Huang-Huai Region Research Articles

Fungal Pathogen Diversity and Fungicide Resistance Assessment in Fusarium Crown Rot of Wheat in the Huanghuai Region of China.

Fusarium crown rot (FCR) poses a major threat to wheat production in the Huanghuai wheat region of China. This study aims to enhance understanding of pathogen populations causing FCR, focusing on their pathogenicity, trichothecene genotypes, and fungicide resistance. During the 2022-2023 growing seasons, we collected 1820 fungal isolates from 233 locations in this region. Our results identified Fusarium pseudograminearum, Fusarium graminearum, and Fusarium asiaticum as the primary pathogens, with F. pseudograminearum exhibiting the highest virulence. Three trichothecene genotypes were identified, including nivalenol, 3-acetyldeoxynivalenol, and 15-acetyldeoxynivalenol. No correlation was observed between trichothecene genotype and virulence, except in F. asiaticum. Antifungal assays demonstrated that all six tested fungicides effectively inhibited F. pseudograminearum, with fludioxonil being particularly effective. Field surveys identified isolates resistant to difenoconazole and pyraclostrobin. Laboratory analysis also revealed strains with FpSdhC1A83V and FpSdhC1S80N mutations conferring resistance to cyclobutrifluram. These findings offer critical insights for developing effective control strategies to manage FCR.

Genome-wide association study of sucrose content in vegetable soybean

BackgroundVegetable soybean is an important legume vegetable. High sucrose content is a significant quality characteristic of vegetable soybean that influences consumers’ taste. However, the genetic basis of sucrose content in vegetable soybean is currently unclear.ResultsIn this study, the genome-wide association study (GWAS) of sucrose content in vegetable soybean was performed using Chinese soybean mini-core collection. The results showed a wide genetic variation for the sucrose content in the mini-core collection. The sucrose content of genotypes from HHR (Huanghuai region) and SR (Southern region) was higher than that of genotypes from NER (Northeast region) and NR (Northern region). Furthermore, 82,187 high quality SNPs (Single nucleotide polymorphism) were used for GWAS of sucrose content. Based on SNPs detected in multiple environments, the chromosome 8 19,496,314–19,698,413 bp interval was identified as the candidate interval. And Glyma.08g234100 was most likely to affect the sucrose content of vegetable soybean seeds.ConclusionsThis study has created new details to be used for breeding for high sucrose content in vegetable soybean.

Design and Analysis of an Electric Integrated Work Vehicle for Corn Intertillage Fertilization and Pesticide Spraying

In response to the situation in the Huanghuai region, where corn fertilization and pesticide application primarily rely on manual methods such as hand broadcasting fertilizer and using manual backpack sprayers, resulting in low levels of mechanization, this study designed an electric integrated work vehicle in line with the trend of developing new energy. The vehicle is powered by six 12 V, 100 Ah lead-acid batteries and integrates the functions of fertilization and pesticide spraying. It can achieve precise hole-fertilization, applying fertilizer to a depth of 100 to 150 mm near the roots of corn, and can also perform multi-row pesticide spraying. The vehicle’s electronic control system is divided into two functional areas: 220 V and 24 V. The walking system uses a 220 V, 2 kW AC servo motor, which is driven by converting the voltage of the 72 V battery group into a 220 V sine wave AC through an inverter, and the motor speed can be adjusted. The working width is adjusted by two fixed electric cylinders at the top of the rear wheel frame. The user can preset the width through the control panel, and during operation, the electric cylinders can be automatically controlled to the optimal working width via a whisker-type limit switch. Analysis using ADAMS software shows that when the vehicle speed is 2, 3, and 5 km per hour, the opening angles of the duckbill controller are 66°, 58°, and 48°, respectively, indicating that the higher the speed, the smaller the opening angle. This shortens the fertilization interval time and makes the fertilization spacing more stable. The maximum opening angle of the adjacent duckbill is 25°, indicating that the fertilization amount remains stable. When the vehicle is moving in reverse, the duckbill always remains closed, and at different speeds, the opening angle change curve of the duckbill controller is smooth and regular. This vehicle significantly improves the efficiency and precision of corn planting. However, improvements are still needed in battery technology, control system optimization, and the high cost of electric agricultural machinery to promote the widespread application of agricultural mechanization.

Stem Rust Resistance and Resistance-Associated Genes in 64 Wheat Cultivars from Southern Huanghuai, China.

Wheat stem rust, caused by Puccinia graminis f. sp. tritici (Pgt), is a devastating fungal disease that affects wheat globally. The planting of resistant cultivars is the most cost-effective strategy for controlling this disease. The Huanghuai region, as a major wheat-growing area, plays a crucial role in the spread and prevalence of wheat stem rust in China. In this study, 64 wheat accessions from this region were tested at the adult stage against two major Pgt races, 34MKGQM and 21C3CTHQM. DNA markers associated with the known resistance genes Sr31, Sr24, Sr25, Sr26, and Sr38 were measured to determine their presence in the tested accessions. In the 2023 field tests, 5 (7.8%) accessions were immune to 21C3CTHQM and 34MKGQM, while 35 (54.7%) and 39 (60.9%) were moderately resistant and resistant, respectively. The remaining 20 (30.7%) accessions were moderately susceptible and susceptible. In the 2024 tests, 12 (18.8%) and 14 (21.9%) entries were immune to both races; 29 (45.3%) and 30 (46.9%) were moderately resistant and resistant, respectively. Only two cultivars, Xinong 816 and Yimai 211, were immune in both years, and three entries showed some degrees of resistance in both years. Seven cultivars, including Zhongzhimai 23, Longxing 1, Yunong 937, Huaguan 301, Wanke 800, Shaanhe 285, and Yunong 612, showed increased susceptibility. DNA markers showed that 30 entries carried Sr31, while 6 entries carried Sr38. Genes Sr24, Sr25, and Sr26, which confer good resistance to the globally prevalent cultivars TKTTF and TTTRF, were absent from the set of tested entries. While this study surveyed the resistance levels of a cross-section of wheat from the southern part of the Huanghuai region and confirmed the presence of two known resistance genes, the basis of immunity or high levels of resistance in several lines remains obscure.

Variations in the Thermal Low-Pressure Location Index over the Qinghai–Tibet Plateau and Its Relationship with Summer Precipitation in China

The thermal and dynamic effects of the special topography of the Qinghai–Tibet Plateau have a significant impact on rainfall in China. Utilizing NCEP/NCAR monthly reanalysis data alongside precipitation observations from 1936 monitoring stations across China spanning from 1966 to 2022, this study establishes a location index for the thermal low-pressure center situated over the Qinghai–Tibet Plateau. Temporal variations in the location index and summer (July) precipitation patterns in China were studied. Over the past six decades, thermal low-pressure centers have been predominantly positioned near 90° E and 32.5° N within a geopotential height of 4360 gpm, with their distribution extending from east to west rather than from south to north. The longitudinal and latitudinal position indices showed the same linear trend, with a negative trend before the 21st century, and then began to turn positive. Mutation analysis highlights pronounced weakening mutations occurring in 1981 and 1973, with the longitudinal index transitioning from an interannual cycle of approximately 6–8 years, while the latitudinal index displays quasi-cyclic oscillations of 5 and 8 and 12–14 years. Strong negative correlations are evident between the location indices and precipitation along the southeastern edge of the Qinghai–Tibet Plateau and in southern China, contrasting with the positive correlations observed in the central-eastern plateau, northwest, north, and the Huang-Huai region of China. The center of the thermal low is located to the east and north, corresponding to the deeper surface thermal low in most areas east of China, and the stronger transport of warm and wet air from the southwest wind, leading to greater convergence of southwest wind and northwest wind in China’s northern region. The south of the Yangtze River is controlled by the strengthening West Pacific subtropical high and South Asia high, resulting in a significant decrease in precipitation, and the warm and humid air from the southwest on the west side of the West Pacific subtropical high is also transported to the north, increasing the precipitation in most parts of the north.

State of China's climate in 2023

China witnessed a warm and dry climate in 2023. The annual surface air temperature reached a new high of 10.71°C, with the hottest autumn and the second hottest summer since 1961. Meanwhile, the annual precipitation was the second lowest since 2012, at 615.0 mm. Precipitation was less than normal from winter to summer, but more in autumn. Consistent with the annual condition, precipitation in the flood season from May to September was also the second lowest since 2012, which was 4.3% less than normal, with the anomalies in the central and eastern parts of China being higher in central areas and lower in the north and south. On the contrary, the West China Autumn Rain brought much more rainfall than normal, with an earlier start and later end. Although there was less annual precipitation in 2023, China suffered seriously from heavy precipitation events and floods. In particular, from the end of July to the beginning of August, a rare, extremely strong rainstorm caused by Typhoon Dussuri hit Beijing, Tianjin, and Hebei, causing an abrupt alteration from drought to flood conditions in North China. By contrast, Southwest China experienced continuous drought from the previous autumn to current spring. In early summer, North China and the Huanghuai region experienced the strongest high-temperature process since 1961. Nevertheless, there were more cold-air processes than normal impacting China, with the most severe of the year occurring in mid-January. Unexpectedly, in spring, there were more sand and dust occurrences in northern China.摘要2023年, 我国气候暖干特征明显, 全国平均气温10.71°C, 为1951年以来最暖; 全国平均降水量615.0 mm, 较常年偏少3.9%, 为2012年以来第二少. 汛期 (5–9月), 全国平均降水量为2012年以来第二少, 中东部降水总体呈“中间多南北少”的分布. 2023年, 我国区域性气象干旱多发, 西南地区遭遇冬春连旱; 春季北方沙尘天气过程偏多; 夏季前期, 华北和黄淮遭受1961年以来最强高温过程; 7月底至8月初, 受台风杜苏芮影响, 京津冀地区发生历史罕见极端强降雨过程, 华北地区出现“旱涝急转”; 华西秋雨开始早, 结束晚, 雨量多.

Research on the Reconstruction of Aquatic Vegetation Landscape in Coal Mining Subsidence Wetlands Based on Ecological Water Level

The eastern region of the Huang-Huai area is vital for China’s coal production, with high water table mining causing significant surface subsidence and the formation of interconnected coal mining subsidence wetlands. Restoring these wetlands is crucial for biodiversity, environmental quality, and sustainable development. Aquatic vegetation plays a crucial role in wetland ecosystems, underscoring its importance in restoration efforts. Understanding and managing water level fluctuations is essential due to their impact on vegetation. This study examines the Qianshiliying coal mining subsidence wetland in the Yanzhou Mining Area, China, with the goal of devising a water level regulation plan based on the minimum ecological water level to improve the growth and recovery of aquatic vegetation. The research delves into landscape ecological restoration techniques for aquatic vegetation in coal mining subsidence wetlands in the eastern Huang-Huai region, emphasizing the importance of water level management. The results reveal that the minimum ecological water level in the Qianshiliying coal mining subsidence wetland is 32.50 m, and an area of 78.09 hectares is suitable for the reconstruction of aquatic vegetation. This paper utilizes lake morphology, minimum biological space, and water level demand methods for aquatic plants in the landscape to promote restoration of coal mining subsidence wetlands. A notable strength of this approach is its ability to quantitatively predict the survival range and area of aquatic vegetation in these wetlands, enabling a more scientifically informed restoration of ecological balance and promoting landscape ecological restoration in the eastern Huang-Huai region.

Comparison of the chemical composition of non-shattering and shattering sesame varieties grown in the Huang-Huai region of China

The nutritional value and chemical composition of two non-shattering sesame varieties, NS610 and ND837, and two shattering varieties, LZ22 and ZZ37, all grown in the Huang-Huai region of China, were comprehensively analyzed and evaluated. Differences in fat, ash, energy and carbohydrate content were significant (p < 0.05) between non-shattering and shattering sesame varieties. Linoleic acid was the most abundant fatty acid, followed by oleic acid. No significant difference in fatty acid and amino acid composition between non-shattering and shattering varieties was found (p > 0.05). Large amounts of Ca, K, Zn, and Mg were detected in all sesame samples, and ND837 contained the highest levels of Ca, K, and Zn. Non-shattering varieties contained more tocopherols, lignans, and oxalic acid compared to shattering varieties. In conclusion, the non-shattering varieties, NS610 and ND837, were close to or higher in nutritional value and chemical composition than the shattering varieties. This is important because non-shattering varieties can be harvested efficiently and cost-effectively by machine while traditional, shattering varieties must be harvested manually.

The Effects of Vernalization and Photoperiod Genes Composition on Heading Date in Wheat

The vernalization characteristics of wheat are mainly controlled by vernalization and photoperiod genes, which determine the winter-spring habit and heading-flowering of wheat, and affect its environmental adaptability. In order to understand the effects of vernalization and photoperiod genes on heading date, 12 common wheat varieties widely cultivated in the Huang-Huai region were used as experimental materials, and the effects of different low-temperature vernalization treatments on wheat heading date were studied. Using molecular markers from previous studies, the allelic variations and genotypes of vernalization genes (VRN-A1, VRN-B1, VRN-D1 and VRN-B3) and photoperiod genes (Ppd-A1, Ppd-B1, Ppd-D1) were detected. By identifying the heading date in a controlled greenhouse, the relationship between the vernalization and photoperiod genes composition and the heading date phenotype was analyzed. The experimental results showed that different wheat varieties had different phenotypes after different vernalization treatments. Tian min 198 carried a dominant vernalization gene, and its vernalization characteristics were expressed as spring wheat varieties, with low requirements for low-temperature vernalization. Wheat without a dominant vernalization gene had winter wheat characteristics, with high requirements for low-temperature vernalization. Wheat varieties carrying a dominant vernalization gene can be used to improve late-maturing wheat varieties, and serve as valuable germ plasma resources for variety improvement and introduction. Exploring the effects of different wheat vernalization and photoperiod genes composition on heading date is beneficial to provide a scientific basis for the rational use of wheat varieties, and studying the vernalization and photoperiod genes composition has guiding significance for wheat introduction and ecological breeding.

Genome Analyses Reveal the Secondary Metabolites that Potentially Influence the Geographical Distribution of Fusarium pseudograminearum Populations.

Fusarium crown rot (FCR), caused by Fusarium pseudograminearum, significantly impacts wheat yield and quality in China's Huanghuai region. The rapid F. pseudograminearum epidemic and FCR outbreak within a decade remain unexplained. In this study, two high-quality, chromosome-level genomes of F. pseudograminearum strains producing 3-acetyl-deoxynivalenol (3AcDON) and 15-acetyl-deoxynivalenol (15AcDON) toxins were assembled. Additionally, 38 related strains were resequenced. Genomic differences such as single nucleotide polymorphisms (SNPs), insertions/deletions (indels), and structural variations (SVs) among F. pseudograminearum strains were analyzed. The whole-genome SNP locus-based population classification mirrored the toxin chemotype (3AcDON and 15AcDON)-based classification, indicating the presence of genes associated with the trichothecene toxin gene cluster. Further analysis of differential SNP, indel, and SV loci between the 3AcDON and 15AcDON populations revealed a predominant connection to secondary metabolite synthesis genes. Notably, the majority of the secondary metabolite biosynthesis gene cluster loci were located in SNP-dense genomic regions, suggesting high mutability and a possible contribution to F. pseudograminearum population structure and environmental adaptability. This study provides insightful perspectives on the distribution and evolution of F. pseudograminearum and for forecasting the spread of wheat FCR, thereby aiding in the development of preventive measures and control strategies.

Validation Analysis of Drought Monitoring Based on FY-4 Satellite

Droughts are natural disasters that have significant implications for agricultural production and human livelihood. Under climate change, the drought process is accelerating, such as the intensification of flash droughts. The efficient and quick monitoring of droughts has increasingly become a crucial measure in responding to extreme drought events. We utilized multi-imagery data from the geostationary meteorological satellite FY-4A within one day; implemented the daily Maximum Value Composite (MVC) method to minimize interference from the clouds, atmosphere, and anomalies; and developed a method for calculating the daily-scale Temperature Vegetation Drought Index (TVDI), which is a dryness index. Three representative drought events (Yunnan Province, Guangdong Province, and the Huanghuai region) from 2021 to 2022 were selected for validation, respectively. We evaluated the spatial and temporal effects of the TVDI with the Soil Relative Humidity Index (SRHI) and the Meteorological Drought Composite Index (MCI). The results show that the TVDI has stronger negative correlations with the MCI and SRHI in moderate and severe drought events. Meanwhile, the TVDI and SRHI exhibited similar trends. The trends of drought areas identified by the TVDI, SRHI, and MCI were consistent, while the drought area identified by the TVDI was slightly higher than the SRHI. Yunnan Province has the most concentrated distribution, which is mostly between 16.93 and 25.22%. The spatial distribution of the TVDI by FY-4A and MODIS is generally consistent, and the differences in severe drought areas may be attributed to disparities in the NDVI. Furthermore, the TVDI based on FY-4A provides a higher number of valid pixels (437 more pixels in the Huanghuai region) than that based on MODIS, yielding better overall drought detection. The spatial distribution of the TVDI between FY-4A and Landsat-8 is also consistent. FY-4A has the advantage of acquiring a complete image on a daily basis, and lower computational cost in regional drought monitoring. The results indicate the effectiveness of the FY-4A TVDI in achieving daily-scale drought monitoring, with a larger number of valid pixels and better spatial consistency with station indices. This study provides a new solution for drought monitoring using a geostationary meteorological satellite from different spatial–temporal perspectives to facilitate comprehensive drought monitoring.

Baseline Pydiflumetofen Sensitivity of Fusarium pseudograminearum Isolates Collected from Henan, China, and Potential Resistance Mechanisms.

Fusarium crown rot (FCR), caused by Fusarium pseudograminearum, is one of the most important diseases impacting wheat production in the Huanghuai region, the most important wheat-growing region of China. The current study found that the SDHI fungicide pydiflumetofen, which was recently developed by Syngenta Crop Protection, provided effective control of 67 wild-type F. pseudograminearum isolates in potato dextrose agar, with an average EC50 value of 0.060 ± 0.0098 μg/ml (SE). Further investigation revealed that the risk of fungicide resistance in pydiflumetofen was medium to high. Four F. pseudograminearum mutants generated by repeated exposure to pydiflumetofen under laboratory conditions indicated that pydiflumetofen resistance was associated with fitness penalties. Mutants exhibited significantly (P < 0.05) reduced sporulation in mung bean broth and significantly (P < 0.05) reduced pathogenicity in wheat seedlings. Sequence analysis indicated that the observed pydiflumetofen resistance of the mutants was likely associated with amino acid changes in the different subunits of the succinate dehydrogenase target protein, including R18L and V160M substitutions in the FpSdhA sequence; D69V, D147G, and C257R in FpSdhB; and W78R in FpSdhC. This study found no evidence of cross-resistance between pydiflumetofen and the alternative fungicides tebuconazole, fludioxonil, carbendazim, or fluazinam, which all have distinct modes of action and could therefore be used in combination or rotation with pydiflumetofen to reduce the risk of resistance emerging in the field. Taken together, these results indicate that pydiflumetofen has potential as a novel fungicide for the control of FCR caused by F. pseudograminearum and could therefore be of great significance in ensuring high and stable wheat yields in China.

Evolution of summer surface ozone pollution patterns in China during 2015–2020

Surface ozone is one of the most severe air pollutants in China and is influenced by meteorological processes on multiple scales. By identifying the two dominant patterns of ozone pollution through Empirical Orthogonal Functions method, we show here that the widespread pollution processes in China may be closely related to high-pressure anomaly in North China and low-pressure anomaly in the western Pacific, respectively. The positive time period of the first pattern (PC1P) extracts the distribution characteristics of the most severe periods of ozone pollution in summer time. It is physically linked to the high-pressure anomaly in North China centered on the Huanghuai Region, which eventually induced the high-temperature anomaly and low-humidity anomaly that enhanced the photochemical reactions to elevate the ozone levels. The spatial and temporal evolution of ozone pollution during this meteorological process shows a uniform pollution characteristic in the northern region and a higher increase in ozone concentration in the Huanghuai Region. The positive time period of the second pattern (PC2P) is associated with the variation of the low-pressure anomaly in the western Pacific. It indicates uniformly high ozone pollution in the south, especially in the Yangtze River Delta, the middle reaches of the Yangtze River (MYR) and the Pearl River Delta. Our results highlight that summer ozone pollution in eastern China is closely related to weather patterns. In addition, it is noteworthy that in the positive time period, the annual growth trends of Huanghuai Region in the first pattern (PC1P) and MYR in the second pattern (PC2P) are significantly higher than the growth trends of the megacity clusters, which requires the attention of relevant policy-making authorities.

Ensemble learning prediction of soybean yields in China based on meteorological data

The accurate prediction of soybean yield is of great significance for agricultural production, monitoring and early warning. Although previous studies have used machine learning algorithms to predict soybean yield based on meteorological data, it is not clear how different models can be used to effectively separate soybean meteorological yield from soybean yield in various regions. In addition, comprehensively integrating the advantages of various machine learning algorithms to improve the prediction accuracy through ensemble learning algorithms has not been studied in depth. This study used and analyzed various daily meteorological data and soybean yield data from 173 county-level administrative regions and meteorological stations in two principal soybean planting areas in China (Northeast China and the Huang–Huai region), covering 34 years. Three effective machine learning algorithms (K-nearest neighbor, random forest, and support vector regression) were adopted as the base-models to establish a high-precision and highly-reliable soybean meteorological yield prediction model based on the stacking ensemble learning framework. The model’s generalizability was further improved through 5-fold cross-validation, and the model was optimized by principal component analysis and hyperparametric optimization. The accuracy of the model was evaluated by using the five-year sliding prediction and four regression indicators of the 173 counties, which showed that the stacking model has higher accuracy and stronger robustness. The 5-year sliding estimations of soybean yield based on the stacking model in 173 counties showed that the prediction effect can reflect the spatiotemporal distribution of soybean yield in detail, and the mean absolute percentage error (MAPE) was less than 5%. The stacking prediction model of soybean meteorological yield provides a new approach for accurately predicting soybean yield.

Characterization and allelism of soybean mosaic virus strain SC3 resistance in ‘Qihuang‐1’ derived soybean cultivars

AbstractSoybean mosaic virus is a severe constraint of soybean production in China. A total of country‐wide 22 SMV strains (SC1‐SC22) were identified. Of these, SC3 is a major strain widely distributed in Huanghuai and Yangtze River Valley region of China. Soybean cultivar ‘Qihuang‐1’ contains RSC3Q locus conditioning the resistance to SC3 and is an important parental line extensively used to breed the soybean cultivars in China. The objective of this study was to elucidate the genetic pattern of SC3 resistance genes in cultivars developed from ‘Qihuang‐1’ or its derivative lines. Hence, we have evaluated the SC3 resistance in 91 cultivars developed from ‘Qihuang‐1’ or its derivative lines. The results showed that a total of 43 cultivars exhibited resistance to the SC3 strain. Among them, 37 cultivars were derived from ‘Qihuang‐1’. Then, we have detected the RSC3Q loci in these cultivars using four SSR markers (Satt334, Sct_033, BARCSOYSSR_13_1114 and BARCSOYSSR_13_1136). It revealed that, among the 37 resistant cultivars derived from ‘Qihuang‐1’, there are 20 cultivars containing RSC3Q loci. Moreover, the allelic relationship of resistance genes was analysed using the crosses from resistance × resistance between ‘Qihuang‐1’ and its resistant derived cultivars. The results showed that the resistance genes of ‘Qihuang‐1’ and its 20 cultivars were allelic. But it is not allelic with those of the other 17 cultivars, different from ‘Qihuang‐1’, and also, RSC3Q does not condition the resistance. These results will be beneficial to exploring the transmission of resistance genes of ‘Qihuang‐1’ and will be useful to the disease resistance breeding of soybean.

Identification of tolerance to high density and lodging in short petiolate germplasm M657 and the effect of density on yield-related phenotypes of soybean

Soybean yield has traditionally been increased through high planting density, but investigating plant height and petiole traits to select for compact architecture, lodging resistance, and high yield varieties is an underexplored option for further improving yield. We compared the relationships between yield-related traits, lodging resistance, and petiole-associated phenotypes in the short petiole germplasm M657 with three control accessions during 2017–2018 in four locations in the Huang–Huai region, China. The results showed that M657 exhibited stable and high tolerance to high planting density and resistance to lodging, especially at the highest density (8×105 plants ha−1). The regression analysis indicated that a shorter petiole length was significantly associated with increased lodging resistance. The yield analysis showed that M657 achieved higher yields under higher densities, especially in the northern part of the Huang–Huai region. Among the varieties, there were markedly different responses to intra- and inter-row spacing designs with respect to both lodging and yield that were related to location and density. Lodging was positively correlated with planting density, plant height, petiole length, and number of effective branches, but negatively correlated with stem diameter, seed number per plant, and seed weight per plant. The yield of soybean was increased by appropriately increasing the planting density on the basis of the current soybean varieties in the Huang–Huai region. This study provides a valuable new germplasm resource for the introgression of compact architecture traits that are amenable to providing a high yield in high density planting systems, and it establishes a high-yield model of soybean in the Huang–Huai region.

Cross-Comparison of channel parameters between FY-3E/MERSI-LL and Himawari-8/AHI in China

ABSTRACT Fengyun-3E (FY-3E) is the world’s first operational meteorological satellite on dawn-dusk orbit. In order to realize the generality of algorithms for different satellites and provide a basis for subsequent inversion studies on remote sensing parameters, such as land surface temperature, fire, and atmospheric water vapour, we perform a cross-comparison of the brightness temperature (TB) of the six infrared (IR) channels between the Medium Resolution Spectral Imager Level L onboard the FY-3E satellite (FY-3E/MERSI-LL) and the Advanced Himawari Imager onboard the Himawari-8 satellite (Himawari-8/AHI). The statistical indicators, correlation coefficient, root mean square error (RMSE) and mean bias, are used to analyse the consistency and differences of the channel parameters between the MERSI-LL and AHI in terms of overall data, different regions and different TB. The results show that the TB data observed by the FY-3E/MERSI-LL and Himawari-8/AHI are generally consistent, with correlation coefficients of more than 0.99, mean biases of less than 1.60 K and RMSEs of less than 1.90 K. In terms of different channels, the TB in channel IR 038 has the best consistency between the two sensors, while the results from the MERSI-LL are higher than those of the AHI for channels IR038, IR086, IR108 and IR120, and lower than those of the AHI for channel IR041. Analysing the situation in different regions, we find that the MERSI-LL and AHI data are highly consistent and relatively stable in the Huang-Huai Region, with low RMSEs, low mean biases and high correlation coefficients (more than 0.95) at all channels. For the different TB ranges, the RMSEs and mean biases for the TB ranges of 270–280 K and 280–290 K between the MERSI-LL and AHI are small, and the data in the 290–300 K TB range has great differences and fluctuations between the two sensors.

Application of Affinity Propagation Clustering Method in Medium and Extended Range Forecasting of Heavy Rainfall Processes in China

Based on the precipitation data of an ensemble forecast from the European Centre for Medium-Range Weather Forecasts, we establish a clustering model named EOF_AP by using the empirical orthogonal function decomposition and the affinity propagation clustering method. Then, using EOF_AP, we conducted research on the identification and classification of the characteristics of medium and extended range forecasts on 11 heavy rainfall events in the middle–lower reaches of the Yangtze River, North China, and the Huanghuai region, from June to September in 2021. We then selected two representative cases to analyze the common characteristics in detail to evaluate the effect of the model. The results show that the EOF_AP clustering model can better identify and classify the main rainfall pattern characteristics, and their corresponding occurrence probability of heavy rainfall processes, on the basis of comprehensively retaining the main forecast information of ensemble members with a few representative types. The rainfall pattern characteristics of some types with low occurrence probability can be identified, such as the extreme type. The distributions of rainfall patterns of the same type are basically consistent, whereas those among different types are distinct. Moreover, through the comparison of the forecast results with different starting times, we analyze the forecast performance of ensemble members and the variation trend of forecast results. We hope this study can provide a reference for the probability forecast of medium and extended range heavy rainfall process.

Application of &amp;lt;italic&amp;gt;Fhb1 &amp;lt;/italic&amp;gt;gene in wheat breeding programs for the Yellow-Huai Rivers valley winter wheat zone of China

<p id="C3"><italic>Fusarium</italic> head blight (FHB), caused by <italic>Fusarium graminearum</italic>, is an important disease that seriously threatens the safety of wheat production. Breeding progress of resistant cultivars has been limited due to absence of the resistant sources with facultative growth habit and poor screening environment in the Huang-Huai region, the main wheat producing area of China. <italic>Fhb1</italic>, as the most effective and stable gene, is the only gene widely used in the global breeding programs for improving FHB resistance of wheat. However, utilization of <italic>Fhb1</italic> in the Yellow-Huai River Valleys Winter Wheat Zone is limited so far. In this study, several excellent advanced lines with <italic>Fhb1</italic> were developed by limited backcrossing and molecular marker-assisted selection in the BC₂F₁ progenies of the susceptible variety Aikang 58 (the recurrent parent) and H35 (the donor parent of <italic>Fhb1</italic> gene). Then, the individuals were used to cross with Xumai 36 and Xumai 2023 (with high yield but susceptible to FHB), and a series of elite lines with <italic>Fhb1</italic> were developed using the doubled haploid and the traditional pedigree selection methods. Xumai DH9 and Xumai 17252 were moderate resistance to FHB in different screening environments for several years. The average resistance level of the lines with <italic>Fhb1</italic> gene was significantly higher than that of the susceptible control. The introduction of <italic>Fhb1</italic> significantly improved the resistance to FHB, but some lines were still highly susceptible, indicating that the resistance to FHB was affected by other genetic factors. This study provides an example for the use of <italic>Fhb1</italic> gene in improving FHB resistance in the Yellow-Huai River Valleys Winter Wheat Zone of China.

Assessment of soil quality for guided fertilization in 7 barley agro-ecological areas of China.

Soil quality is the basis for the development of sustainable agriculture and may be used for evaluating the sustainability of soil management practices. Soil quality status and integrated soil quality index (SQI) in sampled 97 farmlands distributed in 7 barley agro-ecological areas of China were analyzed by using 13 soil chemical parameters. The results showed six principal components totally explained 72% variability for the 13 parameters and identified 9 parameters (includes pH, NH4+-N, NO3--N, available P, available K, exchangeable Mg, DTPA-Fe, DTPA-Cu and Cl-) with high factor loading values as the minimum data set (MDS) for assessing soil quality. Average soil quality of all farmlands is moderate (SQI = 0.62). The SQI of barley farmlands in 7 agro-ecological areas showed the following order: Inner Mongolia Plateau (0.75 ± 0.02) > Yunnan-Kweichow Plateau (0.72 ± 0.06) > Qinghai-Tibet Plateau (0.63 ± 0.08) > Yangtze Plain (0.62 ± 0.10) > Huanghuai Region (0.58 ± 0.09) > Northeast China Plain (0.56 ± 0.07) > Xinjiang Province (0.54 ± 0.07). Total 29 out of 97 farmlands in 7 areas have low SQI level (< 0.55). Hence, these farmlands require urgent attention for soil quality improvement through modification of the soil parameters in the MDS.