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Biomass

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Artificial Neural Network and Remote Sensing combined to predict the Aboveground Biomass in the Cerrado biome.

Anais da Academia Brasileira de Ciencias
Cerrado is the second largest biome in Brazil, and it is responsible for providing us several ecosystem services, including the functions of storing Carbon and biodiversity conservation. In this study, we developed a modeling approach to predict the ...

Machine learning-assisted optimization of food-grade spirulina cultivation in seawater-based media: From laboratory to large-scale production.

Journal of environmental management
The shortage of food and freshwater sources threatens human health and environmental sustainability. Spirulina grown in seawater-based media as a healthy food is promising and environmentally friendly. This study used three machine learning technique...

Deep learning artificial neural network framework to optimize the adsorption capacity of 3-nitrophenol using carbonaceous material obtained from biomass waste.

Scientific reports
The presence of toxic chemicals in water, including heavy metals like mercury and lead, organic pollutants such as pesticides, and industrial chemicals from runoff and discharges, poses critical public health and environmental risks leading to severe...

Detecting the interaction between microparticles and biomass in biological wastewater treatment process with Deep Learning method.

The Science of the total environment
Investigating the interaction between influent particles and biomass is basic and important for the biological wastewater treatment. The micro-level methods allow for this, such as the microscope image analysis method with the conventional ImageJ pro...

Production of high calorific value hydrogen-rich combustible gas by supercritical water gasification of straw assisted by machine learning.

Bioresource technology
This article reveals the basic laws of straw supercritical water gasification (SCWG) and provides basic experimental data for the effective utilization of straw. The paper studied the impact of three operational conditions on the production of high-c...

Low-carbon wastewater treatment and resource recovery of recirculating aquaculture system by immobilized chlorella vulgaris based on machine learning optimization.

Bioresource technology
Immobilized microalgae biotechnologies can conserve water and space by low-carbon wastewater treatment and resource recovery in a recirculating aquaculture system (RAS). However, technical process parameters have been unoptimized considering the mutu...

Unravelling barriers associated with dissemination of large-scale biogas plant with analytical hierarchical process and fuzzy analytical hierarchical process approach: Case study of India.

Bioresource technology
This study explores why large-scale biogas plants are not widely installed in India despite the wealth of biomass resources. The methodology includes an extensive literature review and surveyed biogas experts in different sectors, such as private, pu...

Reducing cadmium and arsenic accumulation in rice grains: The coupled effect of sulfur's biomass dilution and soil immobilization analyzed using meta-analysis and machine learning.

The Science of the total environment
The biogeochemical cycling of sulfur (S) in paddy soil influences cadmium (Cd) and arsenic (As) migration. However, the impact of S application on Cd and As within the soil-rice system has not been fully explored. This study aimed to examine the effe...

Predicting photosynthetic bacteria-derived protein synthesis from wastewater using machine learning and causal inference.

Bioresource technology
Causal inference-assisted machine learning was used to predict photosynthetic bacterial (PSB) protein production capacity and identify key factors. The extreme gradient boosting algorithm effectively predicted protein content, while the gradient boos...

Machine learning prediction and exploration of phosphorus migration and transformation during hydrothermal treatment of biomass waste.

The Science of the total environment
Hydrothermal treatment (HTT) held promise for phosphorus (P) recovery from high-moisture biomass. However, traditional experimental studies of P hydrothermal conversion were time-consuming and labor-intensive. Thus, based on biomass characteristics a...