Scientia Agricultura Sinica ›› 2022, Vol. 55 ›› Issue (11): 2109-2120.doi: 10.3864/j.issn.0578-1752.2022.11.003

• CROP GENETICS & BREEDING·GERMPLASM RESOURCES·MOLECULAR GENETICS • Previous Articles     Next Articles

Establishment of High Efficient Extraction and Detection Technology of Sesamin and Screening of High Sesamin Germplasm

ZHONG YanPing1,2(),SHI LiSong1,ZHOU Rong1,GAO Yuan1,HE YanQing1,FANG Sheng2,ZHANG XiuRong1,WANG LinHai1,WU ZiMing2(),ZHANG YanXin1()   

  1. 1Oil Crops Research Institute, Chinese Academy of Agricultural Sciences/Key Laboratory of Biology and Genetic Improvement of Oil Crops, Ministry of Agriculture and Rural Affairs, Wuhan 430062
    2Key Laboratory of Crop Physiology, Ecology and Genetics Breeding, Ministry of Education, Jiangxi Agricultural University, Nanchang 330045
  • Received:2022-01-20 Accepted:2022-03-14 Online:2022-06-01 Published:2022-06-16
  • Contact: ZiMing WU,YanXin ZHANG E-mail:yanpzhu1996@163.com;wuzmjxau@163.com;zhangyanxin@caas.cn

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Abstract:

【Objective】 Establish an efficient extraction and detection technology for sesamin content evaluation in sesame seeds, then apply it to examine sesamin content variation and identify high-sesamin content materials in sesame germplasm, which will lay the foundation for advancing basic research and breeding of sesame with high sesamin content. 【Method】 Using sesame seeds as raw materials, the single factor tests, including diameters of steel balls, crushing time, crushing amplitude, and seeds weight, were investigated. The seeds were extracted with 80% ethanol via ultrasonic mechanical crushing and cavitation, and the sesamin content was determined by High Performance Liquid Chromatography (HPLC). Based on the Box-Behnken center combined test design principle, we carried out the response surface test with four factors and three levels and established the quadratic polynomial regression equation model with sesamin content as response value. We drew the response surface diagram and contour diagram and determined the main factors affecting sesamin content and the interaction between factors. Finally, the optimal extraction conditions of sesamin were determined, and 1 151 local resources and innovative germplasm were analyzed. The accessions with high sesamin content≥9 g·kg-1 were selected and identified at the Oil and Product Quality Supervision and Testing Center of the Ministry of Agriculture and Rural Affairs. 【Result】 The regression model established in this experiment was extremely significant (P<0.05), and the lack of fit was insignificant (P=0.1768). The model had a good fitting degree and could be used to predict sesamin content. The influence of the four factors on sesamin content was as follows: crusher amplitude>diameters of steel balls>crushing time>seeds weight. The interaction between the crusher amplitude and diameters of steel balls was significant, while that between crusher amplitude and crushing time was close to the significance level. The optimal conditions for ultrasonic-assisted extraction of sesamin were as follows: steel ball diameter of 6.5 mm, crushing time of 225 s, crushing amplitude of 1 335 r/min, and seeds weight of 0.20 g. Under these conditions, the sesamin content detected was 4.601 g·kg-1, which was consistent with the predicted value of 4.633 g·kg-1. Fifteen varieties with specific high sesamin content were identified from 1 151 sesame germplasm for breeding purposes. The highest content was 14.36 g·kg-1, and the average content was 12.35 g·kg-1.【Conclusion】 An efficient extraction technology of sesamin was established,compared with the traditional method, the method only needed 0.2 g seeds, which improved the extraction efficiency and reduced sample consumption, the operation was simple, and the sesamin content in sesame seeds could be accurately detected.

Key words: sesamin, high efficient, extraction process, response surface analysis methodology, screening germplasm

Fig. 1

Working curve of sesamin standard solution"

Fig. 2

HPLC peak surface of standard solution (A) and sample (B)"

Fig. 3

The effects of different diameters of steel ball on sesamin content"

Fig. 4

The effects of different crusher time on sesamin content"

Fig. 5

The effects of different crushing amplitudes on sesamin content"

Fig. 6

The effects of different seeds weight on sesamin content"

Table 1

The factors and levels of response surface test"

水平/因子
Level/Factor		 钢珠直径
Diameter of steel ball (mm)		 粉碎时间
Crusher time (min)		 捣碎振幅
Crusher amplitude (r/min)		 种子量
Seeds weight (g)
-1 5 180 1100 0.17
0 6 210 1300 0.20
1 7 240 1500 0.23

Table 2

The results of response surface experimental design"

试验号
Test number		 钢珠直径
Diameter of steel ball (mm)		 粉碎时间
Crusher time (min)		 捣碎振幅
Crusher amplitude (r/min)		 种子量
Seeds weight (g)		 芝麻素含量
Sesamin content (g∙kg-1)
1 0 1 0 -1 4.431
2 0 0 -1 -1 4.142
3 0 0 -1 1 3.991
4 1 -1 0 0 4.264
5 0 0 0 0 4.488
6 1 0 0 1 4.182
7 -1 -1 0 0 4.005
8 0 1 1 0 4.332
9 1 1 0 0 4.545
10 1 0 -1 0 4.218
11 -1 0 0 1 4.019
12 0 -1 -1 0 3.902
13 -1 0 0 -1 4.170
14 1 0 1 0 4.370
15 0 0 0 0 4.584
16 -1 0 1 0 4.351
17 1 0 0 -1 4.535
18 0 -1 0 -1 4.197
19 0 -1 0 1 4.083
20 0 0 0 0 4.576
21 0 1 0 1 4.229
22 0 0 1 -1 4.457
23 0 1 -1 0 4.220
24 0 0 1 1 4.253
25 0 0 0 0 4.496
26 -1 0 -1 0 3.532
27 0 -1 1 0 4.277
28 -1 1 0 0 4.167
29 0 0 0 0 4.550

Table 3

Analysis of variance table of regression model"

方差来源
Sources of variance		 平方和
Sum of squares		 自由度
df		 均方
Mean square		 F值
F value		 P值
P value		 显著性
Significance
模型Model 1.52 14 0.11 24.67 <0.0001 **
A 0.29 1 0.29 66.40 <0.0001 **
B 0.12 1 0.12 27.16 0.0001 **
C 0.35 1 0.35 78.63 <0.0001 **
D 0.12 1 0.12 26.22 0.0002 **
AB 3.540×10-3 1 3.540×10-3 0.81 0.3843
AC 0.11 1 0.11 25.34 0.0002 **
AD 0.010 1 0.010 2.32 0.1496
BC 0.017 1 0.017 3.94 0.0671
BD 1.936×10-3 1 1.936×10-3 0.44 0.5174
CD 7.023×10-4 1 7.023×10-4 0.16 0.6952
A2 0.20 1 0.20 46.65 <0.0001 **
B2 0.13 1 0.13 29.34 <0.0001 **
C2 0.30 1 0.30 69.45 <0.0001 **
D2 0.12 1 0.12 27.45 0.0001 **
残差Residual 0.061 14 4.389×10-3
失拟误差 Lack of fit 0.053 10 5.348×10-3 2.69 0.1768
纯误差 Pure error 7.965×10-3 4 1.991×10-3
总和 Correlation total 1.58 28
R2=0.9610 R2adj=0.9221 CV=1.55%

Fig. 7

The response surface diagram of the influence of various factors interaction on sesamin content"

Fig. 8

Comparison analysis of sesamin content by national standard method and improved method"

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