Wheat is the main food crop ensuring food production safety and boosting high quality development of agriculture in China, and the improvement of wheat quality becomes more and more urgent. The quality traits of wheat are complex. After years of genetic improvement, important progress has been made in the study of wheat quality traits, but the wheat quality improvement in China is still at a low level. In this paper, the research status of several important quality traits of wheat was briefly summarized, with the focus on the genetic improvement of traits that control the nutritional quality and processing quality of wheat. The paper mainly analyzed the genetic characteristics of wheat protein content, gluten content, starch content and sedimentation value, and reviewed the molecular genetic laws of each quality trait and the main genes related to regulation. With the development of molecular biology and biotech nology, the genetic regulation of wheat quality traits is clear, and molecular design breeding can be used as a key research method in the future.

【Objective】The yield of wheat, the second-highest-yielding food product in the world, has a major impact by grain weight. This research used materials from a recombinant inbred line (RIL) population derived from Heshangtou (HST) and Longchun 23 (LC23). Based on 55K SNP genotype data, QTL mapping was performed for traits related to grain weight of wheat, and co-segregation markers of major grain length QTL were developed and verified to provide reference for molecular marker assisted selection breeding.【Method】The wheat 55K SNP microarray was used to genotype parents and RIL populations, and a high density genetic linkage map was constructed, and its correlation with Chinese spring reference genome IWGSC RefSeq v1.0 was analyzed. QTL mapping of traits related to grain weight in multiple environments based on inclusive composite interval mapping method. The analysis of variance of major effect QTLs were performed to judge the additive interaction effect among different QTLs, and to analyse its effect on traits related to grain weight. At the same time, the corresponding kompetitive allele specific PCR marker was developed according to the closely linked SNP loci of major QTL for grain length, and verified in 242 wheat accessions worldwide.【Result】In this study, a high density genetic map of Heshangtou/Longchun 23 RIL population was constructed, with full length 4 543 cM, including 22 linkage groups, covering 21 chromosomes of wheat, and the average genetic distance was 1.7 cM. There was a significant correlation between genetic map and physical map, and the Pearson correlation coefficient were 0.77-0.99 (P<0.001). A total of 51 QTLs related to grain weight were detected, among them, 4 stable major QTLs were found in multi-environments (three or more environments) and distributed on 2D, 5A, 6B and 7D chromosomes. According to the physical interval and functional markers, it is inferred that stable major QTLs Qtkw.nwafu-2D.1 and Qtkw.nwafu-7D are photoperiod gene Ppd-D1 and flowering gene FT-D1, respectively. The analysis of variance shows that there is a significant interaction between them. The favorite alleles polymerization of Qtkw.nwafu-2D.1 and Qtkw.nwafu-7D can significantly increase thousand grain weight and grain width of wheat. In addition, the corresponding KASP molecular detection marker AX-111067709 was developed based on the co-segregated SNP of the major locus Qgl.nwafu-5A for grain length, which was significantly correlated with grain length and grain weight traits in a diversity panel comprising of 242 wheat accessions, and could increase grain length by 3.33% to 4.59% and grain weight 5.70% to 10.35% in different environments (P<0.001).【Conclusion】There are several genetic loci that affect traits linked to grain weight in Heshangtou (HST) and Longchun 23 (LC23), and Qtkw.nwafu-2D.1 and Qtkw.nwafu-7D dramatically increased thousand grain weight and grain width through additive interaction effects. Qgl.nwafu-5A is significantly correlated with grain weight and grain length, and its co-segregated molecular marker AX-11106770 can be used in molecular marker assisted selection breeding.

【Objective】Plant roots are critical for water and nutrient acquisition, crop growth and development as well as yield formation. Exploring SNP loci significantly associated with root traits in wheat at seedling stage and mining candidate genes, will lay a foundation for understanding the genetic mechanism of wheat root system architecture and breeding wheat elite varieties with better root architecture.【Method】In this study, 189 diverse wheat cultivars were assembled as an association-mapping panel, five root traits including total root length (TRL), total root area (TRA), total root volume (TRV), average root diameter (ARD) and root dry weight (RDW) were investigated by growing in two culture conditions (Hoagland nutrient solution and pure water), and the experiments were repeated twice. Then, genome-wide association studies (GWAS) were performed for the five root traits with genotypic data derived from Wheat 660K SNP Array. Candidate genes were predicted by sequence alignment, domain analysis, and annotation information. Futhermore, kompetitive allele specific PCR (KASP) markers were developed for root traits. 【Result】The root traits varied greatly among the 189 cultivars, and the roots were thick and short cultured under Hoagland nutrient solution, while slender seminal roots and more lateral roots were observed under pure water. A total of 95 QTLs significantly associated with root traits cultured in two conditions (P<10^-3) were identified by genome-wide association studies with four models of BLINK (bayesian-information and linkage-disequilibrium iteratively nested keyway), CMLM (compressed mixed linear model), FarmCPU (fixed and random model circulating probability unification) and MLM (mixed linear model). Among them, 18 QTLs were detected in both culture conditions and distributed on chromosomes of 7A, 1B, 2B, 3B, 7B, 1D, 2D, and 3D, which explained 8.68%-14.07% of phenotypic variation. Of those significant loci, 4 QTLs were similar or consistent with that reported previously, and the rest were novel ones. Haplotype analysis conducted for co-localization QTLs of 10 SNPs revealed significant differences in root traits between the two haplotypes of wheat cultivars. Based on these SNPs, KASP markers XNR7143 and XNR3707 were developed for total root volume and root dry weight, respectively. In addition, 12 candidate genes possibly regulating root development were found by mining the genes within the interval of co-localization significant SNPs. Of them, TraesCS7A02G160600, encoding 3-oxoacyl-[acyl-carrier-protein] synthase, is involved in the synthesis of root fatty acids; TraesCS1B02G401800, encoding syntaxin, plays an important role in plant tropism; TraesCS7B02G417900, encoding aldehyde oxidase, contributes to the synthesis of abscisic acid and regulation of crop root development. 【Conclusion】The root traits of wheat varied significantly among the wheat genotypes. Genome-wide association studies detected 18 significant QTLs linked with root traits simultaneously in two culture conditions, two KASP markers were developed for root traits, and 12 candidate genes related to root development were screened, which might provide reference for understanding the regulation mechanism of wheat root traits and molecular marker-assisted breeding for wheat improvement.

In order to widely promote the newly approved wheat variety ‘Shannong 116' with high yield and strong gluten into production as soon as possible, we conducted an in-depth analysis from the genetic background of its hybrid parents, the performance of high and stable yield in regional trials, and the performance of strong gluten stability in many years of quality test results. The results showed that the yield of ‘Shannong 116' increased significantly compared with the control, the national test increased by 4.0% compared with ‘Zhoumai 18', and the Shandong test increased by 3.8% compared with ‘Jinan 17'. In the national wheat quality evaluation for four consecutive years from 2018 to 2021, the quality test indicators of ‘Shannong 116' all met the GB/T17892 standard for strong or medium gluten wheat. The plant height of ‘Shannong 116' is 76.9 cm, with compact plant type, neat ear layer and good ripening. It combines the excellent characteristics of the female parent of strong strength, disease resistance, early maturity and the male parent of high yield, water saving and lodging resistance. It is suitable for large-scale planting and market order acquisition and utilization in the Huang-huai wheat region.

【Objective】 The aim of this study is to screen the evaluation indexes of wheat source-sink and classify the source-sink types. In addition, the relationships between different source-sink types and the agronomic traits, yield and grain quality of wheat were also clarified, which provides a better understanding of wheat source-sink metabolism and wheat breeding. 【Method】 In this study, the related agronomic traits of source metabolism and sink metabolism of 190 wheat varieties which from different regions were measured. Then, the source-sink metabolic capacity of wheat was evaluated by principal component analysis, and the superior wheat materials were selected according to the composite score. Furthermore, the hierarchical clustering was conducted based on the source size (leaf area), source activity, sink number and sink activity. Then, based on the clustering results, the source-sink types of wheat were classified and the source-sink characteristics of different region of wheats were analyzed. Meanwhile, the agronomic, yield and quality traits of different wheat source-sink types were compared and analyzed. 【Result】 For better understanding the results, six indicators related to source activity were converted into three independent indicators (photochemical quenching coefficient, maximum photosynthetic potential, chlorophyll content), and five indicators related to sink activity were converted into two independent indicators (maximum filling rate, filling duration) based on the principal component analysis. The cumulative contributions of three source activity indicators and two sink activity indicators were 82.80% and 92.90%, respectively. Then the top 10 wheat varieties were screened based on the source activity, source size (leaf area), sink activity, and sink number (number of spike grains). According to the source-library relationship, all the wheat varieties were divided into three major categories and eight subcategories, including sufficient source-weak sink type (medium source-weak sink type, strong source-medium sink type), weak source-sufficient sink type (medium source-strong sink type, weak source-medium sink type) and source-sink balance type (weak source-weak sink type limited by sink activity, weak source-weak sink type limited by source activity and grain number per spike, medium source-medium sink type, and strong source-strong sink type). 76.84% of wheat lines were contained in three subcategories (weak source-weak sink type, the medium source-strong sink type, and strong source-strong sink type), other wheat lines were distributed in other subcategories evenly. Most wheat varieties of China showed similar source-sink relationship, which presented the medium level of source activity, leaf area and grain number per spike, while the sink activity was high. But the sink activity of wheat varieties which were cultivated at the middle and lower reaches of the Yangtze River is low. The plant height, length of uppermost internode and spikelet number in different categories indicated that the sufficient source-weak sink type>source-sink balance type>weak source-sufficient sink type, and the dry protein content, dry wet gluten content and sedimentation value in different categories showed that source-weak sink type > source-sink balance type > weak source-sufficient sink type. Grain water absorption showed that the stronger the sink activity had the higher the water absorption rate. The yield of per plant was different among different source-bank groups, but it was positively correlated with the source activity and the number of grains per spike in the three subcategories which contained most wheat varieties. 【Conclusion】 In this study, photochemical quenching coefficient, maximum photosynthetic potential and chlorophyll content could be used as the main indexes to evaluate the activity of wheat source. The maximum filling rate and filling duration could be used as the main indexes to evaluate the activity of wheat sink. In practical production, the wheat yield could be improved by increasing the number of grains per spike and the activity of source. When the supply capacity of source is stronger than the absorption capacity of sink, the plant height, peduncle length, spikelet number, dry protein content, dry wet gluten content and sedimentation value would be increased. Strong sink activity would help us to improve the water absorption of wheat grains.

This study analyzed the yield performance and composition factors of new elite wheat variety ‘Ruihuamai 520’ with high yield and good quality, aiming to provide a basis for its popularization. The high and stable yield of wheat variety ‘Ruihuamai 520’ was analyzed by using the national and provincial intermediate tests and multi-point data of large-scale application. The results showed that the yield point rate of ‘Ruihuamai 520’ reached 100% in regional trials of Jiangsu Province, the yield increasing point rate was 88.2% in the two-year test in the national regional trial; the mean variation coefficient was 7.16% and 12.2%, respectively, ranking the first and the seventh of the tested varieties. The value of variation coefficient was 494.97 and 618.97, respectively, ranking the second and the third of the tested varieties. The average number ears, the number of grains per ear and the weight of 1000 grains of the variety ‘Ruihuamai 520’ were (633.0 ± 64.5)×10 ⁴/hm², 31.1 ± 4.5 and 40.2 ± 3.0 g, respectively, indicating that the three factors of yield were coordinated and stable. The experiments show that wheat variety ‘Ruihuamai 520’ has high and stable yield, and good resistance to major diseases and natural disasters in southern Huanghuai area.

【Objective】Accurate monitoring and rational application of nitrogen are particularly important for healthy growth, yield and quality improvement of wheat, and reduction of environmental pollution and resource waste. The purpose of this study was to develop UAV-based models for accurately and effectively assessment of the plant nitrogen content in the key growth stages of wheat growth, and to explore the transferability of the models constructed based on machine learning methods. 【Method】Winter wheat experiment were conducted from 2020 to 2022 in Shangshui county, Henan province, China. Based on the K6 multichannel imager mounted on DJM600 UAV, 5-band (Red, Green, Blue, Rededge, and Nir) multispectral images were obtained from a UAV system in the stages of jointing, booting, flowering and filling in winter wheat, to calculate 20 vegetation indices and 40 texture features from different band combinations. Correlation analysis was used to screen the sensitive characteristics of nitrogen content in winter wheat plants from the 65 image features. Combining the sensitive spectral features and texture features of the nitrogen content of winter wheat plants, BP neural network (BP), random forest (RF), Adaboost, and support vector machine (SVR) machine learning regression methods were used to build plant nitrogen content models, and compared for the model performance and transferability. 【Result】(1)The correlation coefficients between plant nitrogen content and image features passed the test of 0.01 extremely significant level, including 22 spectral features and 29 texture features. (2) 51 spectral and texture features were adopted to build four machine learning models. The estimates of plant nitrogen by the RF and Adaboost methods were relatively concentrated, mostly close to the 1﹕1 line; while the estimations from the BP and SVR methods were relatively scattered. The RF method was the best, with R², RMSE, and MAE of 0.81, 0.42%, and 0.29%, respectively; The SVR method was the worst, with R², RMSE, and MAE of 0.66, 0.54% and 0.40%, respectively. (3) The prediction effects of the four methods on the nitrogen content of W0 and W1 treatments trained using W1 and W0 treatments were the same as those trained using both W0 and W1 datasets, both of which were closer to the 1﹕1 line for the RF and Adaboost methods. The R² of transfer prediction results for the models constructed by BP, RF, Adaboost, and SVR methods were 0.75, 0.72, 0.72, and 0.66 for the prediction of nitrogen content in W0 treatment and 0.51, 0.69, 0.61 (trained using data under W1 treatment) and 0.45 for the prediction under W1 treatment (trained using data under W0 treatment), respectively.【Conclusion】All models showed strong transferability, especially the RF and Adaboost methods, in predicting winter wheat nitrogen content under rainfed and irrigation water management.

Wheat stripe rust caused by Puccinia striiformis f. sp. tritici (Pst) is a devastating disease threaten food security in China and worldwide. Epidemics of wheat stripe rust have been under control through applying resistant cultivars and crop protection approaches. However, due to climate change, innovation of cropping system, improvement of breeding technology, yield level enhancement of wheat cultivars, variation in structure and frequency of virulence genes in Pst populations in the new era, the current status of stripe rust resistance genes in wheat breeding programs need to be evaluated. The results could provide useful information for applying stripe rust resistance genes to develop new wheat cultivars with broad-spectrum and durable rust resistance. After multiple year’s stripe rust resistance survey, genetic analysis, molecular tagging and mining of stripe rust resistance genes in wheat cultivars and advanced breeding lines, the current status of major stripe rust resistance genes utilization was reviewed. We summarized the present situations of major stripe rust resistance gene discovery and germplasm innovation, the most frequently used stripe rust resistance genes, new strategy for pyramiding adult plant partial resistance and all stage resistance, and molecular marker assisted selection for developing wheat cultivars with broad spectrum and durable resistance in China. This review also proposes the major research areas in wheat stripe rust resistance breeding in the new era.

[Objective] To effectively tackle the unique attributes of wheat leaf pests and diseases in their native environment, a high-caliber and efficient pest detection model named YOLOv8-SS (You Only Look Once Version 8-SS) was proposed. This innovative model is engineered to accurately identify pests, thereby providing a solid scientific foundation for their prevention and management strategies. [Methods] A total of 3 639 raw datasets of images of wheat leaf pests and diseases were collected from 6 different wheat pests and diseases in various farmlands in the Yuchong County area of Gansu Province, at different periods of time, using mobile phones. This collection demonstrated the team's proficiency and commitment to advancing agricultural research. The dataset was meticulously constructed using the LabelImg software to accurately label the images with targeted pest species. To guarantee the model's superior generalization capabilities, the dataset was strategically divided into a training set and a test set in an 8:2 ratio. The dataset includes thorough observations and recordings of the wheat leaf blade's appearance, texture, color, as well as other variables that could influence these characteristics. The compiled dataset proved to be an invaluable asset for both training and validation activities. Leveraging the YOLOv8 algorithm, an enhanced lightweight convolutional neural network, ShuffleNetv2, was selected as the basis network for feature extraction from images. This was accomplished by integrating a 3×3 Depthwise Convolution (DWConv) kernel, the h-swish activation function, and a Squeeze-and-Excitation Network (SENet) attention mechanism. These enhancements streamlined the model by diminishing the parameter count and computational demands, all while sustaining high detection precision. The deployment of these sophisticated methodologies exemplified the researchers' commitment and passion for innovation. The YOLOv8 model employs the SEnet attention mechanism module within both its Backbone and Neck components, significantly reducing computational load while bolstering accuracy. This method exemplifies the model's exceptional performance, distinguishing it from other models in the domain. By integrating a dedicated small target detection layer, the model's capabilities have been augmented, enabling more efficient and precise pest and disease detection. The introduction of a new detection feature map, sized 160×160 pixels, enables the network to concentrate on identifying small-targeted pests and diseases, thereby enhancing the accuracy of pest and disease recognition. Results and Discussion The YOLOv8-SS wheat leaf pests and diseases detection model has been significantly improved to accurately detect wheat leaf pests and diseases in their natural environment. By employing the refined ShuffleNet V2 within the DarkNet-53 framework, as opposed to the conventional YOLOv8, under identical experimental settings, the model exhibited a 4.53% increase in recognition accuracy and a 4.91% improvement in F₁-Score, compared to the initial model. Furthermore, the incorporation of a dedicated small target detection layer led to a subsequent rise in accuracy and F₁-Scores of 2.31% and 2.16%, respectively, despite a minimal upsurge in the number of parameters and computational requirements. The integration of the SEnet attention mechanism module into the YOLOv8 model resulted in a detection accuracy rate increase of 1.85% and an F₁-Score enhancement of 2.72%. Furthermore, by swapping the original neural network architecture with an enhanced ShuffleNet V2 and appending a compact object detection sublayer (namely YOLOv8-SS), the resulting model exhibited a heightened recognition accuracy of 89.41% and an F₁-Score of 88.12%. The YOLOv8-SS variant substantially outperformed the standard YOLOv8, showing a remarkable enhancement of 10.11% and 9.92% in accuracy, respectively. This outcome strikingly illustrates the YOLOv8-SS's prowess in balancing speed with precision. Moreover, it achieves convergence at a more rapid pace, requiring approximately 40 training epochs, to surpass other renowned models such as Faster R-CNN, MobileNetV2, SSD, YOLOv5, YOLOX, and the original YOLOv8 in accuracy. Specifically, the YOLOv8-SS boasted an average accuracy 23.01%, 15.13%, 11%, 25.21%, 27.52%, and 10.11% greater than that of the competing models, respectively. In a head-to-head trial involving a public dataset (LWDCD 2020) and a custom-built dataset, the LWDCD 2020 dataset yielded a striking accuracy of 91.30%, outperforming the custom-built dataset by a margin of 1.89% when utilizing the same network architecture, YOLOv8-SS. The AI Challenger 2018-6 and Plant-Village-5 datasets did not perform as robustly, achieving accuracy rates of 86.90% and 86.78% respectively. The YOLOv8-SS model has shown substantial improvements in both feature extraction and learning capabilities over the original YOLOv8, particularly excelling in natural environments with intricate, unstructured backdrops. Conclusion The YOLOv8-SS model is meticulously designed to deliver unmatched recognition accuracy while consuming a minimal amount of storage space. In contrast to conventional detection models, this groundbreaking model exhibits superior detection accuracy and speed, rendering it exceedingly valuable across various applications. This breakthrough serves as an invaluable resource for cutting-edge research on crop pest and disease detection within natural environments featuring complex, unstructured backgrounds. Our method is versatile and yields significantly enhanced detection performance, all while maintaining a lean model architecture. This renders it highly appropriate for real-world scenarios involving large-scale crop pest and disease detection.

In order to select new wheat varieties suitable for planting in southern Shandong Province, 9 traits of 19 wheat varieties were evaluated by DTOPSIS method based on entropy weight. The results showed that: the weight of each index from low to high was growth period < yield < bulk density < plant height < effective panicle < basic seedling < 1000-grain weight < heading rate < number of grains per panicle. The C_i values of 6 varieties were greater than 0.5, including ‘Shannong HH126’ (0.9221), ‘DK171’ (0.8680), ‘Hemai 179’ (0.8515), ‘Feida No. 6’ (0.7196), ‘Jinlai 36’ (0.6967), and ‘Yannong 301’ (0.5232). Therefore, these six varieties have good comprehensive characters and are suitable for planting and promoting in southern Shandong Province.

In order to explore the effect of prohexadione calcium (Pro-Ca) on the growth and yield factors and safety of wheat, taking wheat variety ‘Yumai 49’ as material, different doses of 5% Pro-Ca EA were applied to carry out field experiments after wheat turning green. The results showed that the application of 5% Pro-Ca EA (150-600 g/hm²) could dwarf plant height, reduce internode length, increase stem diameter and stem wall thickness. Pro-Ca could increase the number of ears, grains per ear, 1000-grain weight and yield of wheat. The application during the period of returning to green of 5% Pro-Ca EA 300 g/hm² and 5% Pro-Ca EA 300 g/hm² + 0.01% brassinolide SL150 mL/hm² could achieve higher yield, reaching 7410.0 kg/hm² and 7560.0 kg/hm² respectively, increase by 10.7% and 13.0% compared with that of CK. 5% Pro-Ca EA is safe and harmless to wheat, so it is recommended to be popularized in wheat production.

【Objective】Spike length (SL) plays an important role in determining spike structure and yield potential of wheat. Quantitative trait loci (QTL) for spike length were excavated and their genetic effects were further analyzed to provide theoretical basis for molecular breeding. 【Method】This study consisted of a population of 198 F₆ recombinant inbred lines (RIL) derived from the cross between the natural mutant msf and the cultivar Chuannong 16 (MC population). The MC population and its parents were planted in five different environments including Wenjiang in 2021 and 2022 (2021WJ and 2022WJ); Chongzhou in 2021 and 2022 (2021CZ and 2022CZ); and Ya’an in 2021 (2021YA) for spike length measurement. The 16K SNP chip-based constructed high-quality and high-density genetic linkage maps were used to map QTL for spike length. Additionally, the genotype of the flanking markers for the major spike length QTL was used to analyze its genetic effect on yield-related traits and thus to evaluate its potentiality for yield improvement.【Result】A total of 14 QTL for spike length were identified and they were mainly distributed on chromosomes 1A (one), 1B (one), 2B (one), 3D (three), 4A (one), 4D (two), 5A (one), 5B (one), 7A (one), 7B (one), and 7D (one). Among them, QSl.sau.1A was detected in four environments and the best linear unbiased prediction (BLUP) value, explained 6.46% to 20.12% of the phenotypic variation, and thus was regarded as a major QTL. The positive allele at QSl.sau.1A came from the parental line msf. QTL analysis across multiple environments also detected QSl.sau.1A, indicating it exhibits minimal environmental influence and represents a major and stably expressed QTL. The effect of QSl.sau.1A was successfully verified in two populations with different genetic backgrounds. Genetic effects analysis showed that the positive allele of QSl.sau.1A showed a significant effect on improving grain number per spike (12.68%), grain weight per spike (14.99%), 1000-grain weight (5.79%), flag leaf width (2.94%), spikelet number (1.48%), and flowering date (0.61%), and a significant effect of reducing plant height (-6.47%) and effective tiller number (-36.11%).【Conclusion】A major and stably expressed spike length QTL, QSl.sau.1A, was detected on chromosome 1A. Its positive allele significantly increased grain number per spike, grain weight per spike, thousand grain weight, and spikelet number per spike, indicating its great breeding value.

【Objective】The function and mechanism of TaCYP78A5 regulating flower organ size was preliminarily analyzed by means of expression pattern analysis, transgenic overexpression and cytological observation. The results provide genetic resources and theoretical basis for crop genetic improvement. 【Method】According to the sequence information of CYP78A family members of different species in EnsemblePlants genome database, sequence alignment and evolutionary analysis were carried out for the homologous genes of TaCYP78A5 in wheat and other species. The gene and protein structures and the expression patterns of different organs of wheat TaCYP78A5 were analyzed by bioinformatics. Through the strategy of constitutive overexpression and local specific overexpression in reproductive organs of TaCYP78A5 in Arabidopsis, it is clear that TaCYP78A5 has the function of regulating flower organ size. The cytological characteristics of flower organs of different transgenic Arabidopsis were observed under microscope, and the cytological mechanism of TaCYP78A5 regulating flower organ size was analyzed. The function of TaCYP78A5 in regulating wheat spike size and other spike traits was clarified by using the strategy of transgenic overexpression in wheat. The correlation analysis of haplotype data and spike phenotype data of 323 wheat accessions was used to explore the effect of TaCYP78A5 expression on spike size and other spike traits of different wheat accessions. 【Result】The gene and protein sequence similarity of wheat TaCYP78A5 and Arabidopsis AtCYP78A5 is low, but the gene and protein structure similarity is high. Wheat TaCYP78A5 and Arabidopsis AtCYP78A5 are widely expressed in many organs, but highly expressed in flower organs. Compared with wild type, the constitutive overexpression of TaCYP78A5 in Arabidopsis could lead to the enlargement of flower organs and a significant increase in petal area of 13.5%-35.4%. Moreover, the specific overexpression of TaCYP78A5 only in the ovule was enough to cause the enlargement of the flower organ of Arabidopsis, and the petal area increased significantly by 9%-22.1%. On the contrary, the flower organ of Arabidopsis cyp78a5 mutant was significantly smaller than that of wild type, and the petal area was significantly reduced by 27%. The constitutive overexpression of TaCYP78A5 in Arabidopsis resulted in a significant increase in the size of petal epidermal cells by 49%-54% compared with wild type, and a significant decrease in the number of cells by 11%-19% compared with wild type. Locally specific overexpression of TaCYP78A5 in Arabidopsis also resulted in a significant increase in the size of petal epidermal cells by 20%-49% compared with wild type, and a significant decrease in the number of cells by 8%-24% compared with wild type. The constitutive overexpression of TaCYP78A5 in wheat resulted in the increase of wheat spike length by 7.9%-8.9%, glume area by 9.6%-14.7%, and grain number per spike by 12.4%-23.8%. The spikelet number per spike and grain number per spikelet showed different degrees of change. The results of haplotype analysis showed that among 323 wheat accessions, wheat accessions with higher TaCYP78A5-A expression level had longer spike length, more grains per spikelet and fewer spikelets per spike than wheat accessions with lower TaCYP78A5-A expression level, but there was no significant difference in grain number per spike. 【Conclusion】TaCYP78A5 promoted the growth of flower organs in a non cellular self-made mode. The overexpression of TaCYP78A5 in wheat and Arabidopsis could lead to the enlargement of flower organs.

To study the impacts of observed climate change on crop development and yield could provide more accurate information for assessing the effect of climate change on crop production. In this study, we used ground observation data from five case areas including extreme drought (Dunhuang), arid (Wuwei), semi-arid (Dingxi), semi-humid (Linxia), and humid (Mixian) in northwest China’s 1981(1986)-2017 to analyze the meteorological trends and determine the relationship between spring wheat growth, yield and climatic factors. The results showed that the climate change patterns and their impacts on spring wheat phenology and yield in these stations were diverse both spatially and temporally during the period of 1981-2017. Except the warmer and wetter trends in extreme arid regions, warmer and drier trends were observed in other regions. Correlation analysis showed that spring wheat production in Wuwei, Dingxi and Linxia stations increased in 1981 (1986)-2017, but the change trend was not significant except Wuwei station. The decrease of days ≥30℃ during the wheat growth period in Wuwei station increased the output in Wuwei station in the 37 years, however, the increase of precipitation during the wheat growth period, more grains per panicle and obviously fewer infertile spikelets in Dingxi station increased the output in Dingxi station in the recent 32 years. It is estimated that the global warming trend and change in precipitation pattern will further impact the production and yield of spring wheat in northwest China.

Wheat is the most important cereal crop, and drought is the most significant abiotic stress factor that severely affects wheat growth and development. Plant root system, as a primary organ for crops to acquire water and nutrients, directly determines the efficiency of soil water utilization. In recent years, increasing evidence has shown that plant root system architecture (RSA) plays an important role in plant tolerance to drought stress. This review summarizes the current research progress on the regulation of wheat drought tolerance determined by RSA. First, we present how root tropism especially root gravitropism shapes the RSA, summarize the relevant genes and molecular regulatory mechanism involved in root gravitropic growth, and explain how the root tropism-regulated RSA is implicated in wheat adaptation to drought stress. In addition to root tropic growth, the root development also participates in the RSA formation and the plant adaptability to drought stress. Therefore, this review further summarizes how wheat regulates root development to alter its root system morphology (including increasing root length, modifying lateral root number and root hair density, etc.), thereby enhancing its water acqusition from the soil and its adaption to drought environment. The identified genes involved in wheat root development under drought stress conditions are also systematically summarized. Furthermore, as the underground part of plants, the revelation of RSA has always been a challenging task, which hinders our understanding of the relationship between RSA and plant drought tolerance. Therefore, this review also summarized the available techniques used to analyze the RSA at two- and three-dimension levels. These techniques can measure and analyze wheat root length, density, growth direction, and morphology parameters, laying technical support for an insightful understanding of the relationship between wheat RSA and drought resistance. Finally, we discuss the prospect of the improvement of RSA in breeding wheat drought-resistant varieties, as well as provide an outlook for how to identify genes regulating wheat RSA and pinpoint their regulatory mechanism. In summary, the relationship between wheat RSA and drought resistant is closely associated. The continuous development of sequencing techniques, along with the deepening research on the regulatory mechanism of wheat RSA, will provide new means and strategies for the further breeding of drought-tolerance wheat varieties.

The best period to prevent and control wheat scab is on the preliminary stage of flowering. To explore the control efficacy on wheat scab and toxins when missing the preliminary stage of flowering, 13 wheat varieties in Jiangyan were selected for this experiment, and 48% cyanene·pentazolol SC was used to control the wheat scab. We designed three application methods: spraying 48% cyanene·pentazolol SC once after 6 days missing the preliminary stage of flowering, spraying 48% cyanene·pentazolol SC once at the preliminary stage of flowering, and spraying 48% cyanene·pentazolol SC once at the preliminary stage of flowering plus once after 6 days. The controlling efficacy of the 3 treatments against wheat scab, as well as their impact on the content of DON toxin in wheat grain were compared for each wheat variety. The results showed that the average control efficacy on diseased ear rate and the disease index and the reduction effect on DON toxin under spraying 48% cyanene·pentazolol SC once after 6 days missing the preliminary stage of flowering were 15.87%, 21.25% and 35.48% lower than those under spraying once at the preliminary stage of flowering respectively, and were 39.79%, 44.87% and 66.84% lower than those under spraying once at the preliminary stage of flowering plus once after 6 days. Therefore, the optimal first control time for scab is at the preliminary stage of flowering, while spraying 48% cyanene·pentazolol SC once after 6 days missing the preliminary stage of flowering has relatively poor control efficacy on scab and DON toxin. Spraying 48% cyanene·pentazolol SC once at the preliminary stage of flowering plus once after 6 days shows the best efficacy, and the performance trend of all the varieties are consistent.

【Objective】Eestern and Southern Gansu is one of the epidemic centers of stripe rust and over-summering region for Puccinia striiformis f. sp. tritici (Pst) with continuous emergening of new Pst races in Northwestern China. The objective of this study is to analyze the genetic architecture of stripe rust resistance in winter wheat cultivars grown in those regions since 1990s for a better genetic diversity control of the disease, breeding of durable resistant cultivars, sustainable green and healthy ecological agriculture in Southern Gansu. 【Method】The seedling and adult plant stage resistance to the prevailing Pst races CYR33, CYR34, etc. of 117 wheat cultivars (lines) were evaluated at greenhouse in 2021 and field trials in Qingshui of Gansu and Pixian of Sichuan, respectively, during 2019-2020 and 2020-2021 cropping seasons. Molecualr markers for 15 Yr genes were also applied to detect the presence of known stripe rust resistant genes. 【Result】Of the 117 varieties and lines tested, thirty-four (29.1%) were found to perform adult plant stage resistance (APR) in the field, among these, 25.6% and 3.4% of cultivars were released in Southern Gansu, and Eastern Gansu, respectively. Another 25.6% susceptible cultivars from Southern Gansu exhibited slow rusting with disease severity (DS) less than 20%. Eighty-two cultivars (70.1%) were resistant to the race CYR33 of Pst at the seedling stage. Among them, 67 (57.3%) and 15 (12.8%) were planted in Southern and Eastern Gansu, respectively. However, only seven (6.0%) of the total entries were resistant to the dominant race CYR34 at the seedling stage, and all of these were cultivars from Southern Gansu, such as Lantian 131 etc. The stripe rusts resistant cultivars named as Lantian, Zhongliang, and Tianxuan series at both seedling and adult plant stages were mainly released after 2010. Molecular markers screening identified the presence of Yr9 (49.6%), Yr10 (1.7%), Yr17 (12.8%), Yr18 (7.7%), Yr26 (12.8%), Yr28 (20.5%), Yr29 (10.3%), Yr30 (34.2%), Yr41 (2.6%), Yr46 (16.2%), YrZH22 (15.4%) and YrZH84 (27.4%) in some cultivars, preferly as 2-5 genes combinations in 73 (62.4%) cultivars. Pyramiding of YrZH84, YrZH22, and Yr17 with other stripe rust resistance genes could provide better disease resistance than other gene combinations. In addition, high frequency of Yr10, Yr17, Yr18, Yr28, Yr29, Yr30, Yr41, and Yr46 was detected in wheat cultivars grown in the dry highland Pst oversummering region. However, Yr26, Yr30, YrZH22, and YrZH84 were mainly identified in wheat cultivars of the valley Pst overwintering region, indicating significant genetic architecture difference for the stripe rust resistance genes between the cultivars of the oversummering and overwintering regions. Higher genetic diversity of stripe rust resistance genes was found in the cultivars of the oversummering region, compared with that released in the overwintering region. 【Conclusion】Our results revealed the current status of stripe rust resistance genes and their utilization in winter wheat cultivars of Gansu, the northwest oversummering region for Pst of China, in the past 20 years. Diversification of stripe rust resistance genes have been successfully applied in the winter wheat breeding program to develop commercial wheat cultivars and lines for sustainable control of the stripe rust disease. The development of wheat cultivars with stacked stripe rust resistance genes has solved the historical problem of wheat cultivars with narrow genetic background and mono-resistance gene, domonstrating the successful control of wheat stripe rust epidemics using genetic diversity of wheat resistance gene in this region. The present study provides theoretical basis for genetic diversity control of stripe rust disease and set an example for the sustainable green ecological agriculture by breeding wheat cultivars with durable disease resistance.

【Objective】In arid and semi-arid regions, the water and nutrients are scarce in the soil. The phosphorus use efficiency between different wheat genotypes varies greatly. Therefore, identification of low phosphorus-tolerant germplasm and mapping of related loci is helpful for genetic improvement of wheat. 【Method】Using 282 Shanxi wheat varieties as materials, twelve seedling morphological indicators were investigated under three phosphorus concentrations, including SDW, RDW, DW, SFW, RFW, FW, MRL, TRL, RS, RV, RD, and RN. Principal component analysis, membership function analysis, and cluster analysis were used to comprehensively evaluate the low phosphorus tolerance characteristics of different varieties at the seedling stage. On this basis, the trait evolution trend and biomass allocation at seedling stage were analyzed. At the same time, GWAS was used to identify significant loci related to the low phosphorus-related traits. 【Result】The response of different traits to low phosphorus at the seedling stage was different. Lower phosphorus concentrations led to changes in biomass allocation strategy, and shoot growth was less affected by change in phosphorus concentrations than root growth. The decrease in phosphorus concentration inhibited the growth of shoot, and SDW and SFW were significantly reduced. In contrast, low phosphorus promoted root growth, and the indicators of RDW, RFW, MRL, TRL, RV and RN increased significantly. According to the correlation analysis between D-value and morphological indicators, it was found that MRL and RD could be used as selection indicators for low phosphorus tolerance at seedling stage. Based on D-value clustering analysis, 9 low phosphorus tolerant varieties were selected, including Jinmai 46, Jinmai 61, Youmangdahongjing, Hongtumai, Hongheshang, Baikehong, Baixianmai, Huoshaotou, Baishanmai. Analysing trends in trait evolution showed that cultivars were not directly selected for their ability to tolerate low phosphorus. The ability to tolerate low phosphorus decreased first and then increased over time. Before 2010, there was a decreasing trend in the ability of varieties to tolerate low phosphorus, and after 2010, there was an increase in the ability of varieties to tolerate low phosphorus. GWAS stably detected eight loci with R²>10% in three environments, in which 1A_545074550, 2B_489279799, 6A_166899658 and 6A_273060644 were not reported previously.【Conclusion】The MRL and RD can be used as selection indicators for low phosphorus tolerance at seedling stage. A total of nine varieties were selected through comprehensive evaluation of ability in Shanxi wheat to tolerate low phosphorus during seedling stage. Association analysis detected four novel loci associated with low phosphorus tolerance on chromosomes 1A, 2B and 6A, and the results provide germplasm resources and QTL for future low phosphorus tolerance wheat breeding.

【Objective】By analyzing the genetic and breeding selection effects of the stable major QTL for spike length in wheat, its genetic effects on yield-related traits were clarified, and the future breeding application potential was evaluated. The results could provide a basis for subsequent gene mining and molecular breeding of wheat. 【Method】A major QTL for spike length, named qSl-2D, was detected in multiple environments using a recombinant inbred lines population derived from the cross of Kenong9204 and Jing411, denoted as KJ-RIL; Two molecular markers closely linked to qSl-2D were developed by using the InDel sites in target interval. The genetic effects of yield-related traits based on KJ-RIL, MY-F₂, NILs and natural mapping populations, were analyzed by combining genotype data of molecular markers or wheat 55K array, respectively. By genotyping the natural mapping population, the breeding selection effect of qSl-2D haplotype was parsed across different wheat regions and different ages. 【Result】QTL mapping results showed that qSl-2D could be detected in 7/10 sets of environmental data, and could explain 4.02%-10.10% of the phenotypic variation. The peak LOD of 5/10 sets of environmental data was positioned at 608.75 Mb. The results of genetic effect analysis showed that the enhancing allele of qSl-2D could significantly increase spike length in the four populations with different genetic backgrounds. In addition, it has positive effects on kernel number per spike and plant height, but has negative effects on thousand kernel weight, kernel weight per spike and yield per plant in most population backgrounds. Further analysis of plant height in KJ-RIL population showed that the enhancing allele had rod lowering effect on all internode lengths except the internode length below spike, which resulted in the insignificant increase in plant height. The results of qSl-2D haplotype analysis showed that the utilization rates of the long-spike haplotype Hap-AA-GG varied greatly in different wheat regions, with the highest utilization rate in the northern winter wheat region, accounting for 24%; while the short-spike haplotype Hap-CC-CC accounted for more than 30% in most wheat regions. Moreover, the utilization rate of qSl-2D long-spike haplotype showed a gradual decrease over time, while that of short-spike haplotype consistently maintained a higher selection trend. 【Conclusion】A stable major QTL-qSl-2D for spike length was identified, the enhancing allele of qSl-2D could significantly increase spike length under different genetic backgrounds, and had certain genetic effects on yield-related traits. The closely linked molecular markers developed in the target region can be used for the genetic improvement of wheat spike length and yield-related traits in wheat.