Detection of antibiotic and microplastic pollutants in Chrysanthemum coronarium L. based on chlorophyll fluorescence

Abstract

Abbreviations : ChlF – chlorophyll a fluorescence; F i – chlorophyll a fluorescence intensity at the I F j chlorophyll a fluorescence intensity at the m maximal fluorescence yield dark-adapted F minimal fluorescence yield of the dark-adapted variable fluorescence quantum of photochemistry; v quantum of photosystem chlorophyll fluorescence Large amounts of antibiotics and microplastics are used in daily life and agricultural production, which affects not only plant growth but also potentially the food safety of vegetables and other plant products. Fast detection of the presence of antibiotics and microplastics in leafy vegetables is of great interest to the public. In this work, a method was developed to detect sulfadiazine and polystyrene, commonly used antibiotics and microplastics, in vegetables by measuring and modeling photosystem II chlorophyll a fluorescence (ChlF) emission from leaves. Chrysanthemum coronarium L., a common beverage and medicinal plant, was used to verify the developed method. Scanning electron microscopy, transmission electron microscopy, and liquid chromatograph-mass spectrometer analysis were used to show the presence of the two pollutants in the samples. The developed kinetic model could describe measured ChlF variations with an average relative error of 0.6%. The model parameters estimated for the chlorophyll a fluorescence induction kinetics curve (OJIP) induction can differentiate the two types of stresses while the commonly used ChlF OJIP induction characteristics cannot. This work provides a concept to detect antibiotic pollutants and microplastic pollutants in vegetables based on ChlF.