Agricultural information technology is formed as the result of integrating information technology and agricultural science, and has further facilitated the rapid development of digital agriculture (DA) and smart agriculture (SA). As one of the core technologies of DA and SA, crop growth model can dynamically simulate crop growth and development processes and their relationships with climate condition, soil characteristics and management strategy, so as to overcome the limitation of the spatial-temporal characteristics of traditional research on agricultural production management. It can provide powerful quantitative tools for crop productivity prediction and early warning and impact evaluation under different conditions. Through over 20-years systematic and profound exploration and practicing in wheat and rice crops, and based on the workflow of “physiological mechanism analysis-model algorithm development-dynamic productivity prediction-quantitative effect assessment-simulation platform development”, our research team has been devoted to the development and application of crop simulation model CropGrow, by integrating the technologies of system analysis, dynamic modeling, virtual reality, scenario simulation, and decision support. Firstly, based on the system analysis method and dynamic modeling technology, the comprehensive and mechanistic crop growth model CropGrow has been developed, including the submodels of phasic development and phenology, organ development and population establishment, photosynthetic production and biomass accumulation, assimilate partitioning and yield/quality formation, nutrient dynamics, and water balance, along with three-dimensional morphological and visual submodels, which could digitalize and visualize the processes of crop growth and productivity formation under different conditions. Further, by coupling geographic information system (GIS) and remote sensing (RS), the model-based regional crop productivity prediction technology has been established. Then, based on the scenario analysis, the contributions of climate change, soil improvement, variety updating, and strategy optimization to regional crop production have been quantified, and applications extended to generation of suitable management plan, design of ideal cultivar, assessment of climate impact, evaluation of land use and decision-making of agricultural policy. Finally, based on the component-based programming technology, a model-based digital and visual crop growth simulation system and decision support platform has been developed by integrating the crop production database and crop model components, further realizing the comprehensive functions of data management, parameter optimization, growth simulation, remote sensing coupling, regional prediction, management strategy design, effect evaluation, safety early warning and product release. In the future, based on the improvement of agro-information database, additional efforts in crop modeling will be made toward enhancing prediction ability, quantifying gene effects, developing intelligent decision-making, and coupling multiple models, which will provide digital support for the prediction and early warning of food production, quantitative evaluation of scenario effects, decision-making on management strategy, and optimal design of new crop cultivars, thus facilitating the security of national food and development of digital agriculture.

【Objective】Long non-coding RNAs(lncRNAs) are a group of RNA molecules longer than 200 bp with no protein coding capacity, which are involved in various biological regulatory processes. In this study, we aim to analyze the RNA-sequencing data of two Gossypium arboreum isogenic lines, a fuzzless mutant (GA0149) and its wildtype (GA0146), to identify the lncRNA involved in early fuzz fiber development, providing a foundation for investigation the mechanism of fiber development. 【Method】We collected 0 DPA, 3 DPA and 5 DPA ovule and 8 DPA ovule and fiber from the G. arboreum fuzzless mutant GA0149 and its isogenic line GA0146 with normal fuzz and lint fibers, were used for RNA-seq to identify lncRNA and predict their target genes. Differentially expressed mRNA (DE-mRNA) and lncRNA(DE-lncRNAs) between the samples were identified. The KOBAS software was used to predict the KEGG enrichment pathways which DE-lncRNAs targets were involved in. To ensure the quality of high-through sequencing, 25 DE-lncRNAs were selected for RT-qPCR detection. 【Result】We identified 15 339 lncRNA-encoding transcripts that 11 595 lncRNAs were located to intergenic regions, 2 428 lncRNAs were classified as antisense lncRNAs, 350 were categorized as intronic lncRNAs and 966 belonged to sense lncRNAs. Compared to mRNAs, lncRNAs in Asian cotton showed shorter exons and lower GC content. Most of lncRNAs had cis-regulatory effects on their neighboring mRNAs. We identified 1 932 differentially expressed (DE) lncRNAs, with 8 134 predicted DE-lncRNA target genes. Further analysis showed that 788 genes (mRNA) were differentially expressed (DE-genes) during four fiber development stages. KEGG enrichment pathways analysis showed that DE-target-mRNAs were mainly enriched in plant hormone signal transduction and protein processing in endoplasmic reticulum. Co-expression network analysis revealed that lncRNA (MSTRG.454250.3) and its associated target genes showed identical expression trends during four fuzz fiber development stages, while lncRNAs (MSTRG.454261.4) and its associated target genes showed contrary expression tendency, exhibiting dramatic higher expression in fuzzless GA0149 compared to wildtype GA0146. The results of RT-qPCR analysis confirmed the authenticity of our RNA-seq data.【Conclusion】A total of 26 specifically expressed lncRNAs were identified which related to cotton fuzz fiber development process. We further confirmed that these lncRNAs affected the fuzz fiber development by regulating the expression of indole-3-acetic acid-amido synthetase (Ga03G2421) and Auxin-responsive protein (Ga05G1344) in the plant hormone signal transduction pathway.

Genotyping technology, via molecular markers, has been playing a key role in many biological fields including genetic improvement. Genotyping has been widely applied in multi-national seed companies due to their high-throughput, automatic, large-scale and shared genotyping platforms. Genotyping has moved from its third generation (G3), dominated by expensive DNA chips and random genotyping by sequencing (GBS), to the fourth generation (G4), characterized by low-cost, less facility-demanding and performed via genotyping by target sequencing (GBTS). In this article, we first introduced two GBTS protocols, GenoPlexs, based on multiplexing PCR, and GenoBaits, based on sequence capture in-solution (also called liquid chip). For both protocols, multiple single-nucleotide-polymorphisms (mSNP) or multiple dispersed nucleotide polymorphisms (MNP) can be generated to reveal the genetic variation hidden within each amplified locus (amplicon). Compared to DNA chips and GBS, GBTS has several advantages, including wide applicability to genotyping facilities, very flexible marker types, highly efficient genotyping, sharable and accumulative marker data, less required information management and support, and wide suitability in biological applications. With the same marker panel (for example, 40K maize mSNPs), three types of genotyping (40K mSNPs, 260K SNPs, and 754K haplotypes) can be achieved, and multiple panels with various marker densities (1K to 40K mSNPs) can be generated by sequencing at different depths. Applications of GenoPlexs and GenoBaits in biology were then reviewed, including biological evolution, germplasm evaluation, genetic map construction, gene mapping and cloning, marker-trait association (genome-wide association study and bulked sample analysis, BSA), progeny testing, gene introgression, gene pyramiding, variety right protection, variety quality monitoring, transgenic event and gene editing detection, and bioassay. More 50 marker panels have been developed so far for more than 20 plant, animal and microorganism species and applied in some of the fields described above. Lastly, we prospected for future GBTS by looking insights into carry-on, automatic, high-throughput and intelligent genotyping platforms, multi-functional marker panels with various marker densities designed to meet specific requirements, integration with other technologies such as KASP, high-density DNA chips and BSA strategies, and open-source breeding by sharing germplasm and breeding materials and information. The development in these fields will greatly facilitate the applications of GBTS in genetic improvement and other fields of animals, plants and microorganisms.

Genome-wide association study (GWAS) is an effective method to locate genomic loci that are significantly associated with traits. With the accumulated phenotypic data, the continuous development of high-throughput genotyping technology, and the improved statistical methods, it promotes the wide application of GWAS in area of human disease and animal and plant genetics. False positives are one of the important concerns that impair the reliability of genome-wide association results. To control the false positives, in addition to correcting the P-values, GWAS models have been continuously improved from the naive methods like ANOVA (for quantitative trait) or Chi-square test (for quality trait), to general linear model (GLM), which incorporates fixed-effect covariates, to the mixed linear model (MLM), which incorporates random effects. Fitting individual genetic effects into random effects defined by the genomic relationships matrix (GRM) is commonly adapted currently. Since the parameter estimation of MLM consumes a lot of computational resources, researchers have tried to optimize solving models and constructing GRM (which also improves computing efficiency), and the time complexity gradually decreased from O(MN³) to O(MN) for MLM-based methods, achieving a great leap in computational speed and statistical efficacy. For inflations caused by unbalanced case-control data, researchers further correct the generalized mixed linear model (GLMM). This paper comprehensively introduces the basic principles and development of GWAS, with specific emphasis on the model improvement and optimization details. We also list the applications of MLM in GWAS in agriculture, including progress on animals, plants and microbes, as well as the application of haplotype in GWAS. Finally, we give prospects on the future developments of GWAS from the viewpoints of further model optimization and experimental design.

【Objective】 The objectives of the present study were to synthesize the current information on soil quality assessment method and indicator system, and to present the hot topics and frontiers related to soil quality, so as to, provide references for Chinese scholars and experts in the field of soil quality evaluation research and application. 【Method】 The published articles regarding the selection of soil quality indicators, construction of minimum data set, and selection of soil quality evaluation methods were collected based on Web of Science and CNKI databases using bibliometrics method, and a total of 415 articles and 155 minimum data sets related to soil quality evaluation were screened. Development trend, frontier fields and current problems of global soil quality assessment during the past 30 years were analyzed according to selection frequency of indicators, assessment method and construction of minimum data set. 【Result】 The soil quality evaluation indicator system mainly included 25 physical, 36 chemical, 35 biological and 19 environmental indicators. Soil organic matter, as the core indicator of soil quality, was selected with the highest frequency of 96.6%, followed by pH, total nitrogen, available phosphorus, available potassium, and bulk density, with a frequency more than 50%. The selection frequency of biological indicators such as microbial biomass and soil enzyme activity was less than 25%, while increasing over time. Principal component analysis, minimizing indicator redundancy and reflecting most of the information of original variables, was the most widely used for minimum data set construction method. Soil organic matter, available phosphorus, bulk density, and pH were selected into the minimum data set with a frequency of 67.7%, 43.2%, 34.8%, and 34.2%, respectively, being widely used to characterize soil quality. Nowadays, the most studies on soil quality evaluation focus on the utilization of principal component analysis to select soil quality indicators and establish soil quality index for comprehensive soil quality evaluation, which was suitable for sustainable soil management.【Conclusion】 Soil organic matter, available phosphorus, soil pH, bulk density and soil water content were the main parameters selected for soil quality evaluation. Construction a comprehensive and objective soil quality indicator system and the integration with the information technology would be the focus in future research. The application of evaluation indicators in large-scale soil quality assessment was the trend of future development.

Abiotic stress is one of the main factors causing global grain yield reduction. It is of great significance to study the function and response mechanisms of plant stress-related proteins to improve crop stress resistance. Pentatricopeptide repeat (PPR) proteins, belong to the largest family of nuclear coding proteins in higher plants and are named because they contain highly specific PPR motifs. Depending on motif type and arrangement, PPR proteins can be classified as P and PLS, and PLS proteins can be further classified as PLS, E, E+, DYW, and other subclasses based on their carboxyl-terminal domains. PPR proteins are widely distributed in terrestrial plants, mainly in chloroplasts and mitochondria, and a few in the nucleus. As sequence-specific RNA binding proteins, PPR proteins are involved in multiple aspects of plant RNA processing, including RNA editing, splicing, stabilization, and translation. PPR protein plays a variety of important roles in the whole life process of plants, but the mechanism of its action in plant stress resistance is not well understood. Based on the localization and function of PPR proteins related to abiotic stress reported, the mechanism of PPR proteins involved in regulation of abiotic stress, including post-transcriptional regulation and retrograde signaling, was reviewed and discussed in this paper. Post-transcriptional regulation is related to the role of PPR proteins in the modification of RNA after transcription. It is generally believed that PPR affects stress resistance in plants by regulating the expression of stress-related genes via binding RNA and by regulating the metabolism of organelle RNA. In terms of retrograde signaling, damage to PPR proteins can lead to impaired mitochondrial or chloroplast function, and then produce various retrograde signals (such as ROS), thereby regulating the expression of related genes and resisting adversity. However, since plastid signaling is affected by many environmental factors, some of which are still unclear, the mechanism of the PPR protein in retrograde signaling remains to be clarified. In addition, PPR proteins are pleiotropic and some have important effects on plant growth and reproduction while acting on stress resistance. Finally, this paper further analyzed the current research status of PPR protein as an RNA editing tool, discussed the remaining problems and research prospects of PPR protein in the direction of abiotic stress, and pointed out the key points and difficulties that need to be paid attention to in future research, to provide references for further research on PPR protein and crop abiotic stress resistance breeding.

【Objective】To explore the structure and evolution characteristics of cotton NLP transcription factors in the whole genome, and further understand their expressions patterns, so as to lay a foundation for the further function research and utilization of NLP genes. 【Method】The NLP transcription factor family members in the whole genomes of four cotton species, Gossypium arboreum (G. arboreum, Ga), Gossypium raimondii (G. raimondii, Gr), Gossypium barbadense (G. barbadense, Gb) and Gossypium hirsutum (G. hirsutum, GH), were identified using two strategies, BLASTP and HMM search. Further bioinformatics analysis was carried out on the confirmed cotton NLP family members. The molecular weights, theoretical isoelectric points and other physical and chemical properties were predicted using online software Expasy; the MEGA 7 software was used to build the phylogenetic tree; protein conservative motifs were analyzed through MEME website; online software GSDS 2.0 was used to analyze gene structures; TBtools was used to view the chromosome localizations; McscanX was used to analyze the replication genes of cotton NLP family members; the PlantCARE website was used to predict the cis-acting elements in the promoters of cotton NLP family genes. The heat maps of cotton NLP genes expression levels of different tissues and under abiotic stresses were drawn through TBtools to analyze the tissue expression characteristics and abiotic stresses response characteristics. The expressions of GHNLPs in cotton under nitrogen starvation and nitrogen resupply treatments were analyzed by RT-qPCR. 【Result】A total of 11, 11, 21 and 22 NLP members were screened from the four cotton protein databases of G. arboreum, G. raimondii, G. barbadense and G. hirsutum, respectively. These NLP family genes encoded 693-996 amino acids. The relative molecular masses ranged from 76.92-110.02 kDa and the theoretical isoelectric points were 5.13-7.77. The subcellular localization prediction results showed that almost all the NLP members located in the nucleus. Promoter analysis found a large number of cis-acting elements related to phytohormone and stress response. Phylogenetic analysis showed cotton NLPs were divided into three groups, I, II and III. Gene replication analysis showed that fragment replication was the main force for NLP members expansion in cotton. All the Ka/Ks values were less than 1, indicating that evolution of NLP family in cotton mainly underwent purification selection. The results of expression analysis also confirmed that GHNLPs responded to nitrogen starvation and nitrogen resupply. 【Conclusion】From the whole genome of G. arboreum, G. raimondii, G. barbadense, and G. hirsutum, 11, 11, 21 and 22 NLP transcription factor members were identified respectively. They had high conservatism and some degree of differences. The expression levels of GHNLPs changed significantly during nitrogen starvation and nitrogen resupply processes, which may play a role in the response of cotton to nitrate.

【Objective】Stripe rust, caused by Puccinia striiformis f. sp. tritici (Pst), significantly reduced wheat production worldwide. Breeding resistant wheat varieties is currently considered to be one of the most economical and effective ways to control this disease. Understanding the resistance level of Chinese and International Maize and Wheat Improvement Center (CIMMYT) wheat breeding materials and the distribution of known disease resistance genes will greatly helpful for discovering the new resistance resources and improving the utilization efficiency of disease resistance genes.【Method】In the present study, we phenotyped 153 wheat breeding lines derived from China and CIMMYT at both seedling against prevalent Chinese Pst races CYR33 and CYR34. In 2018-2019, 2019-2020 and 2020-2021, using the pst races CYR33 and CYR34 to identify the materials at the adult plant stages in Ezhou, Hubei. In addition, we used the gene-based or closely linked molecular markers of known stripe rust resistance genes Yr5, Yr9, Yr10, Yr15, Yr17, Yr18, Yr26, Yr29 and YrSP to genotype the whole set of wheat collections.【Result】We found 10 lines immune against CYR33 at the seedling stage (IT: 0), including seven Chinese cultivars (Shannong 28, Luomai 163, Shimai 13, Zhongyi 6, Tanmai 98-2, Zhongmai 175, Taishan 21) and three CIMMYT lines (CIM-53, CIM-60 and CIM-71). However, only two cultivars, Tanmai 98-1 and Shannong 102, showed immune to CYR34 at the seedling stage. Based on the three years field tests, we found 64 lines showed highly resistance to stripe rust (final disease severity, FDS≤5%), including seven Chinese cultivars and 57 CIMMYT lines. The molecular marker analysis of known stripe rust resistance genes showed that there were 31, 23, 73, 2, 4, 50 and 2 lines carrying resistance genes Yr9, Yr10, Yr17, Yr18, Yr26, Yr29 and YrSP, respectively. None of any lines had Yr5 and Yr15. Based on the phenotype, only CIM-53 showed immune against two races at both seedling and adult plant stages (IT=0, FDS=0) and it might carry the known stripe rust resistance gene combination of Yr17+Yr29 based on the genotype.【Conclusion】A total of 153 wheat collections from China and CIMMYT were showed adult plant resistance to the prevalent pst races. Among these, Chinese wheat varieties mainly carry Yr9, Yr10 and Yr26, while CIMMYT wheat line mainly carry Yr17,Yr18 and Yr29, indicating that near-immunity resistance of CIMMYT wheat lines due to combinations of 1-2 moderate seedling resistance gene and 2-3 adult plant resistance genes resulting in durable resistance. Therefore, it is very urgent to expand the resistance sources and identify new resistance genes for pyramiding more genes biotechnology methods to develop new wheat varieties with durable rusts resistance and good agronomic traits. This plays an important role for controlling stripe rust in China by improving the resistance level of wheat variety overall.

Global agriculture is facing severe challenges, and breeding technology is the foundation and key to the development of the seed industry. Gene editing technology refers to the precise modification of target genes to achieve deletion, insertion, and replacement of specific target gene fragments. It can precisely modify target genes or introduce certain excellent genes into crops to produce crops with excellent agronomic traits, which has great potential in molecular design breeding and is of great significance to ensuring food security. Weed damage has a huge impact on the yield and quality of crops. To control weed damage efficiently, safely and sustainably has always been a hot research topic. Currently, more than 200 types of chemical herbicides have emerged in the global market. Using chemical methods to control weeds has become an important part of modern agriculture, and the cost of weed control has been significantly reduced by promoting herbicide-resistant crops. However, with the large-scale promotion of herbicide-resistant crops and the long-term use of single herbicides, environmental safety problems such as weed resistance and escape of resistant genes have gradually been discovered. Currently, the development of functional genomics, bioinformatics and genetic engineering technology (especially the widespread application of gene editing technology in plants) has created conditions for the creation of herbicide-resistant crops and new efficient weed control systems. In this article, the main target genes of herbicides that inhibit amino acid biosynthesis, lipid metabolism, carotenoid, plastoquinone and tocopherol biosynthesis pathways and their action mechanisms are introduced at first. Secondly, two methods for mining new herbicide resistance genes and herbicide systems are introduced, including the directed mutation method of herbicide resistance genes within crops based on CRISPR/Cas system and the resistance gene guidance method based on the co-evolution theory of natural product and organisms in nature. Moreover, the research progress of three breeding methods for herbicide resistant crops was reviewed, including conventional breeding, transgenic breeding and CRISPR/Cas genome editing based breeding. Among them, the research progress of CIRSPR/Cas system, base editing technology, and prime editing system in cultivating herbicide resistant crops were highlighted. The main challenge faced by chemical control of weeds and herbicide resistant crops is resistant weeds and environmental safety issues, and gene escape, respectively. At present, the rapid development of genome editing technology provides new solutions and new opportunities for the development of herbicide resistant crops in the post genome era. Finally, the prospects for the future of herbicide-resistant crops were provided.

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

【Objective】Canopy activity is an important indicator of wheat growth and development. Identification the loci for canopy activity related traits and their relationships with grain yield (GY) related traits can provide theoretical support for the dissection of genetic structure of yield trait and assisted wheat breeding.【Method】A total of 166 wheat varieties originating from both domestic and international sources were planted in Anyang of Henan province and Suixi of Anhui province in cropping seasons. With the integrated physical map containing 326 570 SNP markers from the wheat 90K and 660K chips, genome-wide association studies for normalized difference vegetation index at seedling stage (NDVI-S) and 10 days after flowering (NDVI-10), and chlorophyll content in flag leaf at 10 days after flowering (Chl-10) were carried out. The results were compared with the previous study for GY related traits using the same material. 【Result】Analysis of variance (ANOVA) showed highly significant effects (P<0.01) of genotypes, environments and genotype×environment interactions on NDVI-S, NDVI-10 and Chl-10, with broad-sense heritabilities (h2 b) of 0.81, 0.81 and 0.91, respectively. Thirteen, 12 and 15 loci were detected to be significantly correlated with NDVI-S, NDVI-10 and Chl-10, respectively, among which 12, 11 and 12 were new, and five loci were associated with two or more traits. The number of favorable alleles for NDVI-S, NDVI-10 and Chl-10 ranged from 4 to 11, 3 to 11 and 4 to 12, respectively, in the 166 wheat varieties, and the phenotypic values increased with the accumulation of favorable alleles. NDVI-S showed significant (P<0.01) and positive correlations with thousand-kernel weight, kernel length and kernel width. Chl-10 was significant positively correlated with GY and flag leaf width (P<0.01), whereas significant negatively correlated with spike number per unit area, plant height and uppermost internode length (P<0.01). Seven pleiotropic loci were detected co-related with both GY and canopy activity related traits.【Conclusion】NDVI-S can be directly used for selection of yield traits. The stable and pleiotropic loci detected in this study can be used for marker-assisted selection.

TGA family is an important group of bZIP transcription factors in plant, which regulates the downstream target genes by binding to the as-1 cis-elements in the promoter region and subsequently activating or inhibiting their expression, ?nally regulating the resistance or development of floral organ. The first TGA gene was identified in tobacco. Subsequently, TGA members were widely characterized in arabidopsis, rice and apple. In arabidopsis, they constitute a multigene family comprising 10 members based on genome sequence analyses. The members of TGA family can be divided into five subgroups (Ⅰ: TGA1 and TGA4; Ⅱ: TGA2, TGA5 and TGA6; Ⅲ: TGA3 and TGA7; Ⅳ: TGA9 and TGA10; Ⅴ: PAN) according to their sequence similarity. The members of Ⅰ, Ⅱ and Ⅲ subgroups are mainly involved in disease resistance. Yeast two-hybrid and pull-down results showed that all members of subgroupⅠ, Ⅱ, and Ⅲ could interact with NPR1 protein which is the key positive regulator in SA signaling pathway. EMSA results indicated that the interaction between TGA and NPR1 could enhance the expression of pathogenesis-related (PR) genes and disease resistance. However, their roles were different in basal and systemic acquired resistance (SAR): tga3 mutants showed a defect in basal resistance, whereas the induced resistance was unaffected. TGA1 and TGA4 were involved in regulation of basal resistance and SAR. The tga2/5/6 triple mutants but not tga6 or tga2/5 double mutants were defective in SAR, a phenotype similar to that of the npr1 mutants, indicating functional redundancy among TGA2, TGA5 and TGA6. Yeast two-hybrid screen revealed that TGA transcription factors of subgroup Ⅱ could interact with glutaredoxin GRX480 to mediate the repression of the marker genes of JA signaling by SA, and they also could interact with GRAS protein SCL14 to increase the expression of CYP81D11 and GSTU7 in an NPR1-independent manner and enhance the tolerance to xenobiotics. In addition, the primary and lateral root growth was affected in tga1/4 and nrt2.1/2.2 mutants. ChIP and yeast one-hybrid assay results showed that TGA1 and TGA4 regulated the nitrate response via binding to the promoters of NRT2.1 and NRT2.2 to regulate their expression. TGA3 was also involved in the long-distance transport of cadmium. The members of subgroup Ⅳ and Ⅴ played an importance role in the regulation of floral organ development. tga9/10 mutants have defects in male gametogenesis that were similar to those in roxy1/2 mutants. PAN could interact with NPR1-like proteins BOP1 and BOP2. Both pan and bop1/2 double mutants revealed a pentamerous arrangement of sepals, which suggested that a similar signaling mechanism might be used between floral organ development and disease resistance. Finally, the research directions of TGA transcription factors was discussed, which will provide a reference for researchers in this field.

Up to end of last century, studies on SOC were mainly concentrated in identifying chemical structures of different organic materials in soil, such as structural characteristics of humic or fulvic acids and their related functions for soil quality. In recent years, focus on SOC has been laid on SOC transformation characteristics in soil, trying to establish the relationship between SOC functions and the grouping according to SOC transformation characteristics. According to the transformation properties, SOC can be divided into two groups, including the stable SOC and the active SOC. The first one refers mainly to the SOC closely combined with clay or fine silt and it is difficult to be decomposed and mineralized by soil microorganisms. Stable SOC belongs to passive and inert SOC pool in soil. The second one refers to SOC, which mainly consists of crop residues and roots after harvesting, crop straws returned to farmland and organic manures applied. The active SOC belongs to nutritive and labile SOC pool in soil. This part of SOC is of great importance to soil fertility. SOC concentration is actually the expression of dynamic equilibrium of two processes. One is the input of organic materials to soil and the other one is the decomposition and mineralization of SOC. When the amount of organic material input is less than the mineralized amount, the SOC concentration and soil fertility will decrease. When the annual input of organic carbon is greater than the annual mineralization amount, the SOC concentration will keep rising until the annual input is equal to the annual mineralized amount. At this moment, SOC concentration will no longer increase and reaches the equilibrium point. Under normal agricultural production conditions, the duration for reaching equilibrium point needs 20 to 30 years. If the active SOC input is in very high level, the dynamic equilibrium system will also lead to a high amount of SOC mineralization annually. In such case, it might lead to a loss of mineral nutrients from soil into water and atmospheric environments, especially mineral nitrogen loss. For the purposes of soil fertility improvement and environmental protection, the active SOC input for farmland should be controlled to the level equal to the annual SOC mineralization amount, sustaining the so-called balance with positive zero. New research shows that the active SOC, after entering soil, is decomposed into a series of short-chain chemical compounds by soil organisms. These short-chain chemical compounds combine with soil mineral particles and form soil organic-mineral aggregates through bioturbation. A lot of soil fertility properties are positively affected by formation of these aggregates. Influenced by humification, decomposition and other processes of SOC, aggregation and disaggregation in soil occur simultaneously and consistently. In order to maintain stability of the total aggregates in soil and to increase soil fertility, sustained and abundant active SOC should be inputted to soil. Variation of SOC concentration depends mainly on climate, soil texture and land use forms. Among the artificial influences, land use form changing has the greatest impact on SOC concentration. In comparison, farming managements, such as fertilization, straw returning, tillage and crop rotation, have much less impacts on SOC concentration. In arable land, crops with different growth periods, tillage and harvesting managements will produce different amounts of above ground residues and root residues after harvesting. Depending on residue quantity and quality, different crops are of different capacity for SOC reproduction. According to the differentiated SOC reproduction capacities, field crops can be divided into two types: SOC increasing crops and SOC consuming crops. For farmland with SOC consuming crops, it is very important to introduce SOC increasing crops in rotation or to apply organic manure or organic materials to field, in order to sustain soil fertility.

Roots are the vital organs for fixing the plant shoots and absorbing soil water and nutrients. The phenotypic characteristics of roots directly affect crop productivity and adaptability. Optimizing root phenotypes is considered to be one of the important ways to achieve the second “Green Revolution”. However, the invisibility, complexity and plasticity of root system greatly restrict the efficiency of root phenotyping, which makes the root optimization process lag far behind that of aboveground organs. With the rapid development of new technologies, i.e. spectral imaging, machine learning and three-dimensional reconstruction, the approaches to phenotyping roots gradually changed from traditional sampling observation to in-situ, nondestructive and automatic detection, and the evaluation basis expanded from two-dimensional morphological indices to three-dimensional parameters, which promoted the efficiency of root phenotyping and dramatically enriched the data of root phenotype. Meanwhile, the massive data exhibited problems, such as data redundancy and low use efficiency of information resources, which put forward new requirements, i.e. standardization and shareability, for root phenotype studies. This paper summarized the principles and technical keys of main approaches to phenotyping roots, and compared systematically in terms of precision, cost and throughput. The commonly used software for quantification of root phenotype were listed out from the aspects of license, operating platform, analysis mode and so on. The important research direction in the future was put forward, that is, to develop effective approaches to phenotyping roots in the field, to establish the evaluation system for root plasticity, to strengthen the identification and utilization of root anatomical characters, to strengthen the application of molecular detection techniques in root phenotyping, and to promote standardization of root phenotyping techniques and data sharing. The aim is to provide reference for the reasonable selection and improvement of approaches to phenotyping crop root system, so as to promote crop root improvement.

Seed acquired vigor during desiccation stage in seed development, different from the previous opinions, new evidence insisted that seed desiccation is not only involved in water loss process, but also as a significant proportion of the gene expression and metabolic signatures of which resemble those characterized seed germination, implied that the preparation of the seeds for germination began already during seed desiccation. The germination of seeds initiated from water-uptake, accompanied by metabolic recovery, then radicle breaked through endosperm and seed coat and other peripheral completed germination. The main contributor of seed germination success is the quality of the messenger RNAs stored during embryo maturation in the mother plant. In addition, proteostasis and DNA integrity play a major role in the germination phenotype. Plant hormone, as a signal, concentration extremely fewer even approximate to zero, was also important for seed dormancy release and germination. Recently, more and more ideas have considened that the ABA/GA ratio regulats the metabolic transition required for germination. GAs, although required for the completion of germination, are not directly involved in many processes taking place during germination like ABA, which occurred at a stage coinciding with or very close to radicle emergence. It appears that reciprocal downregulation of the respective metabolic pathways accounts for a significant part of GA and ABA interplay, and the α-amylase gene, is transcriptionally regulated by both ABA and GA. In addition to the ABA and GA, recently research found IAA finely regulated radicle emerge that more strictly than cotyledons open during seed germination. Auxin action in seed dormancy and germination requires the auxin response factors 10 and 16 to indirectly control the expression of ABI3. Compared with germination in light condition, seedlings germinated in soil will form a specific organization ‘Apical hook’, its main role was to protect the ‘SAM’. Auxin, accumulating at the concave side, was critical for the formation and maintenance of the hook structure, whereas a release of the auxin maximum correlates with hook opening. To improve the vigor, seed were primed before sowing, the key of which was to control seeds very close to radicle emergence but redried before it in time. In fact, seed stored mRNAs and proteins began to perform its function during priming, and also the molecular biological mechanism was "memorized" at the later redried state, so re-imbibed seeds could quickly germinate. Except as toxic molecules, ROS is also involved in the mobilization of storage and endosperm loose as signaling molecules during seed germination, and it is always interacted with hormone molecule ABA and GA, that also controls seed germination via translation and posttranslational modifications. Methionine metabolism is the metabolism core in seed germination and its metabolites widely regulate the physiological and biochemical reaction of seed germination, such as DNA synthesis, protein stability, chromosome structure formation and remodeling, biotin synthesis, and is also interacted with hormone molecule ABA, GA, ETH, and active oxygen or nitrogen. Recently new evidence insisits on the methionine sulfoxide reductase took part in repair system in plant seed longevity, which also might play a role in seed vigor. This article focused on the domestic and foreign research status on seed vigor, and also provided an outlook of the future research hotspots, such as the senses traits in seeds "preharvest", the molecular mechanism about higher vigor seeds but less field emergence, the important role of auxin in radicle breakout, methionine metabolism, and the methods about seed vigor testing, etc.

【Objective】Aimed at analyzing agronomic traits and yield changes of national Tartary buckwheat varieties in regional trials over 12 consecutive years, and discussing improvements and existing problems with Tartary buckwheat varieties in China, so as to provide basis for future genetic improvements in Tartary buckwheat in China.【Method】Depending on influences of environmental factors such as climate and geography on characteristics of Tartary buckwheat and in terms of southern and northern trial groups classified according to the geographical division standards of North and South China, the cluster analysis, correlation analysis and multiple regression were employed to analyze variations of Tartary buckwheat varieties in growing duration, plant height, branch and node numbers of main stem, grain weight per plant, 1000-grains weight and yield in the National Tests of Tartary Buckwheat Varieties of China in 12 years from 2003 to 2014 and that examined correlations between different traits of Tartary buckwheat in the northern and southern trial groups, and traits differences of Tartary buckwheat varieties developed by the different breeding units between the two trial groups.【Result】Over the 12 years in question, the yields of the Tartary buckwheat varieties in the northern and southern trial groups increased by 21% and 32%, with an average annual rate of increase of 1.8% and 2.6%, respectively. There were totally 42 buckwheat varieties developed by 19 breeding units of 9 provinces, Shaanxi, Gansu, Yunnan, Guizhou, Jiangxi, Shanxi, Sichuan, Hunan and Chongqing. Of these breeding units, there were 5 units in Yunnan, 4 units in Guizhou, 3 units in Shaanxi, 2 units in Gansu, Shanxi and in Sichuan, and 1 unit in Jiangxi, Hunan and Chongqing City. The tested varieties developed by twelve breeding units from Yunnan, Guizhou and Shaanxi, three major Tartary buckwheat producers of China, made up 59.5% of all the tested varieties. The cluster analysis of Tartary buckwheat varieties from the different provinces (regions) showed that when the relative genetic distance was 5, the northern and southern trial groups can be divided into 4 and 3 classes, respectively. Of the northern group, the varieties from Shaanxi, Hunan and Shanxi were grouped into one class, the varieties from Gansu, Guizhou, Jiangxi and Yunnan were grouped into one class, and the varieties from Chongqing and Sichuan were grouped into one class; and of the southern trial group, the varieties from Guizhou, Jiangxi, Yunnan and Chongqing were grouped into one class, the varieties from Shaanxi, Gansu and Shanxi were grouped into one class, and the varieties from Sichuan and Hunan were grouped into one class. Correlation analysis showed that there was significantly positive correlations between the plant weights and yields of the northern and southern trial groups; significantly positive correlations between the grain weight per plant and yields of the northern trial group and significantly positive correlations of the grain weights per plant and plant heights with the branch numbers of main stems of the southern trial group; and there were different correlations in the other traits between the north and south trial groups. Multiple regression analysis showed that the growing durations, branch numbers of main stems, grain weights per plant and 1000-grains weights of the Tartary buckwheat varieties of the northern group jointly contributed 53.0% to their yield variation, and the growing durations, branch and node numbers of main stems, grain weights per plant and 1000-grains weights of the Tartary buckwheat varieties in the southern group jointly contributed 61.4% to their yield variation.【Conclusion】The national Tartary buckwheat variety regional tests in 12 years from 2003 to 2014 showed that certain improvements were made in the yield and related traits of Tartary buckwheat varieties in the northern and southern trial groups, with their yields increased to a certain extent and their growing durations shortened, but with their other traits not much changed. Of all the breeding units in question, the varieties developed by the breeding units in Yunnan, Guizhou and Jiangxi had wider environmental adaptabilities than the varieties developed by the other units in the other provinces. It was still the main goal in current Tartary buckwheat variety improvement to develop Tartary buckwheat varieties with high and stably yields, stress resistances and other excellent agronomic traits. Correlation analysis showed that it was an important approach in Tartary buckwheat variety breeding to improve Tartary buckwheat in grain weight per plant and branch numbers of main stems, etc. It was the key problem to develop Tartary buckwheat varieties with high flavonoids, easy hulling, good shattering and lodging resistances and uniform maturities and good suitability for mechanized cultivation for Tartary buckwheat production. Identifying new Tartary buckwheat germplasm resources and excellent genes, strengthening researches and developments and applications of new technologies such as molecular design breeding, and improving Tartary buckwheat variety improvement technologies and levels were the important directions in Tartary buckwheat variety improvement.

【Objective】The objective of this study is to understand the occurrence status of maize gray leaf spot (GLS) in China, and to predict its spreading areas in near future. It is an important basis for protecting maize production.【Method】The strains isolated from samples of GLS in new areas where were not reported for GLS were identified by using morphologic, cultural characteristics and molecular identification techniques. The occurrence site data of GLS during 2004-2014 were summarized for detailed clearing the status of GLS distribution in China, and monsoon character was analyzed for speculating the spreading lines of GLS before 2014 and in the future.【Result】The strains from Guizhou and Sichuan were identified as Cercospora zeina, and the species C. zeae-maydis was identified in Hebei. Two species were found in strains from Shaanxi and Henan. GLS has been found in fifteen provinces in China and was severe in southwest areas. By the influence of southwest and subtropical monsoons, the GLS, caused by C. zeina, spread into southwest of Yunnan in 2001, and into west of Sichuan by wind and into Hubei maybe by seeds in 2007. In 2013 the disease outbreak in the west of Henan and in 2014 occurred in west of Shaanxi that means C. zeina GLS was colonized in north maize production area. In the future, with the influence of monsoon, C. zeina GLS will spread into southeast of Gansu, south of Ningxia and north of Shaanxi, and will be moved slowly toward the north and east areas which are important production areas of spring maize in China. If the disease reaches the north of China that is the place of C. zeae-maydia GLS occurred at present, C. zeina GLS will be a new destructive disease in the main maize production areas.【Conclusion】It was confirmed that C. zeina was colonized in Guizhou, Sichuan, Shaanxi and Henan as well as C. zeae-maydis in Hebei, Shaanxi and Henan. C. zeina crossed the Bashan and Qinling Mountains into the north spring maize areas and caused severe GLS disease in west of Shaanxi and west of Henan. The main reasons of C. zeina GLS fast spreading were the monsoon action and the seed-borne causal fungus. In the future, C. zeina GLS will be slowly moved to the areas including where the GLS has not occurred yet and C. zeae-maydis GLS spread areas, thus will be a new threat to maize production in China.

【Objective】Genetic transformation plays a significant role in exploring gene function and improving traits in citrus. Tissue-specific promoters is a key to regulate the expression of transgenes in particular tissues. Here, expression characteristics of the PtMLP1 promoter, isolated from the root subtractive library of Poncirus trifoliata, was thoroughly examined, which could lay a foundation for the specific expression of exogenous genes in citrus root tissue. 【Method】The complete sequence of PtMLP1 gene was cloned by PCR using DNA as a template. The physiochemical attributes, secondary and tertiary structures of PtMLP1 protein were predicted by ExPASy, PSIPRED, and SWISS-MODEL tools. Cis-acting elements in PtMLP1 promoter were predicted by PlantCARE. The expression pattern of PtMLP1 in P. trifoliata trees of diverse ages was examined by employing real-time qPCR. Furthermore, to investigate the tissue-specific expression of the PtMLP1 promoter in citrus, a pBI121-ProPtMLP1::GUS plasmid, in which GUS expression was controlled by the PtMLP1 promoter, was constructed and then introduced into P. trifoliata through Agrobacterium-mediated hypocotyl transformation. 【Result】PtMLP1 consisted of two exons and one intron, which possessed a 471 bp open reading frame encoding a protein with 156 amino acid residues. This protein had a molecular weight of 17.63 kilodaltons with an isoelectric point of 5.49 and contained a Bet v I functional domain in its primary structure. Moreover, the secondary structure of PtMLP1 contained three α-helices and seven β-folds, while its tertiary structure had a conserved hydrophobic binding site and a cyclic domain, which was rich in glycine. The PtMLP1 promoter was 1 666 bp long. Multiple root-specific expression elements, phytohormone response elements (such as the TGACG motif, P-box, and ABRE), and the TATA box and CAAT box core elements were predicted in the promoter. Additionally, the 3-terminal untranslated region of PtMLP1 was predicted to contain a poly (A) signal AATAAA. Notably, the expression of PtMLP1 was significantly higher in the roots of 1-month, 6-month, and 20-year-old P. trifoliata, with fold changes of 46.34, 74.82, and 110.25, respectively, compared with those in leaves. GUS expression analysis of pBI121-ProPtMLP1::GUS transgenic plants showed that PtMLP1 promoter exhibited specific and high expression in roots, and its expression levels were 7.76 to 124.78 times of that in the leaves. 【Conclusion】The sequences of the PtMLP1 gene and its promoter were successfully obtained, and the promoter demonstrated the ability to drive specific expression of GUS gene in citrus roots.

Sorghum is the fifth largest grain crop in the world and can be used for food, feed, brewing and bioenergy. Sorghum genetic transformation technology is an essential and important tool in the research of sorghum functional genomics and can also serve as an important complement to traditional breeding methods. In this review, we summarize the research progress of sorghum transformation in recent years, analyze the problems in sorghum genetic transformation and propose strategic solutions to them in order to provide a reference for further improvement of sorghum genetic transformation technology. By summarizing more than 50 literatures on sorghum tissue culture and genetic transformation in recent years, we introduced the current research status of sorghum genotypes, explant sources, and regeneration system construction for genetic transformation, and compared the advantages and disadvantages of four commonly used methods for sorghum genetic transformation: electroporation, pollen-mediated transformation, particle bombardment and Agrobacterium-mediated transformation, summarized the effects of the main components of genetic transformation vectors, including promoters, target genes, selective marker genes and reporter genes, on transformation efficiency, explained the current application status of sorghum genetic transformation, analyzed the main bottleneck problemns in sorghum genetic transformation technology, and studied countermeasures. Sorghum genotypes have a significant influence on tissue culture and P898012 and Tx430 are the most widely used. Gene bombardment and Agrobacterium-mediated transformation are the most commonly used methods for sorghum genetic transformation, and the advantages of Agrobacterium-mediated transformation are gradually emerging. In vector construction, CaMV35S and ubi1 are the most commonly used promoters, and antibiotic resistance genes (nptII, hpt), herbicide resistance genes (bar), and nutrient assimilation genes are the three commonly used selection markers. With the development of sorghum genetic transformation technology and CRISPR/Cas9-mediated gene editing technology, some genes with important agronomic traits have been successfully transferred into sorghum. However, strong genotype dependence, long tissue culture cycle, and poor genetic transformation stability are the main bottlenecks that limit the genetic transformation of sorghum. By introducing morphogenesis regulatory factors, somatic cell generation can be directly performed, which shortens the tissue culture cycle, improves the transformation efficiency, and expands the source of explants. This has become a major breakthrough in sorghum genetic transformation technology. The use of morphogenesis regulatory factors and adoption of cut-dip-budding (CDB) delivery system can further improve the sorghum genetic transformation technology. Combined with the application of CRISPR/Cas9 gene editing technology, they will surely provide an important technical basis for the sorghum molecular breeding and gene function identification.

【Objective】This study was designed to identify the NAC gene family in Rosa chinensis Old Blush and to analyze the sequences characteristics and expression pattern of RcNACs to reveal the biological functions of RcNACs, which also provided an important foundation to explore the role of RcNACs in prickles. 【Method】The BLATP and HMMER search were conducted to identify NAC proteins in Rosa chinensis Old Blush using the sequences of NAC proteins of Arabidopsis. Physical and chemical properties, subcellular location, structure and phylogenetic relationship of each gene were further analyzed. Based on the released transcriptome data, the expression characteristics of RcNACs in different tissues and organs under different stress conditions were analyzed. What’s more, the technology of RNA-seq was used to screen RcNAC genes that might be related to the prickle development. 【Result】In this study, 116 NAC genes from Rosa chinensis Old Blush genome were identified and characterized. These RcNACs genes encoded proteins containing 69 to 713 amino acids, with the theoretical isoelectric points ranging from 4.43 to 9.54 and the molecular weight ranging from 7.87 to 79.99 kD. The prediction of subcellular localization showed that 81 RcNACs were located in the nucleus. Moreover, RcNACs were unevenly distributed on 7 chromosomes. According to phylogenetic relationships, AtNACs, OsNACs and RcNACs were clustered into 21 groups. These 116 RcNACs were differentially expressed in various tissues and organs, and the expression levels of 31 members changed in response to abiotic and biotic stresses. Furthermore, in the RNA-seq data of prickles, 53 RcNACs were detected, among which 26 members were differentially expressed genes. 【Conclusion】This study demonstrated that RcNACs were involved in the regulation of plant development and stress responses. Some members might be involved in the processes of prickle cell proliferation, secondary cell wall biosynthesis, and programmed cell death, which could be selected as candidate genes related with prickle development for further study.

【Objective】Citrus yellow vein clearing virus (CYVCV) is one of the viruses mostly threatening the stable development of citrus industry in China, but its infection and pathogenic mechanism in citrus is still unclear. In this study, the coat protein (CP) of CYVCV was used as a bait to screen the Eureka lemon (Citrus limon Burm. f.) cDNA library, and the function of obtained host factors in the interaction between host and virus was analyzed by bioinformatics method.【Method】The total RNA of Eureka lemon leaves was extracted by the Trizol method, and then reversely transcribed to the First-Stand cDNA with SMART method, which was used as a template for obtaining ds cDNA through Long-Distance PCR. After homogenization, the ds cDNA fragments were ligated to pGADT7 plasmid vector by recombination junctions to construct the primary cDNA library of Eureka lemon. The recombinant plasmids were transfected into Escherichia coli DH10B to obtain the E. coli cDNA library of Eureka lemon, and its quality was identified. Simultaneously, the CP sequence of CYVCV was amplified by PCR and ligated into the yeast two-hybrid (Y2H) bait vector pGBKT7, and the plasmids of pGBKT7-CP and pGADT7 were co-transfected into yeast Y2H Gold. The positive yeast clones were grown on the plate of SD/-Trp, SD/-Leu-Trp, SD/-Leu-Trp/X-α-Gal and SD/-Leu-Trp-His medium, respectively, and then the growth situation of the yeast was tested to identify the toxicity of pGBKT7-CP on yeast Y2H Gold and the self-activating effect of pGBKT7-CP on the reporter gene of yeast was analyzed. Then the Y2H Gold containing bait vector pGBKT7-CP was transformed with the primary cDNA library of Eureka lemon, the co-transformed yeasts were coated on the plate of SD/-Leu-Trp, SD/-Leu-Trp-His/X-α-Gal and SD/-Leu-Trp-His-Ade/X-α-Gal medium in turn. Finally, the blue and well grown positive clones were selected. The plasmids of positive yeast clones were extracted and sequenced. The candidate genes were preliminarily compared in the GenBank, and the interacted protein factors were annotated and the protein’s biological functions were analyzed with gene ontology (GO) pathway of Uniprot online websites. According to the results of the analysis, candidate factors that may be involved in host disease resistance or symptom development were selected, their CDS full-length sequences were amplified and constructed into the target vector pGADT7 and then were verified with pGBKT7-CP by one for one in yeast, respectively.【Result】The titer of the Eureka lemon-E. coli cDNA library was 1.02×10⁸ cfu/mL, and it demonstrated that the cDNA library measured up to the experiment standard. The bait vector of pGBKT7-CP was constructed, which had no ability to activate the reporter gene and had no virulence to the yeast. The 41 positive clones were finally selected by using the SD/-Leu-Trp-His-Ade/X-α-Gal medium. After sequence similarity comparison, removing the repetitive sequences, the vector sequences and the frameshift sequences, the 32 host factors that interacted with CYVCV CP were screened. The GO pathway annotation results indicated that these host factors were involved in several chloroplast-related biological processes, including photosynthesis, metabolic process, carbohydrate metabolic process, response to light stimulus, etc. The molecular functions of the 32 host factors were multiple, including catalytic activity, hydrolase activity, transferase activity, protein binding, DNA-binding transcription factor activity, and translation factor activity, etc. Moreover, the cell components of the 32 host factors were involved in the cytoplasm, membrane, chloroplast, thylakoid, nucleolus, and golgi apparatus, etc. Validation of one-to-one yeast two-hybrid crosses of 14 important proteins selected from candidate host factors with CP showed that CP interacted with all 14 proteins.【Conclusion】The cDNA library of Eureka lemon was constructed successfully, and 32 host factors of Eureka lemon interacted with CYVCV CP were preliminarily screened. According to the results, the function of the important proteins was analyzed. It was presumed that CYVCV CP affects photosystem stability, thylakoid structure and chlorophyll synthesis by interacting with multiple chloroplast-related proteins such as oxygen-evolving enhancer protein 2 (PsbP), chlorophyll a-b binding protein 8 (Lhca3) and ribulose bisphosphate carboxylase small subunit (RbcS), resulting in reduced photosynthesis and damaged chloroplast morphology and function. The interaction of CP with these chloroplast-associated factors was separately verified one-to-one in yeast, which will provide a theoretical basis for revealing the molecular mechanism of CYVCV CP in viral pathogenicity.

Genomic selection is defined as using the molecular marker information that covered the whole genome to estimate individual’s breeding values. Using genome information can avoid many problems caused by pedigree errors so as to improve selection accuracy and shorten breeding generation intervals. According to different statistical models, methods of estimated genomic breeding value (GEBV) can be divided into based on BLUP (best linear unbiased prediction) theory, based on Bayesian theory and others. At present, GBLUP and its improved method ssGBLUP have been widely employed. Accuracy is the most used evaluation metric for genomic selection models, which is to evaluate the similarity between the true value and the estimated value. The factors that affect the accuracy can be reflected from the model, which can be divided into controllable factors and uncontrollable factors. Traditional genomic selection methods have promoted the rapid development of animal breeding, but these methods are currently facing many challenges such as multi-population, multi-omics, and computing. What’s more, they cannot capture the nonlinear relationship between high-dimensional genomic data. As a branch of artificial intelligence, machine learning is very close to biological mastery of natural language processing. Machine learning extracts features from data and automatically summarizes the rules and use to make predictions for new data. For genomic information, machine learning does not require distribution assumptions, and all marker information can be considered in the model. Compared with traditional genomic selection methods, machine learning can more easily capture complex relationships between genotypes, phenotypes, and the environment. Therefore, machine learning has certain advantages in animal genomic selection. According to the amount and type of supervision received during training, machine learning can be classified into supervised learning, unsupervised learning, semi-supervised learning, and reinforcement learning. The main difference is whether the input data is labeled. The machine learning methods currently applied in animal genomic selection are all supervised learning. Supervised learning can handle both classification and regression problems, requiring the algorithm to be provided with labeled data and the desired output. In recent years, the application of machine learning in animal genomic selection has been increasing, especially in dairy and beef cattle. In this review, machine learning algorithms are divided into three categories: single algorithm, ensemble algorithm and deep learning, and their research progress in animal genomic selection were summarized. The most used single algorithms are KRR and SVR, both of which use kernel tricks to learn nonlinear functions and map data to higher-dimensional kernel spaces in the original space. Currently commonly used kernel functions are linear kernel, cosine kernel, Gaussian kernel, and polynomial kernel. Deep learning, also known as a deep neural network, consists of multiple layers of connected neurons. An ensemble learning algorithm refers to fusing different learners together to obtain a stronger supervised model. In the past decade, the related literature on machine learning and deep learning has shown exponential growth. And its application in genomic selection is also gradually increasing. Although machine learning has obvious advantages in some aspects, it still faces many challenges in estimating the genetic breeding value of complex traits in animals. The interpretability of some models is low, which is not conducive to the adjustment of data, parameters, and features. Data heterogeneity, sparsity, and outliers can also cause data noise for machine learning. There are also problems such as overfitting, large marks and small samples, and parameter adjustment. Therefore, each step needs to be handled carefully while training the model. This paper introduced the traditional methods of genomic selection and the problems they face, the concept and classification of machine learning. We discussed the research progress and current challenges of machine learning in animal genomic selection. A Case and some application suggestions were given to provide a certain reference for the application of machine learning in animal genomic selection.

【Objective】The Pi9 resistance gene locus, conferring a broad-spectrum resistance against Magnaporthe oryzae, is consist by several tandem homologous genes. Over 10 resistance genes have been cloned from this gene locus. This study aims to clarify the R gene composition at Pi9 locus in rice resource materials and promote the application of those genes in rice resistance breeding.【Method】Comparing the DNA sequence of cloned R genes at Pi9 locus, the specific nucleotide polymorphism sites were screened as the candidate sites. Subsequently, each R gene was blasted with 155 rice genomes in the database of Rice Resource Center. The most specific nucleotide polymorphism sites were picked out from the candidate site in each gene to develop primer pair of molecular markers. The PCR product of primer pairs was used to mark indicated R gene in tested rice materials via parameter optimization. To verify the results, the R genes were cloned from indicated rice variety randomly and examined by Sanger sequencing, or analyzed the R genes from the genome database if the genome sequence of indicated rice variety exists in Rice Resource Center. The R genes in Pi9 locus have high homology, which cause same specific nucleotide polymorphism sites existing in different R genes. Therefore, some R genes are hardly identified by one molecular marker. For this case, several molecular markers were employed to identify the indicated R gene simultaneously. Moreover, some specific nucleotide polymorphism sites are single nucleotide polymorphism (SNP), in where the primers of molecular markers have a mismatched base. In order to improve the specificity of PCR amplification, the adjacent base of SNP was mutated to generate two mismatched bases at 3′ site of primer.【Result】Finally, the valid molecular markers were developed for each R gene and identified 32.09% tested materials containing R genes at Pi9 locus. Pi9, Pid4, PigmR, Piz-t, Pi2 and Pi9-type5 are present in 1, 7, 8, 14, 23 and 33 tested materials, respectively. The Pi9 only presents in monogenic line but not in rice parent lines. The other genes are usually present in two or more gene combinations in rice parent lines. The Pi9-type5 often presents in pair with Pi2 and Piz-t, and presents alone in three rice parents, Chenghui 993, HR2168 and Mianhui 365. Yuhui 38 contains the most R genes at Pi9 locus, including Pi2, Pi9-type5, PigmR and Pid4. Chuangu B, Chuannong 4B, Neixiang 6B and Shuang 1B contain Piz-t, PigmR and Pid4. Qianxiang 654B contains Piz-t and Pid4.【Conclusion】This study successfully developed specific molecular markers for six homologous rice blast resistance genes in Pi9 locus and identified the R gene composition in Pi9 locus for 110 rice parent lines that used in rice breeding in Sichuan basin. It also discovered different types of R genes combination at Pi9 locus and provided a clear reference for choosing the resistance source in rice breeding.

Sweetpotato is considered as one of important crops for food, feed and industrial materials in the world. China is the largest sweetpotato producer in the world. This paper summarizes history, present situation, main achievement, problems of sweetpotato production and seed industry in China, analyzes the development trend of sweetpotato production and seed industry of the world, and puts forward the future development goal and task in China. At present, the sweetpotato production has developed steadily in China. The planting area tends to be stable, and the annual planting area is about 400 million hectares. The yield has steadily increased and reached to 1.96 times of the world average. The production has realized the transformation and upgrading from quantity to quality. The table use market is increasing continuously, and sweetpotato is well received. Snacks, healthy and functional foods are moderately developed. As the consumption increased, the benefit of sweetpotato planting is raised. The sweetpotato brand has been greatly developed. On the supports of China Agricultural Research System, Sweetpotato (CARS-SP), the molecular breeding platform of sweetpotato has been established, the genome sequencing of sweetpotato has been mainly completed, the high density molecular linkage map has been constructed, molecular markers and QTLs related to stem nematode resistance and starch content have been developed, and some important functional genes related to quality, disease resistance, salt tolerance and drought resistance have been discovered. The platform was constructed for diseases identification and varieties evaluation, and a set of new germplasm and varieties were created and released. More than 95% varieties planted in China were domestic. The national standard and industry standard of new sweetpotato varieties were established for DUS testing to standardize the seed and seedling market. The key technology research was completed for virus-free seed and seedling production. The cooperative innovation system was established to promote the reorganization of seed and seedling enterprises by combining producers, educators and researchers. There are still many problems in sweetpotato production and seed industry in China now. First is the number of excellent germplasm is small, which can’t meet the demand of breeding. Second is the lack of evaluation index of high quality varieties, and less specialized varieties to meet processing demand. The third is the less application of virus-free seed and seedlings, and the propagation technology and market of seed and seedling are not standardized. The fourth is small scale seed industry, weak support from government, and small number of regional seed and seedling enterprises to meet the needs of production. In the next 5-10 years, we should pay attention to construction platform of resource collection, evaluation and preservation, build up public service platform for sweetpotato breeding, release and demonstrate high-quality, high-yield and multi-resistance varieties, construct breeding-propagation-extension system, further extend the processing chain and improve industrial efficiency, and demonstrate varieties with high-quality starch, rich in dietary fiber, anthocyanin, carotene and polyphenols in the “One-Belt and One-Road” countries.

【Objective】 Mining the key drought-resistant genes of maize, revealing its drought-resistant molecular mechanism, and providing genetic resources and theoretical guidance for the cultivation of new drought-resistant maize varieties.【Method】Transcriptome data combined with weighted gene co-expression network (WGCNA) and screening methods for physiological and biochemical indicators of drought resistance were used to identify ZmPAL genes associated with drought resistance and rewatering. Genome-wide analysis of the genes encoding PAL was performed using bioinformatics methods. Quantitative real-time fluorescence PCR (qRT-PCR) was used to detect the expression of ZmPAL genes under drought treatment conditions, as well as the expression characteristics of ZmPAL5 among different inbred lines and the expression patterns in different tissues. Finally, genetic transformation was used to analyze the drought resistance function of ZmPAL5 in maize, and the deletion-type Arabidopsis mutant was analyzed for drought resistance with the help of CRISPR/Cas9 technology for the PAL5 homologous gene.【Result】Nineteen maize ZmPAL genes were identified, six of which were clustered on chromosome 5 and encoded proteins that were mostly hydrophilic acidic proteins and relatively evolutionarily conserved in the PAL family of genes. The promoter region of ZmPAL genes contained a large number of cis-acting elements associated with hormonal and abiotic stress responses. Six core genes were identified, four of which were significantly up-regulated for expression after drought treatment. In particular, ZmPAL5 showed an 8.57-fold increase in expression after drought stress. The expression level of ZmPAL5 was found to be significantly higher in the drought-resistant inbred line Zheng 8713 than in the drought-sensitive inbred line B73 under both drought stress and rewatering treatments. Meanwhile, ZmPAL5, a constitutively expressed gene, showed a high level of expression in young stems. Overexpressed ZmPAL5 maize grew well under drought stress, and its relative water content, lignin, chlorophyll, soluble protein, proline content, and activities of superoxide dismutase, peroxidase, catalase, and ascorbate peroxidase were 1.52, 1.49, 1.47, 1.43, 1.44, 1.41, 1.53, 1.41, and 1.35 times, but the malondialdehyde content was 0.65 times that of the wild type. The PAL5-deficient Arabidopsis mutant was sensitive to drought. Under drought stress, its physiological and biochemical indexes showed the opposite trend to those of overexpression of ZmPAL5 maize. 【Conclusion】 Six core genes (ZmPAL3, ZmPAL5, ZmPAL6, ZmPAL8, ZmPAL11, and ZmPAL13) were screened in response to drought stress, in which the expression of ZmPAL5 was positively correlated with drought resistance. ZmPAL5 positively regulated the drought resistance and resilience of the plant by influencing the content of osmotically regulated substances and antioxidant enzyme activities.

Pre-harvest sprouting (PHS) refers to the germination of cereal crops on the spike in high humidity conditions before grain harvest. Wheat PHS is a significant problem that affects both the yield and quality of wheat. Seed dormancy level is a major factor influencing the resistance of wheat PHS, and domesticated crops often exhibit reduced seed dormancy levels, making cultivated wheat more prone to PHS compared to its wild ancestors. Wheat PHS is mainly regulated by external environmental factors such as temperature and humidity, as well as internal plant hormones (GAs, ABA, IAA, MeJA, ET, BR). Researchers have identified a range of materials resistant to PHS, cloned key genes regulating PHS resistance, such as PM19, MFT, MKK3, Myb10-3D, Vp1. New wheat materials resistant to PHS have been successfully developed through molecular marker-assisted selection, artificial synthesis of wheat, and CRISPR/Cas9 gene editing technology. This article reviews the genetic mechanism of PHS resistance in wheat and the latest progress in PHS resistance breeding research. In the future, it is necessary to continue exploring key genes related to PHS resistance, and employ biotechnological breeding methods to cultivate new PHS-resistant wheat varieties.

本文对中国300个农业气象试验站各种作物的收获资料进行统计分析，计算了收获指数、谷草比和有关的统计参数。结果指出：1.各作物的平均收获指数差别较大，主要粮食作物的收获指数在0.35—0.45之间，谷草比在0.55—0.80之间。2.收获指数和谷草比的变动范围较大，对于同一作物，绝大多数样本的谷草比都分布在平均值附近，而少数的可以偏离平均值较远。3.由粮食产量推算秸秆量，对于大面积的估算有较满意的结果，而对于个别地块，其误差可能较大。4.一些主要作物谷草比的频率分布曲线接近正态分布，而多数则属正偏类型。5.同一作物在丰、平、歉年的平均谷草比各不相同，一般丰年大，歉年小，平年介于其间。6.谷草比与产量水平有关，随着产量的提高而增加，其关系可用一元回归方程表示。

【Objective】By analyzing the yield and agronomic traits alterations of foxtail millet cultivars tested in North China summer-sowing region from the latest 15 years, the change trend in millet breeding level was elucidated to provide references for the future development of foxtail millet cultivars.【Method】The main agronomic traits data of foxtail millet cultivars in North China summer-sowing region from 2001 to 2015 was used to reveal the changing rule of foxtail millet breeding. Correlation analysis between climatic factors and agronomic traits of foxtail millet cultivars tested from 2001 to 2015 was conducted. The types of foxtail millet cultivars were classified.【Result】The agronomic traits of the cultivars altered significantly during 2001 to 2015. As time lapse, yield, growth duration, plant height, panicle length, panicle weight and panicle grain weight increased, while 1000-grain weight decreased slightly, and panicle numbers per hectare decreased. The change trend of the main agronomic traits of the 51 foxtail millet cultivars from year 2001 to 2015 was in accordance with all tested cultivars. Variance analysis showed that yield, growth duration, plant height, panicle length, 1000-grain weight and panicle numbers per hectare were significantly different among the 51 foxtail millet cultivars, while there was no significant difference in panicle weight, panicle grain weight and percentage of grain weight per panicle. The climate trend was warm and humid in North China summer-sowing region. The yield had a higher positive correlation with the growth duration, panicle weight and panicle grain weight, but had a higher negative correlation with the lowest temperature and precipitation. 85.17% of yield variation was determined by lowest temperature, highest temperature, precipitation, growth duration, panicle grain weight and percentage of grain weight per panicle. The lowest temperature had a negative effect on yield, while the highest temperature had a positive effect on yield. The foxtail millet breeding level was progressed from 2001 to 2015, and the types of foxtail millet cultivars were abundant with more herbicide resistance cultivars and high quality cultivars, showing that the main breeding direction was simplified cultivation and quality. However, there were 26 foxtail millet cultivars with the parental source of Jigu19, Yugu1 and Jigu25. The percent was up to 57.8%, showing that the parents used in millet breeding were in a narrow scope.【Conclusion】The yield of foxtail millet cultivars in North China summer-sowing region from 2001 to 2015 was increased somewhat, the types of foxtail millet cultivars were abundant, and the foxtail millet breeding level was progressed to some extent. However, the yield difference was mainly caused by weather fluctuation. In the future, the types of parent should be immensely enriched. And the types of millet cultivars with higher grain weight and higher percentage of grain weight per panicle should be cultivated for adapting climate change and improving yield.

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

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

【Objective】Exploring the genetic loci and related genes that control cottonseed size traits to lay a foundation for subsequent study on the molecular mechanism cottonseed size formation. 【Method】The upland cotton recombinant inbred line (RIL) population composed of 300 lines was used as the research material. Seven phenotypic traits including cottonseed index (SI), seed length-cutting acreage (SLA), seed length-cutting perimeter (SLP), seed length (SL), seed width (SW), length-width ratio (LWR) and seed roundness (SR) were evaluated in four environments. The RIL population was genotyped by liquid phase chip strategy. The high-quality single nucleotide polymorphism (SNP) markers and phenotypic data were subjected to perform genome-wide association study (GWAS), and quantitative trait nucleotides (QTNs) associated with cottonseed size-related traits were mined. The genetic effects of QTNs were analyzed to identify candidate genes. 【Result】Seven cottonseed size-related traits showed a continuous normal distribution in four environments, which expressed a sizable phenotypic variation. The coefficient of variation ranged from 1.82% to 10.70%. The influencing effect on trait formation were basically as genotype>environment>genotype × environment, indicating suitability for GWAS analysis of these results. Correlation analysis showed that the seed index was significantly correlated with SLA, SLP, SL and SW, and LWR was significantly correlated with SR, indicating the possible existence of pleiotropic loci. GWAS was performed using the 3VmrMLM model, and a total of 47 QTNs were associated with these seven traits. A total of 11 QTNs were associated on chromosome A07, of which three physical loci in the region of 71.99-72.87 Mb, A07:71993462, A07:72067994 and A07:72198802 were very close and simultaneously associated with SI, SLA, SLP, SL and SW in four environments. The average value of R2 between markers was>0.8 (P<0.001), showing a large linkage disequilibrium. Genetic effect analysis showed that there were two haplotypes in this region. Among these cottonseed size relating traits, haplotype Ⅱ and haplotype I were significantly different, indicating that these loci directly affected cottonseed size traits and could be used for molecular marker-assisted selection. The expression patterns of the genes in the interval were analyzed using TM-1 transcriptome data. The results revealed that Gh_A07G1767 was preferentially expressed and Gh_A07G1766 specifically expressed at the stage of cottonseed development. These results speculated that these genes may play an important role in the growth and development of cottonseed.【Conclusion】47 QTNs were identified, and two candidate genes related to cottonseed development were screened.

【Background】Fatty acid transporter 1 (FATP1) can promote the uptake of fatty acids in mammals. This process is very important to maintain the balance of lipid metabolism, and also has an important impact on the meat quality of livestock.【Objective】The aim of this study was to obtain the CDS sequence of goat FATP1 gene, to detect the expression of FATP1 gene in different tissues of goats, and to explore its effect on lipid metabolism of goat intramuscular adipocytes, so as to provide a reference for further revealing the mechanism of FATP1 gene in goat lipid metabolism, which can provide a theoretical basis for genetic and breeding improvement of goats.【Method】The CDS of goat FATP1 gene was cloned by real-time fluorescence quantitative PCR (RT-PCR), its biological characteristics, such as hydrophobicity, transmembrane region and signal peptide, were analyzed by online tools, and its amino acid sequence phylogenetic tree was constructed. The expression level of FATP1 gene in different goat tissues was detected by RT-qPCR and its tissue expression pattern was constructed. The constructed eukaryotic expression vector and screened siRNA were used to overexpress and interfere with FATP1 in goat intramuscular adipocytes, the effects of FATP1 gene overexpression and interference on lipid deposition in goat intramuscular adipocytes were detected by oil red O staining and triglyceride determination, and the effects of FATP1 gene overexpression and interference on the expression of genes related to lipid metabolism were further explored by RT-qPCR.【Result】The CDS of FATP1 gene was 1 941 bp, encoding 646 amino acids residues. It was predicted that its molecular formula was C₃₁₉₆H₅₀₂₆N₈₈₄O₈₉₈S₂₅, and the protein was a basic hydrophobic stable protein. Phylogenetic tree analysis of amino acid sequence showed that goat FATP1 was closely related to sheep. RT-qPCR showed that the expression of FATP1 gene was the highest in goat small intestine. Oil red O staining and triglyceride determination showed that the number of lipid droplets and triglyceride content in goat intramuscular adipocytes increased after overexpression of FATP1, but the opposite results were obtained after interference with FATP1. After overexpression of FATP1 in goat adipocytes, the expression levels of fatty acid synthesis, transport and other related genes AGPAT6(P<0.01), PLIN1(P<0.01), DGAT2(P<0.01), FADS2(P<0.01), FADS1(P<0.01), ACSL1(P<0.01) and ELOVL3 (P<0.05) increased significantly, while the expression level of lipolysis related genes ACOX1 (P<0.01) decreased significantly. After interfering FATP1, the expression of fatty acid transport, elongation and other related genes SCD5 (P<0.01), FABP3 (P<0.01) and ELOVL3 (P<0.05) decreased significantly, and the expression of lipolysis related genes ACOX1 (P<0.01) and CPT1B (P<0.05) increased significantly.【Conclusion】FATP1 might significantly promote the lipid deposition of goat intramuscular precursor adipocytes by promoting the expression of genes related to cell lipid production and reducing the expression of genes related to lipolysis, which provided an experimental reference for further revealing the role and molecular mechanism of FATP1 gene in regulating lipid metabolism.

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

【Objective】 The objective of this study was to analyze the impact of intercropping Vulpia myuros on soil nutrient composition, soil microbial community structure, and tea quality components in tea plantations, so as to provide the data support for intercropping V. myuros as a means to enhance the ecological environment and quality of tea cultivation.【Method】The experimental materials consisted of soil and fresh leaves from a tea garden that had been intercropped with V. myuros for a duration of 2 years, and the control group was a clear-ploughed tea garden. The pH, organic matter, and mineral nutrients of the topsoil in the tea garden were measured. Additionally, the population structure of soil bacteria and fungi was analyzed using 16S and ITS high-throughput sequencing techniques. The quality components of tea were determined through Agilent-7890B gas chromatography.【Result】After intercropping V. myuros in a tea garden for 2 years, the soil pH increased by 0.29, and the soil organic matter content increased by 16.46 g∙kg^-1. Additionally, the available phosphorus, available potassium, ammonium nitrogen, and nitrate nitrogen also increased to varying degrees in the tea garden soil planted with V. myuros. Notably, the available phosphorus was 5.88 times higher in the intercropped tea garden compared with the clear-cultivated tea garden. The total nitrogen content in the V. myuros plantation soil was higher than that in the clear-cultivated tea plantation, while the total phosphorus, potassium, and sodium contents were lower. Moreover, the tea garden soil planted with V. myuros had higher levels of available zinc, available iron, available copper, and cation exchange capacity. The intercropping of V. myuros in the tea garden also led to an increase in the number of bacteria and fungi in the soil. Furthermore, the relative abundance of Actinobacteria and Ascomycota associated with organic matter decomposition increased in the soil of the V. myuros tea plantation. A total of 259 metabolites were identified from the fresh leaves of the grass plantation and the clear cultivation garden. Among them, the content of 20 metabolites showed significant differences, and these different metabolites mainly included sugars, fatty acids, and catechins. The tea leaves of the V. myuros plantation had more than 2 times the contents of leucrose, methyl-β-D-glucopyranoside, lacttol alcohol, galactoglycerol, and α-lactose compared to the tea plantation. On the other hand, the content of (9Z)-octadecatrienoic acid and (9Z,12Z,15Z)-octadecatrienoic acid were significantly lower in the cultivated tea garden. Additionally, compared with the clear-ploughed tea garden the intercultivated tea plantation had significantly lower contents of (+)-galligallocatechin, galligallocatechin, and epicatechin metabolites. 【Conclusion】When V. myuros was interplanted with tea gardens, the acidity of the soil might be successfully alleviated, and the amount of organic matter and mineral nutrient components in the soil increased. Then, tea plants could more easily absorb and use soil nutrients when there were changes in the amount and community structure of soil bacteria and fungi. The structure of the microbial population and variations in soil nutrients had a significant impact on the quality of tea.

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

【Objective】The temporal characteristics, spatial pattern, evolution mode, decoupling relationship and performance evaluation of China’s agricultural carbon emissions were analyzed scientifically, so as to provide a basis for helping China achieve the goal of “carbon peaking and carbon neutrality” and strengthen the construction of an agricultural power. 【Method】This study constructed an index system for assessing agricultural carbon emissions and agricultural carbon emission performance in China, and measured the systematic measurement index of agricultural carbon emissions in Chinese provinces from 2007 to 2020. The Kernel density estimation and standardized ellipsoidal visualization analysis were used to analyze the regional distribution characteristics and spatial-temporal evolution trends of agricultural carbon emissions, Tapio model was used to examine the decoupling relationship between examining agricultural carbon emissions and economic growth, and the super-efficient SBM model with non-expected output was constructed to report the agricultural carbon emission performance and decomposition efficiency of China and the seven economic regions. 【Result】 From 2007 to 2020, the overall agricultural carbon emissions in China showed an “inverted U-shaped” curve of rising and then declining, with obvious regional differences and stable distribution of ranks. The eastern region had the best emission reduction effect, the central region had a “bipolar” distribution, and the western region had a higher pressure of emission reduction, with the overall spatial pattern dominated by the northeast-southwest direction, and tended to be decentralized to the northeast and northwest. China’s agricultural carbon emissions and agricultural economic development have been maintained at a weakly decoupled level and have made a breakthrough to a strongly decoupled level, which could be divided into two stages: a stable period (2007-2016) and a breakthrough period (2017-2020). The assessment of agricultural carbon emission performance showed a trend of “rapid rise - slow decline - steady improvement”, with the Great Northwest Economic Zone and the Northern Coastal Economic Zone in the first and last positions, respectively, and the contribution of technological change in agricultural production (TC) was more prominent than that of technical efficiency change (EC). 【Conclusion】With 2017 as the inflection point, China’s agricultural carbon emissions as a whole showed a decreasing trend, and the agricultural economic development as a whole was gradually getting rid of the dependence on agricultural carbon emissions, with different agricultural bases and different emission reduction targets in each region and province. It was necessary to reasonably plan the scale and internal structure of agricultural comparative advantage industries according to local conditions, reasonably select the resource endowment production characteristics of industries in the region. At the same time, we should pay attention to technology iteration and updating in the agricultural economic development and energy conservation and emission reduction in the role of promoting, taking into account the regional ecological benefits and economic benefits.

【Objective】In this study, sensory evaluation, electronic nose detection, electronic tongue detection and texture analyzer detection were used to determine the differences in egg yolk flavor between traditional caging regime and furnished caging regime, to provide basic data on the egg yolk flavor. 【Method】The eggs were produced by Jing Tint 6 laying hens that were 55 weeks old and healthy in traditional caging regime and furnished caging regime that was used as the test objects. The aroma, flavor and texture of egg yolk were detected by sensory evaluation, electronic nose detection and electronic tongue detection, and texture analyzer. Linear discriminant analysis (LDA) analysis, support vector machine (SVM) analysis, K-nearest neighbor method (KNN) analysis and decision tree analysis were used to distinguish the yolk flavor of the two caging regimes to explore the influence of different caging regimes on the flavor of egg yolk.【Result】The yolk color was significantly increased in traditional caging regime compared with furnished caging regime (P<0.05). The milky flavor scores of egg yolk in furnished caging regime were significantly higher than that in traditional caging regime (P<0.05), and the seaweed flavor scores and stickiness scores of egg yolk in traditional caging regime were higher than those in furnished caging regime (P<0.05). The results of correlation analysis showed that the overall preference score of the yolk was significantly correlated with the acceptance of flavor scores and texture scores (P<0.05). Egg flavor was significantly negatively correlated with fishy flavor and sweet flavor (P<0.05), and the fishy flavor was significantly positively correlated with sweet flavor (P<0.05). There was a significant positive correlation between egg yolk lumpy and egg yolk adhesive dentition (P<0.05). The responses of W2W, W2S, W1W and W1S of electronic nose sensors in furnished caging regime were significantly higher than those in traditional caging regime (P<0.05), and the responses of SRS, STS and UMS of egg yolk electronic tongue sensors in furnished caging regime were significantly lower than those in traditional caging regime (P<0.05). The hardness and chewiness of egg yolk in furnished caging regime were significantly higher than that in traditional caging regime (P<0.05). The KNN method could discriminate the differences in egg yolk aroma in the different caging regimes based on the responses of the electronic nose, and the accuracy was 94.5%. The SVM, KNN method and decision tree could distinguish the differences in egg yolk flavor in the different caging regime based on the responses of the electronic tongue, with 100% accuracy rate. 【Conclusion】In conclusion, the milky flavor of egg yolk was increased in furnished caging regime, and seaweed flavor and stickiness were reduced. The instrument detected the increased responses of the electronic nose sulfide sensor and the decreased responses of the electronic tongue umami and salty sensors in furnished caging regime. According to the responses of electronic nose and electronic tongue, the differences in egg yolk flavor in two different caging regimes could be effectively distinguished by KNN analysis, SVM analysis and decision tree analysis.