Highlights•Machine learning to relate aquatic production to water quality.•Identifying the
most influential variables for harvest outcome in freshwater ponds.•Sensor data analytics to …

The rapid growth of prawn farming on an international scale will play an important role in
meeting the protein requirements of an expanding global population. Efficient management …

Monitoring variables such as dissolved oxygen, pH, and pond temperature is a key aspect of
high-quality fish farming. Machine learning (ML) techniques have been proposed to model …

Significant income was promised by giant freshwater prawn farming, which served as a key
occupation for farmers. However, challenges were faced by traditional methods, including …

The P. clarkii aquaculture is mostly conducted using traditional soil-ponds in China, which
are directly exposed to the open-air environment. This study explored the influence of …

The research presented in this paper was conducted as part of a project that aimed at using
biosensors on sentinel oysters to provide a biological perspective of environmental …

Aquaculture is one of the ever-growing food-producing sectors and it is also one of the non-
oil and gas industries that is contributing to Brunei Darussalam gross domestic product. This …

The demand for shrimp from Indonesia continues to increase every year, thus creating
greater interest in the shrimp farming industry. Although shrimp is relatively easy to farm …

The objective of the paper is to explain how we used soft sensing based on machine
learning models to estimate some water quality parameters in lined pond conditions from an …

Machine learning (ML) makes machines independent and self-learning component.
Researchers applying machine learning algorithms to solve various real word problems in …