Nitrogen (N) is a key factor in the positive response of cereal crops that follow leguminous crops when compared to gramineous crops in rotations, with the nonrecyclable rhizosphere-derived N playing an important role.  However, quantitative assessments of differences in the N derived from rhizodeposition (NdfR) between legumes and gramineous crops are lacking, and comparative studies on their contributions to the subsequent cereals are scarce.  In this study, we conducted a meta-analysis of NdfR from leguminous and gramineous crops based on 34 observations published worldwide.  In addition, pot experiments were conducted to study the differences in the NdfR amounts, distributions and subsequent effects of two major wheat (Triticum aestivum L.)-preceding crops, corn (Zea mays L.) and soybean (Glycine max L.), by the cotton wick-labelling method in the main wheat-producing areas of China.  The meta-analysis results showed that the NdfR of legumes was significantly greater by 138.93% compared to gramineous crops.  In our pot experiment, the NdfR values from corn and soybean were 502.32 and 944.12 mg/pot, respectively, and soybean was also significantly higher than corn, accounting for 76.91 and 84.15% of the total belowground nitrogen of the plants, respectively.  Moreover, in different soil particle sizes, NdfR was mainly enriched in the large macro-aggregates (>2 mm), followed by the small macro-aggregates (2–0.25 mm).  The amount and proportion of NdfR in the macro-aggregates (>0.25 mm) of soybean were 3.48 and 1.66 times higher than those of corn, respectively, indicating the high utilization potential of soybean NdfR.  Regarding the N accumulation of subsequent wheat, the contribution of soybean NdfR to wheat was approximately 3 times that of corn, accounting for 8.37 and 4.04% of the total N uptake of wheat, respectively.  In conclusion, soybean NdfR is superior to corn in terms of the quantity and distribution ratio of soil macro-aggregates.  In future field production, legume NdfR should be included in the nitrogen pool that can be absorbed and utilized by subsequent crops, and the role and potential of leguminous plants as nitrogen source providers in crop rotation systems should be fully utilized.

Aphids are major insect pests in agriculture and forestry worldwide. Following attacks by natural enemies, many aphids release an alarm pheromone to protect their population. In most aphids, the main component of the aphid alarm pheromone (AAP) is the sesquiterpene hydrocarbon (E)-β-farnesene (EβF). However, the mechanisms behind its biosynthesis and regulation remain poorly understood. In this study, we used the bird cherry–oat aphid Rhopalosiphum padi, which is an important wheat aphid, to investigate the regulatory mechanisms of EβF biosynthesis. Our results showed that EβF biosynthesis occurs during the mature embryo period and the molting period of the 1st- and 2nd-instar nymphs. Triglycerides provide the prerequisite material for EβF production and release. Based on transcriptome sequencing, RNAi analysis, hormone treatments, and quantitative measurements, we found that the biosynthesis of EβF utilizes acetyl coenzyme A produced from fatty acid degradation, which can be suppressed by juvenile hormone but it is promoted by 20-hydroxyecdysone through the modulation of fatty acid metabolism. This is the first systemic study on the modulation of EβF production in aphids. The results of our study provide insights into the molecular regulatory mechanisms of AAP biosynthesis, as well as valuable information for designing potential aphid control strategies.

The optimized management of crop fertilization is very important for improving crop yield and reducing the consumption of chemical fertilizers. Critical nutrient values can be used for evaluating the nutritional status of a crop, and they reflect the nutrient concentrations above which the plant is sufficiently supplied for achieving the maximum potential yield. Based on on-farm surveys of 504 farmers and 60 field experimental sites in the drylands of China, we proposed a recommended fertilization method to determine nitrogen (N), phosphorus (P), and potassium (K) fertilizer input rates for wheat production, and then validated the method by a field experiment at 66 different sites in northern China. The results showed that wheat grain yield varied from 1.1 to 9.2 t ha⁻¹, averaging 4.6 t ha⁻¹, and it had a quadratic relationship with the topsoil (0−20 cm) nitrate N and soil available P contents at harvest. However, yield was not correlated with the inputs of N, P, and K fertilizers. Based on the relationship (exponential decay model) between 95–105% of the relative yield and topsoil nitrate N, available P, and available K contents at wheat harvest from 60 field experiments, the topsoil critical nutrient values were determined as 34.6, 15.6, and 150 mg kg⁻¹ for soil nitrate N, available P, and available K, respectively. Then, based on five groups of relative yield (>125%, 115–125%, 105–115%, 95–105%, and <95%) and the model, the five groups of topsoil critical nutrient levels and fertilization coefficients (Fc) were determined. Finally, we proposed a new method for calculating the recommended fertilizer input rate as: Fr=Gy×Nr×Fc, where Fr is the recommended fertilizer (N/P/K) input rate; Gy is the potential grain yield; Nr is the N(N_rN), P(N_rP), and K(N_rK) nutrient requirements for wheat to produce 1,000 kg of grain; and Fc is a coefficient for N(N_c)/P(P_c)/K(K_c) fertilizer. A 2-year validated experiment confirmed that the new method reduced N fertilizer input by 17.5% (38.5 kg N ha⁻¹) and P fertilizer input by 43.5% (57.5 kg P₂O₅ ha⁻¹) in northern China and did not reduce the wheat yield. This outcome can significantly increase the farmers’ benefits (by 7.58%, or 139 US$ ha⁻¹).  Therefore, this new recommended fertilization method can be used as a tool to guide N, P, and K fertilizer application rates for dryland wheat production.

Lodging is still the key factor that limits continuous increases in wheat yields today, because the mechanical strength of culms is reduced due to low-light stress in populations under high-yield cultivation.  The mechanical properties of the culm are mainly determined by lignin, which is affected by the light environment.  However, little is known about whether the light environment can be sufficiently improved by changing the population distribution to inhibit culm lodging.  Therefore, in this study, we used the wheat cultivar “Xinong 979” to establish a low-density homogeneous distribution treatment (LD), high-density homogeneous distribution treatment (HD), and high-density heterogeneous distribution treatment (HD-h) to study the regulatory effects and mechanism responsible for differences in the lodging resistance of wheat culms under different population distributions.  Compared with LD, HD significantly reduced the light transmittance in the middle and basal layers of the canopy, the net photosynthetic rate in the middle and lower leaves of plants, the accumulation of lignin in the culm, and the breaking resistance of the culm, and thus the lodging index values increased significantly, with lodging rates of 67.5% in 2020–2021 and 59.3% in 2021–2022.  Under HD-h, the light transmittance and other indicators in the middle and basal canopy layers were significantly higher than those under HD, and the lodging index decreased to the point that no lodging occurred.  Compared with LD, the activities of phenylalanine ammonia-Lyase (PAL), 4-coumarate: coenzyme A ligase (4CL), catechol-O-methyltransferase (COMT), and cinnamyl-alcohol dehydrogenase (CAD) in the lignin synthesis pathway were significantly reduced in the culms under HD during the critical period for culm formation, and the relative expression levels of TaPAL, Ta4CL, TaCOMT, and TaCAD were significantly downregulated.  However, the activities of lignin synthesis-related enzymes and their gene expression levels were significantly increased under HD-h compared with HD.  A partial least squares path modeling analysis found significant positive effects between the canopy light environment, the photosynthetic capacity of the middle and lower leaves of plants, lignin synthesis and accumulation, and lodging resistance in the culms.  Thus, under conventional high-density planting, the risk of wheat lodging was significantly higher.  Accordingly, the canopy light environment can be optimized by changing the heterogeneity of the population distribution to improve the photosynthetic capacity of the middle and lower leaves of plants, promote lignin accumulation in the culm, and enhance lodging resistance in wheat.  These findings provide a basis for understanding the mechanism responsible for the lower mechanical strength of the culm under high-yield wheat cultivation, and a theoretical basis and for developing technical measures to enhance lodging resistance.

【Objective】 Wheat grain phenotype parameters were tested after grains only must been threshed by combine, this process was time-consuming, laborious and complicate. Therefore, a method to test morphological parameters of wheat grains on spike based on improved Mask R-CNN was proposed in this research.【Method】Two sides front images of three varieties wheat spikes, including Zhenmai 25, Ningmai 13 and Longmai 88 (Early maturity variety), were collected, and then the image enhancement data set was constructed by using Gaussian filter, salt and pepper noise, and vertical flip image enhancement method. A method combined with deep learning and morphological processing for testing phenotype parameters of wheat grains on spike was proposed. Firstly, the improved Mask R-CNN network model for segmenting spike glume was constructed, which was based on feature extraction networks of ResNet and FNP, and the innovative components Coordinate Attention (CA) module, Aggregation module, and Halfconv module were integrated into it. And the glumes on spike image were accurately detected, located, segmented and counted by the improved Mask R-CNN network model. Secondly, five phenotype parameters of the glumes on spike were extracted by using morphologic processing method from the segmented mask image of wheat spike glume, and the linear correlation equations between the phenotype parameters of the glumes and the phenotype parameters of grains were established. Finally, the linear correlation equations between the phenotype parameters of glume and the phenotypic parameters of grain were used to predict the phenotype parameters of grain.【Result】(1) F1 score, average precision (AP) and recall rate of the optimal model for separating spike glume based on the improved Mask R-CNN network model were 91.12%, 94.13% and 88.30%, respectively, and the average consuming time for detecting a single image was 97 milliseconds, so the improved Mask R-CNN network model could quickly and accurately identify the glumes on the single wheat spike. The root-mean-square error and average relative error for segmenting spike grain by the model were 0.94 piece and 0.65%, respectively, so this showed that spike glumes were segmented precisely by the model. (2) The established linear correlation equations for length, thickness, area, circumference, and length-thickness ratio between wheat spike glume and actual grain were y=0.7258x, y=0.5166x, y=0.3748x, y=0.6756x and y=1.4085x, respectively, and the determination coefficient (R²) of the linear correlation equations all were greater than 0.85. (3) The above correlation equations were verified and phenotype parameters of grain were predicted by using the extracted phenotype parameter data of wheat spike glume, the root-mean-square errors and average relative error for length, thickness, area, circumference and length-thickness ratio between predicted values and actual values of wheat grains were 0.17 mm, 0.08 mm, 0.46 mm², 0.33 mm, 0.12, and 0.02%, 0.02%, 0.02%, 0.03%, respectively. The determination coefficient (R²) for each phenotype parameter between the predicted data and the actual data was above 0.85, research results indicated that the proposed method in this study was feasible【Conclusion】 The method for testing phenotype parameters of wheat grains on spike based on improved Mask R-CNN was proposed in this research, and the phenotype parameters of wheat grain on spike could be predicted accurately and effectively by the phenotype parameters of wheat spike glume. This research provided a new method to extract rapidly and simply wheat grain phenotype parameters on spike.

In order to explore the effective control methods for wheat crown rot, Bacillus amyloliquefacien（≥100 million cfu/g) AS, 5% mepiquat chloride AS and thifluzamide (240g/L) SC were selected to control the disease in this study. The results showed that the combination of the three agents increased the four evaluation indexes and reduced diseased plants in seeding stage. The combinations also significantly reduced the incidence speed in jointing stage, the treatment 6 was the best and the diseased stem rate was 20.00%. The results of the survey during the seed filling stage showed that the three combinations could control the spread of wheat crown rot and the diseased stem rate was 23.33%-24.44%, the control efficiency was more than 75%. The combinations of the three agents increased the yield rate by more than 21.23%. The result showed that the combinations of the three agents could control the wheat crown rot and increase the wheat yield, which could be popularized in the future.