We can't find the internet
Attempting to reconnect
Something went wrong!
Hang in there while we get back on track
New insights from correlation analysis of microplastics on strawberry surfaces with microplastics in air and pesticides
AI summary Read the abstract
Researchers used hyperspectral imaging and linear analysis to detect and characterize microplastic contamination on strawberry surfaces, identifying correlations between plastic particle characteristics and spectral signatures that could be used to develop real-time food safety monitoring systems.
With the global increase in plastic pollution, microplastic contamination of agricultural products has become an emerging environmental issue that threatens food safety. In this study, linear analysis combined with principal component analysis was used to determine the correlation between microplastics in air and pesticides and the abundance and components of microplastics on the surface of strawberries, which fills the gap of traceability studies of microplastics on the surface of agricultural products. A high correlation coefficient of 0.65 was observed between microplastics on strawberry surfaces and the microplastic abundance in the air; however, the correlation coefficient with the abundance of microplastics in pesticides was only 0.30, which was weak. Polypropylene, polyamide and polyethylene were the polymers detected in the largest proportion of all experimental samples. Polypropylene had the highest percentage of detections in air and pesticides at 70.66 % and 74.04 %, respectively. The percentages of polypropylene, polyamide and polyethylene on strawberry surfaces were 36.97 %, 29.20 % and 17.36 %, respectively. This study provides scientific support for the formulation of microplastic limit standards for agricultural products and the optimization of agricultural production norms, which is of strategic significance for guaranteeing food safety and promoting the sustainable development of agriculture.
More Papers Like This
A novel way to rapidly monitor microplastics in soil by hyperspectral imaging technology and chemometrics
AI summary Read the abstract
Hyperspectral imaging combined with chemometrics was demonstrated as a novel way to rapidly detect and map multiple types of microplastics in soil samples, identifying particles of different polymer types based on their spectral signatures. The approach could enable faster and more spatially detailed monitoring of microplastic contamination in agricultural and environmental soils.
Characterization of microplastics on filter substrates based on hyperspectral imaging: Laboratory assessments
AI summary Read the abstract
Researchers evaluated near-infrared hyperspectral imaging as a method for characterizing microplastics on filter substrates, finding that 11 plastic polymers exhibited distinct spectral features at specific wavelength ranges enabling automatic identification, and also assessed the spectral compatibility of 11 different filter substrate materials.
Hyperspectral imaging as an emerging tool to analyze microplastics: A systematic review and recommendations for future development
AI summary Read the abstract
This systematic review evaluates hyperspectral imaging as a faster, more efficient method for detecting and identifying microplastics. Better detection technology is critical for understanding how much microplastic contamination exists in our food, water, and environment, and for assessing human exposure levels.
Microplastics enter strawberry fruit tissues directly through the epidermis
AI summary Read the abstract
Researchers directly imaged polystyrene microplastic uptake into strawberry fruit tissue, showing that micron-sized particles enter primarily through stomata while nanoscale particles also use endocytosis, and that surface exposure to these particles reduced fruit weight, increased acidity, and altered antioxidant composition — suggesting atmospheric microplastics are an underappreciated route of contamination in edible crops.
Hyperspectral imaging: An early systematic review of emerging applications for rapid microplastic analysis
AI summary Read the abstract
This systematic review examines the emerging use of hyperspectral imaging technology for detecting and analyzing microplastics in environmental samples. Better detection methods matter for human health because accurately measuring microplastic contamination in water, food, and air is essential for understanding our true level of exposure and developing effective strategies to reduce it.
Research digests by email
When a large batch of papers lands in the Atlas, we read through it and send a short write-up of what stood out.