浙江农业学报 ›› 2020, Vol. 32 ›› Issue (4): 653-660.DOI: 10.3969/j.issn.1004-1524.2020.04.12

• 园艺科学 • 上一篇    下一篇

苏南地区29个秋冬茬芹菜品种资源评价

沈迪1, 陈龙正2, 路晓华3, 陶建平4, 冯顾城3, 刘洁霞1, 冯凯1, 尹莲1, 丁旭1, 贾丽丽1, 徐志胜1, 刘惠吉1, 熊爱生1,*   

  1. 1.南京农业大学 园艺学院,作物遗传与种质创新国家重点实验室,农业农村部华东地区园艺作物生物学与种质创制重点实验室,江苏 南京 210095;
    2.江苏省农业科学院 蔬菜研究所,江苏 南京 210014;
    3.南京市溧水区华成蔬菜专业合作社,江苏 南京 211216;
    4.江苏省农业科学院 农业设施与装备研究所,江苏 南京 210014
  • 收稿日期:2019-11-25 出版日期:2020-04-25 发布日期:2020-04-26
  • 通讯作者: *熊爱生,E-mail: xiongaisheng@njau.edu.cn
  • 作者简介:沈迪(1995—),女,山西太原人,硕士研究生,主要从事芹菜遗传育种研究。E-mail: 2018804224@njau.edu.cn
  • 基金资助:
    江苏省农业科技自主创新资金[CX(18)2007]; 国家自然科学基金(31272175); 教育部新世纪优秀人才支持计划(NCET-11-0670); 江苏高校优势学科建设项目(PAPD)

Resources evaluation of 29 celery varieties for autumn-winter cultivation in southern Jiangsu

SHEN Di1, CHEN Longzheng2, LU Xiaohua3, TAO Jianping4, FENG Gucheng3, LIU Jiexia1, FENG Kai1, YIN Lian1, DING Xu1, JIA Lili1, XU Zhisheng1, LIU Huiji1, XIONG Aisheng1,*   

  1. 1. State Key Laboratory of Crop Genetics and Germplasm Enhancement, Ministry of Agriculture and Rural Affairs, Key Laboratory of Biology and Germplasm Enhancement of Horticultural Crops in East China, College of Horticulture, Nanjing Agricultural University, Nanjing 210095, China;
    2. Institute of Vegetable, Jiangsu Academy of Agricultural Sciences, Nanjing 210014, China;
    3. Huacheng Vegetable Professional Cooperative of Lishui District, Nanjing 211216, China;
    4. Institute of Agricultural Facilities and Equipment, Jiangsu Academy of Agricultural Sciences, Nanjing 210014, China
  • Received:2019-11-25 Online:2020-04-25 Published:2020-04-26

摘要: 为对芹菜品种资源进行评价,选取2018年秋季种植于南京市溧水区的29个芹菜品种,对其10个主要农艺性状进行差异性、相关性、主成分和聚类分析。结果表明:芹菜10个主要农艺性状的变异系数为9.11%~39.74%,其中产量变异系数最大,为39.74%;各性状间存在着不同程度的关联,产量与单株质量、株高、叶柄宽、叶柄厚存在极显著正相关;主成分分析显示,有3个成分因子的特征值累计贡献率达到85.586%,分别为株型与产量相关因子、叶片与叶柄数量相关因子和叶片与叶柄形态相关因子,这3个因子基本上覆盖了芹菜农艺性状的总体数据信息。聚类分析将29个芹菜品种在欧式距离为10处分成4组:Ⅰ组包含16个品种,该类芹菜植株较矮小,单株质量中等,叶片叶柄颜色有较大差异,叶柄多为实心;Ⅱ组有2个品种,该类芹菜株型高大粗壮,单株质量大,实心,纤维少,产量高;Ⅲ组有6个品种,该类芹菜植株低矮粗壮,单株质量较大,叶片较圆,产量较低;Ⅳ组包含5个品种,该类芹菜植株矮小,叶片数多,产量低。该结果可为苏南地区芹菜生产,以及芹菜种质资源的收集与鉴定提供参考。

关键词: 芹菜, 苏南地区, 农艺性状, 相关性分析, 主成分分析, 系统聚类分析

Abstract: In order to evaluate the resources of celery varieties, 29 celery varieties were selected and planted in Lishui District of Nanjing City in the autumn of 2018. Then, differences, correlations, principal components and cluster of 10 main agronomic traits were analyzed. The results showed that the variation coefficient of 10 main agronomic traits ranged from 9.11% to 39.74%. The highest coefficient of variation emerged in yield, which was 39.74%. There were different degrees of correlation among the agronomic traits. The yield exhibited a significant positive correlation with individual plant quality, plant height, petiole width and petiole thickness. Principal component analysis indicated that the cumulative contribution rate of eigenvalues of the first three factors reached 85.586%. These three factors, including plant type and yield factors, leaf and petiole number-related factors, as well as leaf and petiole morphology-related factors, summarized the information of original indicators in general. The 29 celery varieties were divided into 4 categories at the location of 10 Euclidean distances through cluster analysis. Among them, 16 varieties belonged to class I, their characteristic were as follow: plants were relatively short, quality of each plant was medium, leaves and leaf petiole color were different, and petiole was mostly solid. Two varieties belonged to class II, they showed a tall and strong type with heavy weight per plant, petiole solid, less fiber, high yield. The six varieties of celery belonged to class III, they were lower and stronger, and had the heavier weight per plant and round leaves, lower yield. Type IV contained five celery varieties, this type had short plants, many leaves, and low yield. The results of this paper would provide potential useful reference information for the production of celery in southern Jiangsu, and the collection and identification of celery germplasm resources.

Key words: celery, southern Jiangsu, agronomic traits, correlation analysis, principal component analysis, systematic cluster analysis

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