Back

Plant functional defects experienced upon growth under Per-/Poly-fluoroalkyl substances (PFAS) conditions

Lim, J.; McKirdy, N.

2026-08-18 plant biology
10.64898/2026.08.14.743998 bioRxiv
Show abstract

Per- and polyfluoroalkyl substances (PFAS) pose significant environmental risks, yet their impact on food crops like legumes remain insufficiently understood. This study investigated the developmental and physiological responses of hydroponically grown mung bean (Vigna radiata) to varying concentrations of perfluorooctanoic acid (PFOA) and perfluorooctanesulfonic acid (PFOS). High concentrations (1 mM) of PFOA severely impaired early plant development, significantly delaying seed germination, reducing leaf emergence, and suppressing root hair formation compared to PFOS and controls. Over a narrower concentration range (5-500 {micro}M), both compounds caused transient growth stunting at early timepoints (48 h), though plants exhibited partial recovery over time. High-dose exposure (500 {micro}M) significantly decreased seedling wet weights, leaf area, and leaf biomass without affecting dry weights, indicating disrupted water retention and homeostasis rather than reduced biomass accumulation. Spectrophotometric analysis revealed a dose- and compound-dependent effect on photosynthesis, with low-dose PFOA (5 {micro}M) significantly increasing leaf chlorophyll absorbance. Furthermore, quantification of callose deposition revealed that high-dose PFOA (500 {micro}M) and medium-dose PFOS (50 {micro}M) raised baseline immune stress responses, which were not further elevated by subsequent flagellin-22 (flg22) challenge, suggesting a contaminant-induced immune priming mechanism. These findings highlight distinct, chemical-specific toxicological impact of PFAS on legume growth, water dynamics, and defence priming, underscoring critical implications for agricultural productivity and food safety.

Matching journals

The top 5 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.