DETECTION OF MICRO(NANO)PLASTICS IN EDIBLE CROPS:A CRITICAL REVIEW OF ANALYTICAL EVIDENCE


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Civan M.

23th INTERNATIONAL İSTANBUL SCIENTIFIC RESEARCH CONGRESS ON LIFE, ENGINEERING, ARCHITECTURE, AND MATHEMATICAL SCIENCES, İstanbul, Türkiye, 20 Kasım - 22 Aralık 2025, cilt.1, sa.1, ss.1271-1279, (Tam Metin Bildiri)

  • Yayın Türü: Bildiri / Tam Metin Bildiri
  • Cilt numarası: 1
  • Doi Numarası: 10.30546/19023.978-9952-8605-7-3.2025.0125-
  • Basıldığı Şehir: İstanbul
  • Basıldığı Ülke: Türkiye
  • Sayfa Sayıları: ss.1271-1279
  • Kocaeli Üniversitesi Adresli: Evet

Özet

The presence of microplastics and nanoplastics (MNPs) in agricultural systems has emerged as a

potential risk to food safety and human health. Edible crops may act as entry points for these plastic

particles into the food chain, yet evidence of their accumulation and translocation remains limited. In

this study, we review and synthesize recent research employing pyrolysis–gas chromatography–mass

spectrometry (Py-GC–MS) to detect M(N)Ps in various edible crops, including cucumber, lettuce,

cowpea, flowering cabbage, rutabaga, and pak choi. Studies included both field-collected and

controlled-environment (greenhouse, hydroponic) samples. Py-GC–MS analysis confirmed the presence

of polymers such as polystyrene (PS), polyethylene (PE), polyvinyl chloride (PVC), polyethylene

terephthalate (PET), and nylon-66 in plant tissues, with reported concentrations ranging from low

nanogram to several hundred micrograms per gram dry weight. Root tissues showed the highest

accumulation, although some studies demonstrated limited upward translocation to edible shoots or

leaves. Factors influencing uptake included particle size, plant species, exposure pathway, and soil type.

These findings provide chemical confirmation that micro- and nanoplastics can accumulate in edible

crops, highlighting the need for further investigation into plant uptake mechanisms, human exposure

risks, and mitigation strategies. Py-GC–MS continues to serve as a critical tool for polymer-specific

identification and quantification in complex biological matrices.