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Microbial communities have been demonstrated to be essential for healthy and productive soil ecosystems. However, an understanding of the relationship between soil microbial community and soil productivity levels is remarkably limited. In this study, bulk soil (BS), rhizosphere soil (RS), and root (R) samples from the historical high-productive (H) and low-productive (L) soil types of wheat in Hebei province of China were collected and analyzed by high-throughput sequencing. The study highlighted the richness, diversity, and structure of bacterial communities, along with the correlation networks among different bacterial genera. Significant differences in the bacterial community structure between samples of different soil types were observed. Compared with the low-productive soil type, the bacterial communities of samples from the highproductive soil type possessed high species richness, low species diversity, complex and stable networks, and a higher relative abundance of beneficial microbes, such as Pseudoxanthomonas, unclassified Vicinamibacteraceae, Lysobacter, Massilia, Pseudomonas, and Bacillus. Further analysis indicated that the differences were mainly driven by soil organic matter (SOM), available nitrogen (AN), and electrical conductivity (EC). Overall, the soil bacterial community is an important factor affecting soil health and crop production, which provides a theoretical basis for the targeted regulation of microbes in low-productivity soil types. [ABSTRACT FROM AUTHOR]

High-temperature (HT) stress can induce male sterility in wheat; however, the underlying mechanisms remain poorly understood. This study examined proteomic alterations across three developmental stages between normal and HT-induced male-sterile (HT-ms) anthers in wheat. Utilizing tandem mass tagsbased proteomics, we identified 2532 differentially abundant proteins (DAPs): 27 in the tetrad stage, 157 in the binuclear stage, and 2348 in the trinuclear stage. Analyses through Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathways indicated significant enrichment of these DAPs in seven pathways, namely phenylpropanoid biosynthesis, flavonoid biosynthesis, sphingolipid metabolism, MAPK signaling pathway, starch and sucrose metabolism, response to heat, and response to reactive oxygen species (ROS). Our results indicated the downregulation of DAPs associated with phenylpropanoid biosynthesis and starch and sucrose metabolism, which aligns with anther indehiscence and the lack of starch in HT-ms anthers. By contrast, DAPs in the ROS pathway were upregulated, which aligns with excessive ROS accumulation in HT-ms anthers. Additionally, we conducted protein-protein interaction analysis for the DAPs of these pathways, identifying 15 hub DAPs. The abundance of these hub proteins was confirmed through qRTPCR, assessing mRNA expression levels of the corresponding transcripts. Collectively, these results offer insights into the molecular mechanisms underlying HT-induced male sterility in wheat at the proteomic level, providing a valuable resource for further research in plant sexual reproduction. [ABSTRACT FROM AUTHOR]

Introduction: Wheat (Triticum aestivum L.) is among themost important crop worldwide. Given a growing population and changing climate, enhancing wheat yield is of great importance. Yield is closely associated with flower and spike development, and E-class genes play important roles in the flower and kernel development of plants. Currently, the absence of systematic analysis on the E gene family hinders our comprehension of their roles in plant growth and development. Methods: Identify E-class genes based on homologous sequence searches. Analyze the identified E-class genes through a series of gene family analyses. Determine the expression levels of wheat E-class genes by searching public databases. Validate the functions of these genes by transforming them into Arabidopsis. Finally, determine the interactions between the genes through yeast two-hybrid experiments. Results: Fifteen E-class genes (TaEs) were identified in common wheat. Nine Eclass genes were detected in five ancestral/closely related species, including one in Aegilops tauschii (AtE), one in T. Urartu (TuEs), two in T. turgidum (TtEs), two in T. dicoccoides (TdEs), and three in T. spelta (TsEs). The 24 E-class genes were classified into three subgroups using a phylogenetic approach. All genes were highly expressed in spikes, and most were only highly expressed at the floret meristem stage. The effects of TaSEP5-A on flowering and growth cycles were confirmed in homologous mutants and transgenic Arabidopsis thaliana. The Eclass genes were able to regulate the growth cycle of Arabidopsis. Finally, we confirmed the interactions between TaSEP5-A and other wheat E-class genes based on yeast two-hybrid assays. Discussion: Our findings provide information regarding the E-class genes in wheat and will potentially promote the application of these genes in wheat improvement. [ABSTRACT FROM AUTHOR]

Anthocyanins are plant secondary metabolites belonging to the polyphenol class of natural water-soluble phytopigments. The accumulation of anthocyanins in different plant tissues can improve plant survival under adverse conditions. In addition, plants with the resulting colorful morphology can be utilized as landscape plants. Triticum boeoticum (syn. Triticum monococcum ssp. aegilopoides, 2n=2x=14, AbAb) serves as a valuable genetic resource for the improvement of its close relative common wheat in terms of enhancing resilience to various biotic and abiotic stresses. In our previous study, the EMSmutagenized mutant Z2921 with a red glume, stem, and rachis was generated from T. boeoticum G52, which has a green glume, stem, and rachis. In this study, the F1, F2, and F2:3 generations of a cross between mutant-type Z2921 and wildtype G52 were developed. A single recessive gene, tentatively designated RgM4G52, was identified in Z2921 via genetic analysis. Using bulked segregant exome capture sequencing (BSE-Seq) analysis, RgM4G52 was mapped to chromosome 6AL and was flanked by the markers KASP-58 and KASP-26 within a 3.40-cM genetic interval corresponding to 1.71-Mb and 1.61-Mb physical regions in the Chinese Spring (IWGSC RefSeq v1.1) and Triticum boeoticum (TA299) reference genomes, respectively, in which seven and four genes related to anthocyanin synthesis development were annotated. Unlike previously reported color morphology-related genes, RgM4G52 is a recessive gene that can simultaneously control the color of glumes, stems, and rachis in wild einkorn. In addition, a synthetic Triticum dicoccum-T. boeoticum amphiploid Syn-ABAb-34, derived from the colchicine treatment of F1 hybrids between tetraploid wheat PI 352367 (T. dicoccum, AABB) and Z2921, expressed the red stems of Z2921. The flanking markers of RgM4G52 developed in this study could be useful for developing additional common wheat lines with red stems, laying the foundation for marker-assisted breeding and the fine mapping of RgM4G52. [ABSTRACT FROM AUTHOR]

Introduction: Wheat awns are crucial determinants of wheat yield due to their capacity to photosynthesize and exchange gas. Understanding the genetic basis of awn length (AL) is essential for improving wheat yield in molecular breeding programs. Methods: In this study, quantitative trait loci (QTLs) of AL were analyzed using recombinant inbred line (RIL) mapping population referred to as YY-RILs, which was derived from a cross between Yannong 15 (YN15) and Yannong 1212 (YN1212). Results and discussion: Seven putative additive QTLs and 30 pairwise epistatic QTLs for AL were identified. Among them, five novel additive QTLs (except qAl- 2A and qAl-5A.2) and 30 novel pairwise epistatic QTLs were identified. qAl-5A.1 was repeatedly identified in all five environment datasets, which was considered to be one novel stable QTL for AL with minor additive effects. eqAl-2B.2-2 significantly interacted with eight loci and could be of great importance in regulating awn development. The genes associated with the major stable QTL of qAl-5A.2 and the minor stable QTL of qAl-2A were B1 and WFZP-A, respectively. Awn lengths exhibited significant genetic correlations with kernel weight and kernels per spike, which could affect grain protein content to a lesser extent. This study enhances our understanding of the genetic basis of awn development and identifies novel genes as well as markers for future genetic improvement of wheat yield. [ABSTRACT FROM AUTHOR]

Bread wheat (T. aestivum) is one of the world's most widely consumed cereals. Since micronutrient deficiencies are becoming more common among people who primarily depend upon cereal-based diets, a need for better-quality wheat varieties has been felt. An association panel of 154 T. aestivum lines was evaluated for the following quality traits: grain appearance (GA) score, grain hardness (GH), phenol reaction (PR) score, protein percent, sodium dodecyl sulfate (SDS) sedimentation value, and test weight (TWt). In addition, the panel was also phenotyped for grain yield and related traits such as days to heading, days to maturity, plant height, and thousand kernel weight for the year 2017-18 at the Borlaug Institute for South Asia (BISA) Ludhiana and Jabalpur sites. We performed a genome-wide association analysis on this panel using 18,351 genotyping-bysequencing (GBS) markers to find marker-trait associations for quality and grain yield-related traits. We detected 55 single nucleotide polymorphism (SNP) marker trait associations (MTAs) for quality-related traits on chromosomes 7B (10), 1A (9), 2A (8), 3B (6), 2B (5), 7A (4), and 1B (3), with 3A, 4A, and 6D, having two and the rest, 4B, 5A, 5B, and 1D, having one each. Additionally, 20 SNP MTAs were detected for yield-related traits based on a field experiment conducted in Ludhiana on 7D (4) and 4D (3) chromosomes, while 44 SNP MTAs were reported for Jabalpur on chromosomes 2D (6), 7A (5), 2A (4), and 4A (4). Utilizing these loci in marker-assisted selection will benefit from further validation studies for these loci to improve hexaploid wheat for better yield and grain quality [ABSTRACT FROM AUTHOR]

Introduction: Gluten quality is one of the most important traits of the common wheat (Triticum aestivum L.). In Chinese wheat production, Yannong series cultivars/derivative lines possess unique characteristics and play an important role in both yield and quality contribution. Methods: To dissect their genetic basis of the gluten quality, in this study, allelic variations of high-molecular-weight glutenin subunit (HMW-GS) and lowmolecular- weight glutenin subunit (LMW-GS) in 30 Yannong series wheat cultivars/derivative lines and three check cultivars were evaluated using the allele-specific molecular markers, and six crucial quality indexes were also further measured and analyzed. Results: The results demonstrated that the frequencies of HMW-GSs By8, Dx5 + Dy10 and Dx5 + Dy10 + Dy12 in these 30 genotypes and three check cultivars accounted for 87.9%, 24.2% and 9.1%, respectively. For the allelic variations of LMW-GSs, Glu-A3a, Glu-A3b, Glu-A3c, Glu-A3f, and Glu-A3g were identified in 18, 9, 13, 11, and 2 genotypes, respectively; Glu-B3d, Glu-B3g and Glu-B3f were identified in 13, 23 and 4 genotypes, respectively. Notably, Yannong 999, containing By8 + Dx5 + Dy10, and Jinan 17 containing By8 + Dy12 both meet the national standard for high-quality wheat and belong to the category of first-class high-quality strong gluten wheat. Discussion: These findings can provide reference for wheat quality improvement and popularization in the production. [ABSTRACT FROM AUTHOR]

Gaining a comprehensive understanding of the carbon emissions cycle in the atmosphere resulting from agricultural activities is crucial for assessing its influence on environmental quality. This study used panel datasets covering the period from 1990-2022 to investigate the influence of wheat and rice production on environmental quality in the six mega agricultural provinces of China namely Anhui, Hebei, Hubei, Henan, Jiangsu, and Sichuan. Study employed several econometric approaches such as Cross-Sectional Dependency tests, unit root and cointegration tests, Panel Mean Group Autoregressive Distributed Lag (PMG-ARDL), Panel Quantile (PQ) and Panel Least Square (PLS) regression analysis for the robustness of the findings. The empirical findings of PMG-ARDL model reveal that rice production positively increases CO2 emissions in the long run. The variables fertilizers usage, agricultural water consumption and agricultural credit also have positive impact on CO2 emission in the long run. Further, short-term results reveal that all the concerned variables positively contribute to increase the CO2 emissions. The PQR results illustrate that rice and wheat production, fertilizer consumption, agricultural water usage, agricultural credit and agricultural GDP have positive and significant impact on CO2 emission across the quantiles. Additionally, PLS outcomes show positive and significant association between wheat productivity, agricultural credit, fertilizer and agricultural GDP on CO2 emissions. The Dumitrescu and Hurlin (D-H) panel causality show unidirectional association among: carbon emission → pesticides use, carbon emission → temperature, and carbon emission → agricultural GDP. A significant bidirectional causal association was found between: carbon emission ↔ rice production, carbon emission ↔ wheat production, carbon emission ↔ fertilizers use, carbon emission ↔ agricultural water use, and carbon emission ↔ agricultural credit. These findings contribute to the understanding of the drivers of CO2 emissions in agriculture and provide valuable insights for policymakers aiming to mitigate environmental impacts while promoting sustainable agriculture, resilience, financial support to encourage green technology and implement robust monitoring mechanisms to protect quality of environment and agricultural sustainability. [ABSTRACT FROM AUTHOR]

Multi-parent populations (MPPs) are attractive for genetic and breeding studies because they combine genetic diversity with an easy-to-control population structure. Most methods for mapping QTLs in MPPs focus on the detection of QTLs in single environments. Little attention has been given to mapping QTLs in multienvironment trials (METs) and to detecting and modeling QTL-byenvironment interactions (QEIs). We present mixed model approaches for the detection and modeling of consistent versus environment-dependent QTLs, i.e., QTL-by-environment interaction (QEI). QTL effects are assumed to be normally distributed with variances expressing consistency or dependence on environments and families. The entries of the corresponding design matrices are functions of identity-by-descent (IBD) probabilities between parents and offspring and follow from the parental origin of offspring DNA. A polygenic effect is added to the models to account for background genetic variation. We illustrate the wide applicability of our method by analyzing several public MPP datasets with observations from METs. The examples include diallel, nested association mapping (NAM), and multi-parent advanced inter-cross (MAGIC) populations. The results of our approach compare favorably with those of previous studies that used tailored methods. [ABSTRACT FROM AUTHOR]

The Hessian fly (HF, Mayetiola destructor) is one of the most destructive pests of wheat and wheat-related cereals. Wheat resistance and/or susceptibility to HF are often affected by the levels of phytohormones in plants. In this study, we tested the impact of phytohormones on Molly wheat resistance to HF biotype GP by externally applying phytohormones, including salicylic acid (SA), jasmonic acid (JA), 12-oxophytodienoic acid (OPDA), and auxin (indole acetic acid, IAA) to wheat seedlings under heat conditions. Our results indicated that the impact of externally applied phytohormones on wheat resistance to HF depends on the timing of phytohormone application and/or HF larval density at HF feeding sites in the plants. The early application of SA, OPDA, and IAA enhanced wheat resistance to HF under heat stress at low larval density, while the delayed application of SA, OPDA, and IAA did not affect wheat resistance to HF at high larval density. [ABSTRACT FROM AUTHOR]

Bread wheat germplasm is accessed from the International Maize and Wheat Improvement Centre (CIMMYT) and the International Centre for Agricultural Research in the Dry Areas (ICARDA) by Australian wheat breeders and researchers through the CIMMYT Australia ICARDA Germplasm Evaluation (CAIGE) program. The CAIGE program coordinates the selection, importation, quarantine, dissemination, and evaluation of the imported bread wheat germplasm and the management of associated data and information. This paper describes the CAIGE model and assesses both the genetic and economic impacts of these materials on the Australian wheat industry after commercialisation of wheat breeding in the early 21st century and the establishment of CAIGE. The CAIGE concept was validated using data collected and analysed from multi-environment trials between 2017 and 2020. The impact of cultivars with and without CAIGE contribution to pedigree on yield was estimated using production-by-variety statistics. Net gain in yield, estimated as the yield difference between CAIGE and Non-CAIGE varieties, was multiplied by the percentage contribution to pedigree to estimate the additional yield. The CAIGE bread wheat program identified diverse, high-yielding, and disease-resistant germplasm and significantly improved the capture and dissemination of information. The benefit-cost ratio, calculated as the sum of benefits divided by investments, indicated that, for every dollar invested in CAIGE, a further $20 was generated in benefits. The internal rate of return was estimated at 163% and the modified rate at 18%. The benefits of these international materials to Australian wheat breeding remained significant. [ABSTRACT FROM AUTHOR]

Introduction: The study aimed to investigate the potential effects of varying wheat levels in broiler diets on growth performance, intestinal barrier, and cecal microbiota. Methods: Day-old male broilers were fed the same diet until 10 d of age. Then they were randomly assigned to 1) the low-level wheat group, where inclusion of 15.0% and 25.0% wheat in the grower and finisher diet, respectively, 2) the medium-level wheat group with 30.0% and 40.0% of wheat in the grower and finisher periods; and 3) the high-level wheat dietary group, in which the grower and finisher diets contained 55.77% and 62.38% of wheat, respectively. Results: Dietary treatments unaffected the body weight at 39 d, whereas incorporating high wheat in diets significantly increased the feed intake and reduced the feed conversion ratio from 10 to 39 d (p<0.05). Except for increased phosphorus digestibility in the high wheat group, dietary treatments had no significant effect on the apparent digestibility of dry matter, crude protein, and ether extract. Meanwhile, the broilers that consumed the medium and high content of wheat presented a higher villus height and the ratio of villus height to crypt depth than those fed the low-level wheat birds. Feeding the medium-level wheat enhanced ileal integrity and depressed the expression of proinflammatory cytokines in the ileum. The addition of high levels of wheat reduced the Chao1 index and the abundance of Lactobacillaceae, Bacteroidaceae, and Ruminococcacea in cecal content, which probably decreased the metabolism of histidine, sulfur-containing amino acids, and the biosynthesis of lysine. Discussion: These results support the medium-level wheat diet improved intestinal barrier function and had no deleterious effects on the growth performance of broiler; dietary inclusion of high wheat reduced the feed conversion rate, which might be associated with the disturbed gut microbiota and decreased metabolism of amino acids. [ABSTRACT FROM AUTHOR]

Rice-wheat and maize-wheat rotations are major cropping systems in the middle and lower reaches of Yangtze River in China, where high nitrogen (N) inputs and low N efficiency often exacerbate resource waste and environmental pollution. Due to the changes in factors such as soil properties and moisture content, the N fate and the N utilization characteristics of wheat in different rotations are significantly different. Efficient N management strategies are thus urgently required for promoting maximum wheat yield in different rotation systems while reducing N loss. A 2-year field experiment using isotopic (15N) tracer technique was conducted to evaluate the fate of 15N-labeled urea in wheat fields and the distribution characteristics of N derived from different sources. The wheat yield and N use efficiency under various N rates (180 and 240 kg ha-1, abbreviated as N180 and N240) and preceding crops (rice and maize, abbreviated as R-wheat and M-wheat) were also investigated. The results showed that N240 increased N uptake and grain yield by only 8.77-14.97% and 2.51-4.49% compared with N 180, but decreased N agronomic efficiency (NAE) and N physiological efficiency (NPE) by 14.78-18.79% and 14.06-31.35%. N240 also decreased N recovery in plants by 2.8% on average compared with N180, and increased N residue in soil and N loss to the environment. Compared with that of basal N, the higher proportion of topdressing N was absorbed by wheat rather than lost to the environment. In addition, the accumulation of topdressing N in grain was much higher than that of basal N. Compared with that in R-wheat treatment, plants in M-wheat treatment trended to absorb more 15N and reduce unaccounted N loss, resulting in higher yield potential. Moreover, the M-wheat treatment increased N recovery in 0-20 cm soil but decreased 80-100 cm soil compared with R-wheat treatment, indicating a lower risk of N loss in deeper soil. Collectively, reducing N application rate and increasing the topdressing ratio is an effectiveway to balance sustainable crop yield for a secure food supply and environmental benefit, which ismore urgent in rice-wheat rotation. [ABSTRACT FROM AUTHOR]

Soil salinity poses a significant threat to agricultural productivity, impacting the growth and yield of wheat (Triticum aestivum L.) plants. This study investigates the potential of melatonin (MT; 100 µM) and hydrogen sulfide (H2S; 200 µM sodium hydrosulfide, NaHS) to confer the tolerance of wheat plants to 100 mM NaCl. Salinity stress induced the outburst of reactive oxygen species (ROS) resulting in damage to the chloroplast structure, growth, photosynthesis, and yield. Application of either MT or NaHS augmented the activity of antioxidant enzymes, superoxide dismutase, ascorbate peroxidase, glutathione reductase, and reduced glutathione (GSH) levels, upregulated the expression of Na+ transport genes (SOS1, SOS2, SOS3, NHX1), resulting in mitigation of salinity stress. Thus, improved stomatal behavior, gas-exchange parameters, and maintenance of chloroplast structure resulted in enhanced activity of the Calvin cycle enzymes and overall enhancement of growth, photosynthetic, and yield performance of plants under salinity stress. The use of DL-propargylglycine (PAG, an inhibitor of hydrogen sulfide biosynthesis) and p-chlorophenyl alanine (p-CPA, an inhibitor of melatonin biosynthesis) to plants under salt stress showed the comparative necessity of MT and H2S in mitigation of salinity stress. In the presence of PAG, more pronounced detrimental effects were observed than in the presence of p-CPA, emphasizing that MT was involved in mitigating salinity through various potential pathways, one of which was through H2S. [ABSTRACT FROM AUTHOR]

Introduction: Wheat grain filling processes under post-anthesis stress scenarios depend mainly on stem traits and remobilization of stem water-soluble carbohydrates (WSC). Methods: A diverse panel of advanced semi-dwarf spring wheat lines, representing a natural variation in stem traits (WSC content, stem diameter, peduncle length, and stem wall width), was used to identify specific traits that reliably reflect the relationship between WSC and grain yield. The panel was phenotyped under various environmental conditions: well-watered, waterlimited, and heat stress in Mexico, and terminal-drought in Israel. Results: Environmental stresses reduced grain yield (from 626 g m-2 under wellwatered to 213 g m-2 under heat), lower internode diameter, and peduncle length. However, stem-WSC generally peaked 3-4 weeks after heading under all environmental conditions except heat (where it peaked earlier) and expressed the highest values under water-limited and terminal-drought environments. Increased investment in internode diameter and peduncle length was associated with a higher accumulation of stem WSC, which showed a positive association with yield and kernel weight. Across all environments, there were no apparent trade-offs between increased crop investment in internode diameter, peduncle length, and grain yield. Discussion: Our results showed that selecting for genotypes with higher resource investment in stem structural biomass, WSC accumulation, and remobilization could be a valuable strategy to ameliorate grain size reduction under stress without compromising grain yield potential. Furthermore, easy-tomeasure proxies for WSC (stem diameter at specific internodes and length of the last internode, i.e., the peduncle) could significantly increase throughput, potentially at the breeding scale. [ABSTRACT FROM AUTHOR]

This study evaluates the biocontrol efficacy of three bacterial strains (Pseudomonas fluorescens DTPF-3, Bacillus amyloliquefaciens DTBA-11, and Bacillus subtilis DTBS-5) and two fungal strains (Trichoderma harzianum Pusa-5SD and Aspergillus niger An-27) antagonists, along with their combinations at varying doses (5.0, 7.5, and 10.0 g/kg of seeds), against wheat powdery mildew. The most effective dose (10 g/kg seeds) was further analyzed for its impact on induced resistance and plant growth promotion under greenhouse conditions. The study measured defense enzyme activities, biochemical changes, and post-infection plant growth metrics. All tested microbial antagonists at 10 g/kg significantly reduced PM severity, with B. subtilis strain DTBS-5 outperforming others in reducing PM severity and achieving the highest biocontrol efficacy. It was followed by B. amyloliquefaciens strain DTBA-11 and P. fluorescens strain DTPF-3, with the fungal antagonists showing no significant effect. Wheat crops treated with B. subtilis strain DTBS-5 exhibited substantial increases in defense-related enzyme activities and biochemicals, suggesting an induced resistance mechanism. The study found a 45% increase in peroxidase (POD) activity, a 50% increase in catalase (CAT) activity, a 30% increase in phenolic content, and a 25% increase in soluble protein content in the wheat plants treated with microbial antagonists. The study highlights the effectiveness of microbial antagonists, particularly B. subtilis strain DTBS-5, in managing wheat PM through biocontrol, induced resistance, and enhanced plant growth, offering a sustainable alternative to chemical treatments. [ABSTRACT FROM AUTHOR]

Grain albumin is highly nutritious and closely related to the processing quality of wheat. However, few studies have explored the grain albumin content (GAC) in wheat. This study aims to uncover quantitative trait loci (QTLs) linked to wheat GAC by analyzing a doubled haploid (DH) population derived from common wheat cultivars ShanNong23 and ZhouMai17. We detected six QTLs controlling GAC on chromosomes 1B, 5A, and 6D, with individual QTL explaining 5.78% to 22.29% of the GAC variation. The effect of QGac.cau-1B.1 on GAC is attributed to the presence of the 1BL/1RS translocation, indicating that the 1BL/1RS translocation increase of GAC compared with the non-1BL/1RS translocation lines. The higher GAC observed in 1BL/1RS lines could be primarily attributed to the increased accumulation of omega-secalin, omega-gliadin, low molecular weight glutenin subunit and ribosomal protein content. Additionally, we also found that the SDS-sedimentation value of whole wheat flour was decreased by adding albumin solution. These results advance our understanding of the genetic basis of GAC and offer novel perspectives for enhancing wheat quality through genetic enhancements. [ABSTRACT FROM AUTHOR]

The gelatinization and retrogradation characteristics of wheat starch affect the eating quality of Chinese-style food. Rapid Visco Analyzer (RVA) parameters have been widely used as important indicators to evaluate and improve the quality of wheat starch. However, the genetic basis of RVA parameters remains to be further explored. In the present study, a natural population was genotyped using 90K single nucleotide polymorphism (SNP) arrays, and the RVA parameters of this population grown in five environments were evaluated. The results showed that 22,068 high-quality SNP markers were identified and distributed unequally on the chromosomes. According to the genetic distance, 214 wheat materials were divided into four groups. Except for the pasting temperature (PTT), six parameters followed a normal distribution. Based on the general linear model, 969 significant association SNPs were detected by genome-wide association studies (GWAS), and chromosomes 7A and 2B had the most associated SNPs. Breakdown viscosity (BV) was associated with the most SNPs (n = 238), followed by PTT (n = 186), peak viscosity (PV; n = 156), trough viscosity (TV; n = 127), and final viscosity (FV; n = 126). According to the average linkage disequilibrium (LD), 33 stable quantitative trait loci (QTLs) were identified for single parameters in multiple environments, of which 12 were associated with BV, followed by peak time (PT; n = 8) and PTT (n = 7). On the other hand, 67 pleiotropic QTLs were identified for multiple parameters. Three candidate genes--TasbeIIa, TasbeI, and TassIIa--were screened for phenotyping analysis. The grain width and the weight of the TasbeIIa and TaSSIIa knockout (KO) lines were significantly lower than those of the TasbeI KO lines and the control (CK). The KO lines had smaller endosperm cells, smaller A-type starch granules, and higher amylose content. The TasbeI KO lines showed normal RVA curves, while the TasbeIIa KO lines showed flat curves. However, the TaSSIIa lines failed to paste under the RVA temperatures. Conclusively, the SNPs/QTLs significantly associated with the RVA parameters and genetic resources with novel haplotypes could be used to improve the quality of wheat starch. [ABSTRACT FROM AUTHOR]

The Poaceae family, commonly known as the grass family, encompasses a diverse group of crops that play an essential role in providing food, fodder, biofuels, environmental conservation, and cultural value for both human and environmental well-being. Crops in Poaceae family are deeply intertwined with human societies, economies, and ecosystems, making it one of the most significant plant families in the world. As the major reservoirs of essential nutrients, seed grain of these crops has garnered substantial attention from researchers. Understanding the molecular and genetic processes that controls seed formation, development and maturation can provide insights for improving crop yield, nutritional quality, and stress tolerance. The diversity in photosynthetic pathways between C3 and C4 plants introduces intriguing variations in their physiological and biochemical processes, potentially affecting seed development. In this review, we explore recent studies performed with omics technologies, such as genomics, transcriptomics, proteomics and metabolomics that shed light on the mechanisms underlying seed development in wheat and maize, as representatives of C3 and C4 plants respectively, providing insights into their unique adaptations and strategies for reproductive success. [ABSTRACT FROM AUTHOR]

The irrational application of chemical fertilizers in wheat cultivation not only threatens the agricultural ecosystem but also significantly contributes to carbon emissions, impeding the achievement of "carbon peaking" and "carbon neutrality" goals. The objective of this research is to assess the efficiency of chemical fertilizer use in wheat production across ten major wheat-producing provinces in China from 2004 to 2020. We employed a stochastic frontier production function to evaluate the technical efficiency of fertilizer use, determining feasible reduction levels. The Gini coefficient, kernel density estimation, and Markov chain analysis were further utilized to dissect the spatio-temporal dynamics of carbon emission reduction potential. Our findings provide a detailed analysis of the carbon emission reduction potential in wheat chemical fertilizer use across China's ten major wheat-producing provinces from 2004 to 2020. The average carbon emission reduction potential is significant, at 251.1 kg CE/hm2, with considerable variation observed among regions. The western region, in particular, stands out with the highest potential, reaching up to 336.51 kg CE/hm2, which is notably higher compared to the eastern (230.05 kg CE/hm2) and central regions (158.28 kg CE/hm2). The spatial distribution of this potential is uneven, and the disparities are progressively increasing, primarily due to inter-regional differences. Despite a general decline in carbon reduction potential, the spatial distribution remains relatively consistent. To foster sustainable wheat production, it is imperative to prioritize the western region for targeted chemical fertilizer carbon reduction initiatives. Attention must also be given to the issue of regional disparities in low-carbon wheat production. Enhancing the role of soil testing and fertilizer recommendations is essential to increase the effectiveness of carbon reduction efforts. Additionally, a multi-faceted approach that incorporates various alternative measures is necessary to drive further reductions in chemical fertilizer-related carbon emissions. [ABSTRACT FROM AUTHOR]

This study employs the stochastic frontier model (SFM) to analyze trade potential and efficiency in wheat and maize among Belt and Road Initiative (BRI) countries from 2002 to 2021, encompassing 45 countries for wheat trade and 55 for maize trade. The empirical findings reveal that economic development level, population growth, government efficiency, political stability, and regulatory quality are critical determinants of trade efficiency. Notably, World Trade Organization (WTO) membership exhibits a negative correlation with trade efficiency, potentially reflecting challenges in rule implementation and opportunity utilization among member states. In the context of maize trade, increased arable land area is inversely associated with efficiency, suggesting potential issues in managing large-scale agricultural regions or optimizing land use. The BRI's impact on trade efficiency varies across countries, with Turkey and Hungary showing improved wheat trade efficiency, while Ethiopia and Georgia experienced declines. During the COVID-19 pandemic, effective disease management strategies and diversified trade mechanisms significantly influenced trade efficiency. Furthermore, the study reveals that larger economies do not necessarily outperform small and medium-sized economies in terms of trade potential. These findings contribute significantly to the literature on agricultural trade and offer valuable insights for policymakers, emphasizing the importance of enhancing government efficiency, political stability, and regulatory quality in the context of regional economic development initiatives such as the BRI. This research underscores the need for tailored approaches to trade policy and agricultural management, considering the unique characteristics and challenges faced by different economies along BRI. [ABSTRACT FROM AUTHOR]

Plant-beneficial Pseudomonas bacteria hold the potential to be used as inoculants in agriculture to promote plant growth and health through various mechanisms. The discovery of new strains tailored to specific agricultural needs remains an open area of research. In this study, we report the isolation and characterization of four novel Pseudomonas species associated with the wheat rhizosphere. Comparative genomic analysis with all available Pseudomonas type strains revealed species-level differences, substantiated by both digital DNADNA hybridization and average nucleotide identity, underscoring their status as novel species. This was further validated by the phenotypic differences observed when compared to their closest relatives. Three of the novel species belong to the P. fluorescens species complex, with two representing a novel lineage in the Pseudomonas phylogeny. Functional genome annotation revealed the presence of specific features contributing to rhizosphere colonization, including flagella and components for biofilm formation. The novel species have the genetic potential to solubilize nutrients by acidifying the environment, releasing alkaline phosphatases and their metabolism of nitrogen species, indicating potential as biofertilizers. Additionally, the novel species possess traits that may facilitate direct promotion of plant growth through the modulation of the plant hormone balance, including the ACC deaminase enzyme and auxin metabolism. The presence of biosynthetic clusters for toxins such as hydrogen cyanide and nonribosomal peptides suggests their ability to compete with other microorganisms, including plant pathogens. Direct inoculation of wheat roots significantly enhanced plant growth, with two strains doubling shoot biomass. Three of the strains effectively antagonized fungal phytopathogens (Thielaviopsis basicola, Fusarium oxysporum, and Botrytis cinerea), demonstrating their potential as biocontrol agents. Based on the observed genetic and phenotypic differences from closely related species, we propose the following names for the four novel species: Pseudomonas grandcourensis sp. nov., type strain DGS24T (= DSM 117501T = CECT 31011T), Pseudomonas purpurea sp. nov., type strain DGS26T (= DSM 117502T = CECT 31012T), Pseudomonas helvetica sp. nov., type strain DGS28T (= DSM 117503T = CECT 31013T) and Pseudomonas aestiva sp. nov., type strain DGS32T (= DSM 117504T = CECT 31014T). [ABSTRACT FROM AUTHOR]

Methods: Cultivar characterization indicated that the increase in yield was negatively affected by spike number and positively affected by the number of kernels per spike before the 2000s and kernel weight after the 2000s. Field trials were conducted across two ecological zones over two consecutive wheatgrowing seasons. The results showed that genetic gains in grain yield, spike number, and kernel weight during 1955 to 2021 were 0.629%, 0.574%, and 0.332% year-1 on a relative basis or 39.12 kg ha-1, 24,350 hm-2, and 0.15 g year-1 on an absolute basis, respectively. However, the increase in the kernel number per spike was not significant. Moreover, cultivar replacement explained 25.6%, 12.8%, and 37.5% of the total variance in grain yield, spike number, and kernel weight, respectively. In summary, during the initial grain-filling stage, wheat cultivar replacement led to the shortening of grain-filling duration and rapid grain-filling rate. However, a longer active grain-filling duration was produced by prolonged durations of rapid and late grain-filling. Additionally, the experimental year had a greater effect on the kernel number, which explained 53.2% of the total variance. Ultimately, modern wheat cultivars had a greater kernel weight. Results: Although the increase in kernel weight has affected grain yield during cultivar replacements in the Haihe Plain, the potential for further yield increase through kernel weight enhancement alone is limited. Consequently, future breeding efforts and cultivation practices should focus on improving spike traits and canopy architecture to enhance productivity. [ABSTRACT FROM AUTHOR]

Powdery mildew (PM), caused by Blumeria graminis f. sp. tritici, poses a significant threat to wheat production, necessitating the development of genetically resistant varieties for long-term control. Therefore, exploring genetic architecture of PM in wheat to uncover important genomic regions is an important area of wheat research. In recent years, the utilization of meta-QTL (MQTL) analysis has gained prominence as an essential tool for unraveling the complex genetic architecture underlying complex quantitative traits. The aim of this research was to conduct a QTL meta-analysis to pinpoint the specific genomic regions in wheat responsible for governing PM resistance. This study integrated 222 QTLs from 33 linkage-based studies using a consensus map with 54,672 markers. The analysis revealed 39 MQTLs, refined to 9 high-confidence MQTLs (hcMQTLs) with confidence intervals of 0.49 to 12.94 cM. The MQTLs had an average physical interval of 41.00 Mb, ranging from 0.000048 Mb to 380.71 Mb per MQTL. Importantly, 18 MQTLs co-localized with known resistance genes like Pm2, Pm3, Pm8, Pm21, Pm38, and Pm41. The study identified 256 gene models within hcMQTLs, providing potential targets for marker-assisted breeding and genomic prediction programs to enhance PM resistance. These MQTLs would serve as a foundation for fine mapping, gene isolation, and functional genomics studies, facilitating a deeper understanding of molecular mechanisms. The identification of candidate genes opens up exciting possibilities for the development of PM-resistant wheat varieties after validation. [ABSTRACT FROM AUTHOR]

Accurate wheat ear counting is one of the key indicators for wheat phenotyping. Convolutional neural network (CNN) algorithms for counting wheat have evolved into sophisticated tools, however because of the limitations of sensory fields, CNN is unable to simulate global context information, which has an impact on counting performance. In this study, we present a hybrid attention network (CTHNet) for wheat ear counting from RGB images that combines local features and global context information. On the one hand, to extract multi-scale local features, a convolutional neural network is built using the Cross Stage Partial framework. On the other hand, to acquire better global context information, tokenized image patches from convolutional neural network feature maps are encoded as input sequences using Pyramid Pooling Transformer. Then, the feature fusion module merges the local features with the global context information to significantly enhance the feature representation. The Global Wheat Head Detection Dataset and Wheat Ear Detection Dataset are used to assess the proposed model. There were 3.40 and 5.21 average absolute errors, respectively. The performance of the proposed model was significantly better than previous studies. [ABSTRACT FROM AUTHOR]

Hybrid breeding can increase the competitiveness of wheat (Triticum aestivum L.) in Sub-Saharan Africa by fostering more public-private partnerships and promoting investment by the private sector. The benefit of hybrid wheat cultivars in South Africa has previously been demonstrated but due to the high cost of hybrid seed production, hybrid breeding has not received significant attention in the past decade. Considering the renewed commitment of the private sector to establish wheat as a hybrid crop globally, coupled with significant research investment into enhancement of outcrossing of wheat, hybrid wheat breeding in Southern and Eastern Africa should be revisited. Our study aimed to identify genetically distinct germplasm groups in spring wheat that would be useful in the establishment of heterotic pools targeting this region. Multi-environment yield testing of a large panel of F1 test hybrids, generated using global elite germplasm, was carried out between 2019 and 2020 in Argentina, Africa, Europe, and Australia. We observed significant genotype by environment interactions within our testing network, confirming the distinctiveness of African trial sites. Relatively high additive genetic variance was observed highlighting the contribution of parental genotypes to the grain yield of test hybrids. We explored the genetic architecture of these parents and the genetic factors underlying the value of parents appear to be associated with their genetic subgroup, with positive marker effects distributed throughout the genome. In testcrosses, elite germplasm from the International Maize and Wheat Improvement Center (CIMMYT) appear to be complementary to the genetically distinct germplasm bred in South Africa. The feasibility of achieving genetic gain via heterotic pool establishment and divergence, and by extension the viability of hybrid cultivars in Sub-Saharan Africa, is supported by the results of our study. [ABSTRACT FROM AUTHOR]

Better crop stand establishment, a function of rapid and uniform seedling emergence, depends on the activities of germination-related enzymes, which is problematic when there is insufficient soil moisture. Different ways are in practice for counteracting this problem, including seed priming with different chemicals, which are considered helpful in obtaining better crop stand establishment to some extent through improved seed germination and seedling emergence. In this growth room experiment, caffeine was used as a seed priming agent to improve germination under moisture scarcity. Polyethylene glycol-8000 (18%) was added to Hoagland’s nutrient solution to create drought stress (−0.65 MPa). The experiment was arranged in a completely randomized design (CRD), having four replications of each treatment. A newly developed wheat genotype SB-1 was used for the experimentation. Different doses of caffeine, i.e., 4 ppm, 8 ppm, 12 ppm, and 16 ppm, including no soaking and water soaking, were used as seed priming treatments. Water deficit caused oxidative stress and adversely affected the seed germination, seedling vigor, activities of germination enzymes, photosynthetic pigments, and antioxidative defense mechanism in roots and shoots of seedlings. Caffeine seed priming ameliorated the negative effects of water deficit on seed germination and seedling vigor, which was attributed to the reduction in lipid peroxidation and improvement in the activities of germination-related enzymes like glucosidase, amylase, and protease. Conclusively, seed priming with 12 ppm caffeine outperformed the other treatments and hence is recommended for better crop stand establishment under conditions of soil moisture deficit. [ABSTRACT FROM AUTHOR]

This study was conducted in controlled environmental conditions to systematically evaluate multi-traits responses of winter wheat (Triticum aestivumL.) genotypes to different salinity levels. Responses were assessed at the germination to early seedling stage (Experiment 1). Seeds of different genotypes (n=292) were subjected to three salinity levels (0 [control], 60, and 120 mM NaCl). Principal Component Analysis (PCA) revealed that among studied traits seedling vigor index (SVI) contributed more towards the diverse response of genotypes to salinity stress. Based on SVI, eight contrasting genotypes assumed to be tolerant (Gage, Guymon, MTS0531, and Tascosa) and susceptible (CO04W320, Carson, TX04M410211) were selected for further physio-biochemical evaluation at the booting stage (Experiment 2) and to monitor grain yield. Higher level of salinity (120 mM NaCl) exposure at the booting stage increased thylakoid membrane damage, lipid peroxidation, sugars, proline, and protein while decreasing photosynthesis, chlorophyll index, starch, and grain yield. Based on grain yield, the assumed magnitude of the genotypic response shown in Experiment 1 was not analogous in Experiment 2. This indicates the necessity of individual screening of genotypes at different sensitive growth stages for identifying true salinity-tolerant and susceptible genotypes at a particular growth stage. However, based on higher grain yield and its least percentage reduction under higher salinity, Guymon and TX04M410211were identified as tolerant, andGage and CO04W320 as susceptible at the booting stage, and their biparental population can be used to identify genomic regions for booting stage-specific salinity response. [ABSTRACT FROM AUTHOR]

Introduction: The precise detection of weeds in the field is the premise of implementing weed management. However, the similar color, morphology, and occlusion between wheat and weeds pose a challenge to the detection of weeds. In this study, a CSCW-YOLOv7 based on an improved YOLOv7 architecture was proposed to identify five types of weeds in complex wheat fields. Methods: First, a dataset was constructed for five weeds that are commonly found, namely, Descurainia sophia, thistle, golden saxifrage, shepherd's purse herb, and Artemisia argyi. Second, a wheat weed detection model called CSCWYOLOv7 was proposed to achieve the accurate identification and classification of wheat weeds. In the CSCW-YOLOv7, the CARAFE operator was introduced as an up-sampling algorithm to improve the recognition of small targets. Then, the Squeeze-and-Excitation (SE) network was added to the Extended Latent Attention Networks (ELAN) module in the backbone network and the concatenation layer in the feature fusion module to enhance important weed features and suppress irrelevant features. In addition, the contextual transformer (CoT) module, a transformer-based architectural design, was used to capture global information and enhance self-attention by mining contextual information between neighboring keys. Finally, the Wise Intersection over Union (WIoU) loss function introducing a dynamic nonmonotonic focusing mechanism was employed to better predict the bounding boxes of the occluded weed. Results and discussion: The ablation experiment results showed that the CSCWYOLOv7 achieved the best performance among the other models. The accuracy, recall, and mean average precision (mAP) values of the CSCW-YOLOv7 were 97.7%, 98%, and 94.4%, respectively. Compared with the baseline YOLOv7, the improved CSCW-YOLOv7 obtained precision, recall, and mAP increases of 1.8%, 1%, and 2.1%, respectively. Meanwhile, the parameters were compressed by 10.7% with a 3.8-MB reduction, resulting in a 10% decrease in floating-point operations per second (FLOPs). The Gradient-weighted Class Activation Mapping (Grad-CAM) visualization method suggested that the CSCW-YOLOv7 can learn a more representative set of features that can help better locate the weeds of different scales in complex field environments. In addition, the performance of the CSCW-YOLOv7 was compared to the widely used deep learning models, and results indicated that the CSCW-YOLOv7 exhibits a better ability to distinguish the overlapped weeds and small-scale weeds. The overall results suggest that the CSCW-YOLOv7 is a promising tool for the detection of weeds and has great potential for field applications. [ABSTRACT FROM AUTHOR]

Introduction: In plant breeding, we often aim to improve multiple traits at once. However, without knowing the economic value of each trait, it is hard to decide which traits to focus on. This is where "desired gain selection indices" come in handy, which can yield optimal gains in each trait based on the breeder's prioritisation of desired improvements when economic weights are not available. However, they lack the ability to maximise the selection response and determine the correlation between the index and net genetic merit. Methods: Here, we report the development of an iterative desired gain selection index method that optimises the sampling of the desired gain values to achieve a targeted or a user-specified selection response for multiple traits. This targeted selection response can be constrained or unconstrained for either a subset or all the studied traits. Results: We tested the method using genomic estimated breeding values (GEBVs) for seven traits in a bread wheat (Triticum aestivum) reference breeding population comprising 3,331 lines and achieved prediction accuracies ranging between 0.29 and 0.47 across the seven traits. The indices were validated using 3,005 double haploid lines that were derived from crosses between parents selected from the reference population. We tested three user-specified response scenarios: a constrained equal weight (INDEX1), a constrained yield dominant weight (INDEX2), and an unconstrained weight (INDEX3). Our method achieved an equivalent response to the user-specified selection response when constraining a set of traits, and this response was much better than the response of the traditional desired gain selection indices method without iteration. Interestingly, when using unconstrained weight, our iterative method maximised the selection response and shifted the average GEBVs of the selection candidates towards the desired direction. Discussion: Our results show that the method is an optimal choice not only when economic weights are unavailable, but also when constraining the selection response is an unfavourable option. [ABSTRACT FROM AUTHOR]

Spring wheat (Triticum aestivum L.) remains an important alternative to winter wheat cultivation at Northern latitudes due to high risk of overwintering or delayed sowing of winter wheat. We studied nine major agronomic traits in a set of 299 spring wheat genotypes in trials across 12-year-site combinations in Lithuania, Latvia, Estonia, and Norway for three consecutive years. The dataset analyzed here consisted of previously published phenotypic data collected in 2021 and 2022, supplemented with additional phenotypic data from the 2023 field season collected in this study. We combined these phenotypic datasets with previously published genotypic data generated using a 25K single nucleotide polymorphism (SNP) array that yielded 18,467 markers with a minor allele frequency above 0.05. Analysis of these datasets via genome-wide association study revealed 18 consistent quantitative trait loci (QTL) replicated in two or more trials that explained more than 5% of phenotypic variance for plant height, grain protein content, thousand kernel weight, or heading date. The most consistent markers across the tested environments were detected for plant height, thousand kernel weight, and days to heading in eight, five, and six trials, respectively. No beneficial effect of the semi-dwarfing alleles Rht-B1b and Rht-D1b on grain yield performance was observed across the 12 tested trials. Moreover, the cultivars carrying these alleles were low yielding in general. Based on principal component analysis, wheat genotypes developed in the Northern European region clustered separately from those developed at the southern latitudes, and markers associated with the clustering were identified. Important phenotypic traits, such as grain yield, days to heading, grain protein content, and thousand kernel weight were associated with this clustering of the genotype sets. Interestingly, despite being adapted to the Nordic environment, genotypes in the Northern set demonstrated lower grain yield performance across all tested environments. The results indicate that spring wheat germplasm harbors valuable QTL/alleles, and the identified traitmarker associations might be useful in improving Nordic-Baltic spring wheat germplasm under global warming conditions. [ABSTRACT FROM AUTHOR]

Rapidly obtaining the chlorophyll content of crop leaves is of great significance for timely diagnosis of crop health and effective field management. Multispectral imagery obtained from unmanned aerial vehicles (UAV) is being used to remotely sense the SPAD (Soil and Plant Analyzer Development) values of wheat crops. However, existing research has not yet fully considered the impact of different growth stages and crop populations on the accuracy of SPAD estimation. In this study, 300 materials from winter wheat natural populations in Xinjiang, collected between 2020 to 2022, were analyzed. UAV multispectral images were obtained in the experimental area, and vegetation indices were extracted to analyze the correlation between the selected vegetation indices and SPAD values. The input variables for the model were screened, and a support vector machine (SVM) model was constructed to estimate SPAD values during the heading, flowering, and filling stages under different water stresses. The aim was to provide a method for the rapid acquisition of winter wheat SPAD values. The results showed that the SPAD values under normal irrigation were higher than those under water restriction. Multiple vegetation indices were significantly correlated with SPAD values. In the prediction model construction of SPAD, the different models had high estimation accuracy under both normal irrigation and water limitation treatments, with correlation coefficients of predicted and measured values under normal irrigation in different environments the value of r from 0.59 to 0.81 and RMSE from 2.15 to 11.64, compared to RE from 0.10% to 1.00%; and under drought stress in different environments, correlation coefficients of predicted and measured values of r was 0.69--0.79, RMSE was 2.30--12.94, and RE was 0.10%--1.30%. This study demonstrated that the optimal combination of feature selection methods and machine learning algorithms can lead to a more accurate estimation of winter wheat SPAD values. In summary, the SVM model based on UAV multispectral images can rapidly and accurately estimate winter wheat SPAD value. [ABSTRACT FROM AUTHOR]

Powdery mildew caused by Blumeria graminis f. sp. tritici (Bgt) seriously threatens wheat production worldwide. It is imperative to identify novel resistance genes from wheat and its wild relatives to control this disease by host resistance. Dasypyrum villosum (2n = 2x = 14, VV) is a relative of wheat and harbors novel genes for resistance against multi-fungal diseases. In the present study, we developed a complete set of new wheat-D. villosum disomic introgression lines through genomic in situ hybridization (GISH), fluorescence in situ hybridization (FISH) and molecular markers analysis, including four disomic substitution lines (2n=42) containing respectively chromosomes 1V#6, 2V#6, 3V#6, and 6V#6, and four disomic addition lines (2n=44) containing respectively chromosomes 4V#6, 5V#6, 6V#6 and 7V#6. These lines were subsequently evaluated for their responses to a mixture Bgt isolates at both seedling and adultplant stages. Results showed that introgression lines containing chromosomes 3V#6, 5V#6, and 6V#6 exhibited resistance at both seedling and adult-plant stages, whereas the chromosome 4V#6 disomic addition line NAU4V#6-1 exhibited a high level of adult plant resistance to powdery mildew. Moreover, two translocation lines were further developed from the progenies of NAU4V#6- 1 and the Ph1b mutation line NAU0686-ph1b. They were T4DL·4V#6S wholearm translocation line NAU4V#6-2 and T7DL·7DS-4V#6L small-fragment translocation line NAU4V#6-3. Powdery mildew tests of the two lines confirmed the presence of an adult-plant powdery mildew resistance gene, Pm4VL, located on the terminal segment of chromosome arm 4V#6L (FL 0.6- 1.00). In comparison with the recurrent parent NAU0686 plants, the T7DL·7DS- 4V#6L translocation line NAU4V#6-3 showed no obvious negative effect on yield-related traits, providing a new germplasm in breeding for resistance. [ABSTRACT FROM AUTHOR]

The number of wheat spikes has an important influence on wheat yield, and the rapid and accurate detection of wheat spike numbers is of great significance for wheat yield estimation and food security. Computer vision and machine learning have been widely studied as potential alternatives to human detection. However, models with high accuracy are computationally intensive and time consuming, and lightweight models tend to have lower precision. To address these concerns, YOLO-FastestV2 was selected as the base model for the comprehensive study and analysis of wheat sheaf detection. In this study, we constructed a wheat target detection dataset comprising 11,451 images and 496,974 bounding boxes. The dataset for this study was constructed based on the Global Wheat Detection Dataset and the Wheat Sheaf Detection Dataset, which was published by PP Flying Paddle. We selected three attention mechanisms, Large Separable Kernel Attention (LSKA), Efficient Channel Attention (ECA), and Efficient Multi-Scale Attention (EMA), to enhance the feature extraction capability of the backbone network and improve the accuracy of the underlying model. First, the attention mechanism was added after the base and output phases of the backbone network. Second, the attention mechanism that further improved the model accuracy after the base and output phases was selected to construct the model with a two-phase added attention mechanism. On the other hand, we constructed SimLightFPN to improve the model accuracy by introducing SimConv to improve the LightFPN module. The results of the study showed that the YOLO-FastestV2-SimLightFPN-ECA-EMA hybrid model, which incorporates the ECA attention mechanism in the base stage and introduces the EMA attention mechanism and the combination of SimLightFPN modules in the output stage, has the best overall performance. The accuracy of the model was P=83.91%, R=78.35%, AP= 81.52%, and F1 = 81.03%, and it ranked first in the GPI (0.84) in the overall evaluation. The research examines the deployment of wheat ear detection and counting models on devices with constrained resources, delivering novel solutions for the evolution of agricultural automation and precision agriculture. [ABSTRACT FROM AUTHOR]

Introduction: Targeted herbicide application refers to precise application of herbicides in weed-infested areas according to the location and density of farmland weeds. At present, targeted herbicide application in wheat fields generally faces problems including the low herbicide adhesion rate, leading to omission and excessive loss of herbicides. Methods: To solve these problems, changes in the impact force of herbicide and the weed leaves in the operation process of a spraying system were studied from the interaction between weeds and herbicides applied. A dynamic model of weed leaves was established. On this basis, the research indicated that the herbicide adhesion rate is highest under spraying pressure of 0.4 MPa and flow rate of 0.011 kg/s when the spray height is 300 mm. To study the dynamic deformation of weed leaves and the distribution of liquid herbicides in the external flow field under weed-herbicide interaction, a dynamic simulation model of herbicide application was built using the finite element method. Results and Discussion: The results show that when the spray height is 300 mm, the maximum weed leaf deformation index (LDI) is 0.43 and the velocity in the external flow field is 0 m/s under spraying pressure of 0.4 MPa and flow rate of 0.011 kg/s. This finding indicates that the herbicide is not splashed elsewhere and the turbulence intensity in the weed area is 2%, implying steady flow of the herbicide, most of which can be retained on weed leaves. Field test results of application quality of the herbicide show that the maximum LDI is 0.41 and the coverage of the herbicide in the sheltered area below the leaves is 19.02% when the spraying pressure is 0.4 MPa, flow rate is 0.011 kg/s, and spray height is 300 mm. This solves the problem of a low rate of utilization of herbicides because the herbicide passes through weed plants, and achieves the precision herbicide application in wheat fields. [ABSTRACT FROM AUTHOR]

This article explores the potential benefits of using zinc lysine and biochar to enhance the growth and physiological performance of wheat plants under saline stress. The study found that the combined application of biochar and zinc lysine significantly improved various physiological attributes and reduced oxidative stress indicators. The authors suggest that this combined treatment could be a practical solution to mitigate salt stress in plants, but further field studies are needed to validate these findings. The document also includes a list of references that library patrons can use to further explore topics related to plant stress and agricultural practices. [Extracted from the article]

The goal of public breeding programs is to develop and disseminate improved varieties to farmers. This strategy aims at providing farming communities with superior crop varieties than they are growing. However, the strategy rarely considers the needs and preferences of farmers, especially gendered preferences, failing to solve real field problems by addressing the differences and inequalities prevalent in the farming communities. Our research examines how personal, household, agronomic and ecological characteristics of wheat growers in Bihar, India's eastern Indo-Gangetic Plains, affect women and men's wheat trait choices. Data were obtained from 1,003 households where both male and female respondents from the same household were interviewed. We accounted for 23 traits of wheat from a careful assessment of production, environment, cooking quality, market demand, and esthetic criteria. Binomial logistic regression was used to determine women's and men's trait preferences. The results imply that gender influences the preferences of wheat traits. Some traits are favored by both women and men, however, in other instances, there are striking disparities. For example, men choose wheat varieties that are well adapted to extreme climate conditions, have a higher grain yield, and produce chapati with a superior taste, while women prefer wheat types with superior chapati making quality, higher grain yield, and high market prices. Other socioeconomic, agronomic, cultural, and geolocational factors have a considerable impact on trait preferences. These human dimensions of traits preferred by women and men farmers are important for trait combinations to develop breeding product profiles for certain market segments. [ABSTRACT FROM AUTHOR]

Enhancing grain yield is a primary goal in the cultivation of major staple crops, including wheat. Recent research has focused on identifying the physiological and molecular factors that influence grain weight, a critical determinant of crop yield. However, a bottleneck has arisen due to the trade-off between grain weight and grain number, whose underlying causes remain elusive. In a novel approach, a wheat expansin gene, TaExpA6, known for its expression in root tissues, was engineered to express in the grains of the spring wheat cultivar Fielder. This modification led to increases in both grain weight and yield without adversely affecting grain number. Conversely, a triple mutant line targeting the gene TaGW2, a known negative regulator of grain weight, resulted in increased grain weight but decreased grain number, potentially offsetting yield gains. This study aimed to evaluate the two aforementioned modified wheat genotypes (TaExpA6 and TaGW2) alongside their respective wild-type counterparts. Conducted in southern Chile, the study employed a Complete Randomized Block Design with four replications, under well-managed field conditions. The primary metrics assessed were grain yield, grain number, and average grain weight per spike, along with detailed measurements of grain weight and dimensions across the spike, ovary weight at pollination (Waddington’s scale 10), and post-anthesis expression levels of TaExpA6 and TaGW2. Results indicated that both the TaExpA6 and the triple mutant lines achieved significantly higher average grain weights compared to their respective wild types. Notably, the TaExpA6 line did not exhibit a reduction in grain number, thereby enhancing grain yield per spike. By contrast, the triple mutant line showed a reduced grain number per spike, with no significant change in overall yield. TaExpA6 expression peaked at 10 days after anthesis (DAA), and its effect on grain weight over the WT became apparent after 15 DAA. In contrast, TaGW2 gene disruption in the triple mutant line increased ovary size at anthesis, leading to improved grain weight above the WT from the onset of grain filling. These findings suggest that the trade-off between grain weight and number could be attributed to the overlapping of the critical periods for the determination of these traits. [ABSTRACT FROM AUTHOR]

The tolerance to salinity stress is an intricate phenomenon at cellular and whole plant level that requires the knowledge of contributing physiological and biochemical processes and the genetic control of participating traits. In this context, present study was conducted with objective to evaluate the physiological, biochemical, and genetic responses of different wheat genotypes including bread wheat (BW) and synthetic hexaploids (SHs) under saline and control environment. The experiment was conducted in two factorial arrangement in randomized complete block design (RCBD), with genotypes as one factor and treatments as another factor. A significant decline in physiological traits (chlorophyll, photosynthesis, stomatal conductance, transpiration, and cell membrane stability) was observed in all genotypes due to salt stress; however, this decline was higher in BW genotypes as compared to four SH genotypes. In addition, the biochemical traits including enzymes [superoxide dismutase, catalase, and peroxidase (POD)] activity, proline, and glycine betaine (GB) illustrated significant increase along with increase in the expression of corresponding genes (TaCAT1, TaSOD, TaPRX2A, TaP5CS, and TaBADH-A1) due to salt stress in SHs as compared to BW. Correspondingly, highly overexpressed genes, TaHKT1;4, TaNHX1, and TaAKT1 caused a significant decline in Na+/K+ in SH as compared to BW genotypes under salt stress. Moreover, correlation analysis, principal component analysis (PCA), and heatmap analysis have further confirmed that the association and expression of physiological and biochemical traits varied significantly with salinity stress and type of genotype. Overall, the physiological, biochemical, and genetic evaluation proved SHs as the most useful stock for transferring salinity tolerance to other superior BW cultivars via the right breeding program. [ABSTRACT FROM AUTHOR]

In crops like wheat, terminal drought is one of the principal stress factors limiting productivity in rain-fed systems. However, little is known about root development after heading, when water uptake can be critical to wheat crops. The impact of water-stress on root growth was investigated in two wheat cultivars, Scout and Mace, under well-watered and post-anthesis water stress in three experiments. Plants were grown outside in 1.5-m long pots at a density similar to local recommended farming practice. Differences in root development were observed between genotypes, especially for water stress conditions under which Scout developed and maintained a larger root system than Mace. While under well-watered conditions both genotypes had shallow roots that appeared to senesce after heading, a moderate water stress stimulated shallow-root growth in Scout but accelerated senescence in Mace. For deep roots, post-heading biomass growth was observed for both genotypes in well-watered conditions, while under moderate water stress, only Scout maintained net growth as Mace deep roots senesced. Water stress of severe intensity affected both genotypes similarly, with root senescence at all depths. Senescence was also observed above ground. Under well-watered conditions, Scout retained leaf greenness (i.e. stay-green phenotype) for slightly longer than Mace. The difference between genotypes accentuated under moderate water stress, with rapid post-anthesis leaf senescence in Mace while Scout leaf greenness was affected little if at all by the stress. As an overall result, grain biomass per plant (‘yield’) was similar in the two genotypes under well-watered conditions, but more affected by a moderate stress in Mace than Scout. The findings from this study will assist improvement in modelling root systems of crop models, development of relevant phenotyping methods and selection of cultivars with better adaptation to drought. [ABSTRACT FROM AUTHOR]

Both subsoiling tillage (ST) and ridge and furrow rainfall harvesting (RF) are widely implemented and play an important role in boosting wheat productivity. However, information about the effects of ST coupled with RF during the summer fallow season on wheat productivity and environmental issues remains limited. This study aims to explore the effects of ST coupled with RF on water harvesting, wheat productivity-yield traits, water and nutrient use efficiency and quality, and soil nitrate-N residue in dryland winter wheat-summer fallow rotation at the intersection of southern Loess Plateau and western Huang-Huai-Hai Plain in China in 2018-2022. Three tillage practices--deep plowing with straw turnover (PTST), subsoiling with straw mulching (STSM), and STSMcoupled with RF (SRFSM)-- are conducted during the summer fallow season. The results indicated that tillage practices during the summer fallow season significantly impacted wheat productivity and soil nitrate-N residue. Compared to PTST, STSM significantly enhanced rainfall fallow efficiency and water use efficiency by 7.0% and 14.2%, respectively, as well as N, P, and K uptake efficiency by 16.9%, 16.2%, and 15.3%, and thus increased grain yield by 14.3% and improved most parameters of protein components and processing quality, albeit with an increase in nitrate-N residue in the 0- to 300-cm soil depth by 12.5%. SRFSM, in turn, led to a further increase in water storage at sowing, resulting in an increase of water use efficiency by 6.8%, as well as N, P, and K uptake efficiency and K internal efficiency by 11.8%, 10.4%, 8.8%, and 4.7%, thereby significantly promoting grain yield by 10.2%, and improving the contents of all the protein components and enhancing the processing quality in grain, and simultaneously reducing the nitrate-N residue in the 0- to 300-cm soil layer by 16.1%, compared to STSM. In essence, this study posits that employing subsoiling coupled with ridge-furrow rainfall harvesting (SRFSM) during the summer fallow season is a promising strategy for enhancing wheat yield, efficiency, and quality, and simultaneously reducing soil nitrate-N residue within the dryland summer fallow-winter wheat rotation system. [ABSTRACT FROM AUTHOR]

Canopy height serves as an important dynamic indicator of crop growth in the decision-making process of field management. Compared with other commonly used canopy height measurement techniques, ultrasonic sensors are inexpensive and can be exposed in fields for long periods of time to obtain easy-to-process data. However, the acoustic wave characteristics and crop canopy structure affect the measurement accuracy. To improve the ultrasonic sensor measurement accuracy, a four-year (2018-2021) field experiment was conducted on maize and wheat, and a measurement platform was developed. A series of single-factor experiments were conducted toinvestigate the significant factors affectingmeasurements, including the observation angle (0-60°), observation height (0.5-2.5 m), observation period (8:00 -18:00), platform moving speed with respect to the crop (0-2.0 m min-1), planting density (0.2-1 time of standard planting density), and growth stage (maize from three -leaf to harvest period and wheat from regreening to maturity period). The results indicated that both the observation angle and planting density significantly affected the results of ultrasonic measurements (p-value< 0.05), whereas the effects of other factors on measurement accuracy were negligible (p-value > 0.05). Moreover, a double-input factor calibrationmodelwasconstructed to assess canopy heightunder different years by utilizing the normalized difference vegetation index and ultrasonic measurements. The model was developed by employing the least-squares method, and ultrasonic measurement accuracy was significantly improved when integrating themeasured value of canopy heights and the normalized difference vegetation index (NDVI). The maize measurement accuracy had a root mean squared error (RMSE) ranging from 81.4 mm to 93.6 mm, while the wheat measurement accuracy had an RMSE from 37.1mmto 47.2mm. The research results effectively combine stable and low-cost commercial sensors with ground-based agricultural machinery platforms, enabling efficient and non-destructive acquisition of crop height information. [ABSTRACT FROM AUTHOR]

Enlarging the lateral space of drip tubes saves irrigation equipment costs (drip tubes and bypass), but it will lead to an increased risk of grain yield heterogeneity between wheat rows. Adjusting wheat row spacing is an effective cultivation measure to regulate a row's yield heterogeneity. During a 2-year field experiment, we investigated the variations in yield traits and photosynthetic physiology by utilizing two different water- and fertilizer-demanding spring wheat cultivars (NS22 and NS44) under four kinds of drip irrigation patterns with different drip tube lateral spacing and wheat row spacing [① TR4, drip tube spacing (DTS) was 60 cm, wheat row horizontal spacing (WRHS) was 15 cm; ② TR6, DTS was 90 cm, WRHS was 15 cm; ③ TR6L, DTS was 90 cm, WRHS was 10 cm, inter-block spacing (IBS) was 35 cm; and ④ TR6S, DTS was 80 cm, WRHS was 10 cm, IBS was 25 cm]. The results showed that under 15-cm equal row spacing condition, after the number of wheat rows served by a single tube increased from four (TR4, control) to six (TR6), NS22 and NS44 exhibited a marked decline in yield. The decline of NS22 (9.93%) was higher than that of NS44 (9.04%), and both cultivars also showed a greater decrease in grain weight and average grain-filling rate (AGFR) of inferior grains (NS22: 23.19%, 13.97%; NS44: 7.78%, 5.86%) than the superior grains (NS22: 10.60%, 8.33%; NS44: 4.89%, 4.62%). After the TR6 was processed to narrow WRHS (from 15 to 10 cm) and add IBS (TR6L: 35 cm; TR6S: 25 cm), the grain weight per panicle (GWP) and AGFR of superior and inferior grains in the third wheat row (RW3) of NS22 and NS44 under TR6L increased significantly by 26.05%, 8.22%, 14.05%, 10.50%, 5.09%, and 5.01%, respectively, and under TR6S, they significantly increased by 20.78%, 9.91%, 16.19%, 9.28%, 5.01%, and 4.14%, respectively. The increase in GWP and AGFR was related to the increase in flag leaf area, net photosynthetic rate, chlorophyll content, relative water content, actual photochemical efficiency of PSII, and photochemical quenching coefficient. Among TR4, TR6, TR6L, and TR6S, for both NS22 and NS44, the yield of TR6S was significantly higher than that of TR6 and TR6L. Furthermore, TR6S showed the highest economic benefit. [ABSTRACT FROM AUTHOR]

The source-sink (S-S) ratio during the grain-filling period is crucial for wheat crop yield. The aim of this study was to investigate the relative sensitivity of grain yield in response to treatments of S-S ratio changes to determine the extent of SS limitation during grain filling in modern wheat genotypes. The S-S manipulation treatments included four levels: check (CH), removal of flag leaf (RFL), removal of all leaves (RAL), and removal of the upper half of the spikes (RHS). The results showed significant differences between genotypes (pb< 0.001%) in all traits. Drought stress decreased grain weight per spike (GWS) (g) and grain yield (GY) (kg/ha) by 18% and 25%, respectively. The average reduction in GWS under irrigation and rainfed conditions was 8.25% and 6.71% for RFL and 12.25% and 11.15% for RAL, respectively. By RFL and RAL, increasing the remobilization from the stem and spike straw helped to reduce the effects of source limitation. Also, by RHS, the reduction in photosynthetic materials production in both conditions was only equivalent to 38% and 29% of the expected values, respectively, which shows the presence of strong sinks in vegetative organs (stem and spike) compared to grains. Vegetative organs seem to have a larger sink for the uptake of photosynthetic materials than grains when the source-sink ratio increases. However, high-yield genotypes showed more severe source limitation, while low-yield genotypes showed more relative sink limitation. Overall, to increase the yield potential in high-yielding genotypes, photosynthetic sources and sinks in low-yielding genotypes should be improved. [ABSTRACT FROM AUTHOR]

Aims: Root system architecture (RSA) plays an important role in the plant’s ability to sustain yield under abiotic stresses such as drought. Preceding crops (precrops) can affect the yield of the proceeding crop, partially by affecting the RSA. This experiment aims to explore the interactions between precrop identity, crop genotype and drought at early growth stages. Methods: Rhizotrons, sized 60 × 80 × 3.5 cm, were used to assess the early root growth of two winter wheat (Triticum aestivum L.) genotypes, using precroptreated soil around the seedlings and differing water regimes. The rhizotrons were automatically imaged 3 times a week to track root development. Results: Precrop-treated soil affected the RSA and changes caused by the reduced water treatment (RWT) were different depending on the precrop. Largest of these was the 36% reduction in root depth after wheat, but 44% after OSR. This indicates that effects caused by the precrop can be simulated, at least partially, by transferring precrop-treated soils to controlled environments. The genotypes had differential RSA and reacted differently to the RWT, with Julius maintaining an 8.8-13.1% deeper root system compared to Brons in the RWT. In addition, the combined environmental treatment affected the genotypes differently. Conclusion: Our results could help explain discrepancies found from using precrops to enhance yield as they indicate differences in the preceding crop effect when experiencing drought stress. Further, these differences are affected by genotypic interactions, which can be used to select and adapt crop genotypes for specific crop rotations, depending on the year. Additionally, we have shown a viable method of stimulating a partial precrop effect at the seedling stage in a controlled greenhouse setting using field soil around the germinated seed. [ABSTRACT FROM AUTHOR]

Climate change is one of the main challenges, and it poses a tough challenge to the agriculture industry globally. Additionally, greenhouse gas (GHG) emissions are the main contributor to climate change; however, croplands are a prominent source of GHG emissions. Yet this complex challenge can be mitigated through climate-smart agricultural practices. Conservation tillage is commonly known to preserve soil and mitigate environmental change by reducing GHG emissions. Nonetheless, there is still a paucity of information on the influences of conservation tillage on wheat yield, soil properties, and GHG flux, particularly in the semi-arid Dingxi belt. Hence, in order to fill this gap, different tillage systems, namely conventional tillage (CT) control, straw incorporation with conventional tillage (CTS), no-tillage (NT), and stubble return with no-tillage (NTS), were laid at Dingxi, Gansu province of China, under a randomized complete block design with three replications to examine their impacts on yield, soil properties, and GHG fluxes. Results depicted that different conservative tillage systems (CTS, NTS, and NT) significantly (p < 0.05) increased the plant height, number of spikes per plant, seed number per meter square, root yield, aboveground biomass yield, thousand-grain weight, grain yield, and dry matter yield compared with CT. Moreover, these conservation tillage systems notably improved the soil properties (soil gravimetric water content, water-filled pore space, water storage, porosity, aggregates, saturated hydraulic conductivity, organic carbon, light fraction organic carbon, carbon storage, microbial biomass carbon, total nitrogen, available nitrogen storage, microbial biomass nitrogen, total phosphorous, available phosphorous, total potassium, available potassium, microbial counts, urease, alkaline phosphatase, invertase, cellulase, and catalase) while decreasing the soil temperature and bulk density over CT. However, CTS, NTS, and NT had non-significant effects on ECe, pH, and stoichiometric properties (C:N ratio, C:P ratio, and N:P ratio). Additionally, conservation-based tillage regimes NTS, NT, and CTS significantly (p < 0.05) reduced the emission and net global warming potential of greenhouse gases (carbon dioxide, methane, and nitrous oxide) by 23.44, 19.57, and 16.54%, respectively, and decreased the greenhouse gas intensity by 23.20, 29.96, and 18.72%, respectively, over CT. We conclude that NTS is the best approach to increasing yield, soil and water conservation, resilience, and mitigation of agroecosystem capacity. [ABSTRACT FROM AUTHOR]

Introduction: With increasing demand for food and changing environmental conditions, a better understanding of the factors impacting wheat yield is essential for ensuring food security and sustainable agriculture. By analyzing the effect of multiple factors on wheat yield, the presented research provides novel insights into the potential impacts of climate change on wheat production in India. In the present study, datasets consisting of countrywide environmental and agronomic factors and wheat yield were collected. In addition, the study also analyzes the effect of information demand of farmers on production. Methodology: The study employs a regional analysis approach by dividing the country into five zonal clusters: Northern Hills, Central India, Indo-Gangetic Plains, North-Eastern India, and Peninsular India. Correlation and Principal Component Analysis (PCA) were performed to uncover the month-wise key factors affecting wheat yield in each zone. Furthermore, four Machine Learning/Deep Learning-based models, including XGBoost, Multi-layer Perceptron (MLP), Gated Recurrent Unit (GRU), and 1-D Convolutional Neural Network (CNN), were developed to estimate wheat yield. This study estimated partial derivatives for all factors using Newton's Quotient Technique, a numerical method-based approach. Results: The analysis focused on applying this technique to the best-performing wheat yield estimation model, which was the GRU-based model (with RMSE and MAE of 0.60 t/ha and 0.46 t/ha, respectively). Discussion: In the later sections of the article, multiple policy recommendations are communicated based on the extracted insights. The results of the presented research help inform decision-making regarding the development of strategies and policies to mitigate the impacts of climate change on wheat production in India. [ABSTRACT FROM AUTHOR]

Integrating high-throughput phenotyping (HTP) based traits into phenomic and genomic selection (GS) can accelerate the breeding of high-yielding and climate-resilient wheat cultivars. In this study, we explored the applicability of Unmanned Aerial Vehicles (UAV)-assisted HTP combined with deep learning (DL) for the phenomic or multi-trait (MT) genomic prediction of grain yield (GY), test weight (TW), and grain protein content (GPC) in winter wheat. Significant correlations were observed between agronomic traits and HTP-based traits across different growth stages of winter wheat. Using a deep neural network (DNN) model, HTP-based phenomic predictions showed robust prediction accuracies for GY, TW, and GPC for a single location with R2 of 0.71, 0.62, and 0.49, respectively. Further prediction accuracies increased (R2 of 0.76, 0.64, and 0.75) for GY, TW, and GPC, respectively when advanced breeding lines from multi-locations were used in the DNN model. Prediction accuracies for GY varied across growth stages, with the highest accuracy at the Feekes 11 (Milky ripe) stage. Furthermore, forward prediction of GY in preliminary breeding lines using DNN trained on multi-location data from advanced breeding lines improved the prediction accuracy by 32% compared to single-location data. Next, we evaluated the potential of incorporating HTP-based traits in multi-trait genomic selection (MT-GS) models in the prediction of GY, TW, and GPC. MTGS, models including UAV data-based anthocyanin reflectance index (ARI), green chlorophyll index (GCI), and ratio vegetation index 2 (RVI_2) as covariates demonstrated higher predictive ability (0.40, 0.40, and 0.37, respectively) as compared to single-trait model (0.23) for GY. Overall, this study demonstrates the potential of integrating HTP traits into DL-based phenomic or MT-GS models for enhancing breeding efficiency. [ABSTRACT FROM AUTHOR]

Wheat is a major food crop that plays a crucial role in the human diet. Various breeding technologies have been developed and refined to meet the increasing global wheat demand. Several studies have suggested breeding strategies that combine generation acceleration systems and molecular breeding methods to maximize breeding efficiency. However, real-world examples demonstrating the effective utilization of these strategies in breeding programs are lacking. In this study, we designed and demonstrated a synergized breeding strategy (SBS) that combines rapid and efficient breeding techniques, including speed breeding, speed vernalization, phenotypic selection, backcrossing, and marker-assisted selection. These breeding techniques were tailored to the specific characteristics of the breeding materials and objectives. Using the SBS approach, from artificial crossing to the initial observed yield trial under field conditions only took 3.5 years, resulting in a 53% reduction in the time required to develop a BC2 nearisogenic line (NIL) and achieving a higher recurrent genome recovery of 91.5% compared to traditional field conditions. We developed a new wheat NIL derived from cv. Jokyoung, a leading cultivar in Korea. Milyang56 exhibited improved protein content, sodium dodecyl sulfate-sedimentation value, and loaf volume compared to Jokyoung, which were attributed to introgression of the Glu-B1i allele from the donor parent, cv. Garnet. SBS represents a flexible breeding model that can be applied by breeders for developing breeding materials and mapping populations, as well as analyzing the environmental effects of specific genes or loci and for trait stacking. [ABSTRACT FROM AUTHOR]

The judicious management of water and nitrogen (N) is pivotal for augmenting crop productivity and N use efficiency, while also mitigating environmental concerns. With the advent of the High-Farmland Construction Program in China, one-off irrigation has become feasible for most dryland fields, presenting a novel opportunity to explore the synergistic strategies of water and N management. This study delves into the impact of one-off alternate furrow irrigation (AFI) and topdressing N fertilizer (TN) on soil nitrate-N distribution, and N productivity--including plant N accumulation, translocation, and allocation, and grain yield, protein content, N use efficiency of winter wheat (Triticum aestivum L.) in 2018-2019 and 2019-2020. Experimental treatments administered at the jointing stage comprised of two irrigation methods--every (EFI) and alternative (AFI) furrow irrigation at 75 mm, and two topdressing N rates--0 (NTN) and60 (TN) kgNha-1. Additionally, a conventional local farmer practice featuring no irrigation and no topdressing N (NINTN) was served as control. Compared to NINTN, EFINTN substantially increased aboveground N accumulation, grain yield, and protein yield, albeit with a reduction in grain protein content by 8.1%-10.6%. AFI, in turn, led to higher nitrate-N accumulation in the 60-160 cm soil depth at booting and anthesis, but diminished levels at maturity, resulting in a significant surge in N accumulation from anthesis to maturity and its contribution to grain, N fertilizer partial factor productivity (PFPN), and N uptake efficiency (NUPE), thereby promoting grain yield by 9.9% and preserving grain protein content. Likewise, TN enhanced soil nitrate-Nat keygrowth stages, reflected in marked improvements in N accumulation both from booting to anthesis and from anthesis to maturity, as well as in grain yield, protein content, and protein yield. The combination of AFI and TN (AFITN) yielded the highest grain yield, protein content, with PFPN, NUPE, and N internal efficiency outstripping those of EFINTN, but not AFINTN. In essence, one-off AFI coupled with TN at the jointing stage is a promising strategy for optimizing soil nitrate-N and enhancing wheat N productivity in dryland where one-off irrigation is assured. [ABSTRACT FROM AUTHOR]