文章摘要
王松林,许星鸿,涂康,刘志鸿,张天时,吴彪,周丽青,孙秀俊.不同地理群体菲律宾蛤仔壳形态对体重性状的影响研究.渔业科学进展,2023,44(6):142-154
不同地理群体菲律宾蛤仔壳形态对体重性状的影响研究
Effects of shell morphology on the weight traits of Manila clam (Ruditapes philippinarum) from different geographical populations
投稿时间:2022-04-12  修订日期:2022-05-06
DOI:
中文关键词: 菲律宾蛤仔  壳形态性状  软体重  通径分析  聚类分析
英文关键词: Ruditapes philippinarum  Shell morphology  Soft body weight  Path analysis  Cluster analysis
基金项目:
作者单位
王松林 江苏海洋大学海洋科学与水产学院 江苏 连云港 222005中国水产科学研究院黄海水产研究所 海洋渔业科学与食物产出过程功能实验室 农业农村部海洋渔业与可持续发展重点实验室 山东 青岛 266071 
许星鸿 江苏海洋大学海洋科学与水产学院 江苏 连云港 222005 
涂康 莆田市水产研究所 福建 莆田 351100 
刘志鸿 中国水产科学研究院黄海水产研究所 海洋渔业科学与食物产出过程功能实验室 农业农村部海洋渔业与可持续发展重点实验室 山东 青岛 266071 
张天时 中国水产科学研究院黄海水产研究所 海洋渔业科学与食物产出过程功能实验室 农业农村部海洋渔业与可持续发展重点实验室 山东 青岛 266072 
吴彪 中国水产科学研究院黄海水产研究所 海洋渔业科学与食物产出过程功能实验室 农业农村部海洋渔业与可持续发展重点实验室 山东 青岛 266073 
周丽青 中国水产科学研究院黄海水产研究所 海洋渔业科学与食物产出过程功能实验室 农业农村部海洋渔业与可持续发展重点实验室 山东 青岛 266074 
孙秀俊 中国水产科学研究院黄海水产研究所 海洋渔业科学与食物产出过程功能实验室 农业农村部海洋渔业与可持续发展重点实验室 山东 青岛 266075 
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中文摘要:
      采集我国南北沿海9个地理群体的菲律宾蛤仔(Ruditapes philippinarum),利用通径分析等方法评估各群体形态性状对活体重和软体重的影响。结果显示,各群体壳长、壳高、壳宽和壳厚4 个形态性状对菲律宾蛤仔活体重和软体重的影响存在显著差异。除壳厚外,其他形态性状与活体重和软体重呈显著相关(P < 0.05)。通径分析和决定系数分析显示,大多数群体的壳宽对活体重和软体重的直接作用最大。2个形态比例参数(壳宽/壳长和壳高/壳长)最大值出现在山东莱州群体(0.49和0.74),而最小值出现在大连东港群体(0.42和0.67)。壳厚的变异系数最大(22.74),而壳高的变异系数最小(9.47)。通过检验偏回归系数的显著性,建立了各群体形态性状对软体重的最优回归方程。聚类分析表明,菲律宾蛤仔不同群体未出现明显的地域分布特征,而呈现出不规律的南北交替聚类现象。本研究查明了不同地理群体菲律宾蛤仔壳形态性状对体重性状的影响,为菲律宾蛤仔地理群体的形态判别、种质资源分析和遗传育种研究等提供了重要科学依据。
英文摘要:
      Shell morphological traits are important quantitative traits in shellfish. Shell morphology is usually affected by many factors, such as the ecological environment and shellfish genetics. It is considered the results of comprehensive actions of natural selection, micro-evolution, and heredity. Measuring shell morphological traits aids our understanding of the current situation of germplasm resources among shellfish species or intraspecific populations and also provides important breeding traits for shellfish breeding programs. For most shellfish, quality traits (eg. live weight and soft body weight) are considered the important breeding traits, but there are practical issues in using these traits, such as the inability or difficulty in measuring them in vivo. It is well known that shellfish quality traits are closely related to shell morphological traits. However, a simple correlation analysis between quality and morphological traits cannot adequately explain all the intrinsic links between these traits. In this study, Manila clams (Ruditapes philippinarum) were collected from nine geographical locations along the north and south coasts of China. The shell morphology and quality characteristics were measured and analyzed for the nine different populations of clams. Furthermore, the main factors affecting the quality traits were analyzed using cluster analysis to reveal the genetic relationships among the populations. The optimal regression equations were constructed using the morphological traits with the soft weights of these populations. For all populations, shell length, shell height, shell width, and shell thickness were measured using a vernier caliper (with an accuracy of 0.01 mm) and a thickness gauge. After wiping the surface of clams with filter paper, their live weight was measured on an electronic balance (with an accuracy of 0.01 g). A scalpel was used to sample the soft body from the clams. After drying, soft body weights were calculated using the difference between live weight and shell weight. The morphological data, including mean values, standard deviation, and coefficient of variation, were calculated using SPSS 26.0. To eliminate the effects of size differences among individuals, two morphological scale parameters (shell width/shell length and shell height/shell length) were calculated to reflect the morphological characteristics of the clams. In addition, stepwise linear regression analyses were performed to obtain the correlation coefficients, direct path coefficients, correlation indexes, indirect path coefficients, and determine the coefficients using SPSS26.0 software. The correlation coefficient and multiple regression analyses of the traits were evaluated. The multiple regression equations were established for all populations. Cluster analysis was used to assess each trait using the calibrations (to calculate the ratio of each trait to shell length). The heatmap displayed the shortest distance method for the Euclidean distance between the different populations. There were significant differences in the effects of shell length, shell height, shell width, and shell thickness on live weight and soft body weight of clams. Morphological traits were significantly correlated with body weight and soft weight (P<0.05), except for shell thickness. The results of determination coefficient revealed shell width had the greatest impact on live weights of the Putian, Jinzhou, and Chaozhou populations, with determination coefficients of 0.277, 0.232, and 0.307, respectively. The determination coefficients of soft body weights indicated that shell width played very important roles in determining soft body weights of the Putian and Chaozhou populations, with determination coefficients of 0.249 and 0.443, respectively. By calculating the total of determination coefficients, the results are consistent with the correlation index R2 for each trait. For the total determinant effects, the sum of determination coefficients for the morphological traits with soft body weights were greater than 0.850 in most populations. In contrast, the sum of determination coefficients for the morphological traits with soft body weights were less than 0.850 in Laizhou, Zhuanghe, Donggang, and Jinzhou. Based on the path analysis and the determination coefficient analysis, shell width had the greatest impact on live weights and soft body weights in most populations. The maximum values of the two morphological proportion parameters (shell width/shell length and shell height/shell length) were found in the Laizhou population (0.49 and 0.74), while the minimum proportion parameters were detected in the Dalian Donggang population (0.42 and 0.67). Among the shell morphological traits, shell thickness had the largest coefficient of variation (22.74), while shell height had the smallest coefficient of variation (9.47). By testing for statistically significant variation in the partial regression coefficient, the optimal regression equations of the morphological traits for soft body weight were constructed for all the populations. The cluster analysis revealed that different clam populations did not have a typically regional characteristic in terms of the shell morphological traits. There was an irregular north-south alternating clustering phenomenon. According to the present findings, shell thickness and morphological ratio parameters (ratio of shell height to shell length and ratio of shell width to shell length) are important indicators for evaluating the growth potential and nutritional status of clams in aquaculture. The present results provide a scientific basis for morphological discrimination and germplasm resource evaluation for geographical populations of clams and also aid breeding strategies to predict breeding traits for aquaculture breeding programs, including guidance for the selective breeding of clams.
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