Modeling and predicting meat yield and growth performance using morphological features of narrow-clawed crayfish with machine learning techniques.

ABSTRACT: In recent studies, artificial intelligence and machine learning methods give higher accuracy than other prediction methods in large data sets with complex structures. Instead of statistical methods, artificial intelligence, and machine learning are used due to the difficulty of constructing mathematical models in multi-parameter and multivariate problems. In this study, predictions of length-weight relationships and meat productivity were generated by machine learning models using measurement data of male and female crayfish in the narrow-clawed crayfish population living in Apolyont Lake. The data set was created using the growth performance and morphometric characters from 1416 crayfish in different years to determine the length-weight relationship and length-meat yield. Statistical meth

SUBMITTER: Gultepe Y 

PROVIDER: S-EPMC11315914 | biostudies-literature | 2024 Aug

REPOSITORIES: biostudies-literature