叶尔羌高原鳅形态性状与体重的通径分析及曲线拟合
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李艳慧(1988–),女,讲师,研究方向为渔业资源保护与利用.E-mail:15569353668@163.com

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S917

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国家自然科学基金项目(31360635); 华中农业大学–塔里木大学联合基金项目(HNLH202006); 新疆生产建设兵团塔里木盆地生物资源保护利用重点实验室–省部共建国家重点实验室培育基地开放基金课题项目(BRYB1801); 塔里木大学校长基金项目(TDZKQN201801).


Path analysis and growth curve fitting of morphological traits and body weight of Triplophysa yarkandensi
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    摘要:

    本研究基于叶尔羌高原鳅(Triplophysa yarkandensis)体重(Y)及形态变量(X1~X9) 10 个性状, 运用相关性分析、 回归分析、通径分析等开展各形态性状与体重间的相关性及各形态性状间的相关性研究, 量化计算各形态性状对体重的影响, 确定影响其体重的主要形态性状, 进一步确定了 3 个主要形态性状与体重的最佳拟合模型。研究发现, 叶尔羌高原鳅各形态性状与体重之间呈极显著正相关(P<0.01), 与体重(Y)相关性最大的是体长(X2), 相关系数为 0.960; 尾柄长(X5)、眼径(X7)与眼间距(X8)之间无显著相关性(P>0.05), 其他形态性状之间均呈显著正相关(P<0.05)。 通径分析量化形态性状对体重(Y)的作用, 直接影响最大的是头长(X4)(0.470), 体长(X2)通过头长(X4)对体重的间接作用最大(0.447); 通过回归分析并计算决定系数发现, 头长(X4)对体重的直接决定系数最大(0.221), 体长(X2)和头长(X4)的共同决定系数最大(0.341)。3 个形态性状与体重的多元回归方程为 Y=–2.8+2.94X2+0.764X4+0.906X5 (R2 =0.958)。 3 个主要形态性状与体重的最佳拟合模型: 体长(X2)与体重(Y)的最佳拟合模型为指数函数方程 Y=2.739e0.158X2 (R2 =0.936); 头长(X4)与体重的最佳拟合模型为幂函数方程 Y=4.946X4 1.100 (R2 =0.931); 尾柄长(X5)与体重的最佳拟合模型为对数函数方程 Y=9.582+8.876lnX5 (R2 =0.807)。研究结果表明, 叶尔羌高原鳅在选育时, 应以体长(X2)和头长(X4)为主要选择性状, 同时辅以尾柄长(X5)。

    Abstract:

    Triplophysa yarkandensi is an indigenous fish in the Tarim River in Xinjiang Province. To accumulate theoretical breeding data for T. yarkandensi, the effects of morphological traits on body weight were explored. Body weight (Y) and nine morphological traits were measured, including the total length (X1), body length (X2), body height (X3), head length (X4), tail stalk length (X5), snout length (X6), eye length (X7), interorbital space (X8), and slit width (X9). Correlation analysis, path analysis, and regression analysis were used to determine the three main morphological traits that affect body weight (Y). The best-fitting model for the three main morphological characters and body weight was determined by curve fitting. Overall, there was a significant positive correlation between body weight and morphological traits (P<0.01); the length of the tail stalk, eye diameter, and eye distance were not related to each other (P>0.05). There were multiple collinear relationships between other traits and body weight; head length had the most direct effect on body weight (0.470), and body length had the most indirect effect on body weight (0.447), although head length and body length were the main variables that affected body weight. Head length was the largest direct determinant of body weight (0.221), and the largest co-determination coefficient of body length and head length was 0.341. The sum of the determinants of body weight (Y) for the three morphological traits was 0.958, which explained 95.8% of the variation. The linear equation for the three main morphological traits and body weight was Y=–2.8+2.94X2+0.764X4+0.906X5 (R2 =0.958). The optimal model equations for the three main morphological traits and body weight contained exponential functions, a power function, and a linear function, and the model equations were Y=2.739e0.158X2 (R2 =0.936), Y=4.946X4 1.100 (R2 =0.931), and Y=9.582+8.876lnX5 (R2 =0.807) for the curve equation for the tail stalk length and body weight (Y). This indicated that the tail stalk length was not a main morphological factor and was the only variable that could not explain the change in body weight. Body length and head length were the main selection traits, and tail stalk length was an auxiliary trait, which could be used to guide T. yarkandensi breeding.

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引用本文

李艳慧,陈生熬,程勇.叶尔羌高原鳅形态性状与体重的通径分析及曲线拟合[J].中国水产科学,2022,29(1):49-57
LI Yanhui, CHEN Sheng’ao, CHENG Yong. Path analysis and growth curve fitting of morphological traits and body weight of Triplophysa yarkandensi[J]. Journal of Fishery Sciences of China,2022,29(1):49-57

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  • 在线发布日期: 2022-01-27
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