Improving Quantitative Traits in Self-Pollinated Crops Using Simulation-Based Selection With Minimal Crossing

Genomic selection and marker-assisted recurrent selection have been applied to improve quantitative traits in many cross-pollinated crops. However, such selection is not feasible in self-pollinated crops owing to laborious crossing procedures. In this study, we developed a simulation-based selection strategy that makes use of a trait prediction model based on genomic information to predict the phenotype of the progeny for all possible crossing combinations. These predictions are then used to select the best cross combinations for the selection of the given trait. In our simulated experiment, using a biparental initial population with a heritability set to 0.3, 0.6, or 1.0 and the number of quantitative trait loci set to 30 or 100, the genetic gain of the proposed strategy was higher or equal to that of conventional recurrent selection method in the early selection cycles, although the number of cross combinations of the proposed strategy was considerably reduced in each cycle. Moreover, this strategy was demonstrated to increase or decrease seed protein content in soybean recombinant inbred lines using SNP markers. Information on 29 genomic regions associated with seed protein content was used to construct the prediction model and conduct simulation. After two selection cycles, the selected progeny had significantly higher or lower seed protein contents than those from the initial population. These results suggest that our strategy is effective in obtaining superior progeny over a short period with minimal crossing and has the potential to efficiently improve the target quantitative traits in self-pollinated crops.

Inter-Relationship between Seed Yield and Some Morphological and Biochemical Traits in Lentil (Lens culinaris L.)

Correlation Study with Path analysis was performed on 29 Lentil Genotypes to determine direct and indirect effect of some morphological as well as Biochemical parameters on Yield. Following traits were studied: Root Nodule number, Nodule weight, Primary Root Length, Secondary root numbers, Root Fresh and Dry weight, Plant Height, Pods per plant, Days to 50% Flowering, 100 seed weight, Leaf chlorophyll content, Seed Carbohydrate with Starch content, Seed Protein content and Yield. Considering both genetic Advance and GCV, it was observed that selection for the following characters viz. Plant Height, Pods per plant, Days to 50% flowering, 100 seed weight, Seed Protein content & Yield will be rewarding. Seed Yield per plant showed significantly Positive correlation with the following traits: 100 Seed weight, Pod number per plant, Plant height and seed starch. Negative association with yield was found for Days to 50% flowering. Path coefficient study revealed that there was a strong positive direct effect of 100 seed weight and Pod no. per plant along with Leaf Chlorophyll content on Yield. Hence, direct selection only for Pods number and 100 seed weight will be rewarding as these characters also gave higher heritability % along with high Genetic advance. Plant height gave strong negative direct effect on yield, but it gave a positive correlation due to high indirect effect in association with pod number. It may be due to short winter span of West Bengal which results into forced maturity of the crops. So short plants with higher pod numbers will be desirable for higher yield in short winter span condition.

Genetic mapping high protein content QTL from soybean ‘Nanxiadou 25’ and candidate gene analysis

Background Soybean is a globally important legume crop that provides a primary source of high-quality vegetable protein and oil. Seed protein content (SPC) is a valuable quality trait controlled by multiple genes in soybean. Results In this study, we performed quantitative trait loci (QTL) mapping, QTL-seq, and RNA sequencing (RNA-seq) to reveal the genes controlling protein content in the soybean by using the high protein content variety Nanxiadou 25. A total of 50 QTL for SPC distributed on 14 chromosomes except chromosomes 4, 12, 14, 17, 18, and 19 were identified by QTL mapping using 178 recombinant inbred lines (RILs). Among these QTL, the major QTL qSPC_20–1 and qSPC_20–2 on chromosome 20 were repeatedly detected across six tested environments, corresponding to the location of the major QTL detected using whole-genome sequencing-based QTL-seq. 329 candidate DEGs were obtained within the QTL region of qSPC_20–1 and qSPC_20–2 via gene expression profile analysis. Nine of which were associated with SPC, potentially representing candidate genes. Clone sequencing results showed that different single nucleotide polymorphisms (SNPs) and indels between high and low protein genotypes in Glyma.20G088000 and Glyma.16G066600 may be the cause of changes in this trait. Conclusions These results provide the basis for research on candidate genes and marker-assisted selection (MAS) in soybean breeding for seed protein content.

RESPONSE OF DIFFERENT PHOSPHORUS LEVELS AND APPLICATION METHODS ON THE GROWTH YIELD AND QUALITY OF LINSEED CROP

The effects of five phosphorus levels and two fertilizer application methods on the growth, yield and quality of linseed were evaluated at the Agronomic Research Area, University of Agriculture, Faisalabad. Linseed variety ‟Chandni” was grown under triplicate RCBD factorial design following two application methods of fertilizer, including side drilling and broadcast, with different doses of P2O5, i.e. 20, 40, 60, 80 and 100 kg ha-1,using DAP as a source in sub plots, with net plot size of 5 m × 1.8 m. The data was recorded for different traits and statistically analyzed which showed highly significant results with respect to side drilling method; while, parameters including time to start germination and time taken to 50% germination showed non-significant effect in regard of phosphorus application methods. Broadcasting method of application has showed statistically significant results for mean emergence time, plant population, plant height, number of branches per plant, number of seeds per capsule, seed yield and biological yield as well. Among different phosphorus levels, phosphorus applied @ 60 kgha-1 significantly affected maximum to start germination, mean emergence time, plant height, number of capsule per plant, number of seeds per capsule, biological yield and seed protein content; while, plant population, 1000-seed weight, seed oil content were significantly affected by the phosphorus applied @ 40 kgha-1. Among the interaction effect between application method and different phosphorus levels, phosphorus applied @ 60 kgha-1 through the method of side drilling significantly affected the time to start germination, mean emergence time, plant height, biological yield and seed protein content. It was concluded from our study that the application method of side drilling and level of phosphorus when applied @ 60 kgha-1 significantly affected on growth, yield and quality of linseed.

Soybean - New Fertilization Opportunities and Uses in the Food, Feed and Industry Sector

Soybean (Glycine max) is one of the most important species of the Fabaceae family worldwide, with many and varied uses, such as food, feed and industry sector. The aim of this study was to evaluate the effect of urea fertilizers in comparison with the new types of fertilizers on the agronomic and quality characteristics of soybean. A field experiment was carried out in the experimental field of the Agricultural University of Athens. The experiment was set up in Randomized Complete Block Design, with 4 treatments (control, 100 kg ha-1 urea, 100 kg ha-1 urea with urease and nitrification inhibitors and 75 kg urea with urease and nitrification inhibitors) and 3 replications. There were studied several plant agronomic characteristics such as plant height, leaf area index and seed yield, as well as the seed protein content. According to the results, the agronomic and quality characteristics were affected significantly by treatments. To sum up, soybean is a crop for which there is room in Greece for cultivation, for a variety of uses.

Meta-analysis of QTL reveals the genetic control of yield-related traits and seed protein content in pea

Pea is one of the most important grain legume crops in temperate regions worldwide. Improving pea yield is a critical breeding target. Nine inter-connected pea recombinant inbred line populations were evaluated in nine environments at INRAE Dijon, France and genotyped using the GenoPea 13.2 K SNP array. Each population has been evaluated in two to four environments. A multi-population Quantitative Trait Loci (QTL) analysis for seed weight per plant (SW), seed number per plant (SN), thousand seed weight (TSW) and seed protein content (SPC) was done. QTL were then projected on the multi-population consensus map and a meta-analysis of QTL was performed. This analysis identified 17 QTL for SW, 16 QTL for SN, 35 QTL for TSW and 21 QTL for SPC, shedding light on trait relationships. These QTL were resolved into 27 metaQTL. Some of them showed small confidence intervals of less than 2 cM encompassing less than one hundred underlying candidate genes. The precision of metaQTL and the potential candidate genes reported in this study enable their use for marker-assisted selection and provide a foundation towards map-based identification of causal polymorphisms.