AIMC Topic: Biomass
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Evaluation of heterotrophic and mixotrophic cultivation of novel Micractinium sp. ME05 on vinasse and its scale up for biodiesel production.
Bioresource technology
Dec 9, 2017
Direct disposal of vinasse, a by-product of molasses fermentation plants, threatens environmental health. This study investigated the usage of vinasse as a nutrient source for the heterotrophic and mixotrophic cultivation of novel Micractinium sp. ME...
An alternative approach for estimating above ground biomass using Resourcesat-2 satellite data and artificial neural network in Bundelkhand region of India.
Environmental monitoring and assessment
Oct 20, 2017
Determination of above ground biomass (AGB) of any forest is a longstanding scientific endeavor, which helps to estimate net primary productivity, carbon stock and other biophysical parameters of that forest. With advancement of geospatial technology...
Improved prediction of higher heating value of biomass using an artificial neural network model based on proximate analysis.
Bioresource technology
Mar 9, 2017
As biomass becomes more integrated into our energy feedstocks, the ability to predict its combustion enthalpies from routine data such as carbon, ash, and moisture content enables rapid decisions about utilization. The present work constructs a novel...
Tricalcium phosphate solubilization and nitrogen fixation by newly isolated Aneurinibacillus aneurinilyticus CKMV1 from rhizosphere of Valeriana jatamansi and its growth promotional effect.
Brazilian journal of microbiology : [publication of the Brazilian Society for Microbiology]
Dec 24, 2016
Aneurinibacillus aneurinilyticus strain CKMV1 was isolated from rhizosphere of Valeriana jatamansi and possessed multiple plant growth promoting traits like production of phosphate solubilization (260mg/L), nitrogen fixation (202.91nmolethylenemLh), ...
Artificial neural network-based model for the prediction of optimal growth and culture conditions for maximum biomass accumulation in multiple shoot cultures of Centella asiatica.
Protoplasma
Apr 11, 2016
An artificial neural network (ANN)-based modelling approach is used to determine the synergistic effect of five major components of growth medium (Mg, Cu, Zn, nitrate and sucrose) on improved in vitro biomass yield in multiple shoot cultures of Cente...
An artificial intelligence approach for modeling volume and fresh weight of callus - A case study of cumin (Cuminum cyminum L.).
Journal of theoretical biology
Mar 14, 2016
Cumin (Cuminum cyminum Linn.) is valued for its aroma and its medicinal and therapeutic properties. A supervised feedforward artificial neural network (ANN) trained with back propagation algorithms, was applied to predict fresh weight and volume of C...
Fuzzy logic feedback control for fed-batch enzymatic hydrolysis of lignocellulosic biomass.
Bioprocess and biosystems engineering
Feb 25, 2016
A fuzzy logic feedback control system was developed for process monitoring and feeding control in fed-batch enzymatic hydrolysis of a lignocellulosic biomass, dilute acid-pretreated corn stover. Digested glucose from hydrolysis reaction was assigned ...
Gross parameters prediction of a granular-attached biomass reactor by means of multi-objective genetic-designed artificial neural networks: touristic pressure management case.
Environmental science and pollution research international
Nov 17, 2015
The Artificial Neural Networks by Multi-objective Genetic Algorithms (ANN-MOGA) model has been applied to gross parameters data of a Sequencing Batch Biofilter Granular Reactor (SBBGR) with the aim of providing an effective tool for predicting the fl...
The potential of random forest and neural networks for biomass and recombinant protein modeling in Escherichia coli fed-batch fermentations.
Biotechnology journal
Aug 11, 2015
Product quality assurance strategies in production of biopharmaceuticals currently undergo a transformation from empirical "quality by testing" to rational, knowledge-based "quality by design" approaches. The major challenges in this context are the ...
Prediction of sugar yields during hydrolysis of lignocellulosic biomass using artificial neural network modeling.
Bioresource technology
Feb 11, 2015
The present investigation was carried out to study application of ANN as a tool for predicting sugar yields of pretreated biomass during hydrolysis process at various time intervals. Since it is known that biomass loading and particle size influences...
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