. The DA7250 NIR analyzer and HPLC instruments were used to analyze total seed protein and sucrose content. Genotypic data were generated using analysis via the SoySNP6k chip. A total of four QTLs were identified in this study. Two QTLs for protein content were located on chromosomes 11 and 20, and two QTLs associated with sucrose content were located on chromosomes 14 and. 11, the latter of which co-localized with detected QTLs for protein, explaining 10% of the phenotypic variation for protein and sucrose content in soybean seed within the study population. Soybean breeding programs can use the results to improve soybean seed quality.

Divergent selection at ultra-low plant density for seed protein and oil content within soybean cultivars