Wastewater salinity assessment using near infrared spectroscopy

2013 ◽  
Vol 68 (4) ◽  
pp. 879-886 ◽  
Author(s):  
Ronald Ontiveros ◽  
Lamine Diakite ◽  
M. Edna Alvarez ◽  
Pablo Coras
Keyword(s):  
Infrared Spectroscopy ◽  
Near Infrared Spectroscopy ◽  
Near Infrared ◽  
Spectral Characteristics ◽  
Visible Region ◽  
Coefficient Of Determination ◽  
Absorption Bands ◽  
Channel Network ◽  
Spectral Signatures ◽  
Wastewater Samples

The visible and near infrared spectroscopy is a fast and inexpensive non-destructive technique for the prediction of concentrations of salts in wastewater. Conventional chemical methods are usually used, which are very accurate, take more time and require special techniques for sampling, storing and pretreatment of wastewater. In this work we studied the spectral characteristics of water and the effect of salts on the perturbations in the water absorption bands. The generation of multiple regression models with principal components was carried out on standard solutions with composition of salts similar to that of wastewater samples taken along the drainage channel network of the Mexico City Metropolitan Area. The spectral signatures were obtained in situ and in the laboratory using a portable high-resolution spectroradiometer (ASD FieldSpec 3). The prediction model generated showed high precision in the estimation of salinity in wastewater, a coefficient of determination of 89.6% and a low root mean square error of 0.12‰. Other compounds, which are not discussed here, cause distortion of the absorption bands of water at wavelengths less than 900 nm or near the visible region, while our results showed distortions in the water spectrum at higher wavelengths (>1,000 nm).

scholarly journals OTIMIZAÇÃO DE CALIBRAÇÕES BASEADAS EM ESPECTROSCOPIA NO INFRAVERMELHO PRÓXIMO PARA ESTIMATIVA DE PROPRIEDADES DA MADEIRA DE Eucalyptus

FLORESTA ◽  
2010 ◽  
Vol 40 (3) ◽  
Author(s):  
Paulo Ricardo Gherardi Hein ◽  
José Tarcísio Lima ◽  
Gilles Chaix Gilles Chaix
Keyword(s):  
Infrared Spectroscopy ◽  
Near Infrared Spectroscopy ◽  
Near Infrared ◽  
Laboratory Data ◽  
Wood Properties ◽  
Coefficient Of Determination ◽  
Mathematical Treatment ◽  
Least Squares Regression ◽  
Eucalyptus Wood ◽  
Prediction Density

A espectroscopia no infravermelho próximo (NIRS) é uma técnica não-destrutiva, rápida e utilizada para avaliação, caracterização e classificação de materiais, sobretudo de origem biológica. A obtenção de informações contida nos espectros NIR é complexa e requer a utilização de métodos quimiométricos. Assim, por meio de regressão multivariada, os espectros de absorbância podem ser associados às propriedades da madeira, tornando possível a sua predição em amostras desconhecidas. Existem algumas ferramentas quimiométricas que melhoram o ajuste dos modelos preditivos. Assim, o objetivo deste trabalho foi simular regressões dos mínimos quadrados parciais baseados nas informações espectrais e de laboratório e estudar a influência da aplicação de tratamentos matemáticos, do descarte de amostras anômalas e da seleção de comprimentos de onda no ajuste dos modelos para estimativa da densidade básica e do módulo de elasticidade em ensaio de compressão paralela às fibras da madeira de Eucalyptus. A aplicação da primeira e segunda derivada nos espectros, o descarte de amostras anômalas e a seleção de algumas das variáveis espectrais melhorou significativamente o ajuste do modelo, reduzindo o erro padrão e aumentando o coeficiente de determinação e a relação de desempenho do desvio.Palavras-chave:  Espectroscopia no infravermelho próximo; predição; densidade básica; MOE; madeira; Eucalyptus. AbstractOptimization of calibrations based on near infrared spectroscopy for estimation of Eucalyptus wood properties. Near infrared spectroscopy (NIRS) is a non-destructive technique used for rapid evaluation, characterization and classification of biological materials. The extraction of the information contained in the NIR spectrum is complex and requires the use of chemo metric methods. Thus, by means of multivariate regression, the absorbance spectra are correlated to wood properties, making possible the prediction in unknown samples. There are some chemo metric tools that can improve the adjustment of the predictive models. The aim of this work was to simulate partial least squares regression based on NIR spectra and laboratory data and to study the influence of the application of mathematical treatment, the removal of outliers and the wavelengths selection in the adjustment of models to estimate the density and modulus of elasticity in Eucalyptus wood. The use of the first and second derivative spectra, the disposal of outliers, and the variables selection improved significantly the model fit, reducing the standard error and increasing the coefficient of determination and the ratio of performance to deviation.Keywords: Near infrared; spectroscopy; prediction; density; MOE; wood; Eucalyptus.

Near Infrared Spectroscopy of Aurichalcite (Zn,Cu2+)5(CO3)2(OH)6

2007 ◽  
Vol 15 (2) ◽  
pp. 115-121 ◽  
Author(s):  
B. Jagannadha Reddy ◽  
Ray L. Frost
Keyword(s):  
Infrared Spectroscopy ◽  
Near Infrared Spectroscopy ◽  
Near Infrared ◽  
Divalent Cations ◽  
Spectral Feature ◽  
Adsorbed Water ◽  
Absorption Bands ◽  
Bending Vibrations ◽  
Show Evidence ◽  
Spectroscopy Studies

In this endeavour, near infrared spectroscopy studies show evidence of variable composition in aurichalcite minerals of zinc copper carbonate hydroxides. The observation of a broad feature in the electronic part of the spectrum around 11,500 cm−1 (870 nm) is a strong indication of Cu2+ substitution for Zn2+ in the mineral. Overtones of OH vibrations in the spectra from 7250 to 5400 cm−1 (1380–1850 nm) show strong hydrogen bonding in these carbonates. A band common to spectra of all carbonates appears near 5400 cm−1 (1850 nm) due to the combination of both OH-stretching and HOH-bending vibrations, which may be attributed to adsorbed water. Aurichalcite minerals display a spectral sequence of five absorption bands with variation of both band positions and intensities and this is the chief spectral feature observed in the range 5200–5100 cm−1 (1920–2380 nm) due to vibrational processes of the carbonate ion. The frequency shift of carbonate bands suggests the effect of divalent cations and/or variations of the Zn/Cu ratio in aurichalcite minerals.

Process Evaluation of Key Parameters during Plant-Field Composting Using Genetic Algorithms and Near-Infrared Spectroscopy

2012 ◽  
Vol 532-533 ◽  
pp. 202-207
Author(s):  
Guang Qun Huang ◽  
Lu Jia Han ◽  
Xiao Yan Wang
Keyword(s):  
Genetic Algorithms ◽  
Infrared Spectroscopy ◽  
Near Infrared Spectroscopy ◽  
Near Infrared ◽  
Electronic Conductivity ◽  
Chicken Manure ◽  
Total Carbon ◽  
Coefficient Of Determination ◽  
Full Spectrum ◽  
Validation Set

The nondestructive estimation of key parameters during plant-field chicken manure composting is of great importance for quality evaluation. In the process of developing regression models using near-infrared spectroscopy (NIRS), methods used for wavelength selection significantly influence on the efficiency of the calibration. This study explored the method of genetic algorithms (GAs) for selecting highly related wavelengths to improve NIRS models for moisture (Miost), pH and electronic conductivity (EC), total carbon (TC), total nitrogen (TN) and C/N ratio determination in chicken manure during composting. Based on the values of coefficient of determination in the validation set (R2) and root mean square error of prediction (RMSEP), the prediction results were evaluated as excellent for Miost, TC and TN, good for pH and EC, and approximate for C/N ratio. But GAs had better performance than using full spectrum for near-infrared spectroscopy model construction in the process of evaluating key parameters during plant-field chicken manure composting.

Quantitative Analysis of Epoxy Resin Cure Reaction: A Study by Near-Infrared Spectroscopy

2002 ◽  
Vol 56 (11) ◽  
pp. 1413-1421 ◽  
Author(s):  
C. Billaud ◽  
M. Vandeuren ◽  
R. Legras ◽  
V. Carlier
Keyword(s):  
Infrared Spectroscopy ◽  
Near Infrared Spectroscopy ◽  
Epoxy Resins ◽  
Model Compound ◽  
Near Infrared ◽  
Curing Process ◽  
Absorption Bands ◽  
Cure Reaction ◽  
Quantitative Results ◽  
Epoxy Resin Cure

Near-infrared spectroscopy was used to quantify the cure reaction of 4,4′-methylene- bis-(2,6-diethylaniline) (MDEA)–epoxy resins (E/A = 1.4) carried out at 72 and 160 °C. The absorption bands of the functional groups of interest in MDEA–epoxy resins are assigned according to the literature. A new assignment at 6580 cm−1 is also proposed for the secondary amine: it was supported by a synthesized model compound. Two different spectrum treatments were proposed. The first one is based only on a normalization at 4610–4620 cm−1, while the second one needs the subtraction of the normalized spectrum of a post-cure sample. To follow the curing process, amines and epoxy were studied at the same time in the combination and the overtone regions. The results are compared. In the combination region, quantitative results are obtained from absorbance measurements, while in the overtone region spectrum decompositions and area measurements are necessary. Complementary and reliable information are so obtained and allow us to calculate conversions of epoxide and amine I and concentrations in amine II, amine III, hydoxyl groups, and ether links. Kinetics are also established. The curing process mechanism is at last discussed for both curing temperatures.

scholarly journals Prediction of water content and soluble solids content of ‘manalagi’ apples using near infrared spectroscopy

2021 ◽  
Vol 922 (1) ◽  
pp. 012062
Author(s):  
K Kusumiyati ◽  
Y Hadiwijaya ◽  
D Suhandy ◽  
A A Munawar
Keyword(s):  
Infrared Spectroscopy ◽  
Water Content ◽  
Near Infrared Spectroscopy ◽  
Near Infrared ◽  
Quality Attributes ◽  
Soluble Solids ◽  
Coefficient Of Determination ◽  
Soluble Solids Content ◽  
Orthogonal Signal Correction ◽  
Solids Content

Abstract The purpose of the research was to predict quality attributes of ‘manalagi’ apples using near infrared spectroscopy (NIRS). The desired quality attributes were water content and soluble solids content. Spectra data collection was performed at wavelength of 702 to 1065 nm using a Nirvana AG410 spectrometer. The original spectra were enhanced using orthogonal signal correction (OSC). The regression approaches used in the study were partial least squares regression (PLSR) and principal component regression (PCR). The results showed that water content prediction acquired coefficient of determination in calibration set (R2cal) of 0.81, coefficient of determination in prediction set (R2pred) of 0.61, root mean squares error of calibration set (RMSEC) of 0.009, root mean squares of prediction set (RMSEP) of 0.020, and ratio performance to deviation (RPD) of 1.62, while soluble solids content prediction displayed R2cal, R2pred, RMSEC, RMSEP, and RPD of 0.79, 0.85, 0.474, 0.420, and 2.69, respectively. These findings indicated that near infrared spectroscopy could be used as an alternative technique to predict water content and soluble solids content of ‘manalagi’ apples.

Determination of gel time of prepreg in copper clad laminate industry by near infrared spectroscopy

2020 ◽  
pp. 096703352096379
Author(s):  
Qian-Fa Liu ◽  
Dan Li ◽  
Yao-De Zeng ◽  
Wei-Zhuang Huang
Keyword(s):  
Infrared Spectroscopy ◽  
Near Infrared Spectroscopy ◽  
Manufacturing Process ◽  
Near Infrared ◽  
Reference Method ◽  
Coefficient Of Determination ◽  
Resin Matrix ◽  
Calibration Model ◽  
Gel Time ◽  
Significant Difference

Gel time of prepreg is an important quality determinant in the manufacturing process of Copper Clad Laminate (CCL). Prepreg consists of a glass fiber reinforcement impregnated to a predetermined level with a resin matrix. In this work, near infrared spectroscopy associated with partial least squares (PLS) regression has been applied to analyse the gel time of prepreg samples in the manufacturing process. A total of 250 prepreg samples were randomly divided into a calibration set and a validation prediction set with a ratio of 4:1. The values of Root Mean Square Error of leave-one-out Cross-Validation (RMSECV) and the coefficient of determination (R2) of the calibration model was 2.95 s and 0.92 respectively, with eight PLS factors used. The results of the paired t-test revealed that there was no significant difference between the NIR method and the reference method. The analytical result showed that, NIR spectroscopy was a rapid, nondestructive, and accurate method for real-time prediction of prepreg quality in the CCL manufacturing process.

scholarly journals Estimate of the density of Eucalyptus grandis W. Hill ex Maiden using near infrared spectroscopy

CERNE ◽  
2013 ◽  
Vol 19 (4) ◽  
pp. 647-652 ◽  
Author(s):  
Silviana Rosso ◽  
Graciela Ines Bolzon de Muniz ◽  
Jorge Luis Monteiro de Matos ◽  
Clóvis Roberto Haselein ◽  
Paulo Ricardo Gherardi Hein ◽  
...  
Keyword(s):  
Infrared Spectroscopy ◽  
Wood Density ◽  
Near Infrared Spectroscopy ◽  
Near Infrared ◽  
Eucalyptus Grandis ◽  
Basic Density ◽  
Coefficient Of Determination ◽  
Least Squares Regression ◽  
Old Trees

This study aimed to analyze use of near infrared spectroscopy (NIRS) to estimate wood density of Eucalyptus grandis. For that, 66 27-year-old trees were logged and central planks were removed from each log. Test pieces 2.5 x 2.5 x 5.0 cm in size were removed from the base of each plank, in the pith-bark direction, and subjected to determination of bulk and basic density at 12% moisture (dry basis), followed by spectral readings in the radial, tangential and transverse directions using a Bruker Tensor 37 infrared spectrophotometer. The calibration to estimate wood density was developed based on the matrix of spectra obtained from the radial face, containing 216 samples. The partial least squares regression to estimate bulk wood density of Eucalyptus grandis provided a coefficient of determination of validation of 0.74 and a ratio performance deviation of 2.29. Statistics relating to the predictive models had adequate magnitudes for estimating wood density from unknown samples, indicating that the above technique has potential for use in replacement of conventional testing.

Analysis of Betaines Using near Infrared Spectroscopy

2005 ◽  
Vol 13 (3) ◽  
pp. 133-138 ◽  
Author(s):  
Emma Ibarra ◽  
Omar Valencia ◽  
Héctor Pérez
Keyword(s):  
Infrared Spectroscopy ◽  
Sodium Chloride ◽  
Near Infrared Spectroscopy ◽  
Near Infrared ◽  
Accurate Method ◽  
Coefficient Of Determination ◽  
Active Matter ◽  
Surface Active Properties ◽  
Surface Active ◽  
True Values

Cocoamidopropyl betaines are becoming increasingly important in cosmetic formulations because of their mild and effective surface active properties. A simple and accurate method is needed for quality control during the production of betaines. The aim of the present study was to determine if near infrared spectroscopy can replace wet methods for routine analysis of betaine. The calibration curve was obtained by partial least squares. The optimisation of calibration factors was guided by coefficient of determination ( R2) and the root mean square error of evaluation ( RMSEE). R2 was 0.99 or higher and RMSEE 0.025, 0.071, 0.03% and 0.007 units for active matter, sodium chloride, solids and pH, respectively. The method was validated with independent samples in the same manner on a different day and true values were obtained with R2 of 0.99 or higher and root mean standard error of prediction of 0.060, 0.074, 0.075% and 0.035 units for active matter, sodium chloride, solids and pH, respectively.

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