Determination of concentration of ACQ wood preservative components by UV-Visible spectroscopy coupled with multivariate data analysis

Adedipe, Oluwatosin E.; Dawson-Andoh, Benjamin; Atta-Obeng, Emmanuel; Slahor, Jeffrey J.; Osborn, Larry

doi:10.1016/j.chemolab.2015.07.013

Cited by 9 publications

(2 citation statements)

References 11 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The traditional methods are based on wet chemical analysis such as High Performance Liquid Chromatography (HPLC), which is very time-consuming. In addition some important solid-state information could be lost because the solid form is dissolved in a liquid to form a solution [4,5]. On the other hand, there are several powder-based methods for the assessment of component inhomogeneity, which are briefly reviewed below.…”

Section: Introductionmentioning

confidence: 99%

Assessment of Near-Infrared (NIR) spectroscopy for segregation measurement of low content level ingredients

et al. 2017

View full text Add to dashboard Cite

Segregation in particulate systems may be caused by particle size, density and shape distributions leading to negative effects on product quality as well as the production costs. Quantifying powder segregation using a reliable and robust method is challenging, particularly for low content level ingredients. In this paper, we evaluate the application of NIR spectral analysis for detecting the extent of segregation of components in a multi-component mixture. As a model system, a typical laundry detergent formulation, comprising spray-dried powder, known as Blown Powder (BP), Tetraacetylethylenediamine (TAED) and enzyme placebo granules, is used. The effect of using different pre-processing methods on the measured component fractions is analysed. These are scatter correction using Standard Normal Variate (SNV) as well as derivative correction using first, second, Norris-Williams and Savitzky-Golay derivatives. The results from the NIR technique are compared to those obtained by image analysis. Concepts of Mean Absolute Error (MAE) and Mean Absolute Percentage Error (MAPE) are used to evaluate the accuracy of different preprocessing methods. The second derivative of Norris-Williams method shows the best pre-processing method for the quantification of low content level enzyme placebo granules in the ternary mixture of detergent powder. Using the proposed NIR technique and the optimum pre-processing method, the segregation index of a low content level ingredient, such as enzyme placebo granules, is estimated to be 0.71 for a ternary heap of washing powders.

show abstract

Section: Introductionmentioning

confidence: 99%

Assessment of Near-Infrared (NIR) spectroscopy for segregation measurement of low content level ingredients

et al. 2017

View full text Add to dashboard Cite

show abstract

“…Partial Least Square Discriminant Analysis is a linear classification method that is based on the PLS regression algorithm [8,16]. This method is a combination of properties of partial least squares regression and the discrimination power of classification technique.…”

Section: Pls Discriminant Analysis (Pls-da)mentioning

confidence: 99%

Comparison Analysis: Large Data Classification Using PLS-DA and Decision Trees

Rashid¹,

Nasaruddin²,

Kassim³

et al. 2020

View full text Add to dashboard Cite

Classification studies are widely applied in many areas of research. In our study, we are using classification analysis to explore approaches for tackling the classification problem for a large number of measures using partial least square discriminant analysis (PLS-DA) and decision trees (DT). The performance for both methods was compared using a sample data of breast tissues from the University of Wisconsin Hospital. A partial least square discriminant analysis (PLS-DA) and decision trees (DT) predict the diagnosis of breast tissues (M = malignant, B = benign). A total of 699 patients diagnose (458 benign and 241 malignant) are used in this study. The performance of PLS-DA and DT has been evaluated based on the misclassification error and accuracy rate. The results show PLS-DA can be considered as a good and reliable technique to be used when dealing with a large dataset for the classification task and have good prediction accuracy.

show abstract

Reaction mechanisms inhibiting the release of aqueous extracts from merbau heartwood by iron(II) and copper(II)

et al. 2017

View full text Add to dashboard Cite

Determination of concentration of ACQ wood preservative components by UV-Visible spectroscopy coupled with multivariate data analysis

Cited by 9 publications

References 11 publications

Assessment of Near-Infrared (NIR) spectroscopy for segregation measurement of low content level ingredients

Assessment of Near-Infrared (NIR) spectroscopy for segregation measurement of low content level ingredients

Comparison Analysis: Large Data Classification Using PLS-DA and Decision Trees

Reaction mechanisms inhibiting the release of aqueous extracts from merbau heartwood by iron(II) and copper(II)

Contact Info

Product

Resources

About