Deciphering the effect of different nitrogen doses on grain protein content, quality attributes and yield related traits of rice

Understanding the gravity of nutritional significance of rice (Oryza sativa L.) protein, an experiment conducted in Randomized Complete Block Design (RCBD) involving effect of nitrogen (N) rates i.e.,140 kg N/ha, 120 kg N/ha, 100 kg N/ha and 80 kg N/ha on grain protein content, yield parameters and cooking characteristics of polished rice from eight rice genotypes was conducted. N application significantly affected the grain protein content, grain yield, head rice recovery, plant height and effective tillers. In high protein cultivars substantially low to intermediate amylose content and more cooking time was recorded while in low protein counterpart amylose content was comparatively high with low cooking time. Maximum cooking time in polished rice was of 25 min at 180 kg N/ha dose and highest amylose content of about 27% at 80 kg N/ha. Gumminess and hardness of cooked rice and cooking time significantly elevated with increase in N dose. The substantial differences in grain protein content in brown, polished and cooked rice was observed. Cooking revealed the significant increase in protein content ranged from 50%-70% in low protein to high protein genotypes. R-RGM-ATN-47 with highest grain yield of 62.13 q/ha, grain protein content of 10.00 % in polished rice and intermediate amylose appears to be the most promising candidate.

Genomic Selection and Genome-Wide Association Studies for Grain Protein Content Stability in a Nested Association Mapping Population of Wheat

Grain protein content (GPC) is controlled by complex genetic systems and their interactions and is an important quality determinant for hard spring wheat as it has a positive effect on bread and pasta quality. GPC is variable among genotypes and strongly influenced by the environment. Thus, understanding the genetic control of wheat GPC and identifying genotypes with improved stability is an important breeding goal. The objectives of this research were to identify genetic backgrounds with less variation for GPC across environments and identify quantitative trait loci (QTLs) controlling the stability of GPC. A spring wheat nested association mapping (NAM) population of 650 recombinant inbred lines (RIL) derived from 26 diverse founder parents crossed to one common parent, ‘Berkut’, was phenotyped over three years of field trials (2014–2016). Genomic selection models were developed and compared based on predictions of GPC and GPC stability. After observing variable genetic control of GPC within the NAM population, seven RIL families displaying reduced marker-by-environment interaction were selected based on a stability index derived from a Finlay–Wilkinson regression. A genome-wide association study identified eighteen significant QTLs for GPC stability with a Bonferroni-adjusted p-value < 0.05 using four different models and out of these eighteen QTLs eight were identified by two or more GWAS models simultaneously. This study also demonstrated that genome-wide prediction of GPC with ridge regression best linear unbiased estimates reached up to r = 0.69. Genomic selection can be used to apply selection pressure for GPC and improve genetic gain for GPC.

Understanding G × E Interaction for Nutritional and Antinutritional Factors in a Diverse Panel of Vigna stipulacea (Lam.) Kuntz Germplasm Tested Over the Locations

Micronutrient malnutrition or hidden hunger is a serious challenge toward societal well-being. Vigna stipulacea (Lam.) Kuntz (known locally as Minni payaru), is an underutilized legume that has the potential to be a global food legume due to its rich nutrient profile. In the present study, 99 accessions of V. stipulacea were tested for iron (Fe), zinc (Zn), calcium (Ca), protein, and phytate concentrations over two locations for appraisal of stable nutrient-rich sources. Analysis of variance revealed significant effects of genotype for all the traits over both locations. Fe concentration ranged from 29.35–130.96 mg kg–1 whereas Zn concentration ranged from 19.44 to 74.20 mg kg–1 across both locations. The highest grain Ca concentration was 251.50 mg kg–1 whereas the highest grain protein concentration was recorded as 25.73%. In the case of grain phytate concentration, a genotype with the lowest value is desirable. IC622867 (G-99) was the lowest phytate containing accession at both locations. All the studied traits revealed highly significant genotypic variances and highly significant genotype × location interaction though less in magnitude than the genotypic variance. GGE Biplot analysis detected that, for grain Fe, Zn, and Ca concentration the ‘ideal’ genotypes were IC331457 (G-75), IC331610 (G-76), and IC553564 (G-60), respectively, whereas for grain protein concentration IC553521 (G-27) was the most “ideal type.” For phytate concentration, IC351407 (G-95) and IC550523 (G-99) were considered as ‘ideal’ and ‘desirable,’ respectively. Based on the desirability index, Location 1 (Kanpur) was identified as ideal for Fe, Zn, Ca, and phytate, and for grain protein concentration, Location 2 (New Delhi) was the ideal type. A significant positive correlation was detected between grain Fe as well as grain Zn and protein concentration considering the pooled analysis over both the locations where as a significant negative association was observed between phytate and protein concentration over the locations. This study has identified useful donors and enhanced our knowledge toward the development of biofortified Vigna cultivars. Promoting domestication of this nutrient-rich semi-domesticated, underutilized species will boost sustainable agriculture and will contribute toward alleviating hidden hunger.

TREND, POPULATION STRUCTURE AND TRAIT MAPPING FROM 15 YEARS OF NATIONAL VARIETAL TRIALS OF UK WINTER WHEAT

There are now a rich variety of genomic and genotypic resources available to wheat researchers and breeders. However, the generation of high-quality and field-relevant phenotyping data which is required to capture the complexities of gene x environment interactions remains a major bottleneck. Historical datasets from national variety performance trials (NVPT) provide sufficient dimensions, in terms of numbers of years and locations, to examine phenotypic trends and study gene x environment interactions. Using NVPT for winter wheat varieties grown in the UK between 2002 – 2017, we examined temporal trends for eight traits related to yield, adaptation, and grain quality performance. We show a non-stationary linear trend for yield, grain protein content, HFN and days to ripening. Our data also show high environmental stability for yield, grain protein content and specific weight in UK winter wheat varieties and high environmental sensitivity for Hagberg Falling Number. We also show that UK varieties released within this period cluster into four main population groups. Using the historical NVPT data in a genome-wide association analysis, we uncovered a significant marker-trait association peak on wheat chromosome 6A spanning the NAM-A1 gene that have been previously associated with early senescence. Together our results show the value of utilizing the data routinely collected during national variety evaluation process for examining breeding progress and the genetic architecture of important traits.

Current Status and Future Opportunities for Grain Protein Prediction Using On- and Off-Combine Sensors: A Synthesis-Analysis of the Literature

The spatial information about crop grain protein concentration (GPC) can be an important layer (i.e., a map that can be utilized in a geographic information system) with uses from nutrient management to grain marketing. Recently, on- and off-combine harvester sensors have been developed for creating spatial GPC layers. The quality of these GPC layers, as measured by the coefficient of determination (R2) and the root mean squared error (RMSE) of the relationship between measured and predicted GPC, is affected by different sensing characteristics. The objectives of this synthesis analysis were to (i) contrast GPC prediction R2 and RMSE for different sensor types (on-combine, off-combine proximal and remote); (ii) contrast and discuss the best spatial, temporal, and spectral resolutions and features, and the best statistical approach for off-combine sensors; and (iii) review current technology limitations and provide future directions for spatial GPC research and application. On-combine sensors were more accurate than remote sensors in predicting GPC, yet with similar precision. The most optimal conditions for creating reliable GPC predictions from off-combine sensors were sensing near anthesis using multiple spectral features that include the blue and green bands, and that are analyzed by complex statistical approaches. We discussed sensor choice in regard to previously identified uses of a GPC layer, and further proposed new uses with remote sensors including same season fertilizer management for increased GPC, and in advance segregated harvest planning related to field prioritization and farm infrastructure. Limitations of the GPC literature were identified and future directions for GPC research were proposed as (i) performing GPC predictive studies on a larger variety of crops and water regimes; (ii) reporting proper GPC ground-truth calibrations; (iii) conducting proper model training, validation, and testing; (iv) reporting model fit metrics that express greater concordance with the ideal predictive model; and (v) implementing and benchmarking one or more uses for a GPC layer.

Dissecting of the Deterioration in Eating Quality for Erect Panicle (Ep) Type High Yield Japonica Super Rice in Northest China

Ep type is an important morphological improvement (following dwarf breeding and ideal plant type) to adapt to super high yield breeding of rice, which shows a pleiotropic effect in increasing grain yield and nitrogen use efficiency (NUE) in rice. Nevertheless, it remains unclear whether Ep has adverse effects on eating quality and its regulatory of increasing nitrogen uptake and assimilation. In this study, we developed a pair of near-isogenic lines (NILs) of dep1 (NIL-Ep, NIL-Non Ep) in the Liaogeng 5 (LG5) and Akihikari (AKI) backgrounds. Here, we report that rice plants NIL-Ep have more grain numbers per panicle in middle to bottom spike positions than plants NIL-non Ep. This part of increased grain not only is the key factor to increase the yield, but also is the reason to reduce the eating quality. The content of prolamin and glutelin in the grain increased significantly, which resulted in higher hardness and worse viscosity of rice after cooking. Additionally, the activity of several essential enzymes catalyzing nitrogen metabolism is higher in the NIL-Ep line than in NIL-non Ep line, especially from the mid to late grain filling stage. Based on these results, we conclude that Ep positively regulates grain protein accumulation primarily through enhance the activity of enzyme enroll nitrogen assimilation and redistribution during the mid to late grain-filling stage, resulting in excessive accumulation of grain protein and decreased the quality of eating.