AIMC Topic: Nitrogen

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Variable weighted convolutional neural network for the nitrogen content quantization of Masson pine seedling leaves with near-infrared spectroscopy.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
Spectroscopy is a powerful non-destructive quantization tool. In this paper, the technology is used to predict the nitrogen content of Masson pine seedling leaves. Masson pine is widely planted in China, and its nitrogen content is an important index...

Nondestructive determination of freshness indicators for tilapia fillets stored at various temperatures by hyperspectral imaging coupled with RBF neural networks.

Food chemistry
This study develops a reliable radial basis function neural networks (RBFNNs) to estimate freshness for tilapia fillets stored under non-isothermal conditions by using optimal wavelengths from hyperspectral imaging (HSI). The results show that, for t...

The key role of inoculated sludge in fast start-up of sequencing batch reactor for the domestication of aerobic granular sludge.

Journal of environmental sciences (China)
Two types of inoculated sludges, granular sludge that had been stored at -20°C and activated sludge, were investigated for the domestication of aerobic granular sludges (AGSs) in sequencing batch reactors (SBRs). The results showed that using the sto...

Evaluation and optimization of anammox baffled reactor (AnBR) by artificial neural network modeling and economic analysis.

Bioresource technology
Anammox baffled reactor (AnBR) had a moderate start-up period of 53 days. Interestingly, tangled relationships between key parameters affecting anammox performance were observed, i.e., polynomial function for nitrogen loading rate (NLR) with extracel...

Effluent composition prediction of a two-stage anaerobic digestion process: machine learning and stoichiometry techniques.

Environmental science and pollution research international
Computational self-adapting methods (Support Vector Machines, SVM) are compared with an analytical method in effluent composition prediction of a two-stage anaerobic digestion (AD) process. Experimental data for the AD of poultry manure were used. Th...

Prediction of soil urea conversion and quantification of the importance degrees of influencing factors through a new combinatorial model based on cluster method and artificial neural network.

Chemosphere
Quantitative prediction of soil urea conversion is crucial in determining the mechanism of nitrogen transformation and understanding the dynamics of soil nutrients. This study aimed to establish a combinatorial prediction model (MCA-F-ANN) for soil u...

Optimization of culture conditions for gamma-aminobutyric acid production in fermented adzuki bean milk.

Journal of food and drug analysis
γ-Aminobutyric acid (GABA), a nonprotein amino acid, is widely distributed in nature and fulfills several physiological functions. In this study, various lactic acid strains commonly used to produce fermented milk products were inoculated into adzuki...

Analyzing the performance of fluorescence parameters in the monitoring of leaf nitrogen content of paddy rice.

Scientific reports
Leaf nitrogen content (LNC) is a significant factor which can be utilized to monitor the status of paddy rice and it requires a reliable approach for fast and precise quantification. This investigation aims to quantitatively analyze the correlation b...

Systematic design of membership functions for fuzzy-logic control: A case study on one-stage partial nitritation/anammox treatment systems.

Water research
A methodology is developed to systematically design the membership functions of fuzzy-logic controllers for multivariable systems. The methodology consists of a systematic derivation of the critical points of the membership functions as a function of...

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
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...