To investigate the water-saving and high-yielding drip irrigation system for spring wheat in the Hetao Irrigation District, a nationally approved spring wheat variety, Bamai 13, was selected as the experimental material. Six drip irrigation frequencies and three drip irrigation levels (300, 450, and 600 m³·hm^-2) were set up in the field, with the conventional furrow irrigation method used by farmers as control. The study focused on the differences in wheat water consumption characteristics, yield formation, and water use efficiency under different drip irrigation frequencies and amounts. The results indicated that the soil evaporation significantly increased from sowing to tillering stage, gradually decreased from tillering to heading stage, and significantly increased from heading to maturity stage. The water consumption during wheat growth stages follows an ascending-descending trend, reaching its maximum from jointing to booting period. With the increase in drip irrigation frequency and water amount, evaporation and water consumption exhibited a gradual upward trend, while wheat yield showed an initial increase followed by a decline. Compared to the control group, low-frequency high-volume drip irrigation significantly reduced soil evaporation and water consumption. Specifically, irrigating six times during the growth period with 300 m³·hm^-2 each time resulted in a 50% reduction in water consumption compared to the control, leading to a significant decrease rate of 26.3% in water usage. Moreover, the yield and water use efficiency was significantly increased by 16.3% and 57.6%, respectively. Therefore, the recommended irrigation regimen for achieving high yield and efficiency in drip-irrigated wheat in the Hetao Irrigation District is six irrigation sessions during the tillering, jointing, booting, flowering, early grain-filling, and mid-grain-filling stages, with 300 m³·hm^-2 of water for each session.

Accurate and effective yield prediction is essential for wheat breeding, cultivation and field management. In this study, the multispectral and RGB images of winter wheat during the grain filling stage were collected from UAV, and 14 spectral traits and 28 morphological traits were extracted as feature variables. Ten machine learning methods, including linear regression, random forest and neural network, were used to construct wheat yield prediction models, and the differences between the models were compared to select the best one. Additionally, machine learning interpretability method SHAP was introduced to analyze the importance of the feature variables, in order to improve the prediction performance of the model. The results showed that among the 10 machine learning methods used, the BPNN model had the best prediction performance (r²=0.826, RMSE=0.094 t·hm^-2). According to the feature importance ranking determined by SHAP, Anthocyanin Reflectance Index (ARI) and Three-Dimensional Canopy Volume (Volume) had the greatest impact on the prediction results, accounting for 45.48% of the total feature importance. After feature selection using SHAP, the BPNN model with the best performance was determined based on nine feature variables (r²=0.865, RMSE=0.075 t·hm^-2). This improved the prediction accuracy compared to the BPNN model using all features and the pre-analysis method Pearson correlation analysis. Therefore, based on the optimal yield prediction model, SHAP mechanism can be used to select and analyze the importance of feature variables, so as to further improve the accuracy of wheat yield prediction.

In order to explore the genetic rules of important traits of the spring wheat varieties (lines) in Xinjiang in the past 40 years, 65 spring wheat varieties of different decades from 1985 to 2024 and 2 lines to be approved were used as materials. The main traits of wheat were subjected for genetic variation, correlation analysis, cluster analysis, principal component analysis, and comprehensive analysis. The agronomic traits among different varieties (lines) showed rich genetic diversity. The diversity index of 67 wheat materials ranged from 1.96 to 2.08, with the largest thousand-grain weight of 2.08 and the smallestpeduncle length of 1.96. The number of grains per spike was significantly (P<0.01) positively correlated with plant height, flag leaf width, flag leaf area, and ear length, and was significantly (P<0.05) positively correlated with peduncle diameter and flag leaf length; the number of thousand-grain weight was significantly (P<0.01) positively correlated with peduncle diameter, flag leaf width, and was significantly (P<0.05) positively correlated with flag leaf area. Principal component analysis converted 9 traits into 3 principal components, with a cumulative contribution rate of 72.049%. Combined with theweighted contribution rate of the 3 principal component factors, the top 10 materials with the highest comprehensive score were Xinchun 35, Xinchun 45, Xinchun 41, Xinhan 688, Liangchun 1571, Xinchun 8, Xinchun 20, Liangchun 1242, Xinchun 18, and Xinchun 16, which can be promoted as excellent varieties for planting.

To understand the current situation of disease resistance breeding in wheat in the middle and lower reaches of Yangtze River, and to identify and screen excellent disease resistant strains, in this study, the resistance of 414 advanced wheat lines from the national regional trial in the middle and lower reaches of the Yangtze River and the regional trial in Jiangsu Province in the past six years was identified, and the molecular markers of Fhb1 and Pm21/PmV genes were used for genotyping. The results of resistance showed that: 42 advanced wheat lines were resistant to Fusarium head blight (FHB)） (R), 262 advanced lines were moderate resistant (MR), accounting for 10.1% and 62.3%, respectively, among which Yang 15-9, Yang 17021, and Ning 20419 were resistant to FHB for two consecutive years. Most FHB resistance culticars/lines were derived from Ningmai 9, Yangmai 158, and their derivative varieties through analysis of pedigree. A total of 97 advanced lines were immune (IM) to powdery mildew; 8 advanced lines were high resistant (HR) and 35 strains were moderate resistant (MR), accounting for 23.4%, 1.9%, and 8.5%, respectively. Among them, Yang 15-9, Ruihumai 505, Yanmai 0916, Ninghong 1761, Yan H1902 and Dongmai 1901 were immune (IM) to powdery mildew for three consecutive years. A total of 15 advanced lines with simultaneous resistance (R) or immunity (IM) to FHB and powdery mildew can be used as resistant parents in wheat breeding. The results of detection of resistance gene combining with resistance phenotypy showed that: 63 advanced lines carried Fhb1 gene, accounting for 15.1% of the tested materials, and 88.0% of the advanced lines had resistance above MR. Fhb1 gene was detected in only 35.7% of advanced lines with resistance to FHB (R). Only 14.9% of the advanced lines with moderate resistance to FHB were detected to carry Fhb1 gene. 143 advanced lines carried Pm21/PmV genes, accounting for 34.5% of the tested materials, of which 73 advanced lines were identified as immune (IM) to high resistance (HR) to powdery mildew. 70.1% of the 97 advanced lines that were immune to powdery mildew carried Pm21/PmV genes, and 29.9% of the other advanced lines were resistant to powdery mildew with the unknown genes to be discovered. 10 advanced lines carried both Fhb1 and Pm21/PmV genes, and the resistance to both diseases was above MR, which can be directly used as resistance sources. This study suggested that Pm21/PmV genes can be continuously used in wheat disease resistance breeding in the middle and lower reaches of the Yangtze River. Combining Fhb1 gene with FHB resistance gene of Yangmai variety can improve the FHB resistance.

In order to investigate the interaction effect of nitrogen (N) and sulfur (S) fertilizer on dry matter accumulation and grain yield of winter wheat in eastern Hebei Province, a winter wheat Shinong 952 was used as material. A split plot design was adopted, with the N application as main plot: 0 kg·hm^-2 (N0), 180 kg·hm^-2 (N1), 240 kg·hm^-2 (N2) and 300 kg·hm^-2 (N3), and S application as the sub-plot:82.5 kg·hm^-2 (S1), 112.5 kg·hm^-2 (S2), 142.5 kg·hm^-2 (S3) and 172.5 kg·hm^-2 (S4). The differences of chlorophyll relative content (SPAD), leaf area index (LAI), dry matter and nitrogen translocation, and grain yield of winter wheat under different treatments were analyzed. The results showed that N and S application significantly affected LAI and flag leaf SPAD of winter wheat. The SPAD value of N1S2 treatment was the highest at anthesis, which was significantly higher than the other treatments except N2S2 and N3S2. The N and S application had positive effects on the translocation of dry matter and nitrogen restored before anthesis, and the accumulation of dry matter and nitrogen after anthesis, the interaction between N and S nutrition also was significant. Wheat grain yield ranged from 7 364.71 kg·hm^-2 to 10 078.20 kg·hm^-2 under different treatments, and increased significantly with the increase of N application amount. The grain yield of N2S3 treatment was significantly higher than the treatments under N0 and N1 levels, but was no significantly different from the other treatments under N2 and N3 levels. S application had no significant effect on grain yield and 1 000-grain weight of wheat. Overall, the application of nitrogen-sulfur fertilizer with right amounts is conducive to higher SPAD values and LAI in the flag leaves of winter wheat, can enhance the photosynthetic capacity of the leaves, promote post-anthesis dry matter accumulation and pre-anthesis nitrogen translocation, and ultimately increase winter wheat yield. 240 kg N·hm^-2 and 82.5 kg S·hm^-2 were the most suitable N and S fertilizer combinations for saving fertilizer and increasing efficiency in winter wheat production.

To investigate the effects of nitrogen reduction combined with application of arbuscular mycorrhizal fungi (AMF) on the growth characteristics, photosynthetic physiology, nitrogen metabolism process, and yield of wheat during the grain-filling stage under water-saving irrigation, a wheat line Landa 211 was used as the experimental material. Two irrigation amounts (normal irrigation of 400 mm, water-saving irrigation of 280 mm) and three nitrogen application levels［conventional nitrogen application (250 kg·hm^-2), reduced 20% nitrogen fertilizer application (200 kg·hm^-2), and reduced 40% nitrogen fertilizer application (150 kg·hm^-2)］ were set up, inoculated with the AMF strain Funneliformes mosesae（FM） and no inoculation. The results indicated that FM could infect wheat roots and formed a stable symbiotic relationship. Compared with normal irrigation, the mycorrhizal infection rate, arbuscular growth rate, number of invasion points, and number of vesicles of FM decreased under water-saving irrigation. Compared with the conventional nitrogen application treatment under normal irrigation, reduced 20% nitrogen under water-saving irrigation and inoculation with FM treatment had no significant effect on the dry matter accumulation and leaf area of wheat population, but the plant height and total stem number of the population decreased. The chlorophyll content, chlorophyll fluorescence parameters, and gas exchange parameters of wheat showed no significant differences compared to the conventional nitrogen application treatment under normal irrigation, but were significantly higher than reduced 40% nitrogen treatments under water-saving irrigation and FM inoculation. Compared with the conventional nitrogen application treatment under normal irrigation, there was no significant difference in the total nitrogen content, free amino acid content, soluble protein content of wheat flag leaves, and the activities of nitrate reductase, glutamine synthase, glutamic pyruvate transaminase, and glutamic acid synthase under reduced 20% nitrogen with water-saving irrigation and FM inoculation. The wheat yield under water-saving irrigation and reduced 20% nitrogen combined with FM treatment reached 7 786.0 kg·hm^-2, which was not significantly different from the yield under normal irrigation with conventional nitrogen application. To conclude, reduced 20% nitrogen and applying FM in combination with water-saving irrigation could maintain the chlorophyll content and photosynthesis of wheat during the grain-filling period, and maintain the activity of wheat nitrogen metabolism enzymes and metabolite content, which was a green water and fertilizer management model for water-saving, fertilizer saving, and high-yield maintenance in arid irrigation areas.

Dwarf male-sterile wheat is a specific germplasm with phenotypic genetic markers closely linked to the dominant nuclear sterile gene (Ms2) and dominant dwarf gene (Rht-D1c), and is an ideal tool for population improvement and related genetic research. The breeding technology system constructed by dwarf male-sterile wheat is continuously developed, innovated and improved in wheat breeding practice. This technology, combined with haploid breeding and molecular marker assisted selection, can quickly cultivate introgression lines with target traits, achieve the aggregation of multiple target genes in a favorable genetic background, and orientingly construct a recurrent selection population, so as to accelerate the improvement speed of important wheat traits. It is of great value for breeding new varieties with breakthrough traits and creating excellent breeding materials with various genetic backgrounds.

To investigate the effect of phosphorus application mode on the grain setting characteristics of wheat ears under late spring coldness, wheat varieties Xinmai 26 with weak resistance to late spring coldness and Yannong 19 with strong resistance to late spring coldness were selected as experimental materials from 2022 to 2023. Field pot planting was adopted, and a low temperature light incubator was used to simulate late spring coldness. The main stem and grain setting characteristics of two wheat varieties were analyzed under the treatments of full basal application of phosphorus fertilizer under conventional temperature, 50% of phosphorus fertilizer postpone under conventional temperature, full basal application of phosphorus fertilizer under late spring coldness, and 50% of phosphorus fertilizer postpone under late spring coldness. The results showed that compared with normal temperature, the late spring coldness significantly reduced the number of grains and weight per spike in the main stem of Xinmai 26 and Yannong 19, with a decrease rate of 25.63% and 23.43%, respectively, and a decrease rate of 26.74% and 20.65% in weight per spike, respectively. Among them, the number of grains in the lower spikelets of both varieties decreased the most (40.21% and 31.91%, respectively). The grain position with the largest decrease in grain number was the third and fourth grain positions (40.00% and 80.77%, respectively). Under normal temperature conditions, after applying phosphorus fertilizer, the single spike weight of the main stem of the two varieties was higher than that of the full basal phosphorus fertilizer, with an increase rate of 9.37% and 19.48%, respectively, and the number of grains was increased by 11.17% and 8.45%, respectively. The largest increase in grain number was observed in the lower and upper spikelets (with increase rate of 30.93% and 31.25%, respectively). The thousand-grain weight of Yannong 19 significantly increased (with an increase rate of 12.49%). Compared with the full basal application of phosphorus fertilizer, the postpone of phosphorus fertilizer significantly increased the number of grains and weight per spike in the main stem of two varieties under the risk of late spring coldness. The increase rate of grain number per spike was 22.53% and 14.20%, and the increase rate of grain weight per spike was 25.94% and 10.96%, respectively. The highest increase in grain number in Xinmai 26 was observed in the lower spikelet and the third grain position (with an increase rate of 101.72% and 42.86%, respectively); The spikelet position with the largest increase in grain number of Yannong 19 was the upper spikelet (with an increase rate of 73.68%). In summary, late spring coldness can reduce the number of grains and weight per spike in the main stem of wheat. After applying phosphorus fertilizer, applying phosphorus postpone can alleviate the impact of late spring coldness on wheat spike fruiting by increasing the number of grains and weight per spike in the main stem.

In order to screen the suitable irrigation amount for strong gluten wheat in the eastern Hebei region in spring, two strong gluten wheat varieties (Zhongmai 886 and Zhongmai 998) were selected as materials, with five irrigation treatments during the jointing and anthesis stages: no irrigation (W₀), 300 m³·hm^-2 (W₁) each time, 450 m³·hm^-2 (W₂) each time, 600 m³·hm^-2 (W₃) each time, and 750 m³·hm^-2 (W₄) each time, the effects of drip irrigation on the SPAD value of flag leaves, dry matter accumulation and transportation, grain filling rate, yield, and yield components of strong gluten wheat were studied. The results showed that with the increase of drip irrigation amount, the SPAD value of flag leaves after anthesis of strong gluten wheat and the duration of grain filling increased. The accumulation and transportation of dry matter and grain yield increased in the range of 0-600 m³·hm^-2, but significantly decreased at 750 m³·hm^-2, while water use efficiency decreased. Under W₃ treatment, the two strong gluten wheat varieties showed the best performance in terms of spike number, grain number per spike, thousand-grain weight, and yield. Taking into account both grain yield and water use efficiency, the optimal drip irrigation amount for strong gluten wheat during jointing and anthesis periods in the eastern Hebei region is 600 m³·hm^-2 each time.

Estimation of the leaf water content (LWC) plays an important role in field irrigation management. This study aimed to estimate the LWC of winter wheat based on hyperspectral data of leaf blades, especially focusing on the effect of different variable screening methods and growth stages on the estimation model. Research data were obtained from field trials in 2022 and 2023 at the booting, heading, and grain-filling stages. Vegetation indices were constructed for each growth stage by combining the two bands. Tthe input characteristic variables based on vegetation indices were screened by two methods: (I) the input characteristic variables were directly obtained by ranking the correlation coefficients; (II) based on the method I, the vegetation index was further screened by the ReliefF algorithm to obtain a second set of input characteristic variables. The LWC estimation models were constructed using random forest (RF), long short-term memory (LSTM) network and back propagation neural network (BPNN) based on particle swarm optimization (PSO). The best method for estimating LWC was derived by comparing the accuracy of the models. The results showed that comparing the two variable screening methods, the characteristic variables further screened by ReliefF could effectively improve the accuracy of the LSTM and PSO-BPNN models, while the effect of improving the RF model is not obvious. The best model for each growth stage was established by the ReliefF screening method combined with the PSO-BPNN, at the booting stage, heading stage and grain-filling stage. The r² of the validation set was 0.816, 0.736, and 0.806, respectively, and the RMSE was 0.546%, 0.899%, and 1.531%, respectively, and the NRMSE was 0.681%, 1.195%, and 2.185%, respectively. It was suggested that the screening method of feature variables through the ReliefF algorithm could improve its estimation accuracy in the particular model. Its combination with the PSO-BPNN model had the best application effect in the estimation of LWC in winter wheat at the growth stages.