In the heart of agricultural innovation, a groundbreaking study has emerged, shedding light on the untapped potential of apricot fruits (Prunus armeniaca L.). Researchers have successfully optimized the extraction of biologically active components from apricots, paving the way for enhanced functional food and pharmaceutical applications. This research, published in *Scientific Reports*, not only underscores the importance of advanced extraction techniques but also highlights the commercial impacts for the agriculture sector.
The study, led by Nazan Çömlekçioğlu from the Department of Biology at Kahramanmaraş Sütçü İmam University, employed two distinct methods—Response Surface Method (RSM) and Artificial Neural Networks-GENetic Algorithms (ANN-GA)—to determine the optimum extraction conditions. The goal was to maximize the biological activities of apricot fruit extracts. The results were striking. “The ANN-GA method significantly increased the extraction efficiency of biologically active components, enhancing their antioxidant, antiproliferative, and anticholinesterase activities,” Çömlekçioğlu explained.
The antioxidant activity tests revealed that extracts optimized by the ANN-GA method exhibited higher total antioxidant status (TAS) and DPPH free radical scavenging activity compared to those obtained through RSM. This finding is particularly noteworthy for the agriculture sector, as it suggests that advanced extraction techniques can unlock greater value from crops, potentially leading to higher market prices for farmers.
In antiproliferative activity tests, the optimized extracts showed a dose-dependent suppression of cell viability in A549 lung cancer cell lines. The ANN-GA method yielded extracts with stronger antiproliferative effects at certain concentrations, indicating its potential in developing novel cancer treatments. “The extracts optimized by ANN-GA showed a remarkable ability to inhibit acetylcholinesterase (AChE) and butyrylcholinesterase (BChE) enzymes, although their inhibitory effect was lower compared to galantamine, a reference inhibitor,” Çömlekçioğlu noted.
The phenolic component analysis further underscored the superiority of the ANN-GA method. Extracts obtained through this technique had higher concentrations of phenolic components such as kaempferol, fumaric acid, gallic acid, caffeic acid, and naringenin. However, some compounds like resveratrol and salicylic acid were extracted more efficiently using the RSM method, highlighting the complementary nature of these techniques.
The commercial implications of this research are profound. By optimizing extraction processes, farmers and agricultural businesses can enhance the value of their crops, opening new avenues for functional food and pharmaceutical applications. This study not only advances our understanding of extraction techniques but also sets the stage for future developments in the field. As Çömlekçioğlu aptly put it, “AI-supported extraction methods have the potential to revolutionize the way we process and utilize agricultural products, benefiting both the industry and consumers.”