索引于
  • 在线访问环境研究 (OARE)
  • 打开 J 门
  • Genamics 期刊搜索
  • 期刊目录
  • 西马戈
  • 乌尔里希的期刊目录
  • 访问全球在线农业研究 (AGORA)
  • 电子期刊图书馆
  • 国际农业与生物科学中心 (CABI)
  • 参考搜索
  • 研究期刊索引目录 (DRJI)
  • 哈姆达大学
  • 亚利桑那州EBSCO
  • OCLC-WorldCat
  • 学者指导
  • SWB 在线目录
  • 虚拟生物学图书馆 (vifabio)
  • 普布隆斯
  • 米亚尔
  • 大学教育资助委员会
  • 欧洲酒吧
  • 谷歌学术
分享此页面
期刊传单
Flyer image

抽象的

Advanced Techniques for Morphometric Analysis in Fish

Mojekwu TO *,Anumudu CI

Information on the biology and population structure of any species is a prerequisite for developing management and conservation strategies. Morphometric characters of fish are the measurable characters common to all fishes. Some arbitrarily selected points on a fish body known as landmarks help the individual fish shape to be analyzed. A landmark is a point of correspondence on an object that matches between and within populations. Advanced techniques for morphometric analysis offers more efficient and powerful tools in identify differences between fish populations, detecting differences among groups and to differentiate between species of similar shape. Morphometric methods such as univariate comparisons, bivariate analyses of relative growth pattern and a series of multivariate methods have been developed and applied to discriminate stocks. The use of multivariate techniques such as principal components and discriminant analyses to quantify morphometric variables are also receiving increased attention in stock identification. Some of the advanced techniques developed for morphometric analysis in fish population are Truss network measurement, Image analysis- Univarite, Bivariate, and Multivariate, Principal Component Analysis (PCA).

免责声明: 此摘要通过人工智能工具翻译,尚未经过审核或验证