Crops ›› 2022, Vol. 38 ›› Issue (5): 146-152.doi: 10.16035/j.issn.1001-7283.2022.05.021

Previous Articles     Next Articles

Analysis of Physiological and Biochemical Mechanism and Growth and Development Characteristics of Saline and Alkali Resistance in Sunflower

Jia Xiuping1(), Mao Xuhui1, Liang Gensheng1, Liu Runping2, Liu Feng2, Wang Xingzhen1   

  1. 1Institute of Crop, Gansu Academy of Agriculture Sciences, Lanzhou 730070, Gansu, China
    2Institute of Agricultural Economics and Information, Gansu Academy of Agricultural Sciences, Lanzhou 730070, Gansu, China
  • Received:2021-05-18 Revised:2021-08-16 Online:2022-10-15 Published:2022-10-19

Abstract:

A total of 135 strains of the F2 population, produced by crossing of Y05-222A and Y06-136R, were used as materials to assess the levels of proline (Pro), soluble protein, malondialdehyde (MDA) as well as the activities of peroxidase (POD), superoxide dismutase (SOD) and catalase (CAT), and variance, correlation, and path analyses were performed. The F2 populationʼs skewness and kurtosis were also examined. The outcomes demonstrated that the frequencies followed a normal distribution and the six physiological indexes of the F2 population were P > 0.05. It simultaneously demonstrated the separation of the bidirectional superaffinity. The six physiological indexes had highly correlations with salinity and alkali resistance coefficients, according to correlation and path analysis. The direction of the total indirect path coefficient and correlation was identical. The direct path coefficient of POD activity was 0.5003, which indicated it directly affected saline and alkali resistance. The direct path coefficients of CAT activity and Pro content were -0.1317 and -0.0384, respectively, which indicated it indirectly affected saline and alkali resistance, and SOD, MDA and soluble protein directly or indirectly affected salinity resistance. The Anti-saline effects of POD, SOD, Pro, CAT, soluble protein, MDA showed POD > CAT > Pro > soluble protein > MDA > SOD. Number of leaves, plant height, stem diameter and disk diameter had significant positive correlation with the salinity and alkali resistance coefficient. And the correlation showed number of leaves > disk diameter > plant height > stem diameter. The results provide theoretical basis for salinity salt and alkali resistance of oil sunflower.

Key words: Oil sunflower, F2 populations, Correlation analysis, Path analysis

Table 1

Performance and analysis of specificity of physiological indicators in the F2 population and its parents"

指标
Index
亲本Parents F2群体F2 population
P1 P2 F检测值
F-value
均值
Mean
变异范围
Range of
variation
偏度数
Skewness
偏度系数P
Skewness P
value
峰度
系数
Kurtosis
峰度系数P
Kurtosis
P value
SOD活性
SOD activity (U/mg)
660.47±10.96 346.58±10.84 868.31** 552.61 100.86~897.25 -0.03 0.90 -0.39 0.35
POD活性
POD activity (U/g)
24.63±1.15 12.27±0.48 295.21** 45.60 4.67~91.67 0.15 0.49 -0.30 0.47
CAT活性
CAT activity (U/g)
12.22±0.98 2.58±0.19 93.69** 32.86 2.39~66.00 0.21 0.30 0.00 0.99
可溶性蛋白含量
Soluble protein content (mg/g)
191.90±6.57 104.63±10.47 149.62** 24.10 9.79~41.67 0.11 0.59 -0.61 0.14
Pro含量
Pro content (µg/g)
146.15±6.61 95.67±4.92 112.63** 219.49 120.79~354.65 0.25 0.21 -0.38 0.36
MDA含量
MDA content (µmol/g)
1.14±0.03 1.51±0.44 157.96** 57.97 16.50~94.49 0.26 0.21 0.02 0.99
抗盐碱系数
Salt-alkali resistance coefficient
0.75±0.07 0.54±0.01 27.80** 0.70 0.22~0.90

Fig.1

Frequency distribution of related indicators for F2 population"

Table 2

Correlation analysis salt-alkali resistance coefficient and related indicators in the F2 population"

指标
Index
SOD活性
SOD
activity
POD活性
POD
activity
CAT活性
CAT
activity
可溶性蛋白含量
Soluble
protein content
Pro含量
Pro
content
MDA含量
MDA
content
抗盐碱性系数
Salt-alkali resistance
coefficient
SOD活性SOD activity 1.0000
POD活性POD activity 0.6577** 1.0000
CAT活性CAT activity 0.6455** 0.6681** 1.0000
可溶性蛋白含量Soluble protein content -0.7061** -0.5194** -0.5262** 1.0000
Pro含量Pro content 0.7935** 0.6493** 0.8013** -0.6383** 1.0000
MDA含量MDA content -0.5347** -0.5967** -0.5123** 0.4699** -0.5563** 1.0000
抗盐碱系数
Salt-alkali resistance coefficient
0.3904** 0.5256** 0.2987** -0.2675** 0.3298** -0.3725** 1.0000

Table 3

Path analysis of salt-alkali resistance coefficient and its indexes of F2 population"

指标
Index
直接通径系数
DPC
间接通径系数IPC 总间接通径系数
TIPC
X1Y X2Y X3Y X4Y X5Y X6Y
X1 0.1676 0.3291 -0.085 -0.0464 -0.0305 0.0556 0.2228
X2 0.5003 0.1102 -0.088 -0.0341 -0.0249 0.0621 0.0253
X3 -0.1317 0.1081 0.3343 -0.0346 -0.0308 0.0533 0.4303
X4 0.0657 -0.1183 -0.2599 0.0693 0.0245 -0.0489 -0.3333
X5 -0.0384 0.1329 0.3249 -0.1055 -0.0420 0.0579 0.3682
X6 -0.1040 -0.0896 -0.2985 0.0674 0.0309 0.0214 -0.2684

Table 4

Analysis of morphological characteristics in parents and F2 population"

性状
Trait
亲本Parents F2群体F2 population
P1 P2 F检测值F detection value 均值Mean 变异范围Range of variation
株高Plant height (cm) 148.30 96.53 68.62** 110.98 36.42~166.18
茎粗Stem diameter (cm) 1.70 1.38 74.93** 1.42 0.54~2.25
叶片数Number of leaves 15.33 12.00 16.20* 8.96 5.00~12.00
盘径Disk diameter (cm) 12.97 10.07 30.66** 8.42 3.20~12.40

Table 5

Correlation analysis of salt-alkali resistance coefficient and morphological characteristics in F2 population"

性状
Trait
株高
Plant height
茎粗
Stem diameter
叶片数
Number of leaves
盘径
Disk diameter
抗盐碱系数
Salt-alkali resistance coefficient
株高Plant height 1.0000
茎粗Stem diameter 0.8361** 1.0000
叶片数Number of leaves 0.9150** 0.7902** 1.0000
盘径Disk diameter 0.9378** 0.8180** 0.9238** 1.0000
抗盐碱系数Salt and alkali resistance coefficient 0.8501** 0.8440** 0.8786** 0.8759** 1.0000
[1] 吴晓东, 王巍, 金路路, 等. 盐胁迫对棉花光合作用和生理指标的影响. 中国棉花, 2013, 40(6):24-26.
[2] Iang Y C, Yang C G, Shi H H. Effects of silicon on growth and mineral composition of barley grown under toxic levels of aluminium. Journal of Plant Nutrition, 2001, 24(2):229-243.
doi: 10.1081/PLN-100001384
[3] 黄秉信. 中国农村统计年鉴. 北京: 中国统计出版社, 2019.
[4] 郭园, 张玉霞, 于华荣, 等. 13个油葵品种苗期生长、生理指标比较及抗盐碱性分析. 东北农业科学, 2016, 41(4):32-36.
[5] 崔云玲, 王生录, 陈炳东, 等. 不同品种油葵对盐胁迫响应研究. 土壤学报, 2011, 48(5):1051-1058.
[6] 张俊莲, 张国斌, 王蒂. 向日葵耐盐性比较及耐盐生理指标选择. 中国油料作物学报, 2006, 28(2):176-179.
[7] 陈炳东, 岳云, 黄高宝, 等. 油葵含油率及脂肪酸组成与土壤盐含量的关系. 中国油料作物学报, 2007, 29(4):483-486.
[8] 陈炳东, 黄高宝, 陈玉梁, 等. 盐胁迫对油葵根系活力和幼苗生长的影响. 中国油料作物学报, 2008, 30(3):327-330.
[9] 刘杰. 向日葵对碱胁迫和盐胁迫适应机制比较. 长春:东北师范大学, 2011.
[10] 裴怀弟, 吴科生, 王红梅, 等. 混合盐胁迫对油葵保护性酶活性、细胞膜透性及其主要农艺性状的影响. 干旱地区农业研究, 2012, 30(1):151-153.
[11] 高猛, 安玉麟, 孙瑞芬, 等. 向日葵rRNA基因克隆及其染色体定位研究. 中国细胞生物学学报, 2014, 36(2):195-199.
[12] 吕品, 于海峰, 于志贤, 等. 向日葵高密度遗传连锁图谱构建及两种水分条件下芽期性状的QTL分析. 作物学报, 2017, 43(1):19-30.
[13] Pandey N, Ranjan A, Pant P, et al. CAMTA 1 regulates drought responses in Arabidopsis thaliana. BMC Genomics,201, 14:216.
doi: 10.1186/1471-2164-14-216
[14] Weng H, Yoo C Y, Gosney M J, et al. Poplar GTL1 is a Ca2+/calmodulin-binding transcription fact or that functions in plant water use efficiency and drought tolerance. PLoS ONE, 2012, 7(3):1-10.
[15] Yoo J H, Park C Y, Kim J C, et al. Direct interaction of a divergent CaM isoform and the transcription factor,MYB2,enhances salt tolerance in Arabidopsis. Biological Chemistry, 2005, 280(5):3697-3706.
[16] 吴运荣, 林宏伟, 莫肖蓉. 植物抗盐分子机制及作物遗传改良耐盐性的研究进展. 植物生理学报, 2014, 50(11):1621-1629.
[17] 陈洁, 林栖凤. 植物耐盐生理及耐盐机理研究进展. 海南大学学报(自然科学版), 2003, 21(2):177-182.
[18] 林晓红, 景岚, 康振生. 向日葵抗锈病基因同源序列的克隆与分析. 中国油料作物学报, 2014, 36(4):508-512.
[19] 焦德志, 赵泽龙. 盐碱胁迫对植物形态和生理生化影响及植物响应的研究进展. 江苏农业科学, 2019, 47(20):1-4.
[20] 张楠楠, 徐香玲. 植物抗盐机理的研究. 哈尔滨师范大学自然科学学报, 2005, 21(1):65-68.
[21] 郝再彬, 苍晶, 徐仲. 植物生理实验. 哈尔滨: 哈尔滨工业大学出版社, 2004.
[22] 刘祖祺, 张石城. 抗性生理学. 北京: 中国农业出版社, 1990:371-372.
[23] 邹琦. 植物生理学实验指导. 北京: 中国农业出版社, 2000:7.
[24] 王学奎. 植物生理生化试验原理和技术:第2版. 北京: 高等教育出版社, 2006.
[25] 齐会楠. CO2诱导库尔勒香梨果心褐变发生机理的研究. 乌鲁木齐:新疆农业大学, 2014.
[26] 焦德志, 赵泽龙. 盐碱胁迫对植物形态和生理生化影响及植物响应的研究进展. 江苏农业科学, 2019, 47(20):1-4.
[27] Zhu S, Rossnagel B G, Kaepple H F. Genetic analysis of quantitative trait loci for groat protein oil content in oat. Crop Science, 2004, 44(1):254-260.
doi: 10.2135/cropsci2004.2540
[1] Shi Guanyan, Wang Juanfei, Ma Huifang, Zhao Xiongwei. Correlation and Regression Analysis between Yield and Main Agronomic Traits in Foxtail Millet Hybrids [J]. Crops, 2022, 38(6): 82-87.
[2] Zhao Bin, Ji Changhao, Sun Hao, Zhu Bin, Wang Rui, Chen Xiaodong. Comprehensive Assessment of the Yield and Quality of Forage and Grain among Multi-Rowed Barley Lines [J]. Crops, 2022, 38(6): 93-97.
[3] Xiao Mingkun, Liu Guanghua, Song Jiming, Liu Qian, Duan Chunfang, Jiang Tailing, Zhang Linhui, Yan Wei, Shen Shaobin, Zhou Yingchun, Xiong Xiankun, Luo Xin, Bai Lina, Li Yuexian. Analysis of Agronomic Characteristics of Different Cassava Varieties (Lines) and Screening of High-Yielding Varieties (Lines) [J]. Crops, 2022, 38(4): 77-82.
[4] Wang Siyu, Zuo Wenbo, Zhu Kaili, Guo Huimin, Xing Bao, Guo Yuqing, Bao Yuying, Yang Xiushi, Ren Guixing. Analysis and Evaluation of Agronomic Characteristics and Nutritional Qualities of 71 Quinoa Accessions [J]. Crops, 2022, 38(3): 63-72.
[5] Zhao Lirong, Ma Ke, Zhang Liguang, Tang Sha, Yuan Xiangyang, Diao Xianmin. Analysis of Agronomic Traits and Quality of Foxtail Millet Varieties in Different Ecological Regions [J]. Crops, 2022, 38(2): 44-53.
[6] Gao Fengyun, Siqin Bateer, Zhou Yu, Jia Xiaoyun, Su Shaofeng, Zhao Xiaoqing, Jin Xiaolei. Association Analysis of Crude Fat and Fatty Acid Components in Flax Based on SSR Markers [J]. Crops, 2022, 38(1): 44-49.
[7] Zhang Qi, Wei Zhenwu, Yan Tianfang. Correlation and Path Analysis of Oat Seed Yield with Agronomic Characters in Jiang-Huai Area [J]. Crops, 2021, 37(5): 146-152.
[8] Liu Wenlong, Ning Shanghui, Cao Mingfeng, Zhu Li, Gao Yuzhen, Zhang Xuewei, Wen Zixiang, Jiang Baodi, Jing Yanqiu, Deng Yong. Correlation Analysis of Soil Micronutrient and Chemical Components of Tobacco Leaves in Taoyuan County [J]. Crops, 2021, 37(5): 176-180.
[9] Zhou Fei, Wang Wenjun, Liu Yan, Ma Jun, Wang Jing, Wu Liren, Guan Hongjiang, Huang Xutang. Establishment of Near-Infrared Spectroscopy Model for the Contents of Fat and Fatty Acids in Sunflower Husked Seeds [J]. Crops, 2021, 37(2): 200-206.
[10] Jin Jiangang, Tian Zaifang. Grey Correlation Analysis of Introduced Tartary Buckwheat in the Northern Shanxi [J]. Crops, 2021, 37(2): 52-56.
[11] Zhou Qilong. Grey Relational Grade Evaluation of 19 Oat Varieties Introduced in Ali of Tibet [J]. Crops, 2021, 37(1): 26-31.
[12] Zhang Xiaoyan, Wang Xiaonan, Cao Kun, Sun Yufeng. Correlation Analysis of Fiber Yield and Yield Components in Five Industrial Hemp Varieties (Lines) [J]. Crops, 2020, 36(4): 121-126.
[13] Wang Zhongqiu, Ying Pengfei, Chen Mengtao, He Qiongying, Hu Xin. Analysis of Grain and Quality Traits of Chromosome Arm Substitution Lines of Triticum dicoccoides in the Background of Triticum aestivum [J]. Crops, 2020, 36(4): 37-44.
[14] Yang Bin, Yan Xue, Wen Hongwei, Wang Shuguang, Lu Lahu, Fan Hua, Jing Ruilian, Sun Daizhen. Study on the Evaluation of Stay-Green Traits of Wheat and Its Correlation with Yield-Related Traits under Different Water Conditions [J]. Crops, 2020, 36(4): 45-52.
[15] Li Jiming,Li Aiguo,Jia Yingquan,Song Congmin,Liu Guihua,Xu Guizhen,Li Heping. Effects of Plant Spacing on Growth and Yield of Oil Sunflower under Mechanized Cultivation Conditions [J]. Crops, 2019, 35(6): 71-75.
Viewed
Full text


Abstract

Cited

  Shared   
  Discussed   
[1] Guangcai Zhao,Xuhong Chang,Demei Wang,Zhiqiang Tao,Yanjie Wang,Yushuang Yang,Yingjie Zhu. General Situation and Development of Wheat Production[J]. Crops, 2018, 34(4): 1 -7 .
[2] Baoquan Quan,Dongmei Bai,Yuexia Tian,Yunyun Xue. Effects of Different Leaf-Peg Ratio on Photosynthesis and Yield of Peanut[J]. Crops, 2018, 34(4): 102 -105 .
[3] Yun Zhao,Cailong Xu,Xu Yang,Suzhen Li,Jing Zhou,Jicun Li,Tianfu Han,Cunxiang Wu. Effects of Sowing Methods on Seedling Stand and Production Profit of Summer Soybean under Wheat-Soybean System[J]. Crops, 2018, 34(4): 114 -120 .
[4] Jie Gao,Qingfeng Li,Qiu Peng,Xiaoyan Jiao,Jinsong Wang. Effects of Different Nutrient Combinations on Plant Production and Nitrogen, Phosphorus and Potassium Utilization Characteristics in Waxy Sorghum[J]. Crops, 2018, 34(4): 138 -142 .
[5] Na Shang,Zhongxu Yang,Qiuzhi Li,Huihui Yin,Shihong Wang,Haitao Li,Tong Li,Han Zhang. Response of Cotton with Vegetative Branches to Plant Density in the Western of Shandong Province[J]. Crops, 2018, 34(4): 143 -148 .
[6] Wenlian Bai,Yi Zheng,Jingxiu Xiao. Below-Ground Biotic Mechanisms of Phosphorus Uptake and Utilization Improved by Cereal and Legume Intercropping-A Review[J]. Crops, 2018, 34(4): 20 -27 .
[7] Menghan Wei, Huifang Xie, Lu Xing, Hui Song, Shujun Wang, Suying Wang, Haiping Liu, Nan Fu, Jinrong Liu. Comprehensive Evaluation of Yield and Agronomic Characters of Foxtail Millet Germplasms from North China[J]. Crops, 2018, 34(4): 42 -47 .
[8] Xiaoyu Liang, Chunyu Lin, Shumei Ma, Yang Wang. Mining Elite Alleles for Germination Ability in Rice (Oryza sativa L.) under Salt and Alkaline Stress[J]. Crops, 2018, 34(4): 48 -52 .
[9] Haibin Luo, Shengli Jiang, Chengmei Huang, Huiqing Cao, Zhinian Deng, Kaichao Wu, Lin Xu, Zhen Lu, Yuanwen Wei. Cloning and Expression of ScHAK10 Gene in Sugarcane[J]. Crops, 2018, 34(4): 53 -61 .
[10] Shaokun Li,Wanxu Zhang,Keru Wang,Wanbing Yu,Yongsheng Chen,Dongsheng Han,Xiaoxia Yang,Chaowei Liu,Guoqiang Zhang,Yizhou Wang,Fenghe Liu,Jianglu Chen,Jingjing Yang,Ruizhi Xie,Peng Hou,Bo Ming. The Selection of High Yield Maize Cultivars Suitable for Dense Planting and Grain Mechanical Harvesting in North of Xinjiang[J]. Crops, 2018, 34(4): 62 -68 .