Health Risk Assessment of Pesticide Residues in Three Representative Tropical Fruits From Agricultural Crops in Antioquia, Colombia (2025)
Tropical fruits are of great importance to Colombian agriculture due to their high export potential, which has shown an increasing trend in recent years. By 2023, fruits such as Golden Gooseberry (GG) (Physalis peruviana), Purple Passion Fruit (PPF) (Passiflora edulis) and Hass Avocado (HA) (Persea americana var. Hass) accounted for 6.8% (3.6 million USD), 7.7% (4.2 million USD), and 26.2% (14.1 million USD), respectively, of the total export revenue (53.6 million USD) in the country. GG, PPF and HA have proven to be fruit suppliers of excellent functional compounds to human health and these three fruits are highly cultivated in Antioquia region of Colombia. However, the excessive use of pesticides on the crops may contaminate food and cause several health issues in humans, which have concerned researchers from all over the globe. Therefore, regulatory bodies and surveillance organizations have established maximum residue levels (MRLs) for these compounds to ensure food safety for consumers. On this way, monitoring of pesticides and the human health risk evaluation of their concentration levels in food have become important issues to guarantee the safety of the population. Hence, this research was focused on the analysis of 74 pesticides in GG, PPF and HA samples collected from agricultural crops located at the eastern site of the Department of Antioquia to mainly assess the risk that these substances posed to consumer health based on the concentration results obtained by UPLC-MS/MS. To achieve this objective, validation methodologies were performed for the matrices under study according to the recommendations of SANTE guideline; Matrix effect (ME) was assessed as part of the validation procedure in the three matrices of study using both calibration-graph and concentration-based methods which compare matrix-matched and solvent calibration curves for every pesticide. The results obtained from the ME assessment showed that the nature of the matrix (aqueous or fatty) is an implicated variable in the quantification of pesticides. In this way, most of the pesticides showed to have related behavior (ion suppression/enhancement) in GG and PPF but different in HA. Despite most of the compounds tending to have a similar behavior in the aqueous matrices, some compounds exhibited opposite behavior in the same two fruits. Consequently, we highlighted the importance of validating each fruit matrix even within a single commodity group to prevent false negative or positive results during routine analysis. This refutes the recommendation given at the SANTE guideline to validate one matrix per commodity group as minimum to run routine analysis in a whole group. Likewise, the lower levels of concentration demonstrated to be more affected than higher levels by ME (within the calibration range). Therefore, the concentration-based method applied to individual matrices exhibited to be the most proper way to assess the ME due to the obtention of more accurate results for all analytes by each concentration level. Thus, this research evidences a great strategy for multi-residue pesticide determination in fruits with the obtention of non-biased and more trustworthy results than those usually reported by using matrix/solvent-matched calibration curves. On the other hand, the average concentration of the determined pesticides showed to be below their respective MRLs, except for methamidophos in GG. The health risk associated with dietary consumption of these compounds was evaluated by a point estimation method (deterministic) and a Monte Carlo simulation (probabilistic), where factors such as pesticide concentration, food eating rate, body weight and time of exposure were considered. The results suggested that the quantified concentrations exhibit Hazard Indexes (HI) < 1 using both assessments methods, indicating an acceptable long-term risk and a favorable residual state of the studied crops for fruit consumption. However, the probabilistic method demonstrates to be more precise and realistic due to the confidence intervals that account for uncertainty and variability of exposure, thereby providing a more comprehensive representation of consumers potentially at risk. One of the most remarkable outcomes of this study was to demonstrate the importance of determining the ME for each individual fruit even within the same commodity group to conduct unbiased multi-residue pesticide analyses. Nevertheless, it is recommended that future research delve deeper into the specific chemical components influencing pesticide behavior within matrices of similar nature (e.g. citrus fruits: oranges, lemons, limes) as well as the behavioral observation and comparison across different pesticide chemical families.