马铃薯（Solanum tuberosum L）生长、产量及其组成因素的遗传参数、表型多样性、选择差异和增益分析（EFA、HCA及多变量分析）

IF 1 Q4 GENETICS & HEREDITY

Gene Reports Pub Date : 2025-04-17 DOI:10.1016/j.genrep.2025.102225

K. Hanume Gowda , H. Amarananjundeswara , B. Fakrudin , K.R. Vasudeva , Jyoti Kattegoudar , B. Doddabasappa

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引用次数: 0

摘要

马铃薯是全球重要的粮食作物和重要的营养来源，由于其高生产力、营养价值和对多种农业气候条件的适应性，在粮食安全中发挥着至关重要的作用。本研究于2021 - 2022年哈桑园艺研究与推广中心进行，旨在利用Pearson相关分析、层次聚类分析（HCA）、主成分分析（PCA）、探索因子分析（EFA）和多性状基因型理想型距离指数（MGIDI）分析，研究遗传参数、表型多样性、选择差异和增益，以鉴定马铃薯高产优势基因型，促进马铃薯生长。产量和产量成分。综合方差分析显示了显著的基因型、环境和G × E相互作用，具有稳定的生长、产量性状和对块茎大小和重量的基因型特异性反应。单株块茎产量与块茎大小（r = 0.52）、块茎直径（r = 0.44）和株高（r = 0.50）呈显著正相关。分层聚类鉴定出2个主要聚类，聚类1基因型表现出较高的生长和产量性状。PCA显示了6个分量，解释了81.05%的方差，其中PC1与每公顷块茎产量（0.34）、每块块茎产量（0.34）、每株块茎数（0.33）和每株块茎产量（0.33）相关，PC2与种植后75天叶片数（DAP）（0.52）、节间数（0.49）和每株分枝数（75 DAP）相关，PCA双图将基因型分为4个象限。在生长和产量性状方面，在象限II表现优异，在象限IV表现较差。因子分析确定了影响马铃薯生长、产量和产量构成的6个因素。FA1主要与产量性状有关，如每公顷块茎产量（- 0.94）、每块块茎数量（- 0.87）、每块块茎产量（- 0.94）和以鲜重为基础的块茎产量（- 0.80）。FA2与营养生长有关，捕获75 DAP时枝数（0.79）、75 DAP时叶数（0.69）和节间数（0.87）。单株块茎数（31.7%）、单株块茎数（24.1%）、单株块茎产量（23.8%）均有较高的选择增益，强调育种潜力。MGIDI分析发现，基因型P-85、P-73、RH-2、P-69、P-83和P-58在多个性状上都具有优势。本研究通过遗传参数分析、主成分分析、HCA分析、EFA分析、选择差异分析和MGIDI分析等方法，成功鉴定出具有高产潜力和生长稳定性状的马铃薯优良基因型，为马铃薯定向育种提高产量和适应性提供了有价值的见解。

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Genetic parameters, phenotypic diversity, selection differential and gain analysis through EFA, HCA and multivariate analysis for growth, yield and yield components in potato (Solanum tuberosum L)

Potato is a globally significant food crop and a vital source of nutrition, plays a crucial role in food security due to its high productivity, nutritional value and adaptability to diverse agro-climatic conditions. This study was conducted at Horticulture Research and Extension Centre, Haasan during kharif and rabi season of 2021–22, aimed to investigates genetic parameters, phenotypic diversity, selection differential and gain to identify high yielding superior potato genotypes using Pearson's correlation analysis, hierarchical cluster analysis (HCA), principal component analysis (PCA), exploratory factor analysis (EFA) and multi-trait genotype ideotype distance index (MGIDI) analysis to enhance growth, yield and yield components. The pooled ANOVA revealed significant genotypic, environmental and G × E interactions, with stable growth, yield traits and genotype-specific responses for tuber size and weight. Significant positive correlations were found between tuber yield per plant and traits like tuber size (r = 0.52), tuber diameter (r = 0.44) and plant height (r = 0.50). Hierarchical clustering identified 2 major clusters, with Cluster 1 genotypes showing high performance for growth and yield traits. PCA revealed 6 components explaining 81.05 % of variance, with PC1 associated with tuber yield per hectare (0.34), tuber yield per plot (0.34), number of tubers per plant (0.33), and tuber yield per plant (0.33) and PC2 on number of leaves at 75 days after planting (DAP) (0.52), number of internodes (0.49) and number of branches per plant at 75 DAP (0.43), while the PCA biplot grouped genotypes into 4 quadrants, highlighting superior performance in Quadrant II and lower performance in Quadrant IV for growth and yield traits. The factor analysis identified 6 factors influencing growth, yield, and yield components in potatoes. FA1 primarily relates to yield traits, such as tuber yield per hectare (−0.94), number of tubers per plot (−0.87), tuber yield per plot (−0.94), and haulm yield on a fresh weight basis (−0.80). FA2 is associated with vegetative growth, capturing the number of branches at 75 DAP (0.79), number of leaves at 75 DAP (0.69), and number of internodes (0.87). High selection gain was reported for number of tubers per plant (31.7 %), number of tubers per plant (24.1 %), tuber yield per plant (23.8 %) emphasizing breeding potential. The MGIDI analysis identified genotypes P-85, P-73, RH-2, P-69, P-83, and P-58 as superior for multiple traits. This study successfully identified superior potato genotypes with high yield potential and stable growth traits through genetic parameter analysis, PCA, HCA, EFA, selection differential, and MGIDI, offering valuable insights for targeted breeding to enhance productivity and adaptability.

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来源期刊

Gene Reports Biochemistry, Genetics and Molecular Biology-Genetics

CiteScore

3.30

自引率

7.70%

发文量

246

审稿时长

49 days

期刊介绍： Gene Reports publishes papers that focus on the regulation, expression, function and evolution of genes in all biological contexts, including all prokaryotic and eukaryotic organisms, as well as viruses. Gene Reports strives to be a very diverse journal and topics in all fields will be considered for publication. Although not limited to the following, some general topics include: DNA Organization, Replication & Evolution -Focus on genomic DNA (chromosomal organization, comparative genomics, DNA replication, DNA repair, mobile DNA, mitochondrial DNA, chloroplast DNA). Expression & Function - Focus on functional RNAs (microRNAs, tRNAs, rRNAs, mRNA splicing, alternative polyadenylation) Regulation - Focus on processes that mediate gene-read out (epigenetics, chromatin, histone code, transcription, translation, protein degradation). Cell Signaling - Focus on mechanisms that control information flow into the nucleus to control gene expression (kinase and phosphatase pathways controlled by extra-cellular ligands, Wnt, Notch, TGFbeta/BMPs, FGFs, IGFs etc.) Profiling of gene expression and genetic variation - Focus on high throughput approaches (e.g., DeepSeq, ChIP-Seq, Affymetrix microarrays, proteomics) that define gene regulatory circuitry, molecular pathways and protein/protein networks. Genetics - Focus on development in model organisms (e.g., mouse, frog, fruit fly, worm), human genetic variation, population genetics, as well as agricultural and veterinary genetics. Molecular Pathology & Regenerative Medicine - Focus on the deregulation of molecular processes in human diseases and mechanisms supporting regeneration of tissues through pluripotent or multipotent stem cells.