摘要
壳色是长牡蛎(Crassostrea gigas)重要的可遗传经济性状,对壳色进行量化分析可为长牡蛎壳色判定提供有效方法。本研究运用国际照明委员会(CIE)L*a*b*颜色模型评估了黑壳、紫壳、白壳和金壳4个长牡蛎选育群体以及1个普通养殖群体的贝壳颜色参数(L*、a*和b*)。对比壳色参数,结果显示,L*、a*、b*值的方差均小于普通养殖群体,表明经过继代选育,纯化的壳色已经得到较稳定的遗传。通过主成分分析,从3个参数中提取了2个主成分(PC1和PC2),分别解释了53.09%和38.89%变异,PC1解释大部分变异且PC1中参数a*负荷值最大,表明影响壳色不同的主要因素是参数a*。通过逐步判别法分析黑壳、紫壳、白壳和金壳长牡蛎群体,建立了4个判别方程,4种壳色综合判别准确率为96.05%,说明该判别方程在实际应用时参考价值较大。
The shell color of Pacific oyster(Crassostrea gigas)is one of the important economic traits.The quantitative analysis of shell color is an effective method for color determination of oyster shell.In this study,CIE L*a*b*(CIELAB)system was used to evaluate the effectiveness of the shell color selection of Pacific oyster.The shell color parameters(including L*,a*and b*)of the golden,white,black and purple shell strains,and one commercially cultured control population were characgerized.The analysis of four strains color parameters showed that the variances of L*,a*and b*in the four shell color strains were smaller than those in the control,suggesting that pure shell color obtained stably inherited through successive selective breeding.The principal component analysis indicated that the first principal component(PC1)was most affected by color parameter a*,and the second(PC2)by color parameter L*.The contribution rates of the two principal components were 53.09%and 38.89%,respectively.The results also showed that the difference among shell color strains was mainly due to color parameter a*.The discriminant functions for shell color traits were established and the rate of discriminant accuracy(P1 and P2)was 96.05%for four shell color strains,which showed a great application value.
作者
宋俊霖
李琪
孔令锋
SONG Jun-Lin;LI Qi;KONG Ling-Feng(The Key Laboratory of Mariculture(Ocean University of China),Ministry of Education,Qingdao 266003,China)
出处
《中国海洋大学学报（自然科学版）》
CAS
CSCD
北大核心
2018年第1期25-30,共6页
Periodical of Ocean University of China
基金
国家自然科学基金项目(31372524)
泰山学者种业计划专家项目
山东省科技发展计划项目(2016ZDJS06A06)资助~~
关键词
长牡蛎
壳色
量化分析
判别分析
Crassostrea gigas
shell color
quantitative analysis
discriminant analysi
