Digital ‘CEC’ & Related Inputs are Everything that Matter in Inland Fisheries & Allied with the Principle Example with Hilsa, Seabass and Rainbow Trout

Book dealt a brief on AI/ML with data science ecotechnology which we find unbiased using modern applicable digital principles. Recent past last Century we have undergone Central Dogma Modeks stating Genetuc materials are Central Dogma the basic of all biological science. In this biok we describe digital Cation Exchange Capacity or digital CEC and its allied are everything that matte and supporting Central Dogma and Beyond central dogma models. According the digital CEC science there is every negetive correlation between its cationic charged value in meq and every biological growth and species repriductions and all other positive phenomenons are determined to every plants and Animals or total Biology. Additionally we find a very low digital CEC can reproduce a huge biomass of petroleum, Fats and Oils and many aspects of disease resistant behaviour among the existing biology by means of environment editing models EEM or DIseasePERcentage zero with Environment Editing Model with given examples in Fisheries HILSA, SEABAS, Rainbow Trout and a few ithers since Authors finds water may be better media than Soils in this Water-Planet. etc.

This book explores the intersection of artificial intelligence, machine learning, and data science with eco-technology, presenting a novel framework rooted in digital principles for unbiased scientific applications. Building upon the foundational concept of the Central Dogma in biological sciences, the authors introduce the concept of Digital Cation Exchange Capacity (digital CEC) as a critical determinant of biological phenomena. The digital CEC model posits an inverse correlation between cationic charge values (meq) and biological growth, reproduction, and other positive outcomes across plant and animal species. Furthermore, the book highlights the role of low digital CEC in driving significant biomass production, including petroleum, fats, and oils, alongside fostering disease resistance through Environment Editing Models (EEM). These models are exemplified by their applications in fisheries such as Hilsa, Seabass, and Rainbow Trout, underscoring water as a superior medium for biological innovation on this water-dominated planet. The work bridges biological principles with modern digital methodologies, offering insights into sustainable and disease-resistant ecosystems.