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Modelling the Combined Effects of Oxalic Acid, Water Activity, and pH on the Growth and Mycotoxin Production of Aspergillus spp. in a Dried Fig System

Summary

This research develops computer models to predict when dangerous molds grow on dried figs and produce toxins. Scientists tested how wet the figs are, their acidity, and a natural plant compound called oxalic acid affect the growth of two common toxic molds. The study found that drier figs are much safer from toxin production, and while oxalic acid alone isn’t a strong mold-fighter, it can help when combined with other conditions. These models can help the fig industry prevent contamination and keep dried figs safe for consumers.

Background

Dried figs are susceptible to fungal contamination, particularly by Aspergillus welwitschiae and Aspergillus flavus, which produce ochratoxin A (OTA) and aflatoxins (AFs) respectively. Traditional sun-drying methods combined with high sugar content promote mycotoxin accumulation. Recent research has explored oxalic acid (OA) as a plant elicitor to enhance fruit quality and potentially inhibit fungal growth, though its interactive effects with abiotic factors remain largely unexplored.

Objective

To model the combined effects of water activity (aw), pH, and oxalic acid concentration on the growth and mycotoxin production of A. welwitschiae and A. flavus using response surface methodology (RSM) with Box-Behnken design (BBD). The study aimed to develop semi-quantitative predictive tools for identifying high-risk conditions in dried fig systems.

Results

Water activity was the most influential factor, with aw 0.92 significantly delaying growth and completely inhibiting OTA and AFB1 production, while aw 0.99 was prerequisite for significant mycotoxin accumulation. OA at tested elicitor concentrations was not a potent independent inhibitor but showed significant interactions with aw and pH in delaying growth. Growth models showed high R² values (>96%), while mycotoxin models had more moderate R² values (51-86%), reflecting secondary metabolism complexity.

Conclusion

The developed models serve as valuable semi-quantitative tools for identifying high-risk conditions for mycotoxin contamination in dried figs. Water activity emerged as the critical controlling factor for fungal behavior and toxin production. These models provide practical frameworks for the fig industry to implement predictive control strategies, though mycotoxin models should be regarded as trend-identification tools rather than precise quantitative predictors.
  • Published in:Foods,
  • Study Type:Experimental Research,
  • Source: PMID: 41300011
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