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Smart Agriculture ›› 2021, Vol. 3 ›› Issue (1): 16-28.doi: 10.12133/j.smartag.2021.3.1.202103-SA004

• 专题--作物表型前沿技术与应用 • 上一篇    下一篇

基于Micro-CT的玉米籽粒显微表型特征研究

赵欢1,2,3(), 王璟璐1,2, 廖生进1,2, 张颖1,2, 卢宪菊1,2, 郭新宇1,2, 赵春江1,2()   

  1. 1.北京农业信息技术研究中心,北京 100097
    2.国家农业信息化工程技术研究中心/数字植物北京市重点实验室,北京 100097
    3.华中农业大学 植物科学技术学院,湖北 武汉 430070
  • 收稿日期:2021-03-11 修回日期:2021-03-26 出版日期:2021-03-30
  • 基金资助:
    北京市农林科学院作物表型协同创新中心项目(KJCX201917);国家现代农业产业技术体系专项资金(CARS-02);北京市农林科学院创新能力建设专项(KJCX20180423);北京市农林科学院改革与发展项目
  • 作者简介:赵 欢(1997-),女,硕士研究生,研究方向为作物表型组学。E-mail:3321621249@qq.com
  • 通信作者:

Study on the Micro-Phenotype of Different Types of Maize Kernels Based on Micro-CT

ZHAO Huan1,2,3(), WANG Jinglu1,2, LIAO Shengjin1,2, ZHANG Ying1,2, LU Xianju1,2, GUO Xinyu1,2, ZHAO Chunjiang1,2()   

  1. 1.Beijing Research Center for Information Technology, Beijing 100097, China
    2.National Engineering Research Center for Information Technology in Agriculture/Beijing Key Lab of Digital Plant, Beijing 100097, China
    3.College of Plant Science & Technology of Huazhong Agricultural University, Wuhan 430070, China
  • Received:2021-03-11 Revised:2021-03-26 Online:2021-03-30

摘要:

植物显微表型主要是指植物组织、细胞和亚细胞水平的表型信息,是植物表型组学研究的重要组成部分。针对传统籽粒显微性状检测方法效率低、误差大且指标单一等问题,本研究利用Micro-CT扫描技术对5种类型11个品种玉米籽粒开展显微表型精准鉴定研究。基于对CT序列图像的处理解析,共获取籽粒、胚、胚乳、空腔、皮下空腔、胚乳空腔和胚空腔的34项显微表型指标。其中,胚乳空腔表面积、籽粒体积、胚乳体积比和胚乳空腔比表面积等4项表型指标在不同类型玉米间差异显著(P-value<0.05)。普通玉米胚乳空腔表面积和籽粒体积显著大于其它类型玉米,高油玉米胚乳空腔比表面积最大,甜玉米胚乳空腔比表面积最小,爆裂玉米胚乳体积比最大。进一步利用34项玉米籽粒表型指标开展差异分析和聚类分析,可将11个不同品种玉米分为四类,其中第一类以普通玉米为主,第二类以爆裂玉米为主,第三类是甜玉米,第四类是高油玉米。结果表明,Micro-CT扫描技术不仅可以实现玉米籽粒显微表型的精准鉴定,还可以为玉米籽粒分类、品种检测等提供技术支撑。

关键词: 植物表型组学, 显微表型, Micro-CT, 玉米籽粒, 表型鉴定

Abstract:

Plant micro-phenotype mainly refers to the phenotypic information at the tissue, cell, and subcellular levels, which is an important part of plant phenomics research. In view of the problems of low efficiency, large error, and few traits of traditional methods for detecting kernel microscopic traits, Micro-CT scanning technology was used to carry out precise identification of micro-phenotype on 11 varieties of maize kernels. A total of 34 microscopic traits were obtained based on CT sequence images of 7 tissues, including seed, embryo, endosperm, cavity, subcutaneous cavity, endosperm cavity and embryo cavity. Among the 34 microscopic traits, 4 traits, including endosperm cavity surface area, kernel volume, endosperm volume ratio and endosperm cavity specific surface area, were significantly different among maize types (P-value<0.05). The surface area of endosperm cavity and kernel volume of common maize were significantly higher than those of other types of maize. The specific surface area of endosperm cavity of high oil maize was the largest. The endosperm cavity of sweet corn had the smallest specific surface area. The endosperm volume ration of popcorn was the largest. Furthermore, 34 traits were used for One-way ANOVA and cluster analysis, and 11 different maize varieties were divided into four categories, of which the first category was mainly common maize, the second category was mainly popcorn, the third category was sweet corn, and the fourth category was high oil maize. The results indicated that Micro-CT scanning technology could not only achieve precise identification of micro-phenotype of maize kernels, but also provide supports for kernel classification and variety detection, and so on.

Key words: plant phenomics, micro-phenotype, Micro-CT, maize kernel, phenotype identification

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