インデックス付き
  • 環境研究へのオンライン アクセス (OARE)
  • Jゲートを開く
  • Genamics JournalSeek
  • ジャーナル目次
  • シマゴ
  • ウルリッヒの定期刊行物ディレクトリ
  • Global Online Research in Agriculture (AGORA) へのアクセス
  • 電子ジャーナルライブラリ
  • 国際農業生物科学センター (CABI)
  • レフシーク
  • 研究ジャーナル索引作成ディレクトリ (DRJI)
  • ハムダード大学
  • エブスコ アリゾナ州
  • OCLC-WorldCat
  • 学者の舵取り
  • SWBオンラインカタログ
  • 仮想生物学図書館 (vifabio)
  • パブロン
  • ミアル
  • 大学補助金委員会
  • ユーロパブ
  • Google スカラー
このページをシェアする
ジャーナルチラシ
Flyer image

概要

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).

免責事項: この要約は人工知能ツールを使用して翻訳されており、まだレビューまたは確認されていません