Fuente: PubMed "apiculture" Food Sci Biotechnol. 2026 Jun 29;35(9):2691-2702. doi: 10.1007/s10068-026-02217-6. eCollection 2026 Aug.ABSTRACTExperiments were conducted to evaluate the antifungal activity of chain aldehydes with potent antifungal properties against Penicillium italicum (P. italicum) resistant to prochloraz. The results showed that trans,trans-2,4-nonadienal and trans,trans-2,4-octadienal possessed the strong antifungal activity with MIC values of 0.10 μL/mL for both compounds. Density functional theory (DFT) revealed that compounds with highly delocalized electron systems exhibited significantly stronger antifungal potency. Machine learning (ML) techniques were used to build regression models for identifying the influential structure features of aldehydes, and the random forest (RF) model had lower error levels. We can conclude that the DFT coupled with ML is a reliable, fast and inexpensive tool for solving problems related to the structure properties and antifungal activity. The strategy can be extended to find safe and effective novel inhibitors of P. italicum resistant to prochloraz for the development of green inhibitors of postharvest diseases in fruits and vegetables.SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s10068-026-02217-6.PMID:42534596 | PMC:PMC13421488 | DOI:10.1007/s10068-026-02217-6