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Durum wheat is mainly used for products for human consumption, the quality of which depends on the content of protein and yellow pigments in the semolina. The challenges faced by modern breeding, related to population growth and climate change, imply improvement of both grain yields and quality in durum wheat germplasm well adapted to specific agro-climatic conditions. To address those challenges, a better understanding of the genetic architecture of agronomic and quality traits is needed. In the current study we used the Genome-Wide Association Study (GWAS) approach in a panel of Bulgarian and foreign genotypes to define loci controlling agronomic and quality traits in durum wheat. We mapped 26 marker traits associations (MTAs) for four of the six studied traits—grain yield, grain protein content, seed yellow colour (CIELAB b*), and plant height. The greatest number of MTAs was detected for grain yield. Seven MTAs were detected for each grain protein content and seed colour, and one MTA for plant height. Most of the reported associations had confidence intervals overlapping with already reported quantitative trait loci (QTLs). Two loci controlling grain yield were not reported previously. The MTAs reported here may be a valuable tool in future breeding for improvement of both grain yield and quality in durum wheat. [ABSTRACT FROM AUTHOR]

Breeding wheat cultivars with high nitrogen use efficiency is crucial for sustainable agriculture. In this study, 130 durum wheat accessions from 53 countries were cultivated under two nitrogen fertilization levels to investigate variations in agronomic traits and identify accessions suitable for low-nitrogen conditions. Under no nitrogen fertilization, SPAD value (-99.2), flag leaf length (−15.8 mm), grain area (−0.52 mm² ), grain length (−0.27 mm), thousand-grain weight (+5.2 g), and grain protein content (−4.2%) showed significant differences compared to that under standard nitrogen fertilization. Among these traits, the SPAD value exhibited a strong positive correlation with protein content in the absence of nitrogen fertilization, suggesting its potential as an indicator for selecting germplasm with superior nitrogen use efficiency. Hierarchical cluster analysis, based on the differences in the six traits under the two nitrogen fertilization levels, classified the 130 durum wheat accessions into three groups (Groups 1, 2, and 3). Accessions in Group 2 exhibited superior adaptability under no nitrogen fertilization compared with those in the other two groups. We identified seven accessions in Group 2 that exhibited minimal decreases in SPAD values and protein content under no nitrogen fertilization for use in wheat breeding programs aimed at developing cultivars with high nitrogen use efficiencies. [ABSTRACT FROM AUTHOR]

Societal Impact Statement: Increasing crop productivity is often proposed as a key goal for meeting the food security demands of a growing global population. However, achieving high crop yields alone without meeting end‐use quality requirements is counter to this objective and can lead to negative environmental and sustainability issues. High yielding feed wheat crops in the United Kingdom are a typical example of this. The historical context of UK agricultural industrialisation, developments in plant breeding and wheat end‐use processing are examined. We then outline how employing innovations in plant breeding methods offer the potential to redress the balance between wheat quantity and quality. Summary: Bread wheat (Triticum aestivum L.) has historically been an important crop for many human civilisations. Today, variability in wheat supply and trade has a large influence on global economies and food security. The United Kingdom is an example of an industrialised country that achieves high wheat yields through intensive cropping systems and a favourable climate. However, only a minority of the wheat grain produced is of suitable end‐use quality for modern bread baking methods and most wheat produced is fed to livestock. A large agricultural land area and input use dedicated to producing grain for animal rather than human food has wide‐ranging negative impacts for environmental sustainability and domestic food production. Here we present an historical perspective of agricultural and economic changes that have resulted in UK production primarily focussing on wheat quantity over quality. Agricultural intensification, liberalisation of free trade in agricultural commodities, innovations in the milling and baking sector, developments in scientific understanding of genetics and plant breeding, and geopolitical changes have all played a role. We propose that wheat breeding plays a crucial role in influencing these issues and although wheat breeders in the United Kingdom have historically applied the most‐up‐to‐date scientific advances, recent advances in genomics tools and quantitative genetics present a unique opportunity for breeders to redress the balance between quantity and quality. [ABSTRACT FROM AUTHOR]

The present study was undertaken to investigate the genetic parameters of yield component and quality traits of the F3 population from BPT 5204 and JAK-686 cross in rice. High heritability and high genetic advance as a percentage of the mean were recorded for productive tillers per plant, grains per panicle, panicle length and grain yield per plant indicating the effectiveness of direct phenotypic selection for improvement of these traits. For traits such as grains per panicle, 1000 grain weight, amylose content and grain protein content, the magnitude of additive (d) effects surpassed dominance (h) gene effects. This implies that phenotypic selection using methods like pureline selection, mass selection would be beneficial. Gel consistency exhibited complimentary gene interaction. Furthermore, duplicate gene interaction was prevalent in traits like days to 50% flowering, productive tillers per plant, plant height, panicle length, grain yield per plant, kernel length, kernel breadth, and kernel L/B ratio, making selection in later generations more effective. The inheritance studies highlighted the importance of selecting desired recombinants from the segregating population to enhance rice quality as well as grain yield.

Societal Impact Statement Increasing crop productivity is often proposed as a key goal for meeting the food security demands of a growing global population. However, achieving high crop yields alone without meeting end‐use quality requirements is counter to this objective and can lead to negative environmental and sustainability issues. High yielding feed wheat crops in the United Kingdom are a typical example of this. The historical context of UK agricultural industrialisation, developments in plant breeding and wheat end‐use processing are examined. We then outline how employing innovations in plant breeding methods offer the potential to redress the balance between wheat quantity and quality. Summary Bread wheat (Triticum aestivum L.) has historically been an important crop for many human civilisations. Today, variability in wheat supply and trade has a large influence on global economies and food security. The United Kingdom is an example of an industrialised country that achieves high wheat yields through intensive cropping systems and a favourable climate. However, only a minority of the wheat grain produced is of suitable end‐use quality for modern bread baking methods and most wheat produced is fed to livestock. A large agricultural land area and input use dedicated to producing grain for animal rather than human food has wide‐ranging negative impacts for environmental sustainability and domestic food production. Here we present an historical perspective of agricultural and economic changes that have resulted in UK production primarily focussing on wheat quantity over quality. Agricultural intensification, liberalisation of free trade in agricultural commodities, innovations in the milling and baking sector, developments in scientific understanding of genetics and plant breeding, and geopolitical changes have all played a role. We propose that wheat breeding plays a crucial role in influencing these issues and although wheat breeders in the United Kingdom have historically applied the most‐up‐to‐date scientific advances, recent advances in genomics tools and quantitative genetics present a unique opportunity for breeders to redress the balance between quantity and quality.

Premium-tasty japonica rice, distinguished by its unique flavor and enriched nutritional value, has attracted significant attention across Asia. Nitrogen metabolism plays a crucial role in determining the growth, development, and quality of rice grains. This study investigates the effects of nitrogen application rates on the enzymatic activities related to nitrogen metabolism, nitrogen metabolites, and grain protein content in the premium-tasty japonica rice variety, Suxiangjing 100. Using a range of nitrogen application rates (0, 80, 160, 240, 320, and 400 kg per hectare), comprehensive analyses were conducted across various developmental stages. Results indicate that as nitrogen application increased, there were distinct patterns in the enzyme activities and metabolite concentrations related to nitrogen metabolism in the leaves of premium-tasty japonica rice. The activities of nitrate reductase (NR), glutamine synthetase (GS), and glutamate synthase (GOGAT) peaked at moderate nitrogen applications, while excessive nitrogen led to a decrease in their activities. The activity of Glutamate Dehydrogenase (GDH) generally increased, but showed a decline after the filling stage. With increasing nitrogen application, the concentrations of nitrate nitrogen (NO3–N), ammonium nitrogen (NH4–N), free amino acids (FAA), and soluble proteins (SP) initially rose but declined at excessive application rates. The grain protein content increased, with levels of prolamin, glutelin, and globulin peaking at nitrogen applications of 240 kg/ha and 320 kg/ha, while changes in albumin levels were minimal. This study not only provides novel insights into the role of nitrogen in shaping the growth and quality of premium-tasty japonica rice, but also suggests refined nitrogen management strategies for sustainable agricultural practices. [ABSTRACT FROM AUTHOR]

The grain protein content (GPC) is the key parameter for wheat grain nutritional quality. This study conducted a resampling GWAS analysis using 406 wheat accessions across eight environments, and identified four previously reported GPC QTLs. An analysis of 87 landraces and 259 modern cultivars revealed the loss of superior GPC haplotypes, especially in Chinese cultivars. These haplotypes were preferentially adopted in different agroecological zones and had broad effects on wheat yield and agronomic traits. Most GPC QTLs did not significantly reduce yield, suggesting that high GPC can be achieved without a yield penalty. The results of this study provide a reference for future GPC breeding in wheat using the four identified QTLs.

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A field experiment was conducted to evaluate the effect of the salinity stress on plants physical and grain yields attribute, also changes at proteomic level in grains of different stages were investigated. Six contrasting wheat genotypes, salt-tolerant (Kharchia-65, KRL-19, KRL-99, KRL-213), and salt-susceptible (HD-2329, PBW-373) were selected and exposed to four salinity levels (control, 100-, 200-, and 300-mM NaCl). Significant changes were observed in 1000 kernel weight, spike length, and the number of seeds per spike, while changes in plant height were negligible. The kernel weight of the wheat cultivar 'Kharchia-65' showed a minimum reduction (7%) when subjected to salt stress of 300 mM compared with the control, followed by 'KRL-213' (8%), 'KRL-99' (9%), 'KRL-19' (16%), and 'PBW-373' (32%), and HD-2329 showed maximum reduction (36%). The protein content was increased significantly in stressed plants than control plants, and in HD-2329, protein content was 10.07 ± 0.01% in control which increased to 13.46 ± 0.02% at 300-mM NaCl. It was observed that stress has more effect on susceptible lines than the tolerant lines. Seed protein fractionation was done, and the percent composition of albumin–globulin, gliadin, and glutenin was calculated during seed developmental stages. An increasing pattern of gliadin and the gli–glu ratio (1.01 in control to 2.99 in stressed condition in PBW-343) was observed in all the genotypes with increasing salt stress-induced conditions. The changes in polypeptide pattern were also analyzed for gliadin and glutenins using 1D SDS-PAGE under reducing conditions, and it was concluded that as stress conditions increases, it negatively affects the wheat cultivars. [ABSTRACT FROM AUTHOR]

Genetic enhancement of grain production and quality is a priority in wheat breeding projects. In this study, we assessed two key agronomic traits—grain protein content (GPC) and thousand kernel weight (TKW)—across 179 Bulgarian contemporary and historic varieties and landraces across three growing seasons. Significant phenotypic variation existed for both traits among genotypes and seasons, and no discernible difference was evident between the old and modern accessions. To understand the genetic basis of the traits, we conducted a genome-wide association study with MLM using phenotypic data from the crop seasons, best linear unbiased estimators, and genotypic data from the 25K Infinium iSelect array. As a result, we detected 16 quantitative trait nucleotides (QTNs) associated with GPC and 15 associated with TKW, all of which passed the false discovery rate threshold. Seven loci favorably influenced GPC, resulting in an increase of 1.4% to 8.1%, while four loci had a positive impact on TKW with increases ranging from 1.9% to 8.4%. While some loci confirmed previously published associations, four QTNs linked to GPC on chromosomes 2A, 7A, and 7B, as well as two QTNs related to TKW on chromosomes 1B and 6A, may represent novel associations. Annotations for proteins involved in the senescence-associated nutrient remobilization and in the following buildup of resources required for seed germination have been found for selected putative candidate genes. These include genes coding for storage proteins, cysteine proteases, cellulose-synthase, alpha-amylase, transcriptional regulators, and F-box and RWP-RK family proteins. Our findings highlight promising genomic regions for targeted breeding programs aimed at improving grain yield and protein content. [ABSTRACT FROM AUTHOR]

Salinity is an environmental stress that severely impacts rice grain yield and quality. However, limited information is available on the molecular mechanism by which salinity reduces grain quality. In this study, we investigated the milling, appearance, eating and cooking, and nutritional quality among three japonica rice cultivars grown either under moderate salinity with an electrical conductivity of 4 dS/m or under non-saline conditions in a paddy field in Dongying, Shandong, China. Moderate salinity affected rice appearance quality predominantly by increasing chalkiness rate and chalkiness degree and affected rice eating and cooking and nutritional quality predominantly by decreasing amylose content and increasing protein content. We compared the expression levels of genes determining grain chalkiness, amylose content, and protein content in developing seeds (0, 5, 10, 15, and 20 days after flowering) of plants grown under saline or non-saline conditions. The chalkiness-related gene Chalk5 was up-regulated and WHITE-CORE RATE 1 was repressed. The genes Nuclear factor Y and Wx, which determine amylose content, were downregulated, while protein-content-associated genes OsAAP6 and OsGluA2 were upregulated by salinity in the developing seeds. These findings suggest some target genes that may be utilized to improve the grain quality under salinity stress conditions via gene-pyramiding breeding approaches. [ABSTRACT FROM AUTHOR]

To predict the grain protein content of foxtail millet in a timely, effective, and rapid manner, the study used the net photosynthetic rate of leaves as an intermediate parameter. By using hyperspectral reflectance-net photosynthetic rate of leaves-grain protein content and using the 2020 potted plant experiment data, hyperspectral data and its first derivative (1ST) data with different photoperiod treatments, the models were constructed using machine learning algorithms (SVM, PLS and BP) based on net photosynthetic rate. The results revealed that the accuracy of the SVM model was better than that of the PLS model and BP model, and the SVM model based on the first derivative (1ST) spectral reflectivity was better than the original spectral (R) reflectivity, the R2, RMSE, RPD of the modeling set and validation set were 0.988, 0.732, 0.823, 4.061, 8.697, 1.810, respectively The correlation coefficient between net photosynthetic rate and grain protein content was 0.872 and R2 was 0.719 at 10 days after anthesis. The SVM model can be used to accurately monitor the grain protein content of foxtail millet, and provide technical support for hyperspectral techniques in high-yield cultivation and Intensive farming of foxtail millet. [ABSTRACT FROM AUTHOR]

Durum wheat is mainly used for products for human consumption, the quality of which depends on the content of protein and yellow pigments in the semolina. The challenges faced by modern breeding, related to population growth and climate change, imply improvement of both grain yields and quality in durum wheat germplasm well adapted to specific agro-climatic conditions. To address those challenges, a better understanding of the genetic architecture of agronomic and quality traits is needed. In the current study we used the Genome-Wide Association Study (GWAS) approach in a panel of Bulgarian and foreign genotypes to define loci controlling agronomic and quality traits in durum wheat. We mapped 26 marker traits associations (MTAs) for four of the six studied traits—grain yield, grain protein content, seed yellow colour (CIELAB b*), and plant height. The greatest number of MTAs was detected for grain yield. Seven MTAs were detected for each grain protein content and seed colour, and one MTA for plant height. Most of the reported associations had confidence intervals overlapping with already reported quantitative trait loci (QTLs). Two loci controlling grain yield were not reported previously. The MTAs reported here may be a valuable tool in future breeding for improvement of both grain yield and quality in durum wheat.

Yield and quality are two crucial breeding objects of wheat therein grain weight and grain protein content (GPC) are two key relevant factors correspondingly. Investigations of their genetic mechanisms represent special significance for breeding. In this study, 199 F2 plants and corresponding F2:3 families derived from Nongda3753 (ND3753) and its EMS-generated mutant 564 (M564) were used to investigate the genetic basis of larger grain and higher GPC of M564. QTL analysis identified a total of 33 environmentally stable QTLs related to thousand grain weight (TGW), grain area (GA), grain circle (GC), grain length (GL), grain width (GW), and GPC on chromosomes 1B, 2A, 2B, 4D, 6B, and 7D, respectively, among which QGw.cau-6B.1, QTgw.cau-6B.1, QGa.cau-6B.1, and QGc.cau-6B.1 shared overlap confidence interval on chromosome 6B. This interval contained the TaGW2 gene playing the same role as the QTLs, so TaGW2-6B was cloned and sequenced. Sequence alignment revealed two G/A SNPs between two parents, among which the SNP in the seventh exon led to a premature termination in M564. A KASP marker was developed based on the SNP, and single-marker analysis on biparental populations showed that the mutant allele could significantly increase GW and TGW, but had no effect on GPC. Distribution detection of the mutant allele through KASP marker genotyping and sequence alignment against databases ascertained that no materials harbored this allele within natural populations. This allele was subsequently introduced into three different varieties through molecular marker-assisted backcrossing, and it was revealed that the allele had a significant effect on simultaneously increasing GW, TGW, and even GPC in all of three backgrounds. Summing up the above, it could be concluded that a novel elite allele of TaGW2-6B was artificially created and might play an important role in wheat breeding for high yield and quality. [ABSTRACT FROM AUTHOR]

Well-performing genomic prediction (GP) models for polygenic traits and molecular marker sets for oligogenic traits could be useful for identifying promising genetic resources in germplasm collections, setting core collections, and establishing molecular variety distinction. This study aimed at (i) defining GP models and key marker sets for predicting 15 agronomic or morphological traits in germplasm collections, (ii) verifying the GP model usefulness also for selection in breeding programs, (iii) investigating the consistency between molecular and phenotypic diversity patterns, and (iv) identifying genomic regions associated with to the target traits. The study was based on phenotyping data and over 41,000 genotyping-by-sequencing-generated SNP markers of 220 landraces or old cultivars belonging to a world germplasm collection and 11 modern cultivars. Nonmetric multi-dimensional scaling (NMDS) and an analysis of population genetic structure indicated a high level of genetic differentiation of material from Western Asia, a major West-East diversity gradient, and quite limited genetic diversity of the improved germplasm. Mantel's test revealed a low correlation (r = 0.12) between phenotypic and molecular diversity, which increased (r = 0.45) when considering only the molecular diversity relative to significant SNPs from genome-wide association analyses. These analyses identified, inter alia, several areas of chromosome 6 involved in a largely pleiotropic control of vegetative or reproductive organ pigmentation. We found various significant SNPs for grain and straw yield under severe drought and onset of flowering, and one SNP on chromosome 5 for grain protein content. GP models displayed moderately high predictive ability (0.43 to 0.61) for protein content, grain and straw yield, and onset of flowering, and high predictive ability (0.76) for individual seed weight, based on intra-population, intra-environment cross-validations. The inter-population, inter-environment assessment of the models trained on the germplasm collection for breeding material of three recombinant inbred line (RIL) populations, which was challenged by much narrower diversity of the material, over eight-fold less available markers and quite different test environments, led to an overall loss of predictive ability of about 40% for seed weight, 50% for protein content and straw yield, and 60% for onset of flowering, and no prediction for grain yield. Within-RIL population predictive ability differed among populations. [ABSTRACT FROM AUTHOR]

Zinc (Zn) deficiency is a widespread problem in agricultural soils all over the globe. As an essential element, Zn plays a decisive role in realization of high yields of wheat, the changes in activities of Zn dependent enzymes and its accumulation in various plant parts of wheat varieties of differential susceptibility. The aim of the study was to examine the activities of Zn dependent enzymes, i.e. superoxide dismutase (SOD), carbonic anhydrase (CA); chlorophyll and grain protein content and to evaluate the pattern of Zn transport in two wheat varieties (UP2628-Zn efficient and UP262-Zn inefficient). All these parameters were evaluated in a pot experiment under different modes of Zn applications viz., control (C), soil application (S), foliar application (F), soil+foliar application (S+F). The accumulation of Zn in different plant parts of both wheat varieties under different Zn supply regimes was monitored in a separate autoradiography experiment where radiolabelled Zn was used. An increased activity of SOD, CA and total chlorophyll content in leaves, high protein content in grains and 65Zn accumulation was observed under S+F mode of Zn application. Zinc efficient variety (UP2628) showed higher SOD, CA activities, chlorophyll content in leaves and grain protein content as compared to UP262. Both soil application + foliar spray of Zn and cultivation of Zn efficient variety (UP2628) can be best approach for Zn biofortification of wheat. [ABSTRACT FROM AUTHOR]

Rice grain quality is a multifarious attribute mainly governed by multiple nutritional factors. Grain protein is the central component of rice grain nutrition dominantly affecting eating–cooking qualities. Grain protein content is quantitatively influenced by its protein fractions. Genetic quantification of five protein fractions—albumins, globulins, prolamins, glutelin, and grain protein content—were evaluated by exploiting two BC3F2 mapping populations, derived from Kongyu131/TKM9 (population-I) and Kongyu131/Bg94-1 (population-II), which were grown in a single environment. Correlation studies among protein fractions and grain protein content were thoroughly investigated. A genetic linkage map was developed by using 146 single sequence repeat (SSR) markers in population-I and 167 markers in population-II. In total, 40 QTLs were delineated for five traits in both populations. Approximately 22 QTLs were dissected in population-I, derived from Kongyu131/TKM9, seven QTLs for albumin content, four QTLs for globulin content, three QTLs for prolamin content, four QTLs for glutelin content, and four QTLs for grain protein content. In total, 18 QTLs were detected in population-II, derived from Kongyu131/Bg94-1, five QTLs for albumin content, three QTLs for globulin content, four QTLs for prolamin content, two QTLs for glutelin content, and four QTLs for grain protein content. Three QTLs, qAlb7.1, Alb7.2, and qGPC7.2, derived from population-II (Kongyu131/Bg94-1) for albumin and grain protein content were successfully validated in the near isogenic line (NIL) populations. The localized chromosomal locus of the validated QTLs could be helpful for fine mapping via map-based cloning to discover underlying candidate genes. The functional insights of the underlying candidate gene would furnish novel perceptivity for the foundation of rice grain protein content and trigger the development of nutritionally important rice cultivars by combining marker-assisted selection (MAS) breeding. [ABSTRACT FROM AUTHOR]

The grain protein content is an important quality trait in cereals, and the expression level of the OsAAP6 can significantly affect the grain protein content in rice. Through site-directed mutagenesis, we found that the position from −7 to −12 bp upstream of the transcription start site of the OsAAP6 was the functional variation site. By using the yeast single hybrid test, point-to-point in yeast, and the local surface plasmon resonance test, the OsNAC74 was screened and verified to be a regulator upstream of OsAAP6. The OsNAC74 is a constitutively expressed gene whose product is located on the cell membrane. The OsAAP6 and the genes related to the seed storage in the Osnac74 mutants were downregulated, and grain protein content was significantly reduced. In addition, OsNAC74 had a significant impact on quality traits such as grain chalkiness and gel consistency in rice. Although the Osnac74 mutant seeds were relatively small, the individual plant yield was not decreased. Therefore, OsNAC74 is an important regulatory factor with multiple biological functions. This study provides important information for the later use of OsNAC74 gene for molecular design and breeding in rice. [ABSTRACT FROM AUTHOR]

Wheat (Triticum spp.) is crucial to food security. Grain protein content (GPC) is key to its nutritional and economic value and is controlled by genetic and agronomic factors, soil properties and weather. GPC prediction from remote sensing could reduce nitrogen (N) losses, help management decisions, and improve profit. However, GPC prediction is complex because multiple plant traits influence GPC and their effects change through the growing season. Traits with known physiological links to GPC, which can be retrieved from imaging spectroscopy, include leaf area index (LAI), chlorophyll (C a+b), and stress indicators. Further inspection of these and other traits retrieved from satellite data can advance research relevant to precision agriculture. Sentinel-2 (S2) timeseries (TS) were acquired for 6,355 ha of commercial dryland bread (T. aestivum) and durum (T. durum) wheat fields in south-east Australia through two consecutive years with dissimilar rainfall. Wheat growers provided ∼ 92,000 GPC data points from harvester-mounted protein monitors. For each, C a+b , leaf dry matter, leaf water content (C w) and LAI were retrieved from the S2 images by radiative transfer model inversion. A gradient boosted machine learning algorithm was applied to analyse these traits' importance to GPC and to predict GPC in 30% of samples unseen by the algorithm in training. The strongest relationships between predicted and observed GPC (R 2 = 0.86, RMSE = 0.56 %), in a model built from five S2 images across a season, were better than those from single-date hyperspectral (HS). In severe water stress, LAI was the main predictor of GPC early in the season, but this switched to C w later. Trait importance was more evenly distributed in milder conditions. S2 TS had a clear accuracy advantage over single-date S2 and HS, especially in benign conditions, emphasising the potential of S2 TS for large-scale GPC monitoring. [ABSTRACT FROM AUTHOR]

Nitrogen (N) fertilisers used in barley production serve as the primary contributors to total greenhouse gas (GHG) emissions. Consequently, to lower the carbon footprint (CF) and GHG emissions, it is imperative to either reduce N fertiliser rates or enhance grain yield and improve nitrogen use efficiency (NUE). To address this challenge, we combined two strategies related to N: (1) a 34% reduction in the total N rate compared to the control (total N rate 108–110 kg N ha−1), and (2) testing two types of N fertilisers for topdressing against the control (common sulfur urea). These types included (a) a mixture comprising controlled-release fertiliser (CRF) combined with ammonium sulfate nitrate fertiliser in a 40:60 ratio (CRF + Nitro) and (b) ammonium sulfate nitrate (Nitro). Experiments were conducted in two distinct areas of Greece specialising in cereal production, aiming to unveil the effects of these strategies on all sustainability aspects of malting barley production. The results showed that although a 34% reduction in N rate did not result in yield penalties or a decrease in grain size, it did have a negative impact on grain protein content (GPC). CRF + Nitro not only reduced CF by approximately 30% compared to the control but also increased N agronomic efficiency by 51.5% and net profit by 7.1%. Additionally, it was demonstrated that the maximum achievable reduction in total GHG emissions and CF, by excluding N fertilisation from the crop system, ranged from 68.5% to 74.3% for GHG emissions and 53.8% to 67.1% for CF. [ABSTRACT FROM AUTHOR]

IntroductionMicronutrient deficiencies, particularly iron (Fe) and zinc (Zn), are prevalent in a large part of the human population across the world, especially in children below 5 years of age and pregnant women in developing countries. Since wheat constitutes a significant proportion of the human diet, improving grain Fe and Zn content in wheat has become important in improving human health.ObjectiveThis study aimed to quantify the effect of foliar application of iron sulfate heptahydrate (FeSO4.7H2O) and zinc sulfate heptahydrate (ZnSO4.7H2O) and their combination on grain Fe and Zn concentrations, as well as grain protein content (GPC). The study also aimed to assess the utility of these applications in large field conditions.MethodsTo address this issue, field experiments were conducted using 10 wheat cultivars and applying a foliar spray of FeSO4.7H2O (0.25%) and ZnSO4.7H2O (0.50%) separately (@400 L of solution in water per hectare during each spray) and in combination at two different crop growth stages (flowering and milking) for three consecutive crop seasons (2017–2020). The study used a split-plot design with two replications to assess the impact of foliar application on GFeC, GZnC, and GPC. In addition, an experiment was also conducted to assess the effect of soil (basal) @ 25 kg/ha ZnSO4, foliar @ 2 kg/ha, ZnSO4.7H2O (0.50%), and the combination of basal + foliar application of ZnSO4 on the grain micronutrient content of wheat cultivar WB 02 under large field conditions.ResultsGFeC increased by 5.1, 6.1, and 5.9% with foliar applications of FeSO4, ZnSO4, and their combination, respectively. GZnC increased by 5.2, 39.6, and 43.8% with foliar applications of FeSO4, ZnSO4, and their combination, respectively. DBW 173 recorded the highest increase in GZnC at 56.9% with the combined foliar application of FeSO4 and ZnSO4, followed closely by HPBW 01 at 53.0% with the ZnSO4 foliar application, compared to the control. The GPC increased by 6.8, 4.9, and 3.3% with foliar applications of FeSO4, ZnSO4, and their combination, respectively. Large-plot experiments also exhibited a significant positive effect of ZnSO4 not only on grain Zn (40.3%, p ≤ 0.001) and protein content (p ≤ 0.05) but also on grain yield (p ≤ 0.05) and hectoliter weight (p ≤ 0.01), indicating the suitability of the technology in large field conditions.ConclusionCultivars exhibited a slight increase in GFeC with solitary foliar applications of FeSO4, ZnSO4, and their combination. In contrast, a significant increase in GZnC was observed with the foliar application of ZnSO4 and the combined application of FeSO4 and ZnSO4. In terms of GPC, the most significant enhancement occurred with the foliar application of FeSO4, followed by ZnSO4 and their combination. Data demonstrated the significant effect of foliar application of ZnSO4 on enhancing GZnC by 39.6%. Large plot experiments also exhibited an increase of 40.3% in GZnC through the foliar application of ZnSO4, indicating the effectiveness of the technology to be adopted in the farmer’s field.

Background. Knowledge about the genetic gain for fundamental traits over time is essential for a critical assessment and improvement of breeding programs, especially regarding staple crops like bread wheat.Materials and methods. To estimate the genetic gain in bread wheat breeding in Morocco, grain yield (GY) and grain protein content (GPC) data were collected from 12 multi-environment field trials for 20 bread wheat cultivars released between 1980 and 2022.Results and discussion. Analysis of variance highlighted a high significant variability between environments (E), cultivars (G), and a significant G × E interaction (P < 0.001). Based on stability analysis, the modern cultivars released during the two last decades (2002–2012 and 2013–2022) showed the highest performances and wider stability than old ones, especially in low-yielding environments. Genetic gain (GG) for GY was 21.4 kg ha−1 yr−1 (0.75% yr–1) over 4 decades of breeding. This progress was declining when advancing in decades and ranged from 11% (from 1980–1990 to 1991–2001) to less than 7% (from 2002–2012 to 2013–2022). The GG in low and intermediate yielding environments were the most important (17.34% and 6.88% yr–1 respectively), while GG was nonsignificant in high-yielding environments (4.62% yr–1). Within the same period, GPC showed a nonsignificant negative trend of –0.007% (–0.002% yr–1), while derivative parameters from GY and GPC indicated high positive genetic progress. More efforts should be deployed to implement a good balance between yield performance and quality in the new released cultivars despite the negative correlation between these two traits (r = –0.36; P < 0.001).Conclusion. Adopting advanced technologies, like genomic selection, adequate agronomic practices, and more efficient selection criteria are essential steps to further increase simultaneously grain yield and quality traits.

The objectives of this study were to identify genetic loci in the bread wheat genome that would influence yield stability and quality under water stress, and to identify accessions that can be recommended for cultivation in dry and hot regions. We performed a genome-wide association study (GWAS) using a panel of 232 wheat accessions spanning diverse ecogeographic regions. Plants were evaluated in the Israeli Northern Negev, under two environments: water-limited (D; 250 mm) and well-watered (W; 450 mm) conditions; they were genotyped with ~71,500 SNPs derived from exome capture sequencing. Of the 14 phenotypic traits evaluated, 12 had significantly lower values under D compared to W conditions, while the values for two traits were higher under D. High heritability (H2 = 0.5-0.9) was observed for grain yield, spike weight, number of grains per spike, peduncle length, and plant height. Days to heading and grain yield could be partitioned based on accession origins. GWAS identified 154 marker-trait associations (MTAs) for yield and quality-related traits, 82 under D and 72 under W, and identified potential candidate genes. We identified 24 accessions showing high and/or stable yields under D conditions that can be recommended for cultivation in regions under the threat of global climate change.

Modern varieties of common wheat (Triticum aestivum L.) bred mainly for high productivity are often of low grain quality. The identification of NAM-1 alleles associated with high grain protein content in wheat relatives has enhanced the significance of distant hybridization for the nutritional value of T. aestivum L. grain. In this work we aimed to study the allelic polymorphism of the NAM-A1 and NAM-B1 genes in wheat introgression lines and their parental forms and evaluate the effects of various NAM-1 variants on the grain protein content and productivity traits in the field conditions of Belarus. We studied parental varieties of spring common wheat, the accessions of tetraploid and hexaploid species of the genus Triticum and 22 introgression lines obtained using them (2017–2021 vegetation periods). Full-length NAM-A1 nucleotide sequences of T. dicoccoides k-5199, T. dicoccum k-45926, T. kiharae, and T. spelta k-1731 accessions were established and registered with the international molecular database GenBank. Six combinations of NAM-A1/B1 alleles were identified in the accessions studied and their frequency of occurrence varied from 40 to 3 %. The cumulative contribution of NAM-A1 and NAM-B1 genes to the variability of economically important wheat traits ranged from 8–10 % (grain weight per plant and thousand kernel weight) to up to 72 % (grain protein content). For most of the traits studied, the proportion of variability determined by weather conditions was small (1.57–18.48 %). It was shown that, regardless of weather conditions, the presence of a functional NAM-B1 allele ensures a high level of grain protein content; at the same time, it does not significantly decrease thousand kernel weight. The genotypes combining the NAM-A1d haplotype and a functional NAM-B1 allele demonstrated high levels of productivity and grain protein content. The results obtained demonstrate the effective introgression of a functional NAM-В1 allele of related species increasing the nutritional value of common wheat.

Well-performing genomic prediction (GP) models for polygenic traits and molecular marker sets for oligogenic traits could be useful for identifying promising genetic resources in germplasm collections, setting core collections, and establishing molecular variety distinction. This study aimed at (i) defining GP models and key marker sets for predicting 15 agronomic or morphological traits in germplasm collections, (ii) verifying the GP model usefulness also for selection in breeding programs, (iii) investigating the consistency between molecular and phenotypic diversity patterns, and (iv) identifying genomic regions associated with to the target traits. The study was based on phenotyping data and over 41,000 genotyping-by-sequencing-generated SNP markers of 220 landraces or old cultivars belonging to a world germplasm collection and 11 modern cultivars. Non-metric multi-dimensional scaling (NMDS) and an analysis of population genetic structure indicated a high level of genetic differentiation of material from Western Asia, a major West-East diversity gradient, and quite limited genetic diversity of the improved germplasm. Mantel’s test revealed a low correlation (r = 0.12) between phenotypic and molecular diversity, which increased (r = 0.45) when considering only the molecular diversity relative to significant SNPs from genome-wide association analyses. These analyses identified, inter alia, several areas of chromosome 6 involved in a largely pleiotropic control of vegetative or reproductive organ pigmentation. We found various significant SNPs for grain and straw yield under severe drought and onset of flowering, and one SNP on chromosome 5 for grain protein content. GP models displayed moderately high predictive ability (0.43 to 0.61) for protein content, grain and straw yield, and onset of flowering, and high predictive ability (0.76) for individual seed weight, based on intra-population, intra-environment cross-validations. The inter-population, inter-environment assessment of the models trained on the germplasm collection for breeding material of three recombinant inbred line (RIL) populations, which was challenged by much narrower diversity of the material, over eight-fold less available markers and quite different test environments, led to an overall loss of predictive ability of about 40% for seed weight, 50% for protein content and straw yield, and 60% for onset of flowering, and no prediction for grain yield. Within-RIL population predictive ability differed among populations.

Wheat is an important food crop in China. The quality of wheat affects the development of the agricultural economy. However, the high-quality wheat produced in China cannot meet the demand, so it would be an important direction for research to develop high-quality wheat. Grain protein content (GPC) is an important criterion for the quality of winter wheat and its content directly affects the quality of wheat. Studying the spatial heterogeneity of wheat grain proteins is beneficial to the prediction of wheat quality, and it plays a guiding role in the identification, grading, and processing of wheat quality. Due to the complexity and variability of wheat quality, conventional evaluation methods have shortcomings such as low accuracy and poor applicability. To better predict the GPC, geographically weighted regression (GWR) models, multiple linear regression, random forest (RF), BP neural networks, support vector machine, and long-and-short-term memory algorithms were used to analyze the meteorological data and soil data of Jiangsu Province from March to May in 2019–2022. It was found that the winter wheat GPC rises by 0.17% with every 0.1° increase in north latitude at the county level in Jiangsu. Comparison of the prediction accuracy of the coefficient of determination, mean deviation error, root mean square error, and mean absolute error by analyzing multiple algorithms showed that the GWR model was the most accurate, followed by the RF model. The regression coefficient of precipitation in April showed the smallest range of variation among all factors, indicating that precipitation in April had a more stable effect on GPC in the study area than the other meteorological factors. Therefore, consideration of spatial information might be beneficial in predicting county-level winter wheat GPC. GWR models based on meteorological and soil factors enrich the studies regarding the prediction of wheat GPC based on environmental data. It might be applied to predict winter wheat GPC and improve wheat quality to better guide large-scale production and processing. [ABSTRACT FROM AUTHOR]

Nutritional grain quality is mainly influenced by the protein fraction content and grain protein content. Quantitative trait loci (QTL) mining for five traits, about 245 and 284 BC3F3 individual families of two introgression line (IL) populations were derived from Kongyu 131/Cypress (population-I) and Kongyu 131/Vary Tarva Osla (population-II), respectively. A genetic linkage map was developed using 127 simple sequence repeat (SSR) markers in population-I and 119 SSR markers in population-II. In total, 20 and 5 QTLs were detected in population-I and population-II, respectively. About twenty QTLs were mapped in population-I: five QTLs for albumin, seven QTLs for globulin, six QTLs for prolamin, one QTL for glutelin, and one QTL for grain protein content. In total, five QTLs were mapped in population-II: one QTL for albumin and four QTLs for grain protein content. Out of 25 QTLs, 19 QTLs exhibit co-localization with the previously reported QTLs. QTL-like qGPC7.3 was delineated for total protein content. This QTL was derived from population-I and was successfully validated in NILs (near-isogenic lines). The grain protein phenotype showed a significant variation between two NILs. This investigation serves as groundwork for additional cloning of nutritional quality-related genes in rice grains. [ABSTRACT FROM AUTHOR]

Genetic enhancement of grain production and quality is a priority in wheat breeding projects. In this study, we assessed two key agronomic traits—grain protein content (GPC) and thousand kernel weight (TKW)—across 179 Bulgarian contemporary and historic varieties and landraces across three growing seasons. Significant phenotypic variation existed for both traits among genotypes and seasons, and no discernible difference was evident between the old and modern accessions. To understand the genetic basis of the traits, we conducted a genome-wide association study with MLM using phenotypic data from the crop seasons, best linear unbiased estimators, and genotypic data from the 25K Infinium iSelect array. As a result, we detected 16 quantitative trait nucleotides (QTNs) associated with GPC and 15 associated with TKW, all of which passed the false discovery rate threshold. Seven loci favorably influenced GPC, resulting in an increase of 1.4% to 8.1%, while four loci had a positive impact on TKW with increases ranging from 1.9% to 8.4%. While some loci confirmed previously published associations, four QTNs linked to GPC on chromosomes 2A, 7A, and 7B, as well as two QTNs related to TKW on chromosomes 1B and 6A, may represent novel associations. Annotations for proteins involved in the senescence-associated nutrient remobilization and in the following buildup of resources required for seed germination have been found for selected putative candidate genes. These include genes coding for storage proteins, cysteine proteases, cellulose-synthase, alpha-amylase, transcriptional regulators, and F-box and RWP-RK family proteins. Our findings highlight promising genomic regions for targeted breeding programs aimed at improving grain yield and protein content.

Salinity is an environmental stress that severely impacts rice grain yield and quality. However, limited information is available on the molecular mechanism by which salinity reduces grain quality. In this study, we investigated the milling, appearance, eating and cooking, and nutritional quality among three japonica rice cultivars grown either under moderate salinity with an electrical conductivity of 4 dS/m or under non-saline conditions in a paddy field in Dongying, Shandong, China. Moderate salinity affected rice appearance quality predominantly by increasing chalkiness rate and chalkiness degree and affected rice eating and cooking and nutritional quality predominantly by decreasing amylose content and increasing protein content. We compared the expression levels of genes determining grain chalkiness, amylose content, and protein content in developing seeds (0, 5, 10, 15, and 20 days after flowering) of plants grown under saline or non-saline conditions. The chalkiness-related gene Chalk5 was up-regulated and WHITE-CORE RATE 1 was repressed. The genes Nuclear factor Y and Wx, which determine amylose content, were downregulated, while protein-content-associated genes OsAAP6 and OsGluA2 were upregulated by salinity in the developing seeds. These findings suggest some target genes that may be utilized to improve the grain quality under salinity stress conditions via gene-pyramiding breeding approaches.

Salinity exerts significant negative impacts on growth and productivity of crop plants and numerous management practices are used to improve crop performance under saline environments. Micronutrients, plant growth promoting bacteria and biochar are known to improve crop productivity under stressful environments. Maize (Zea mays L.) is an important cereal crop and its productivity is adversely impacted by salinity. Although boron (B) application, seed inoculation with boron-tolerant bacteria (BTB) and biochar are known to improve maize growth under stressful environments, there is less information on their combined impact in enhancing maize productivity on saline soils. This study investigated the impact of B seed coating combined with seed inoculation with BTB + biochar on maize productivity under saline soil. Four B seed coating levels [0.0 (no seed coating), 1.0, 1.5, 2.0 g B kg−1 seed], and individual or combined application of 5 % (w/w) maize stalk biochar, and seed inoculation with Bacillus sp. MN-54 BTB were included in the study. Different growth and yield attributes and grain quality were significantly improved by seed coating with 1.5 B kg−1 seed coupled with biochar + BTB. Seed coating with 1.5 B kg−1 seed combined with biochar + BTB improved stomatal conductance by 32 %, photosynthetic rate by 15 %, and transpiration ratio by 52 % compared to seed coating (0 B kg−1 seed) combined with biochar only. Similarly, the highest plant height (189 cm), number of grain rows cob−1 (15.5), grain yield (54.9 g plant−1), biological yield (95.5 g plant−1), and harvest index (57.6 %) were noted for B seed coating (1.5 g B kg−1 seed) combined with biochar + BTB inoculation. The same treatment resulted in the highest grain protein and B contents. It is concluded that B seed coating at 1.5 g B kg−1 seed combined with biochar + BTB inoculation could significantly improve yield and quality of maize crop on saline soils. However, further field experiments investigating the underlying mechanisms are needed to reach concrete conclusions and large-scale recommendations.

Wheat is one of the most important global crops and selection for better performance has been ongoing since ancient times. As a quantitative trait controlled by the interplay of several genomic loci and under the strong influence of the environment, grain protein content (GPC) is of major interest in breeding programs. Here, we review the most recent contributions to the genetics underlying wheat GPC and grain protein deviation (GPD, representing the relationship between grain protein content and yield), together with the performance of genomic prediction models characterizing these traits. A total of 364 significant loci related to GPC and GPD are positioned on the hexaploid wheat genome, highlighting genomic regions where significant independent QTL overlap, with special focus on two regions located on chromosomes 3A and 5A. Some of the corresponding homoeologous sequences co‐locate with significant independent QTL reported on the B and D subgenomes. Overlapping independent QTL from different studies are indicative of genomic regions exhibiting stability across environments and genotypes, with promising candidates for improving grain quality. [ABSTRACT FROM AUTHOR]

Wheat grain quality is equivalent to grain yield in terms of ensuring food security under climate change but has received less attention. Identifying critical meteorological conditions in key phenological periods to account for the variability in grain protein content (GPC) can provide insight into linkages between climate change and wheat quality. The wheat GPC data from different counties of Hebei Province, China during 2006-2018 and corresponding observational meteorological data were used in our study. Through a fitted gradient boosting decision tree model, latitude of the study area, accumulated sunlight hours during the growth season, accumulated temperature and averaged relative humidity from filling to maturity were suggested as the most relevant influencing variables. The relationship between GPC and latitude was distinguished between areas north and south of 38.0° N. GPC decreased with the increasing latitude in areas south of 38.0° N, where at least accumulated temperatures of 515°C from filling to maturity were preferred to maintain high GPC. Besides, averaged relative humidity during the same phenological period exceeding 59% could generate an extra benefit to GPC here. However, GPC increased with increasing latitude in areas north of 38.0° N and was mainly attributed to more than 1500 sunlight hours during the growth season. Our findings that different meteorological factors played a major role in deciding regional wheat quality provided a scientific basis for adopting better regional planning and developing adaptive strategies to minimize climate impacts. [ABSTRACT FROM AUTHOR]

Water stress has adverse effects on crop yield and food quality. In this study, a diverse set of durum wheat genotypes including Iranian landraces and some new cultivars; ICARDA and SIMMYT accessions; and a few foreign landraces were evaluated for agronomic and biochemical traits. Two field experiments were conducted in randomized complete block designs with three replicates under supplementary irrigated (non-stress) and rain-fed (terminal drought stress) environments using the 73 durum wheat genotypes. A combined analysis of variance indicated highly significant genotypic differences for all the traits. Terminal drought stress decreased grain yield, 1000-grain weight and the number of grains per spike, while total gluten content and grain protein content increased. In both experiments, grain yield was positively correlated with the number of spikes per m2 and the number of grains per spike. Gluten index showed a significant negative correlation with wet, total and dry gluten. Grain protein content was positively correlated with wet, total and dry gluten in the both conditions. In order to identify terminal drought-resistant genotypes, drought tolerance indices including tolerance index (TOL), stress tolerance index (STI), mean productivity (MP), geometric mean productivity (GMP), stress susceptibility index (SSI), and yield stability index (YSI) were calculated. Among the indices, GMP, MP and STI were positively correlated with grain yield in both environments. The results of this study showed that yield and yield components were affected by environmental factors, while qualitative characters were more affected by the genotype (genotype dependent). Some superior durum wheat accessions were identified and may be used in breeding programs, as well as for food and industrial products. The application of principal component analysis (PCA) to discriminate the durum wheat genotypes has been discussed. [ABSTRACT FROM AUTHOR]

In the last century wheat breeding programs have shown consistent yield increases, often associated with lower grain protein concentrations (GPC). A better understanding of the genetic basis of grain yield and grain protein content can help break the grain yield—GPC negative correlation. We developed a nested association mapping population composing a set of spring wheat genotypes for genetic dissection of grain yield and quality with 'Blanca Fuerte' (high yield and low grain protein content) as recurrent parent and cultivars and advanced lines from CIMMYT and California (UC Davis breeding program, medium–high yield and grain protein content). The QTL analyses revealed three genomic regions on chromosomes 2B, 6A, and 6B associated with significant increases in GPC but negative effects on yield, and one region on chromosome 5B associated with significant increases in grain yield but negative effects on GPC. More interestingly, we identified two genomic regions on chromosomes 2B and 3B associated with increases in GPC and no significant effects on grain yield and a genomic region on chromosome 1A associated with a significant increase in grain yield and no penalty in GPC. These last three genomic regions and their associated markers are promising tools for wheat breeding programs interested in breaking the negative correlation between GPC and grain yield. [ABSTRACT FROM AUTHOR]

In present-day Japan, high quality is the first requirement of rice production. To maintain the quality of rice, the prejudgment technique has been proposed to control rice growth or to separately harvest rice depending on its quality. Since the quality of rice is generally indexed by grain protein content, which is strongly affected by nitrogen content of leaves, one of the major prejudgment techniques is based on leaf greenness evaluation (i.e., SPAD value). However, the technique is under research and not popular with the farmers because the reliability of prejudgment is inadequate. In this study, we investigated the leaf SPAD value at different growth stages of different cultivars and with cultivation methods in farmer fields over four years, and we validated the applicability of prejudgment by comparing with the grain protein content. The results showed that the grain protein content was positively correlated with leaf SPAD value at the maturity stage, but correlated weakly with those at the booting, heading, and milking stages. Since the regression coefficients significantly differed depending on the year, cultivar, and planting method, the acquisition of a regression equation for each target is recommended to predict grain protein content more accurately. The validation in this study suggests that the prejudgment of grain protein content just before harvest has generality for several targets and is useful for harvesting rice depending on the quality. The results in this study may contribute to the attempts to evaluate SPAD value and then rice quality by remote sensing.

The assimilation of remote sensing data into mechanistic models of crop growth has become an available method for estimating yield. The objective of this study was to explore an effective assimilation approach for estimating maize grain protein content and yield using a canopy remote sensing data and crop growth model. Based on two years of field experiment data, the remote sensing inversion model using assimilation intermediate variables, namely leaf area index (LAI) and leaf nitrogen accumulation (LNA), was constructed with an R2 greater than 0.80 and a low root-mean-square error (RMSE). The different data assimilation approaches showed that when the LAI and LNA variables were used together in the assimilation process (VLAI+LNA), better accuracy was achieved for LNA estimations than the assimilation process using single variables of LAI or LNA (VLAI or VLNA). Similar differences in estimation accuracy were found in the maize yield and grain protein content (GPC) simulations. When the LAI and LNA were both intermediate variables in the assimilation process, the estimation accuracy of the yield and GPC were better than that of the assimilation process with only one variable. In summary, these results indicate that two physiological and biochemical parameters of maize retrieved from hyperspectral data can be combined with the crop growth model through the assimilation method, which provides a feasible method for improving the estimation accuracy of maize LAI, LNA, GPC and yield. [ABSTRACT FROM AUTHOR]

Public awareness is gradually growing in favour of consuming nutritionally superior brown and pigmented rice which is in general relatively poor in eating and cooking quality. Understanding inheritance pattern of nutritional and quality traits is prerequisite for further improvement exercising molecular tools. A holistic approach was adopted to identify unique and common genomic regions regulating 17 grain nutritional as well as physiochemical traits using a diverse panel of 96 rice genotypes. Seventy eight significant marker-trait associations distributed in all chromosomes with phenotypic variance ranging from 4 to 27% were detected. Marker RM 467 was co-localized with previously identified QTL qPC10.1 and gene OsGluA2. Grain protein and metal content were associated with cooking quality which was also supported by the marker-trait association. Two QTLs for each of grain protein and amylose content (AC) with associated markers RM 17600 and RM 1272 were found co-localized with additive effect in opposite direction. Similarly, RM 162 was associated with both zinc content and cooking time (alkali spreading value). Iron content was also associated with grain size which was supported by the association of RM8050 with the both Fe content and kernel length/breadth ratio. Phenotypically pigmented rice was detected with low AC and one genetic locus for anthocyanin (qANTH5.1) was also found to be co-localized with a QTL for AC (qAC5.1) with additive effect in opposite direction. Co-localized associated loci for nutritional and cooking and eating quality can guide strategic biofotification programs for improving rice for nutritional traits without distracting consumer preference. [ABSTRACT FROM AUTHOR]

To improve the yield and quality of wheat is of great importance for food security worldwide. One of the most effective and significant approaches to achieve this goal is to enhance the nitrogen use efficiency (NUE) in wheat. In this review, a comprehensive understanding of the factors involved in the process of the wheat nitrogen uptake, assimilation and remobilization of nitrogen in wheat were introduced. An appropriate definition of NUE is vital prior to its precise evaluation for the following gene identification and breeding process. Apart from grain yield (GY) and grain protein content (GPC), the commonly recognized major indicators of NUE, grain protein deviation (GPD) could also be considered as a potential trait for NUE evaluation. As a complex quantitative trait, NUE is affected by transporter proteins, kinases, transcription factors (TFs) and micro RNAs (miRNAs), which participate in the nitrogen uptake process, as well as key enzymes, circadian regulators, cross-talks between carbon metabolism, which are associated with nitrogen assimilation and remobilization. A series of quantitative genetic loci (QTLs) and linking markers were compiled in the hope to help discover more efficient and useful genetic resources for breeding program. For future NUE improvement, an exploration for other criteria during selection process that incorporates morphological, physiological and biochemical traits is needed. Applying new technologies from phenomics will allow high-throughput NUE phenotyping and accelerate the breeding process. A combination of multi-omics techniques and the previously verified QTLs and molecular markers will facilitate the NUE QTL-mapping and novel gene identification. [ABSTRACT FROM AUTHOR]

Identification of genotypes that can maintain a good yield and quality performance under climatic variability is critical for ensuring future food security. The aim of this study was to determine the stability of fifty-four durum wheat varieties with different geographical origins conceming the traits grain yield and grain protein content by parametric and nonparametric assessments. The varieties were tested in three consecutive years 2019-2021 in a randomized block design in three replications. Four nonparametric stability assessment, four parametric stability assessment, the coefficient of variation and the simulated assessment of yield and stability by Kang were determined. The analysis of variance revealed a significant influence of genotypes, environment and the genotype and environment interaction (GxE) on the expression of both studied traits. The environment showed a greatest influence on the variation of both traits. Eleven genotypes achieved average yield above 6.00 t ha-1. The genotypes with a high average yield and grain protein content and high stability as determined by the most stability assessments were identified as Melina (BG), Raylidur (BG) and Beloslava (BG) - for grain yield and varieties as Cesare and Beloslava (BG) - for grain protein content. The Bulgarian variety Beloslava was the most valuable combination high yield and grain protein content along with high stability for both traits across different seasons. Beloslava can be recommended for involvement in durum wheat breeding programs for simultaneously improvement of productivity and grain quality and to develop new durum wheat varieties well adapted to changing climate conditions. [ABSTRACT FROM AUTHOR]

Rice is a staple food for vast majority of population through out world. In a study an eperiment was conducted to check the variability among the recombinant inbreed lines for the mapping population. Genetic variability, Heritability and genetic advance study for protein content, amylase content, Seed yield and its components was conducted in recombinant inbreed lines (in F9 generation) of Oryza sativa indica L. at the K-block, UAS, Bengaluru, India. Genetic Variance was less than enviormental variance for all the traits. High broad sence heritability and genetic gain were recorded for grain protein content, amylase content, grain yield and yield attributing traits. These results suggest that there is sufficient genetic variability for all the traits studied in the recombinant inbreed lines, Suggesting suitability of the population for mapping. [ABSTRACT FROM AUTHOR]

In present-day Japan, high quality is the first requirement of rice production. To maintain the quality of rice, the prejudgment technique has been proposed to control rice growth or to separately harvest rice depending on its quality. Since the quality of rice is generally indexed by grain protein content, which is strongly affected by nitrogen content of leaves, one of the major prejudgment techniques is based on leaf greenness evaluation (i.e., SPAD value). However, the technique is under research and not popular with the farmers because the reliability of prejudgment is inadequate. In this study, we investigated the leaf SPAD value at different growth stages of different cultivars and with cultivation methods in farmer fields over four years, and we validated the applicability of prejudgment by comparing with the grain protein content. The results showed that the grain protein content was positively correlated with leaf SPAD value at the maturity stage, but correlated weakly with those at the booting, heading, and milking stages. Since the regression coefficients significantly differed depending on the year, cultivar, and planting method, the acquisition of a regression equation for each target is recommended to predict grain protein content more accurately. The validation in this study suggests that the prejudgment of grain protein content just before harvest has generality for several targets and is useful for harvesting rice depending on the quality. The results in this study may contribute to the attempts to evaluate SPAD value and then rice quality by remote sensing. [ABSTRACT FROM AUTHOR]

The aim of our study was to evaluate the effect of different foliar fertilizers on the yield and grain protein, oil and starch content of maize. The experiment was set up in 2021 at the Öthalom research station of the Hungarian University of Agriculture and Life Sciences in Szeged. The soil was deeply salt meadow chernozem. Its nitrogen content was medium, phosphorus and potassium content was good. The experiment was carried out in three replications, using random blocks design. The size of plots were 14 m2. The produced maize hybrid was DKC 4555 (FAO 350). We sprayed three foliar fertilizers individually and combined with each other. We processed the obtained data by single factor variant analysis. 2021 was unfavourable year for maize. The amount of precipitation was lower by 113.58 mm than the average in the vegetative period of maize, therefore we got relatively low yields. The yield amount of control plot was 2.44 t ha-1. As a result of lack of precipitation the foliar fertilizers resulted low yield increasing (0.04-0.7 t/ha) which was not significant. The highest yield (3.14 t ha-1) we got in Amalgerol+Fitohorm Zn treatment. The foliar fertilizers resulted minimal and not significant changes in maize grain protein, starch and oil contents. We can conclude, that in unfavourable relatively dry year caused low effectiveness of foliar fertilizers in maize production. [ABSTRACT FROM AUTHOR]

The grain protein content (GPC) of rice is an important factor that determines its nutritional, cooking, and eating qualities. To date, although a number of genes affecting GPC have been identified in rice, most of them have been cloned using mutants, and only a few genes have been cloned in the natural population. In this study, 135 significant loci were detected in a genome-wide association study (GWAS), many of which could be repeatedly detected across different years and populations. Four minor quantitative trait loci affecting rice GPC at four significant association loci, qPC2.1, qPC7.1, qPC7.2, and qPC1.1, were further identified and validated in near-isogenic line F2 populations (NIL-F2), explaining 9.82, 43.4, 29.2, and 13.6% of the phenotypic variation, respectively. The role of the associated flo5 was evaluated with knockdown mutants, which exhibited both increased grain chalkiness rate and GPC. Three candidate genes in a significant association locus region were analyzed using haplotype and expression profiles. The findings of this study will help elucidate the genetic regulatory network of protein synthesis and accumulation in rice through cloning of GPC genes and provide new insights on dominant alleles for marker-assisted selection in the genetic improvement of rice grain quality. [ABSTRACT FROM AUTHOR]

Background: Barley has been bred for more than a century in the Nordic countries, with dramatic improvements of yield traits. In this study we investigate if this has come at the cost of lower grain protein and micronutrient (iron, zinc) content, by analysing 80 accessions representing four different improvement stages. We further re-sequenced the two grain protein content associated genes HvNAM-1 and HvNAM-2 in full and performed expression analyses of the same genes to search for genetic associations with nutrient content. Results: We found higher thousand grain weight in barley landraces and in accessions from the late improvement group compared to accessions from the mid of the twentieth century. Straw length was much reduced in late stage accessions. No significant temporal decrease in grain protein, iron or zinc content during twentieth century Nordic crop improvement could be detected. Out of the 80 accessions only two deviant HvNAM-1 sequences were found, represented by one accession each. These do not appear to be correlated to grain protein content. The sequence of HvNAM-2 was invariable in all accessions and no correlations between expression levels of HvNAM-1 and HvNAM-2 and with grain protein content was found. Conclusions: In contrast to studies in wheat, where a strong negative correlation between straw length and grain protein and micronutrient content has been found, we do not see this relationship in Nordic barley. The last 60 years of breeding has reduced straw length but, contrary to expectations, not protein and micronutrient content. Variation in grain protein and micronutrient content was found among the Nordic barley accessions, but it is not explained by variation of HvNAM genes. This means that HvNAM is an unexploited source of genetic variation for nutrient content in Nordic barley. [ABSTRACT FROM AUTHOR]

Cereal and legume intercropping could improve cereal yield, but the role of intercropping in grain quality still lacks a full understanding. A two-year bi-factorial trial was conducted to investigate the role of two planting patterns (mono-cropped wheat (MW) and intercropped wheat+faba bean (IW)) and four nitrogen (N) fertilization levels (N0, no N fertilizer applied to both wheat and faba bean; N1, 90 and 45 kg N ha–1 applied to wheat and faba bean; N2, 180 and 90 kg N ha–1 applied to wheat and faba bean; N3, 270 and 135 kg N ha–1 applied to wheat and faba bean), as well as their interaction on the productivity of wheat grain yield (GY) and quality. The results showed that intercropping increased both the yields of wheat grain protein and amino acids (AAs) relative to MW in both years. No difference in Aas content between IW and MW was found but the 9% grain protein content (GPC) of IW was higher than that of MW in 2020. By contrast, wheat gliadin content was increased by 8–14% when wheat was intercropped with faba bean in both years, and some AAs fractions including essential and non-essential AAs were increased under N0 and N1 levels but declined at the N3 level. This means that intercropping increased the grain quality either for protein and AAs content or for fractions. There was no negative relationship between GPC and GY in the present study, and intercropping tended to increase GPC with increasing GY. In conclusion, wheat and faba bean mainly affected GPC and fractions rather than AAs, and intercropping presented a potential to improve both wheat quality and yield concurrently. Modulated N rates benefitted the stimulation of intercropping advantages in terms of grain yield and quality in the southwest of China and similar regions. [ABSTRACT FROM AUTHOR]

Grain protein content (GPC) is an indicator of cereal nutritional quality. Identification of genes involved in the regulation of GPC provides targets for molecular breeding for crop protein quality. We characterized a maize gene encoding the putative amino acid transporter ZmAAP6, a gene expressed mainly in immature seeds, especially in the basal endosperm transfer layer. Total protein and zein contents were decreased in ZmAAP6 null mutants and increased in ZmAAP6 overexpression (OE) lines, consistent with their changed in the size of protein bodies. Metabolic and transcriptomic analysis supported the regulatory role of ZmAAP6 in amino acid transportation. These results suggest that ZmAAP6 functions as a positive regulator of GPC in maize, shedding new light on the genetic basis of GPC regulation. [ABSTRACT FROM AUTHOR]

Conventionally, split nitrogen (N) applications at tillering and stem elongation enhance winter wheat yield, protein content, and nitrogen use efficiency. Vegetation indices, such as the Normalized Difference Vegetation Index (NDVI), Normalized Difference Red Edge index (NDRE), and leaf chlorophyll content (LCC) can be used as crop N status indicators (CNSIs) to easily underline the N deficiency. The aim of this study, conducted across 4 growing seasons in North-West Italy, was to create a model for regulating wheat fertilization rates and improve crop yield. The model relies on CNSIs measurements collected during the initial stages of stem elongation, aiming to achieve predetermined yield targets. In each year, the experimental design was a factorial combination of four N rates (0, 33, 66, and 99 kg N ha−1) at tillering and five at stem elongations (0, 33, 66, 99 and 132 kg N ha−1). The Aubusson cultivar, characterized by intermediate yield potential and protein content, was used to calibrate and validate the model in a 3-year trial (2018–2020), while the model was also applied to cv LG Ayrton (high yield potential) and Izalco (high protein content) in the 2020–21 season. Yield and protein content trends in function of N rate were parabolic or sigmoidal respectively and both tillering and stem elongation rate contributed to increase the grain yield and protein content. Furthermore, the significant interaction between tillering and stem elongation fertilization on grain yield suggested the possibility of correcting the N deficiency after tillering fertilization with a further application. A calibration function for a variable rate application was established related to the CNSIs; all of them were good predictors but NDRE showed a higher overall correlation (R2 = 0.479) with grain yield than NDVI (R2= 0.461) or the LCC values (R2= 0.236) considering all the 3 years of experiments. The model's intercept was reduced according to the decrease in the grain yield goal. The model's validation was accomplished by comparing the outcomes predicted by the model yields with the measured. The yield's Root Mean Square Error (RMSE) values were low for cv. Aubusson (0.85, on average) in all 3 years, while the RMSE was higher in 2021 for LG Ayrton (1.90) and Izalco (1.35), in a production situation with a higher yield potential. The results suggest that the topdressing N fertilization rate could be accurately determined from measured CNSI values for a site-specific N fertilization management, but they also highlight the requirement of a model adaptation for different genotypes and environments. [Display omitted] • Crop N status indicator can detect N deficiency allowing in season correction. • Yield and protein content trends in function of N rate were parabolic or sigmoidal, respectively. • Proposed calibration functions considered only crop N status indicators and yield goals. • NDRE was the best vegetation index to guide N fertilization at the beginning of stem elongation. • Different cultivars require a model adjustment according mainly to the specific yield potential. [ABSTRACT FROM AUTHOR]

Soil organic carbon (SOC) is crucial for mitigating global warming and significantly impacts crop production. While the relationship between SOC and wheat yield is well-documented, its effect on wheat grain protein content, which is essential for food security and human health, remains unclear. This study gathered management data from wheat farmers and collected plant and soil samples in the Huang-Huai winter wheat region, China's primary wheat-growing area, from 2015 to 2022. Boundary line analysis was used to quantify the responses of wheat yield and protein content to variations in SOC. Our findings reveal that increases in SOC significantly enhance wheat yield and protein content. The highest yields, reaching up to 10,848 kg ha–1, and a maximum protein content of 17.3 % were observed in soils with SOC ranging from 7.8–18.1 g kg–1, and high-yielding, high-protein wheat exhibited higher spike numbers and grain weights and more efficient nutrient accumulation from soil or fertilizer to shoots. Optimizing SOC levels to produce high-yielding, high-protein wheat could substantially reduce nitrogen (N), phosphorus (P), and potassium (K) fertilizer use by 9.42×104, 0.70×104, and 3.66×104 Mg per year, decrease greenhouse gas emissions by 3.36 Mt CO 2 eq and generate an economic benefit of 2.77 billion USD. In conclusion, our study expands the understanding of SOC's role in crop production beyond crop yield, providing valuable insights for producing high-yielding, high-protein wheat. [ABSTRACT FROM AUTHOR]