首页|基于耳石形态判别舟山海域条石鲷自然群体和养殖群体

基于耳石形态判别舟山海域条石鲷自然群体和养殖群体

扫码查看
为有效判别条石鲷自然群体和养殖群体,本研究基于174尾随机样品(自然群体100尾、养殖群体74尾),利用传统统计分析和神经网络方法对自然和养殖两个群体耳石的6个形状指标和21个框架指标进行研究。结果表明:形状指标中椭圆率、圆度和幅形比在两个群体间差异显著,框架指标中有12个指标差异显著。判别结果表明,传统统计分析和神经网络方法基于形状指标的判别正确率分别为57。5%和81。4%,基于框架指标的判别正确率分别为69。5%和85。4%。研究表明,与传统统计分析方法相比,基于耳石形态的神经网络判别方法更能有效区分条石鲷自然群体和养殖群体。
Discrimination of natural and cultured Oplegnathus fasciatus populations in Zhoushan sea area based on otolith morphology
To effectively distinguish natural and cultured populations of Oplegnathus fasciatus,we used both tradi-tional statistical analysis and neural network methods to compare six shape indices and twenty-one truss indices from otoliths of 174 randomly selected specimens(100 from a natural population and 74 from a cultured population).The results showed that among the six shape indices,ellipticity,roundness,and aspect ratio exhibited significant differences between the two populations.Twelve out of the twenty-one truss indices displayed significant differences.Results of discriminant analysis indicated that traditional statistical analysis and neural network methods achieved correct discrimination rates of 57.5%and 81.4%for shape indices,while for truss indices were 69.5%and 85.4%,respectively.These findings indicated that neural network technique is more effectively than traditional statistical method to distinguish natural and cultured populations of O.fasciatus.

Oplegnathusfasciatuspopulation discriminationotolithstepwise discriminant analysisneural net-work

王嘉浩、朱凯、徐开达、王好学、陈睿毅、曾佳颖

展开 >

浙江省海洋水产研究所/农业农村部重点渔场渔业资源环境科学观测实验站/浙江省海洋渔业资源可持续利用技术研究重点实验室,浙江舟山 316021

条石鲷 群体判别 耳石 逐步判别分析 神经网络

2024

应用生态学报
中国生态学学会 中国科学院沈阳应用生态研究所

应用生态学报

CSTPCD北大核心
影响因子:2.114
ISSN:1001-9332
年,卷(期):2024.35(11)