aspg-28-4112-1792155135 20261016125215 American Scientific Publishing Group admin@americaspg.com American Scientific Publishing Group Journal of Artificial Intelligence and Metaheuristics JAIM 2833-5597 2025 10 1 El-Sayed M. El-Kenawy Department of Communications and Electronics, Delta Higher Institute of Engineering and Technology, Mansoura 35111, Egypt Applied Science Research Center, Applied Science Private University, Amman 11931, Jordan This study presents a comprehensive evaluation of metaheuristic-optimized machine learning models for automated apple quality classification, addressing the critical need for accurate and consistent fruit grading systems in agricul-tural applications. The research integrates four bio-inspired optimization algorithms—Whale Optimization Algorithm (WOA), Salp Swarm Algorithm (SSA), Cuckoo Search (CS), and Bat Algorithm (BAT)—with Multi-Layer Percep-tron (MLP) classifiers to enhance fruit quality assessment performance. Experimental validation was conducted using a comprehensive apple quality dataset containing seven key attributes: size, weight, sweetness, crunchiness, juiciness, ripeness, and acidity. The results demonstrate that WOA-MLPClassifier achieves superior performance with 95.37%accuracy, 95.99% sensitivity, and balanced effectiveness across all evaluation metrics including specificity, positive predictive value, negative predictive value, and F1 Score. Statistical validation through one-way ANOVA and Wilcoxon signed-rank tests confirms significant performance improvements over baseline models and alternative optimization approaches, with p-values less than 0.001. The proposed framework exhibits remarkable consistency across multiple evaluation runs, with perfect positive rank sums indicating reliable optimization behavior. These findings establish a new benchmark for automated fruit quality classification systems and provide valuable insights for deploying bio-inspired optimization techniques in agricultural machine learning applications where both accuracy and reliability are essential for commercial viability. 2025 08 19 4112 https://creativecommons.org/licenses/by/4.0/ 10.54216/JAIM.100102 https://www.americaspg.com/journal/28/article/4112