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Mehedi Hassan

Researcher at Jiangsu University

Publications -  62
Citations -  1778

Mehedi Hassan is an academic researcher from Jiangsu University. The author has contributed to research in topics: Chemistry & Detection limit. The author has an hindex of 17, co-authored 46 publications receiving 735 citations. Previous affiliations of Mehedi Hassan include Jimei University.

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Near infrared system coupled chemometric algorithms for enumeration of total fungi count in cocoa beans neat solution

TL;DR: Fourier transform near infrared spectroscopy combined with FT-NIRS combined with Si-GAPLS may be employed for in-situ and noninvasive quantification of TFC in cocoa beans for quality and safety monitoring.
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Evolving trends in SERS-based techniques for food quality and safety: A review

TL;DR: In order to establish SERS as a routine tool for the monitoring of food safety and quality, future research should focus on minimizing technical costs, standardizing experimental protocols, developing new SERS substrates, and integrating SERS with other methods to overcome its shortcomings.
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Fabricating an Acetylcholinesterase Modulated UCNPs-Cu2+ Fluorescence Biosensor for Ultrasensitive Detection of Organophosphorus Pesticides-Diazinon in Food.

TL;DR: The ability of the biosensor to detect OPs was also confirmed in adulterated environmental and agricultural samples and in validation analysis, the proposed sensor showed satisfactory results.
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Mesoporous silica supported orderly-spaced gold nanoparticles SERS-based sensor for pesticides detection in food.

TL;DR: A novel sensor fabricated with compactly arranged gold nanoparticles (AuNPs) templated from mesoporous silica film (MSF) via air-water interface has been confirmed as a promising surface-enhanced Raman scattering (SERS) substrate for detecting trace levels of 2,4-dichlorophenoxyacetic acid, pymetrozine and thiamethoxam.
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An Overview on the Applications of Typical Non-linear Algorithms Coupled With NIR Spectroscopy in Food Analysis

TL;DR: An overview of the application of non- linear algorithms in food quality and safety specific to NIR spectroscopy along with different non-linear models such as artificial neural network (ANN), AdaBoost, local algorithm (LA), support vector machine (SVM), and extreme learning machine (ELM).