中国稻米

中国稻米 ›› 2021, Vol. 27 ›› Issue (2): 51-54.DOI: 10.3969/j.issn.1006-8082.2021.02.010

• 专论与研究 • 上一篇    下一篇

水稻赖氨酸含量测定方法改进及其最优动态分类研究

陈庭木(), 李景芳, 邢运高, 徐波, 王宝祥, 徐大勇*()   

  1. 江苏省连云港市农业科学院/江苏省现代作物生产协同创新中心,江苏 连云港 222006
  • 收稿日期:2020-12-09 出版日期:2021-03-20 发布日期:2021-03-20
  • 通讯作者: 徐大勇
  • 作者简介:

    第一作者：chentingmu@139.com

  • 基金资助:
    现代农业技术体系建设专项;江苏省科技计划重点项目“清香软粳的水稻基因发掘、育种材料创制及其方法”（BE2017323）;国家七大育种专项“长江中下游优质高产高效粳稻新品种培育”（2017YFD0100400）;江苏省政策引导类计划（苏北科技专项）（LYG-SZ201930）;江苏省科技支撑项目（重点研发）“适宜轻简栽培抗病优质水稻新品种选育”（BE2018337）

Improvement of Lysine Content Determination Method and its Optimal Dynamic Classification in Rice

Tingmu CHEN(), Jingfang LI, Yungao XING, Bo XU, Baoxiang WANG, Dayong XU*()   

  1. Lianyungang Academy of Agricultural Sciences / Jiangsu Collaborative Innovation Centre for Modern Crop Production, Lianyungang, Jiangsu 222006, China
  • Received:2020-12-09 Online:2021-03-20 Published:2021-03-20
  • Contact: Dayong XU
  • About author:

    1st author: chentingmu@139.com

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摘要：

赖氨酸是水稻营养成分中第一限制性氨基酸。为优化赖氨酸的测定方法,设置了本试验,通过超声振荡器取代普通振荡器,进行300W超声功率下酰化用时及染料结合反应用时的研究。结果表明,最佳酰化用时为15 min,染料结合用时为90 min。与国标法相比,优化后的方法酰化用时变长、染料结合用时变短,测定总用时明显缩短,但测定结果和试验精度更高。可见,采用超声波振荡代替传统振荡器振荡能改进赖氨酸的测定方法。另外,采用最优动态聚类法对赖氨酸含量进行分类,能防止人为分类的不确定性,做到分类方案的最优化。

关键词: 赖氨酸含量, 测定方法, 动态聚类, 轮回选择算法

Abstract:

Lysine is the first limiting amino acid in rice nutrition. In order to optimize the determination method of lysine content, this experiment was set up, the acylation time and dye binding reaction time under 300W ultrasonic power were studied by using ultrasonic oscillator instead of common oscillator. The results showed that, when the optimal acylation time was 15 min, and the dye combination time was 90 min has the best effect. Compared with the national standard method, the improved method has a longer acylation time and a shorter dye combination time, and the total determination time is significantly shortened, but the determination results and test accuracy are higher. Using ultrasonic oscillation instead of traditional oscillator oscillation could optimize the determination method of lysine content. In addition, the optimal dynamic clustering method could prevent the uncertainty of artificial classification and optimize the classification scheme.

Key words: lysine content, determination method, dynamic clustering, recurrent selection algorithm

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