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Detection Methods
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Major factors influencing the quantification of Nile Red stained microplastics and improved automatic quantification (MP-VAT 2.0)
The Science of The Total Environment2020
99 citations
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Citation count from OpenAlex, updated daily. May differ slightly from the publisher's own count.
Score: 40
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0–100 AI score estimating relevance to the microplastics field. Papers below 30 are filtered from public browse.
Joana C. Prata,
João Pinto da Costa,
Joana C. Prata,
Joana C. Prata,
Joana C. Prata,
Joana C. Prata,
Joana C. Prata,
Joana C. Prata,
Joana C. Prata,
João Pinto da Costa,
João Pinto da Costa,
João Pinto da Costa,
Joana C. Prata,
Joana C. Prata,
Joana C. Prata,
João Pinto da Costa,
Joana C. Prata,
Joana C. Prata,
Joana C. Prata,
Armando C. Duarte,
Joana C. Prata,
Joana C. Prata,
Joana C. Prata,
Joana C. Prata,
Joana C. Prata,
Joana C. Prata,
João Pinto da Costa,
Joana C. Prata,
Joana C. Prata,
Joana C. Prata,
Joana C. Prata,
Joana C. Prata,
Joana C. Prata,
João Pinto da Costa,
Joana C. Prata,
João Pinto da Costa,
Joana C. Prata,
Joana C. Prata,
Joana C. Prata,
Joana C. Prata,
Joana C. Prata,
Joana C. Prata,
Joana C. Prata,
Joana C. Prata,
Joana C. Prata,
Joana C. Prata,
Joana C. Prata,
Joana C. Prata,
Joana C. Prata,
Joana C. Prata,
Joana C. Prata,
Teresa Rocha‐Santos
Teresa Rocha‐Santos
Teresa Rocha‐Santos
Teresa Rocha‐Santos
João Pinto da Costa,
João Pinto da Costa,
João Pinto da Costa,
João Pinto da Costa,
João Pinto da Costa,
João Pinto da Costa,
João Pinto da Costa,
João Pinto da Costa,
João Pinto da Costa,
João Pinto da Costa,
João Pinto da Costa,
João Pinto da Costa,
João Pinto da Costa,
João Pinto da Costa,
João Pinto da Costa,
João Pinto da Costa,
João Pinto da Costa,
Joana C. Prata,
Joana C. Prata,
Armando C. Duarte,
João Pinto da Costa,
Joana C. Prata,
Joana C. Prata,
João Pinto da Costa,
Armando C. Duarte,
Joana C. Prata,
Armando C. Duarte,
Armando C. Duarte,
Joana C. Prata,
Armando C. Duarte,
Armando C. Duarte,
João Pinto da Costa,
Teresa Rocha‐Santos
João Pinto da Costa,
Armando C. Duarte,
Teresa Rocha‐Santos
Joana C. Prata,
Teresa Rocha‐Santos
Jorge Alves,
João Pinto da Costa,
João Pinto da Costa,
Armando C. Duarte,
Armando C. Duarte,
Armando C. Duarte,
Armando C. Duarte,
João Pinto da Costa,
João Pinto da Costa,
João Pinto da Costa,
João Pinto da Costa,
João Pinto da Costa,
João Pinto da Costa,
João Pinto da Costa,
Jorge Alves,
Joana C. Prata,
João Pinto da Costa,
Joana C. Prata,
Joana C. Prata,
Joana C. Prata,
Armando C. Duarte,
Joana C. Prata,
Joana C. Prata,
Armando C. Duarte,
João Pinto da Costa,
João Pinto da Costa,
João Pinto da Costa,
João Pinto da Costa,
João Pinto da Costa,
João Pinto da Costa,
João Pinto da Costa,
João Pinto da Costa,
João Pinto da Costa,
João Pinto da Costa,
João Pinto da Costa,
João Pinto da Costa,
João Pinto da Costa,
João Pinto da Costa,
João Pinto da Costa,
João Pinto da Costa,
João Pinto da Costa,
João Pinto da Costa,
João Pinto da Costa,
João Pinto da Costa,
Armando C. Duarte,
Armando C. Duarte,
Armando C. Duarte,
Armando C. Duarte,
Armando C. Duarte,
Armando C. Duarte,
Armando C. Duarte,
Armando C. Duarte,
Armando C. Duarte,
Armando C. Duarte,
Teresa Rocha‐Santos
Teresa Rocha‐Santos
Teresa Rocha‐Santos
Teresa Rocha‐Santos
Teresa Rocha‐Santos
Teresa Rocha‐Santos
Joana C. Prata,
Joana C. Prata,
Jorge Alves,
Jorge Alves,
João Pinto da Costa,
Armando C. Duarte,
Armando C. Duarte,
João Pinto da Costa,
Armando C. Duarte,
Teresa Rocha‐Santos
Armando C. Duarte,
Teresa Rocha‐Santos
Teresa Rocha‐Santos
João Pinto da Costa,
Teresa Rocha‐Santos
Teresa Rocha‐Santos
João Pinto da Costa,
João Pinto da Costa,
Armando C. Duarte,
Armando C. Duarte,
Armando C. Duarte,
Teresa Rocha‐Santos
Teresa Rocha‐Santos
Teresa Rocha‐Santos
Armando C. Duarte,
João Pinto da Costa,
Armando C. Duarte,
João Pinto da Costa,
Armando C. Duarte,
Armando C. Duarte,
João Pinto da Costa,
Armando C. Duarte,
Armando C. Duarte,
Armando C. Duarte,
Armando C. Duarte,
Teresa Rocha‐Santos
Armando C. Duarte,
Armando C. Duarte,
Armando C. Duarte,
Armando C. Duarte,
Armando C. Duarte,
Teresa Rocha‐Santos
Teresa Rocha‐Santos
Teresa Rocha‐Santos
Teresa Rocha‐Santos
Teresa Rocha‐Santos
Teresa Rocha‐Santos
Teresa Rocha‐Santos
Teresa Rocha‐Santos
Teresa Rocha‐Santos
Teresa Rocha‐Santos
Teresa Rocha‐Santos
Teresa Rocha‐Santos
Teresa Rocha‐Santos
Teresa Rocha‐Santos
Teresa Rocha‐Santos
Teresa Rocha‐Santos
Teresa Rocha‐Santos
Teresa Rocha‐Santos
Teresa Rocha‐Santos
Armando C. Duarte,
Armando C. Duarte,
Teresa Rocha‐Santos
Teresa Rocha‐Santos
Teresa Rocha‐Santos
Armando C. Duarte,
Armando C. Duarte,
Armando C. Duarte,
Armando C. Duarte,
Armando C. Duarte,
Armando C. Duarte,
Armando C. Duarte,
Armando C. Duarte,
Armando C. Duarte,
Armando C. Duarte,
Armando C. Duarte,
Armando C. Duarte,
Armando C. Duarte,
Armando C. Duarte,
Armando C. Duarte,
João Pinto da Costa,
Armando C. Duarte,
Armando C. Duarte,
Armando C. Duarte,
Armando C. Duarte,
Armando C. Duarte,
João Pinto da Costa,
Teresa Rocha‐Santos
Teresa Rocha‐Santos
Armando C. Duarte,
Teresa Rocha‐Santos
Teresa Rocha‐Santos
Teresa Rocha‐Santos
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Armando C. Duarte,
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Teresa Rocha‐Santos
Teresa Rocha‐Santos
Teresa Rocha‐Santos
Teresa Rocha‐Santos
Teresa Rocha‐Santos
Teresa Rocha‐Santos
Armando C. Duarte,
João Pinto da Costa,
Armando C. Duarte,
Armando C. Duarte,
Armando C. Duarte,
Teresa Rocha‐Santos
Armando C. Duarte,
Teresa Rocha‐Santos
Teresa Rocha‐Santos
Teresa Rocha‐Santos
Teresa Rocha‐Santos
Teresa Rocha‐Santos
Armando C. Duarte,
Teresa Rocha‐Santos
Teresa Rocha‐Santos
Teresa Rocha‐Santos
João Pinto da Costa,
Armando C. Duarte,
Teresa Rocha‐Santos
Armando C. Duarte,
Armando C. Duarte,
Teresa Rocha‐Santos
Teresa Rocha‐Santos
Teresa Rocha‐Santos
Teresa Rocha‐Santos
Teresa Rocha‐Santos
Teresa Rocha‐Santos
Armando C. Duarte,
Teresa Rocha‐Santos
Teresa Rocha‐Santos
Armando C. Duarte,
Teresa Rocha‐Santos
Summary
Researchers identified key variables — staining conditions, camera settings, and image processing — that introduce quantification errors when using Nile Red fluorescence to count microplastics, and developed an improved automated tool (MP-VAT 2.0) to reduce this variability. The upgraded system provides more reliable, reproducible results for high-throughput microplastic analysis.
Automated count of Nile Red fluorescent microplastics allows fast and reliable quantification. However, factors involving staining, digital camera conditions and settings introduce variability to the results. The objective of this paper is to identify and propose solutions to these factors and improve on the previous MP-VAT script. While removal of digital sensor defects had little influence on results and staining can be reduced to 5 min, Nile Red concentrations cannot be reduced <0.01 mg mL, the 470 nm LED lantern emission must be >1600 lx, and photographic conditions should be maintained as stable as possible ideally improving the filter membrane area and using the recommended settings of 2 s, ISO100, F5.6. It was also found that Nile Red can be removed from microplastics using acetone or hydrogen peroxide with iron. More importantly, both particles and fluorescent are lost with time and thus quantification should be conducted within a week. Finally, MP-VAT 2.0 was developed to remove unselected areas and to identify only red particles, excluding white reflections from quantification. This updated version of MP-VAT produced improved recovery rates of 98.2 ± 6.9 for spiked samples and 95.9 ± 10.3 on actual environmental samples, presenting a cheap and reliable complementary method for microplastic identification.