The mechanization of fruit harvesting has become an essential component of modern agricultural engineering, particularly in the context of labor shortages, efficiency demands, and precision farming requirements. This study presents the construction and assessment of a terrain-level fruit picking system inspired by natural movement strategies, integrating biomimetic principles with mechanical design and computational optimization. The research aims to develop a system capable of efficiently collecting fallen fruits from ground surfaces while minimizing damage and maximizing operational efficiency.

The conceptual framework of the study is grounded in biomimicry, which emphasizes the replication of natural movement patterns observed in biological organisms. These principles are applied to design a picking mechanism that adapts to irregular terrain conditions and varying fruit distributions. The system incorporates pneumatic conveying, vibration-assisted separation, and adaptive collection modules, supported by simulation-based optimization techniques. Computational modeling approaches, including hybrid optimization algorithms and neural network-based prediction models, are utilized to enhance system performance and operational stability (Bouktif et al., 2018; Zheng et al., 2017).

The methodology involves a combination of mechanical design, computational simulation, and experimental validation. Laboratory-based simulations evaluate force transfer mechanisms under vibration excitation, while field testing assesses real-world performance in agricultural settings (Fu et al., 2017; Zhang et al., 2020). The integration of artificial intelligence frameworks enables dynamic adjustment of operational parameters, improving efficiency under varying environmental conditions.

The findings indicate that biomimetic design significantly enhances the adaptability and efficiency of terrain-level fruit picking systems. The system demonstrates improved collection rates, reduced fruit damage, and enhanced energy efficiency compared to conventional methods. However, challenges related to system complexity, cost, and scalability remain critical considerations.

This study contributes to the field of agricultural mechanization by providing a comprehensive framework for integrating biomimetic design with advanced computational techniques. The research highlights the potential of interdisciplinary approaches in addressing complex agricultural challenges and offers practical insights for the development of next-generation harvesting systems.

This article presents a comprehensive scientific analysis of the composition, taxonomic structure, and structural characteristics of the flora of the Andijan Region. Based on long-term field investigations, herbarium materials, and international digitized data sources, it was established that the regional flora comprises 653 species belonging to 341 genera and 67 families. The results of the taxonomic analysis indicate the predominance of low-diversity and moderately polymorphic families and genera, while the leading families account for the major proportion of the total number of species. The obtained findings provide an important scientific basis for assessing the biological and ecological significance of the flora of the Andijan Region, its conservation, and for conducting future comparative floristic studies.