Division of Applied Phycology and Biotechnology, CSIR-Central Salt & Marine Chemicals Research Institute, Bhavnagar, Gujarat, India.
Academy of Scientific and Innovative Research (AcSIR), Ghaziabad, Uttar Pradesh, India.
Methods Mol Biol. 2024;2827:99-107. doi: 10.1007/978-1-0716-3954-2_7.
Marine macro-algae, commonly known as "seaweed," are used in everyday commodity products worldwide for food, feed, and biostimulant for plants and animals and continue to be one of the conspicuous components of world aquaculture production. However, the application of ANN in seaweeds remains limited. Here, we described how to perform ANN-based machine learning modeling and GA-based optimization to enhance seedling production for implications on commercial farming. The critical steps from seaweed seedling explant preparation, selection of independent variables for laboratory culture, formulating experimental design, executing ANN Modelling, and implementing optimization algorithm are described.
海洋大型藻类,通常被称为“海藻”,在全球范围内被广泛应用于食品、饲料以及动植物生物刺激素等日常商品中,并且仍然是世界水产养殖生产的显著组成部分之一。然而,人工神经网络(ANN)在海藻中的应用仍然有限。在这里,我们描述了如何进行基于 ANN 的机器学习建模和基于 GA 的优化,以提高种苗生产,从而对商业养殖产生影响。从海藻种苗外植体准备、实验室培养自变量选择、制定实验设计、执行 ANN 建模和实施优化算法等关键步骤进行了描述。