AIMC Topic: Phycocyanin

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Artificial Neural Network - Multi-Objective Genetic Algorithm based optimization for the enhanced pigment accumulation in Synechocystis sp. PCC 6803.

BMC biotechnology Mar 15, 2025
BACKGROUND: Natural colorants produced by the cyanobacterium include carotenoids, chlorophyll a and phycocyanin. The current study used the Synechocystis sp. PCC 6803 to examine how abiotic stress conditions, such as low temperature as well as high l...
Neural Networks, Computer Algorithms Carotenoids Chlorophyll Chlorophyll A Pigments, Biological Phycocyanin Synechocystis Genetic Algorithms
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Monitoring the vertical distribution of HABs using hyperspectral imagery and deep learning models.

The Science of the total environment Jun 19, 2021
Remote sensing techniques have been applied to monitor the spatiotemporal variation of harmful algal blooms (HABs) in many inland waters. However, these studies have been limited to monitor the vertical distribution of HABs due to the optical complex...
Deep Learning Environmental Monitoring Harmful Algal Bloom Chlorophyll Chlorophyll A Phycocyanin
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Multilayer perceptron neural network-based approach for modeling phycocyanin pigment concentrations: case study from lower Charles River buoy, USA.

Environmental science and pollution research international May 24, 2016
This paper proposes multilayer perceptron neural network (MLPNN) to predict phycocyanin (PC) pigment using water quality variables as predictor. In the proposed model, four water quality variables that are water temperature, dissolved oxygen, pH, and...
Neural Networks, Computer Water Pollutants, Chemical Oxygen Water Quality Rivers Linear Models Multivariate Analysis Phycocyanin
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