Intelligent image-based colourimetric tests using machine learning framework for lateral flow assays

This paper aims to deliberately examine the scope of an intelligent colourimetric test that fulfils ASSURED criteria (Affordable, Sensitive, Specific, User-friendly, Rapid and robust, Equipment-free, and Deliverable) and demonstrate the claim as well. This paper presents an investigation into an intelligent image-based system to perform automatic paper-based colourimetric tests in real-time to provide a proof-of-concept for a dry-chemical based or microfluidic, stable and semi-quantitative assay using a larger dataset with diverse conditions. The universal pH indicator papers were utilised as a case study. Unlike the works done in the literature, this work performs multiclass colourimetric tests using histogram based image processing and machine learning algorithm without any user intervention. The proposed image processing framework is based on colour channel separation, global thresholding, morphological operation and object detection. We have also deployed a server based convolutional neural network framework for image classification using inductive transfer learning on a mobile platform. The results obtained by both traditional machine learning and pre-trained model-based deep learning were critically analysed with the set evaluation criteria (ASSURED criteria). The features were optimised using univariate analysis and exploratory data analysis to improve the performance. The image processing algorithm showed >98% accuracy while the classification accuracy by Least Squares Support Vector Machine (LS- SVM) was 100%. On the other hand, the deep learning technique provided >86% accuracy, which could be further improved with a large amount of data. The k-fold cross validated LS- SVM based final system, examined on different datasets, confirmed the robustness and reliability of the presented approach, which was further validated using statistical analysis. The understaffed and resource limited healthcare system can benefit from such an easy-to-use technology to support remote aid workers, assist in elderly care and promote personalised healthcare by eliminating the subjectivity of interpretation

Spectrophotometric flow-injection analysis assay of tetracycline antibiotics using a dual light-emitting diode based detector

In this paper, a small dual light-emitting diode (LED)-based detector for FIA process analyser has been designed. The detector’s optical parts comprise a flow-through cell, a dual-blue LED and a photodiode. Neither mirrors nor lenses are used. The optical path for the first LED detects the blank, while the other LED detects the sample. The detector’s electronic components including a signal amplifier and an A/D converter are integrated on one small board connected to a PC for measuring the results. The designed spectrophotometric detector was used for the determination of tetracycline antibiotics. Uranyl acetate was used as a reagent forming orange-red complexes with the drugs in N,N– dimethylformamide. The complexes show absorption maxima at 410, 416 and 408 nm for tetracycline hydrochloride (TCH), chlortetracycline hydrochloride (CTCH), and doxycycline hydrochloride (DCH), respectively. The detection limit was found to be 0.38, 0.75, 1.44 µg mL-1 and the linear range was obtained at 1.0-3.0, 3.0-5.0, and 3.0-10.0 µg mL-1 for TCH, CTCH and DCH, respectively. The proposed method has been successfully applied to the determination of tetracycline antibiotic residues in milk samples. Moreover, this method is an environmentally friendly approach and suitable for routine analysis

On-line preconcentration and determination of tetracycline residues in milk using solid-phase extraction in conjunction with flow injection spectrophotometry

A simple, cheap and highly sensitive system with on-line preconcentration using solid-phase extraction in conjunction with flow injection spectrophotometry for the determination of tetracycline residues in milk samples is described. C18 was used as packing material in a designed minicolumn used for preconcentration of tetracyclines. Tetracycline standard or sample solutions were dissolved in a mixed buffer solution of pH 4.0 containing boric acid, citric acid and sodium phosphate, then loaded to the minicolumn for 6 min followed by elution with a solution containing methanol : mixed buffer solution (40:60 by volume) of pH 6.5 The absorbance of the eluate was measured at 370 nm. The calibration graph was linear in the range of 0.20-1.00, 0.20-4.00, and 0.20-1.00 mg L-1 for tetracycline (TC), oxytetracycline (OTC), and chlortetracycline (CTC) respectively. The limits of detection were 0.08, 0.10, and 0.09mg L-1 for TC, OTC, and CTC respectively. Relative standard deviations for 20 replicated determinations of 0.20, 0.40, and 0.60 mg L-1 of TC were 7.03, 7.23, and 6.55 % respectively. Per cent recoveries for four commercial types of milk: U.H.T., pasteurised, raw, and sterilised milk were in the range of 86–109 (TC), 90–109 (OTC), and 89–108 (CTC). The sample throughput was 6 h-1

The determination of tetracycline residues in food using a disposable screen-printed gold electrode (SPGE)

The electrochemical analysis of tetracyclines was investigated using a gold screen-printed electrode by cyclic voltammetry and flow injection analysis with dc amperometry. Cyclic voltammetry was used to study the electrochemical oxidation of tetracyclines. For all the tetracyclines investigated a well-defined cyclic voltammogram providing the highest peak current, at 1.2 V versus Ag/AgCl, was obtained when using potassium dihydrogen phosphate solution at pH 2. Flow injection analysis with dc amperometry using the specially fabricated wall-jet flow-through cell was also studied. Under amperometric conditions (Eapp = 1.2 V; flow rate = 2.0 mL min−1), analytical calibration graphs for tetracycline, chlortetracycline and oxytetracycline were obtained from 1 to 500, 5 to 50 and 1 to 500 μmol L−1 with detection limits of 0.96, 0.58 and 0.35 μmol L−1, respectively. The proposed method was successfully applied to the determination of tetracycline, chlortetracycline and oxytetracycline in pharmaceutical products and foods