Abbreviation (ISO4): Chin Agric Sci Bull
Editor in chief: Yulong YIN
Traditional rice breeding is characterized by long cycles, low selection efficiency and experience-dependent decision-making, which can hardly meet the demands for efficient and precise breeding in the modern seed industry. The explosive growth of multi-omics data and the rise of artificial intelligence (AI) have opened up a new avenue for intelligent rice breeding. To systematically integrate database resources and AI technologies and establish a data-driven intelligent rice breeding and selection system, this paper reviews the functional characteristics and typical platforms of four major categories of rice databases, including rice genome, transcriptional regulation, gene interaction networks and germplasm resource pedigrees, with representative platforms covering RiceVarMap, Ribo-uORF, RiceNet v2 and the Chinese Rice Variety Pedigree Database. It also summarizes the research progress of AI applications in multiple scenarios, such as intelligent phenotypic prediction, breeding efficiency improvement, environmental adaptability evaluation, key gene mining and genomic analysis. Furthermore, a breeding application framework integrating databases and AI is constructed, which consists of core modules including data integration and management, high-throughput data processing and compression, in-depth genomic analysis, multi-dimensional phenotypic prediction and intelligent decision support. The results indicate that the in-depth integration of databases and AI can remarkably enhance the efficiency of gene mapping, the accuracy of phenotypic prediction and the rationality of parent selection, as well as improve the scientificity and effectiveness of intelligent breeding decision-making. The breeding cycle can be shortened from 8-10 years to 3-5 years. At present, the development still faces bottlenecks such as inconsistent data standards, insufficient multimodal data fusion and lagging field application. In the future, it is necessary to formulate unified data standards, develop multimodal large models and strengthen collaborative verification among industry, academia and research institutes, so as to accelerate the realization of precise, efficient and intelligent rice breeding. This paper provides a systematic reference for the research, development and industrial application of intelligent rice breeding technologies.
The study aims to screen high-quality forage triticale germplasm resources in alpine pastoral areas, and to provide a theoretical basis for the breeding and promotion of high-yield and high-efficiency forage triticale varieties in this area. In this study, five forage triticale varieties were used as test materials, and their grain traits including ear length and ear weight, as well as photosynthetic parameters such as chlorophyll content and net photosynthetic rate were systematically determined. Single factor analysis of variance was used to compare the differences of indexes among different cultivars, Pearson correlation analysis was adopted to explore the correlation between various indexes, and principal component analysis(PCA) was combined for dimensionality reduction and extraction of key comprehensive indexes. Finally, TOPSIS ideal solution ranking method was used to comprehensively evaluate the tested triticale varieties. The results showed that there were significant differences in grain traits and photosynthetic characteristic indexes among all tested triticale cultivars (P<0.05). There was a close synergistic relationship between grain traits and photosynthetic performance. Specifically, ear length was significantly positively correlated with ear weight, grain number per ear, ear weight per unit area, grain weight per unit area and chlorophyll content; grain weight per ear was significantly positively correlated with ear weight per unit area and grain weight per unit area (P<0.05); thousand-grain weight was significantly negatively correlated with panicle length and grain number per panicle (P<0.05), and extremely significantly positively correlated with stomatal conductance (P<0.01). Two core components were extracted by PCA, and ear length and thousand-grain weight were identified as the core indexes determining the comprehensive performance of the tested cultivars. The comprehensive ranking of the tested cultivars by TOPSIS was as follows: ‘Qingsimai 8’ > ‘Qingsimai 7’ > ‘Qingsimai 1’ > ‘Qingsimai 2’ > ‘Qingsimai 3’. In conclusion, ‘Qingsimai 8’ presented outstanding performance in both grain traits and photosynthetic efficiency, and is a preferred cultivar with great popularization and application potential in alpine pastoral areas. This study can provide a theoretical reference for the breeding and promotion of forage triticale cultivars.
Shuozhou City, located in the semi-arid and ecologically fragile region of northern Shanxi, is highly sensitive to precipitation changes due to its rain-fed agricultural system. Climate change has intensified spatiotemporal fluctuations in precipitation and increased the frequency of droughts and floods, severely affecting agricultural stability. This study aims to reveal the spatiotemporal patterns of precipitation evolution and their dual impacts on agriculture, providing scientific support for optimizing local agricultural planning and disaster risk prevention and management capabilities. Based on precipitation data of 54 years (1972-2025) from six counties and districts in Shuozhou, we applied linear trend estimation, the Mann-Kendall test, and Morlet wavelet analysis to examine precipitation trends and their effects on agriculture. Results showed that the annual precipitation in Shuozhou decreased gradually from west to east, with higher values in the western regions. Both annual and daily maximum precipitations showed increasing trends, rising by 18.0 mm per decade and 1.5 mm per decade, respectively. Precipitation during spring, summer, and autumn had all increased significantly, while winter precipitation showed no notable change. Since 1991, precipitation had steadily increased across decades, with the most pronounced growth occurring between 2016 and 2025; average precipitation over the past 30 years had been significantly higher than in earlier periods. Precipitation was concentrated from May to September, accounting for 70% of the annual total, with July and August alone contributing 48%. Extreme precipitation events peaked from late July to mid-August, with a record high of 117.1 mm recorded in Shuocheng District. Annual precipitation showed a sudden shift in 2023 and exhibited a 3-year cycle, while daily extreme precipitation experienced two abrupt shifts (in 1979 and 2001) and followed a 2-5 year cycle. The impact of precipitation changes on agriculture is mixed: increased rainfall helps alleviate spring and summer droughts, improves soil moisture, and promotes higher yields of drought-tolerant crops. However, more frequent short-term heavy rains in summer and prolonged rainy spells in autumn increase risks of flooding, water logging, crop lodging, and disease outbreaks. Uneven spatial distribution further intensifies regional disparities in agricultural vulnerability. Overall, over the past 54 years, Shuozhou has experienced an upward trend in precipitation, with greater concentration and increased extremity. While this generally benefits dry land farming, seasonal imbalance and frequent extreme events threaten production stability. Future strategies should account for regional differences-improving drainage and flood prevention in eastern areas and promoting rainwater harvesting and supplementary irrigation in western areas, while optimizing crop varieties and sowing schedules to achieve efficient water use and effective disaster mitigation. This research provides a scientific basis for climate resource utilization and agricultural planning in the region.
To quantitatively assess the impact of meteorological conditions on the quality of sand pears, the key meteorological factors affecting the quality of sand pears were screen out by using the methods of correlation analysis, multiple stepwise regression analysis and weighted calculation based on the quality data of sand pears from 2018 to 2024 and the meteorological observation data of the same period. The climate quality evaluation models and fruit climate quality classification index for Jinshan sand pears were constructed. The results showed that the soluble solids content of sand pears was significantly positively correlated with the daily temperature range and sunshine duration during the fruit expansion period, with correlation coefficients of 0.75 and 0.76 respectively, while it was significantly negatively correlated with the minimum temperature during the fruit expansion period and the precipitation at maturity stage, with correlation coefficients of -0.81 and -0.73 respectively. The single fruit weight had the greatest positive correlation with the precipitation during the fruit expansion period, with a correlation coefficient of 0.96. The climate quality grade indicators for the super-grade sand pear were as follows: the average daily minimum temperature within 35 days before picking was no more than 24.0℃, the daily temperature range within15 days before picking was no less than 7.0℃, the sunshine duration within 31 days before picking was no less than 175.6 hours, the precipitation within 36 days before picking was no less than 186.0 mm, and the precipitation within 10 days before picking was no more than 66.0 mm. Upon verification, the sand pear climate quality evaluation models established in this paper can effectively reflect the impact of climatic conditions on sand pear quality. This research outcome can provide a scientific decision-making reference for sand pear production and relevant management departments.
To accurately retrieve phenological information of grasslands in northern Xizang using remote sensing methods, based on MODIS 13Q1 NDVI data with 250 m spatial resolution and 16-day composite intervals from 2001 to 2023, combined with daily MODIS 250 m data received at Lhasa Station in 2024, a dataset of annual 16-day maximum NDVI was constructed after preprocessing such as calculating vegetation indices and maximum value composite (MVC). The phenological periods of grasslands in northern Xizang were extracted by combining the dynamic threshold method with elevation zonings, and the spatial differentiation pattern and inter-annual variation trend of phenology were analyzed. Correlation analysis was then conducted with annual cumulative precipitation, annual mean air temperature, and annual total sunshine hours from 7 meteorological stations in Nagqu City, northern Xizang, from 2001 to 2024. The results showed that the green-up period of grasslands in Nagqu City mostly occurred from day 171 to day 181, and the senescence period mostly occurred before day 257. The green-up period showed an advancing trend, while the senescence period showed a delaying trend. There were obvious spatial differences in the response of grassland phenology to meteorological factors. Most of the regional correlations did not reach the significant level, and only some areas had significant correlations. Among them, the correlation between the green-up period and the temperature covered a wider range, and the proportion of significant correlation was the highest; it was mainly negatively correlated with precipitation, and the overall impact of sunshine was weak, accounting for a very low proportion. The senescence period was positively correlated with both precipitation and temperature, and negatively correlated with sunshine. In summary, grassland phenology in northern Xizang exhibits obvious elevation differentiation, with an overall trend of “earlier green-up and later senescence”. Temperature is the most critical factor affecting the spatial pattern of grassland phenology in northern Xizang, and its regulatory effect is significantly stronger than precipitation and sunshine. The 7 meteorological stations are all located in the central and southern parts of Nagqu City, where a persistent “warming-drying” climate trend is observed, and the grassland ecosystem is highly dependent on water resources.
To investigate the characteristics of climate change in Xihe County, Gansu Province, and explore its impact on maize growth stages and yield, this study analyzed meteorological and maize observation data from 1991 to 2025. Univariate linear regression, correlation analysis, and climate contribution rate analysis were applied to systematically analyze changes in key meteorological elements during maize growth stages and their effects on growth duration and yield. The findings indicate: (1) Over the past 35 years, the climate during the maize growing season in Xihe County has shown a warming and moistening trend. The average temperature has significantly increased at a rate of 0.5℃ per decade (P<0.05). Although precipitation showed an increasing trend (19.9 mm per decade), it was not significant. Sunshine duration has significantly decreased at a rate of 39.2 hours per decade (P<0.05). (2) Influenced by climate change, maize emergence, milk stage, and maturity have significantly advanced, while the whole growth duration has significantly shortened (-4.5 days/decade, P<0.05). Correlation analysis revealed a significant negative correlation between whole growth duration and average temperature (R=−0.39, P<0.05), while correlations with precipitation and sunshine duration were not significant. Water and light factors significantly influenced only specific growth stages: emergence showed a significant negative correlation with precipitation (R=−0.42, P<0.05), and adequate rainfall promoting earlier emergence; while tasseling exhibited a significant negative correlation with sunshine duration (R=−0.45, P<0.05), suggesting that insufficient sunshine may delay tasseling. (3) Actual maize yields showed a significant downward trend from 1991 to 2025, with considerable meteorological yield variability. Key factors limiting meteorological yield included insufficient precipitation during tasseling, insufficient sunshine duration during maturity, and excessive precipitation during maturity. On this basis, it is recommended that local producers in Xihe County should select and breed maize varieties with longer growing seasons and heat tolerance. Special attention should be paid to preventing drought during the tasseling stage and continuous rainy weather during the ripening stage, and measures such as supplemental irrigation and timely drainage should be taken to ensure stable yields.
Proteomics technology, as it can systematically analyze the spatiotemporal expression changes of proteins, has become one of the indispensable multi-omics research methods in wheat biological research. To comprehensively review the research progress of proteomics in the regulation of important agronomic traits in wheat, this paper summarizes the major advances of quantitative proteomics and post-translational modification proteomics over the past five years in research topics including wheat seed development and storage, disease resistance regulation, abiotic stress response, cultivation management and basic biological research, and elaborates on the latest research findings of quantitative proteomics technology and post-translational modification proteomics technology in the dissection of regulatory mechanisms for important agronomic traits in wheat. On this basis, this review points out that current research on wheat proteomics is still confronted with three major challenges: (1) there is a lack of a special technical system adapted to the complex genome of wheat; (2) most studies only stay at the stage of differential protein screening and functional enrichment, and the in-depth functional verification of candidate proteins as well as the efficiency of breeding application transformation need to be urgently improved; (3) the in-depth mining of proteomic data and its integration with cutting-edge technologies including artificial intelligence, genomics and metabolomics remain insufficient. In view of the above mentioned problems, it is proposed that efforts should be made to build professional research teams for wheat proteomics, to develop wheat-specific analytical tools, to construct an artificial intelligence-driven multi-omics intelligent breeding platform, to accelerate the translation of key proteins and molecular modules into breeding practices, and to provide stronger scientific and technological support for green and efficient breeding as well as sustainable production of wheat.
To analyze the complete chloroplast genome characteristics of the local population of Suichuan Gougunao tea tree, the DNBSEQ-T7 BGI sequencing platform and bioinformatics analysis software were used in this study to analyze the chloroplast genome of the local population of Suichuan Gougunao tea tree. The chloroplast genome of the local population of Suichuan Gougunao tea tree was a typical quadripartite circular structure with a total length of 157099 bp. A total of 135 functional genes were annotated, and 53 simple sequence repeat (SSR) loci and 48 long repeats were detected. The variation range of nucleotide polymorphism (Pi) was 0-0.01265, with weak codon bias. There were a total of 14 optimal codons, with the ndhB gene and rps8 gene undergoing positive selection, while the remaining genes were subject to purifying selection. The local population of Suichuan Gougunao tea tree was closely related to Dehong tea (KJ806279). The divergence time between the local population of Suichuan Gougunao tea tree and Tingpingdong (PP231879) and Liubao tea (OQ281601) was approximately 5.55 million years ago.
This study optimized key cultivation parameters of a wild Sanghuangporus sp., aiming to provide a theoretical basis for efficient cultivation of Sanghuangporus sp.. Using a wild Sanghuangporus sp. as material, PDA medium was employed for mycelial isolation and purification culture, and the effects of different temperatures and nutritional conditions on the mycelial growth of this Sanghuangporus sp. were investigated. The results showed that 30℃ was more favorable than 20℃ for the germination and growth of Sanghuangporus sp. mycelia. In the carbon source experiment, the starch treatment group exhibited the fastest mycelial growth rate (3.5 mm/d), with significant differences compared to other groups, followed by the glucose treatment group. In the nitrogen source experiment, the beef extract treatment group had the shortest mycelial germination time, with robust and rapidly growing mycelia; the glycine treatment group showed prolonged germination time and slow growth. In the inorganic salt experiment, calcium chloride had the best promoting effect on Sanghuangporus sp. mycelia, with a daily mycelial growth of 3.5 mm/d, followed by the sodium chloride treatment group. The mycelial growth of this Sanghuangporus sp. strain is highly sensitive to temperature and nitrogen source, and appropriate culture temperature and nitrogen source type are key factors for promoting efficient mycelial growth.
The study aims to investigate the expression characteristics of growth factor independent 1B (GFI1B) and Tropomodulin (TMODs) family member TMOD4 gene in common carp (Cyprinus carpio) following acute and chronic infection with Aeromonas veronii (A. veronii), in order to reveal the molecular mechanisms by which these two genes participate in antibacterial infection through the regulation of hematopoietic cell generation and immune cell migration pathways. In this study, the full-length coding regions (CDS) of GFI1B and TMOD4 in common carp were cloned, and their sequences were subjected to bioinformatics analysis. The expression patterns of GFI1B and TMOD4 in response to A. veronii infection were analyzed using two models: chronic infection in carp for 15 days and acute infection in carp leukocyte cell lines for 24 hours. Protein-protein interaction networks of GFI1B and TMOD4 were predicted using STRING12.0 software based on zebrafish homologous proteins, followed by joint analysis incorporating expression data. The GFI1B CDS region spanned 762 bp and encoded a 253-amino acid protein, whereas the TMOD4 CDS comprised 1032 bp and translates into a 343-amino acid protein. The GFI1B protein features a conserved zinc finger domain at its C-terminus, while TMOD4 contains both Tropomodulin and ribonuclease inhibitor domains. The common carp GFI1B shared over 91% identity with Sinocyclocheilus anshuiensis but only 43.92% to 65.56% identity with other teleosts, in contrast to TMOD4, which exhibited 80.88% to 96.79% similarity across teleosts. Both genes were expressed in all tested tissues of healthy carp. GFI1B exhibited the highest expression level in the head kidney, while TMOD4 showed expression levels second only to muscles and skin in the head kidney. STRING prediction revealed that GFI1B interacts with multiple hematopoietic transcription factors, and TMOD4 interacts with myotonic structural proteins and cytoskeletal regulatory factors. After 15 days A. veronii infection, GFI1B and TMOD4 transcripts were significantly upregulated in the head kidney, reaching 6.75-fold and 5.66-fold higher levels compared to controls, respectively. In carp leukocyte cell line, acute infection with A. veronii, the expression levels of GFI1B and TMOD4 genes rapidly increased at 6 hours post-infection, significantly decreased at 12 hours, and rose again at 24 hours. These results demonstrated that after acute and chronic A. veronii infections, GFI1B and TMOD4 exhibited high expression in the head kidney tissue and carp leukocyte cells, highlighting these two genes may synergistically play a crucial role in anti-A. veronii defense. Overall, this work provides a foundational basis for further investigation into the antibacterial regulatory functions of GFI1B and TMOD4 in teleosts.
The lack of effective molecular markers for germplasm identification and ambiguous genetic diversity characteristics severely restrict the research progress of Hemitrygon bennettii. This study aimed to establish fundamental data for germplasm identification and population genetic diversity evaluation of H. bennettii, and to provide molecular evidence for its phylogenetic analysis, genetic diversity conservation, and fishery resource management. The findings are expected to further promote the in-depth development of conservation genetics research on this species. High-throughput sequencing data and bioinformatics approaches were applied to screen genome-wide single nucleotide polymorphism (SNP) markers and analyze the population demographic history of H. bennettii. Genome-wide microsatellite loci were identified, and high-quality loci were screened for specific primer design. Furthermore, interspecific microsatellite variations between H. bennettii and H. akajei were comparatively analyzed. In addition, the complete mitochondrial genome of H. bennettii was assembled, and its genomic structure and variation characteristics were systematically analyzed. A total of 16150339 SNP loci were screened and annotated. Population demographic analysis based on genome-wide SNPs indicated that the H. bennettii population had experienced two expansion events and one bottleneck contraction event. In total, 521449 microsatellite loci were identified in the genome, with a distribution frequency of 163.02 loci per Mb. After strict screening, 116 high-quality microsatellite loci were obtained with specific primers successfully designed. Meanwhile, 19 microsatellite loci shared by H. bennettii and H. akajei with high interspecific heterogeneity were screened out. The total length of the assembled mitochondrial genome of H. bennettii was 17724 bp. A total of 49 variable sites were detected, and obvious intraspecific length heterogeneity was found in its mitochondrial genome. The SNP markers, microsatellite loci, and complete mitochondrial genome sequence obtained in this study can be effectively applied to subsequent population genetic analysis and germplasm identification of H. bennettii. This study provides reliable molecular baseline data for phylogenetic research, genetic diversity assessment, and scientific conservation and management of H. bennettii germplasm resources.
Submerged macrophytes such as Elodea nuttallii and Vallisneria natans are essential for ecological stability and stable production in ponds used for the culture of the Chinese mitten crab (Eriocheir sinensis). Under increasingly frequent summer heat events, the decline of aquatic plants has become a major constraint on pond aquaculture. This study aimed to clarify the effects of high-temperature stress on the growth condition of dominant aquatic plants in crab ponds and on production performance, and to construct a response model linking climatic stress, aquatic plant condition, and production outcome. Based on meteorological data, industrial information, sales records of aquatic-plant protection products from three representative aquatic drugstores, and survey data from 36 representative crab ponds in Taizhou for three consecutive years during 2023-2025, eight heat-related indicators, including mean air temperature in July-August, extreme maximum temperature, number of days with temperature≥35℃, maximum consecutive high-temperature days, number of hot nights, precipitation anomaly, sunshine duration, and mean wind speed, were selected. The analytic hierarchy process was used to construct a high-temperature hazard index (HMI). An aquatic plant condition index (WCI) was established using June aquatic plant coverage and the August aquatic plant decline score. Correlation analysis and multiple linear regression were applied to develop a chain-response model of “HMI-WCI-production outcome”. High-temperature stress in Taizhou showed a clear interannual pattern, being lowest in 2023, highest in 2024, and second highest in 2025. The most severe heat damage occurred in 2024, when prolonged heat, frequent hot nights, and reduced precipitation occurred simultaneously. Aquatic plant condition showed the opposite trend, being best in 2023, worst in 2024, and partially recovering in 2025. Changes in yield, mean body size, and proportion of high-quality crabs were generally consistent with the variation in aquatic plant condition. Monthly sales of aquatic-plant protection products and the number of consulting ponds were both significantly positively correlated with the number of days with temperature≥35℃, maximum consecutive high-temperature days, and hot nights. The August aquatic plant decline score and the maximum crab mortality during the high-temperature period were significantly negatively correlated with yield, mean body size, and the proportion of high-quality crabs, with the decline score showing a stronger effect than mortality. The yield-estimation model established using the August aquatic plant decline score and maximum mortality rate showed good performance (R2=0.580, P<0.001). The chain-response model demonstrated that increasing high-temperature hazard reduced the aquatic plant condition index, which in turn led to declines in yield and body size. Aquatic plant decline was the key intermediate link through which heat stress affected production outcome. The effects of high-temperature stress on crab pond production in Taizhou showed a clear chain-response pattern. Maximum consecutive high-temperature days were the key meteorological hazard factors, and the August aquatic plant decline score was the core biological indicator restricting aquaculture benefit. These results provide a scientific basis for heat-disaster warning, pond management optimization, and yield prediction in Eriocheir sinensis culture.
ISSN 1000-6850 (Print)
Started from 1984
Published by: China Association of Agricultural Science Societies
