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Biomass

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Develop a hybrid machine learning model for promoting microbe biomass production.

Bioresource technology
Since the cultivation condition of microbe biomass production (mycelia yield) involves a variety of factors, it's a laborious process to obtain the optimal cultivation condition of Antrodia cinnamomea (A. cinnamomea). This study proposed a hybrid mac...

Use of synthetic images for training a deep learning model for weed detection and biomass estimation in cotton.

Scientific reports
Site-specific treatment of weeds in agricultural landscapes has been gaining importance in recent years due to economic savings and minimal impact on the environment. Different detection methods have been developed and tested for precision weed manag...

Waste-to-energy as a tool of circular economy: Prediction of higher heating value of biomass by artificial neural network (ANN) and multivariate linear regression (MLR).

Waste management (New York, N.Y.)
Circular economy is a global trend as a promising strategy for the sustainable use of natural resources. In this context, waste-to-energy presents an effective solution to respond to the ever-increasing waste generation and energy demand duality. How...

RETRACTED: Chemistry-Informed Neural Networks modelling of lignocellulosic biomass pyrolysis.

Bioresource technology
This article has been retracted: please see Elsevier Policy on Article Withdrawal (http://www.elsevier.com/locate/withdrawalpolicy). This article has been retracted at the request of the authors and the Editor-in-Chief. The article has reused text fr...

Machine learning-informed and synthetic biology-enabled semi-continuous algal cultivation to unleash renewable fuel productivity.

Nature communications
Algal biofuel is regarded as one of the ultimate solutions for renewable energy, but its commercialization is hindered by growth limitations caused by mutual shading and high harvest costs. We overcome these challenges by advancing machine learning t...

Machine learning based analysis of reaction phenomena in catalytic lignin depolymerization.

Bioresource technology
Heterogeneously catalyzed lignin solvolysis opens the possibility of transforming low value biomass into high value, useful aromatic chemicals, however, its reaction behavior is poorly understood due to the many possible interactions between reaction...

A transfer learning approach for predictive modeling of bioprocesses using small data.

Biotechnology and bioengineering
Predictive modeling of new biochemical systems with small data is a great challenge. To fill this gap, transfer learning, a subdomain of machine learning that serves to transfer knowledge from a generalized model to a more domain-specific model, prov...

Smart sustainable biorefineries for lignocellulosic biomass.

Bioresource technology
Lignocellulosic biomass (LCB) is considered as a sustainable feedstock for a biorefinery to generate biofuels and other bio-chemicals. However, commercialization is one of the challenges that limits cost-effective operation of conventional LCB bioref...

Recent advances of thermochemical conversion processes for biorefinery.

Bioresource technology
Lignocellulosic biomass is one of the most promising renewable resources and can replace fossil fuels via various biorefinery processes. Through this study, we addressed and analyzed recent advances in the thermochemical conversion of various lignoce...

Yield prediction of "Thermal-dissolution based carbon enrichment" treatment on biomass wastes through coupled model of artificial neural network and AdaBoost.

Bioresource technology
The "Thermal-dissolution based carbon enrichment" was proven as an efficient and homogenizing treatment method in converting biomass wastes into similar high-quality carbon materials. However, their yields varied significantly with respect to the dif...