In the heart of Baghdad, researchers are pioneering a dual approach to revolutionize apricot preservation and detection, with implications that could ripple through the agricultural and energy sectors. Mustafa A. J. Al-Sammarraie, from the Department of Agricultural Machinery and Equipment at the University of Baghdad’s College of Agricultural Engineering Sciences, is leading the charge. His latest study, published in Discover Food, explores the effectiveness of natural treatments for preserving apricots and the application of advanced AI for early damage detection.
Al-Sammarraie’s research delves into the challenges of maintaining apricot quality during storage. The fruits’ physical and chemical properties change over time, making preservation a complex task. Traditional methods often rely on expensive or environmentally harmful chemicals. Al-Sammarraie’s team sought a greener, more cost-effective solution.
The team immersed apricots in lemon juice and sugar-water solutions, observing the effects on sweetness, color, hardness, and water content. The results were promising. “We found that sweetness increased with longer immersion in the sugar-water solution, reaching up to 22.1 Brix,” Al-Sammarraie explained. “Conversely, lemon juice immersion decreased sweetness, but it had other beneficial effects on the fruit’s properties.”
The study also revealed that hardness increased with longer sugar-water immersion, while water content decreased with prolonged immersion in both solutions. These changes were accompanied by increases in CIE-L*a*b levels, indicating alterations in the fruits’ color properties.
But Al-Sammarraie’s innovation doesn’t stop at preservation. His team also employed the YOLOv7 algorithm, a state-of-the-art object detection system, to identify damaged fruits. By training the algorithm on images of apricots, they achieved impressive results. The system demonstrated a precision of 84.5%, recall of 87%, and a mean average precision ([email protected]) of 77.2. This means the algorithm can accurately and efficiently detect damaged fruits, even in varying conditions.
The implications of this research are vast. For the agricultural sector, these findings could lead to reduced post-harvest losses, improved sorting efficiency, and enhanced food safety. But the energy sector could also benefit. As the world shifts towards renewable energy, the demand for biofuels and biogas produced from agricultural waste is rising. By reducing fruit waste and improving preservation, Al-Sammarraie’s methods could increase the availability of biomass for energy production.
Moreover, the application of AI in agriculture, as demonstrated by the YOLOv7 algorithm, could pave the way for smarter, more efficient farming practices. This could lead to reduced energy consumption in agriculture, further contributing to sustainability goals.
Al-Sammarraie’s work, published in Discover Food, is a testament to the power of interdisciplinary research. By combining agricultural science, food technology, and AI, he and his team are shaping the future of food preservation and detection. As the world grapples with food security and sustainability challenges, their work offers a glimmer of hope, a testament to human ingenuity and the power of science.
The future of apricot preservation and detection is here, and it’s smarter, greener, and more efficient than ever before. As Al-Sammarraie puts it, “This study is just the beginning. The potential applications of these technologies are vast, and we’re excited to explore them further.” The energy sector would be wise to take note and consider how these advancements could fuel their own innovations.
