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Effects of morphological traits on body mass of Phoxinus lagowskii Dybowskii.

ZHANG Yong-quan1, BAI Qing-li1, GUO Wen-xue1, FENG Cheng-cheng1,2, YIN Jia-sheng1**   

  1. (1Heilongjiang River Fisheries Research Institute, Chinese Academy of Fishery Sciences, Harbin 150070, China; 2College of Fisheries and Life Science, Shanghai Ocean University, Shanghai 201306, China)
  • Online:2013-11-10 Published:2013-11-10

Abstract: By using correlation analysis, path analysis, and multiple linear regression method, this paper studied the effects of the morphological traits of 1 and 2 years old Phoxinus lagowskii Dybowski individuals on their body mass, aimed to provide reference for selecting the indicators of P. lagowskii growth. For the 1 year old P. lagowskii individuals, the correlation coefficients of body mass with total length, body length, body height, and caudal peduncle depth were 0.953, 0.958, 0.951, and 0.948, respectively (P<0.01), and the path coefficients also reached very significant level (P<0.01). The strongest determinant on body mass was body length, followed by total length, body height, and caudal peduncle depth. The high correlation index of the four morphological traits and the body mass (0.954) suggested that the selected traits were the main morphological traits affecting the body mass. The related multiple regression equation was Y =-12.375+2.255X2+4.683X3+4.722X8-1.162X1, where Y is body weight, and the X1, X2, X3 and X8 are total length, body length, body height, and caudal peduncle depth, respectively. For the 2 years old P. lagowskii individuals, total length and caudal peduncle depth were the independent variables that significantly affected body mass, with the correlation coefficient being 0.939 and 0.846, respectively (P<0.01). The path coefficients also reached very significant level (P<0.01). The strongest determinant on body mass was body length, followed by body height. Judged from the high correlation index (0.912), these two morphological traits affected the body mass significantly. The related multiple regression equation was Y= -188.444+11.416X2+16.304X3.

Key words: introduction and acclimatization, bioactive compound, antioxidant capacity, volatile constituent., Rhodiola kirilowii