Theoretical and Applied Genetics最新文献

{"title":"Genetic dissection of grain yield and correlated proxy traits under suboptimal conditions.","authors":"Yan-Cheng Lin, Claude Urbany, Antonina Shlykova, Armin C Hölker, Milena Ouzunova, Thomas Presterl, Torsten Pook, Manfred Mayer, Sebastian Urzinger, Chris-Carolin Schön","doi":"10.1007/s00122-026-05364-w","DOIUrl":"10.1007/s00122-026-05364-w","url":null,"abstract":"<p><strong>Key message: </strong>This eight-founder MAGIC population represents a powerful resource for dissecting complex traits in maize, assessing the utility of drought proxy traits, and optimizing low-coverage whole-genome sequencing approaches. Securing sustainable crop production requires the genetic improvement of abiotic stress tolerance. Due to the broad range of environmental factors causing abiotic stress and complex genotype-by-environment interactions, it is crucial to understand the genetic basis of crop yield under suboptimal conditions. Here, we developed a dent maize Multi-parent Advanced Generation Inter-Cross (MAGIC) population comprising 388 doubled-haploid (DH) lines. The population was derived from eight founders with varying stress tolerance, selected from a dent diversity panel evaluated for yield performance across a wide range of European environments. The MAGIC DH lines were genotyped via whole-genome sequencing (~ 5× coverage) and evaluated in seven testcross and 14 line per se trials, for grain yield, leaf senescence, leaf rolling, anthesis-silking interval, and six additional agronomic traits. Genetic dissection identified 22 grain yield QTL, explaining 45% of the genetic variance. Under heat and drought stress, testcross grain yield correlated significantly with leaf senescence and leaf rolling measured in line per se trials. Bivariate multi-trait analysis showed that alleles for delayed senescence and reduced rolling at detected QTL generally exhibited positive effects on grain yield, suggesting that accumulating these favorable alleles could enhance yield performance. Incorporating these proxies into multi-trait genomic prediction models improved yield prediction accuracy, although gains were constrained by modest trait correlations. Given the comprehensive data, we also provide recommendations for optimizing sequencing depth and QTL mapping strategies in experimental maize populations.</p>","PeriodicalId":22955,"journal":{"name":"Theoretical and Applied Genetics","volume":"139 9","pages":""},"PeriodicalIF":4.1,"publicationDate":"2026-09-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13538158/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148881674","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Correction: The candidate gene SibHLHA regulates anthocyanin-driven purple pigmentation in Sesamum indicum flowers.","authors":"Fengli Zhao, Chengqi Cui, Wenxing Wei, Zhenwei Du, Ke Wu, Xiaolin Jiang, Yongzhan Zheng, Yanyang Liu, Hongxian Mei, Haiyang Zhang","doi":"10.1007/s00122-026-05335-1","DOIUrl":"10.1007/s00122-026-05335-1","url":null,"abstract":"","PeriodicalId":22955,"journal":{"name":"Theoretical and Applied Genetics","volume":"139 9","pages":""},"PeriodicalIF":4.1,"publicationDate":"2026-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148881738","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Yield-graph: multi-stage growth-aware maize yield prediction via graph neural networks.","authors":"Jiahui Wang, Yong Zhang, Bo Li, Yuqing Zhang, Xinglin Piao, Aiwen Wang, Xiangyu Zhao, Kaiyi Wang","doi":"10.1007/s00122-026-05354-y","DOIUrl":"10.1007/s00122-026-05354-y","url":null,"abstract":"<p><strong>Key message: </strong>Yield-Graph enables accurate maize yield prediction from incomplete multi-stage phenotypic and environmental data by modeling higher-order environment-trait interactions, with robust applicability across growth stages, regions, and crop species. Accurate yield prediction before maize harvest is crucial for advancing agricultural management and ensuring food security. Unlike conventional approaches that rely on traits from a single growth stage, this study models multiple traits across different developmental stages, all targeting final yield, thereby uncovering their stage-specific contributions and demonstrating the feasibility of early yield prediction. We introduce Yield-Graph, an innovative framework that evaluates phenotypic data at distinct developmental stages for yield prediction. The method employs a bipartite graph structure to impute missing trait values at each stage and leverages a hypergraph attention mechanism to capture high-order sample relationships. Comprehensive benchmark experiments demonstrate that Yield-Graph matches the top-tier predictive accuracy of exhaustively optimized tree models. Moreover, the framework exhibits strong robustness across growth stages, high adaptability to regional variations, and effective generalization across datasets. These findings highlight the potential of graph-enhanced multi-stage modeling for early-stage yield prediction, offering a scalable solution for precision agriculture and intelligent crop management.</p>","PeriodicalId":22955,"journal":{"name":"Theoretical and Applied Genetics","volume":"139 9","pages":""},"PeriodicalIF":4.1,"publicationDate":"2026-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148881733","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Multi-environment dissection of the genetic architecture of grain color and milling-related recovery traits in foxtail millet.","authors":"Wei Zhou, Hui Zhi, Qiang He, Haigang Wang, Yanyan Zhang, Liwei Wang, Zhijun Qiao, Xianmin Diao","doi":"10.1007/s00122-026-05369-5","DOIUrl":"10.1007/s00122-026-05369-5","url":null,"abstract":"<p><strong>Key message: </strong>Multi-environment QTL analysis uncovered reproducible and novel loci underlying grain color and milling-related recovery traits in foxtail millet, and Seita.5G392600 was prioritized as a putative candidate gene for kernel yellowness and a potential breeding target. Grain appearance and processing quality are major determinants of the market value and end-use performance of foxtail millet, yet the genetic basis of these traits remains incompletely understood, particularly for kernel color and milling-related recovery traits. Here, we used 256 recombinant inbred lines derived from Jingu 21 × Chuang 29 and an ultra-high-density bin map generated by whole-genome resequencing to dissect the genetic architecture of grain color and milling-related recovery traits across eight environments. Three hull color traits (L, a, b), three kernel color traits (L, a, b), and two milling-related recovery traits, percentage of grain weight per panicle (PGWP) and percentage of kernel weight (PKW), were evaluated. In total, 74 QTL occurrences were identified and integrated into 45 distinct QTLs, including 11 reproducible loci detected in at least two environments and 34 environment-specific loci. Based on physical overlap with previously reported regions, 39 QTLs were considered putatively novel, whereas six co-localized with previously reported loci. We also identified seven multi-trait QTL clusters on chromosomes 1, 2, 3, 5, and 9. Candidate gene prioritization identified 11 genes within major QTL intervals. Among them, Seita.5G392600, encoding a putative glycosyltransferase, was prioritized as a putative candidate gene for kernel yellowness based on QTL co-localization, haplotype association, and detectable expression during grain development. The rare haplotype of Seita.5G392600 associated with higher kernel yellowness may provide useful variation for kernel color improvement, although further validation is required. These findings advance our understanding of the genetic architecture of grain appearance and milling-related recovery traits in foxtail millet and provide targets for fine mapping, functional validation, and marker-assisted improvement.</p>","PeriodicalId":22955,"journal":{"name":"Theoretical and Applied Genetics","volume":"139 9","pages":""},"PeriodicalIF":4.1,"publicationDate":"2026-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148875994","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Genome wide association studies and expression analyses identify candidate genes for spot blotch resistance in bread wheat.","authors":"G Mahendra Singh, Uttam Kumar, Bhagya Shree Acharya, Pradeep Bhati, Manish Vishwakarma, Dinesh Kumar Saini, Sundeep Kumar, Vinod K Mishra, Arun K Joshi, Sandeep Sharma","doi":"10.1007/s00122-026-05362-y","DOIUrl":"10.1007/s00122-026-05362-y","url":null,"abstract":"<p><strong>Key message: </strong>GWAS of 1,273 wheat lines identified a stable MTA 3B_6127880 on 3BS chromosome arm for spot blotch resistance, and the associated candidate genes were differentially expressed in resistant vs. susceptible genotypes. Spot blotch (SB), caused by Bipolaris sorokiniana, poses a threat to global wheat production. We evaluated 1,500 elite wheat lines for SB across two environments to identify genomic regions and candidate genes (CGs) conferring resistance. Disease severity, measured as area under the disease progress curve (AUDPC), was negatively correlated with days to heading (DH) and stay-green traits (SGTs). Genome-wide association studies (GWAS) using three different models (MLM, FarmCPU, BLINK) identified seven and eleven stable MTAs for AUDPC and SGTs, respectively, with three (3B_6127880, 5B_546704556, 5B_546132836) common to both traits. To reduce the confounding effects of DH, a separate GWAS was conducted on a subset of genotypes with similar heading dates, confirming 3B_6127880 as a consistent locus for AUDPC, located near to previously known SB QTLs on 3BS chromosome arm. Several other putative MTAs and haplotypes associated with AUDPC and SGTs were identified. A time-course analysis of CGs associated with the important MTAs revealed differential expression in the resistant (Chirya 3) and susceptible (Sonalika) genotypes under SB infection. The identified SNPs, alleles, haplotypes, and CGs may be used in marker-assisted selection and breeding programs to develop wheat varieties with enhanced resistance to SB.</p>","PeriodicalId":22955,"journal":{"name":"Theoretical and Applied Genetics","volume":"139 9","pages":""},"PeriodicalIF":4.1,"publicationDate":"2026-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148866627","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The SlDREBA4-SlASIL2 module mediates tomato thermotolerance by regulating the expression of SlHSP20/90.","authors":"Xinyun Li, Haoran Zhang, Yunrong Mo, Yu Liu, Yuhao Jing, Kaiyun Chen, Ying Zhou, Zushuai Ma, Wei Fan, Junqiang Xu, Kai Zhao, Yanyan Wang","doi":"10.1007/s00122-026-05361-z","DOIUrl":"10.1007/s00122-026-05361-z","url":null,"abstract":"<p><strong>Key message: </strong>SlASIL2 can regulate tomato heat tolerance by suppressing the expression of SlHSP20/SlHSP90 and forming protein complexes with SlDREBA4. Tomato (Solanum lycopersicum) is an important vegetable crop with substantial economic value. High-temperature stress severely impacts tomato yield and quality, making it a major constraint on the development of the tomato industry. The DREBA4 transcription factor is thought to play a key role in the high-temperature stress response pathway; however, its regulatory mechanism remains to be fully elucidated. In this study, a combination of genetic and biochemical approaches was used to elucidate the roles of SlDREBA4 and SlASIL2 in regulating the transcription of SlHSP20 and SlHSP90. Further analysis were performed to investigate the function of the SlASIL2 gene using overexpression and silencing systems. Additionally, SlASIL2 was found to suppress the reactive oxygen species (ROS) scavenging system, thereby negatively regulating tomato heat tolerance. Moreover, SlASIL2 directly binds to the promoters of SlHSP20 and SlHSP90, repressing their expression and thereby reducing tomato heat tolerance. Importantly, the interaction between SlDREBA4 and SlASIL2 mitigated the inhibitory effect of SlASIL2 on SlHSP20 and SlHSP90, contributing to the establishment of a stable physiological state in tomatoes under high-temperature conditions. These results indicate that the transcriptional regulation of SlHSP20 and SlHSP90 by SlDREBA4 and SlASIL2, together with the modulation of the ROS scavenging system, collectively fine-tune the tomato response to short-term heat stress. Our findings further expand the understanding of the molecular regulatory network involved in plant heat stress responses.</p>","PeriodicalId":22955,"journal":{"name":"Theoretical and Applied Genetics","volume":"139 9","pages":""},"PeriodicalIF":4.1,"publicationDate":"2026-08-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148857751","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Approximating prediction error variances and reliabilities in a multiple-trait genomic prediction model using Monte Carlo sampling.","authors":"Antero Heikkilä, Ismo Strandén, Martin H Lidauer, Klaus Nordhausen, Sara Taskinen","doi":"10.1007/s00122-026-05336-0","DOIUrl":"10.1007/s00122-026-05336-0","url":null,"abstract":"<p><strong>Key message: </strong>We evaluated four existing Monte Carlo-based methods for approximating prediction error variances and reliabilities in a multiple-trait genomic prediction model. All four methods yielded consistent approximations of the exact values. Genomic prediction models, such as genomic best linear unbiased prediction (GBLUP), use genomic data to improve the accuracy of estimated genetic values. As the number of genotypes and traits increases, the exact calculation of prediction error variances (PEVs) and reliabilities becomes computationally infeasible due to the need to invert the coefficient matrix of the mixed model equations, whose dimension increases directly with the number of individuals and traits. The objective of this study was to evaluate the applicability of the Monte Carlo (MC) sampling method to approximate PEVs and reliabilities in a multiple-trait GBLUP framework relevant to hybrid breeding. The MC method avoids direct matrix inversion by repeatedly sampling genetic values from their assumed distributions to approximate PEVs. We applied the MC method using four previously published formulas to approximate PEVs and reliabilities. All formulas produced consistent estimates of PEVs and reliabilities, with convergence rates depending on the formula, the level of reliability, and the MC sample size.</p>","PeriodicalId":22955,"journal":{"name":"Theoretical and Applied Genetics","volume":"139 9","pages":""},"PeriodicalIF":4.1,"publicationDate":"2026-08-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13525033/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148851513","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Unveiling the interactions between design optimization, modeling strategies, and spatial analysis in genomic selection.","authors":"Javier Fernández-González, Jordi Comadran Trabal, Bertrand Haquin, Alix Allard, Eliette Combes, Karine Bernard, Julio Isidro Y Sánchez","doi":"10.1007/s00122-026-05285-8","DOIUrl":"10.1007/s00122-026-05285-8","url":null,"abstract":"<p><strong>Key message: </strong>Partially-replicated designs are more efficient than fully-replicated ones. They can be further enhanced through optimization and present positive synergy with fully-efficient models and 2D P-splines. In plant breeding, traditional field trials rely on balanced designs with high replication to ensure robust breeding value predictions. However, genomic technologies leveraging genomic relationship matrices have reduced the need for extensive replication, favoring partially-replicated (p-rep) designs. These designs, while effective, pose statistical challenges due to low replication and imbalance. To address these, we conducted simulations using datasets from maize, sunflower, and oat, evaluating interactions between experimental designs and modeling strategies across varying field sizes. Classical and p-rep designs, generated via randomization or optimization, were compared, using a novel, faster implementation of the CDmean optimization criterion developed to overcome computational limits. Modeling strategies included single-stage models, unweighted and fully efficient two-stage analysis, and spatial analysis with blocking structures or high-resolution 2D P-splines. Our findings showed p-rep designs consistently outperformed classical designs in predicting unobserved lines, achieving 1-25% higher accuracies depending on the scenario. Within observed training sets, p-rep designs exhibited slightly lower accuracy than classical designs, but it is compensated with increased selection intensity. Design optimization enhanced accuracy by  1% over randomized p-rep designs, while 2D P-splines improved accuracy by 1-2% when paired with single-stage or fully efficient models.</p>","PeriodicalId":22955,"journal":{"name":"Theoretical and Applied Genetics","volume":"139 9","pages":""},"PeriodicalIF":4.1,"publicationDate":"2026-08-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13524979/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148851522","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Identification of candidate genes associated with major QTL controlling Vertcillium wilt resistance in cotton (Gossypium hirsutum L.).","authors":"Yunlei Zhao, Baimei Cheng, Jinfa Zhang, Pei Zhao, Wei Chen, Xiaohui Sang, Jianhua Lu, Hongmei Wang","doi":"10.1007/s00122-026-05355-x","DOIUrl":"10.1007/s00122-026-05355-x","url":null,"abstract":"<p><p>Vertcillium wilt (VW), a soil-borne disease causing cotton yield loss and fiber quality reduction, is a major stumbling block in cotton production. It is a challenging job to detect key genes associated with major quantitative trait loci (QTL) that can be used to develop VW-resistant varieties. In this study, several genome regions associated with major QTL controlling VW resistance were fine mapped by constructing the high-density genetic map of major QTL regions using Kompetitive Allele-Specific PCR (KASP) markers. Candidate genes were subsequently identified by combining gene annotation, genome resequencing, transcriptome sequencing and qRT-PCR, and functions of several genes associated with major QTL were demonstrated based on gene VIGS silencing and overexpressing. The results showed that six QTL were identified, among which five were regarded as major QTL detected in at least two environments, and four QTL, qVW-D05-1, qVW-D05-2, qVW-D05-3 and qVW-A01-1, were fine mapped to 15.2-241.3 kb physical regions located on chromosome D05 and A01, respectively. Polymerizing of major QTL on different chromosomes showed that the more the resistant QTL were polymerized in a line, the stronger the VW resistance of the line became, and those lines polymerizing 4 resistant QTL showed much higher and more stable VW resistance in each environments, implying the potential of multi-locus QTL polymerization in improving VW resistance. Fifteen candidate genes showing both gDNA sequence variation and expression difference between resistant and susceptible lines were identified to be associated with VW resistance in cotton. Four candidate genes associated with qVW-D05-1 were cloned and conducted function analysis, it was showed that the sequence variation of functional genes, especially the variation resulting in amino acid differences of the domains, might be the molecular mechanisms of VW resistance in cotton.</p>","PeriodicalId":22955,"journal":{"name":"Theoretical and Applied Genetics","volume":"139 9","pages":""},"PeriodicalIF":4.1,"publicationDate":"2026-08-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148851478","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Day-neutral flowering candidate genes identified by selection mapping in an upland cotton (Gossypium hirsutum L.) RIL population.","authors":"Ganesh Pinnika, Martin J Wubben, Jack C McCarty, David D Fang, Gregory N Thyssen","doi":"10.1007/s00122-026-05357-9","DOIUrl":"10.1007/s00122-026-05357-9","url":null,"abstract":"<p><strong>Key message: </strong>Variants of flowering time genes identified from selective sweep selection of cotton breeding lines. Day-neutrality is essential for modern upland cotton (Gossypium hirsutum L.) cultivation at temperate latitudes, yet the molecular basis of the transition from photoperiod sensitive to day-neutral achieved by selective breeding remains incompletely understood. We conducted whole-genome resequencing of the day-neutral cultivar DP61, the reniform nematode-resistant line MT2468 Ren1, and 40 recombinant inbred lines (RILs) derived from their cross, all selected for day-neutral flowering. Since MT2468 was derived from a population that included photoperiod sensitive T2468 as a parent, there may be residual variation in the genes that affect photoperiodism. Using a selection mapping approach, we identified 23,961 SNPs fixed for the DP61 allele across all RILs from an initial set of 1,092,427 parental polymorphisms. A major peak resulting from the selection was detected on chromosome D07:1.20-2.45 Mb (433 SNPs). Variant effect annotation identified 17 missense variants across 16 candidate genes within this region. Two candidate genes for involvement in photoperiodism with non-synonymous variants and nearby indels, Gohir.D07G014500, orthologous to ELF8/VIP6 (AT2G06210) and Gohir.D07G013300, orthologous to VIP3/SKI8 (AT4G29830), both encode components of the PAF1 transcriptional elongation complex required for expression of the floral repressor FLOWERING LOCUS C in Arabidopsis. Loss of function mutations in either gene confers early, photoperiod-insensitive flowering in Arabidopsis. A 16.5 kb deletion on Chr. D07 in the MT2468 Ren1 parent may disrupt cis-regulatory elements upstream of these candidate genes. These results identify the PAF1 complex as a priority candidate for the control of day-neutral flowering in upland cotton and warrant further investigation as a potential source of markers for marker-assisted introgression of reduced photoperiod sensitivity.</p>","PeriodicalId":22955,"journal":{"name":"Theoretical and Applied Genetics","volume":"139 9","pages":""},"PeriodicalIF":4.1,"publicationDate":"2026-08-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148841415","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}