- Chinese Core Journal
- Chinese Science Citation Database (CSCD) Source journal
- Journal of Citation Report of Chinese S&T Journals (Core Edition)
| Citation: |
LIN Wei, ZHOU Peng, ZHOU Xiangbin, WU Linying, ZHAO Yanxin, ZHAO Shuai, CHEN Xiaoyang. Geographic variation in seed traits of different Zenia insignis provenances[J]. Journal of South China Agricultural University, 2016, 37(4): 69-74. DOI: 10.7671/j.issn.1001-411X.2016.04.012
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In order to investigate the geographical variation in seed traits among different provenances of Zenia insignis.
The seeds from 21 counties of five provinces were collected, six phenotypic traits of the seed were recorded, and the geographic variation in seed traits was analyzed by ANOVA, correlation and partial correlation analysis, and cluster analysis.
There were highly significant differences in six seed traits including seed length, width, thickness, length/width ratio, width/thickness ratio and 100-seed mass among different provenances. The coefficients of variation of seed traits ranged from 5.76% to 10.16%, among them the highest was seed thickness(10.16%)while the lowest was seed width (5.76%). The repeatabilities of all six traits were above 80%.The repeatability of seed length was the highest(98.1%), followed by seed thickness and seed width (>90%), and the repeatability of seed length/width ratio was the lowest (84.2%). All six seed traits showed negative correlations with latitude, longitude and altitude of seed origin.Seed thickness and 100-seed mass had significant negative correlations with latitude, and seed length/width ratio had significant negative correlation with altitude. All seed traits except seed thickness were highly negatively correlated with the average annual temperature, but positively correlated with the average annual precipitation. The correlations between the average annual sunshine hour and seed traits were not significant.Based on the six seed traits, the 21 provenances of Z.insignis were clustered into five groups.
The 21 provenances of Z.insignis can be clustered into five groups with clear geographic and regional characteristics.
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