Cherry Fruit-Thinning Decision Support via Visual Phenotypic Analysis of Ripeness and Fruiting-Branch Spatial Compactness

To address subjective manual judgment in cherry fruit thinning and the difficulty of reliably acquiring ripeness and spatial structure information in dense fruit-cluster scenes, a unified visual phenotypic analysis framework for fruit-thinning decision support is proposed. The framework comprises three components: ripeness detection, cluster spatial structure modeling, and two-level fruit-thinning priority analysis, corresponding to ripeness recognition, quantitative characterization of cluster structural phenotypes, and thinning-order determination, respectively. First, a CS-Transformer and a multi-path feature enhancement module (MSFE) were designed, and the ripeness detection model DEIM-CMFNet was developed based on them. This model significantly improved ripeness recognition and instance separation under occlusion and fruit adhesion conditions, achieving AP(50), AP(50–95), and AR(50–95) of 92.1%, 80.9%, and 90.8%, respectively, on a greenhouse Meizao cherry dataset. Second, a cluster spatial structure modeling method was proposed. By combining dynamic EPS adaptive clustering with an intra-cluster reclustering mechanism, robust cluster partitioning and spatial structure representation were achieved in complex fruit-cluster scenes, thereby improving the ability of the density index D to characterize cluster crowding. In addition, by combining fruit spacing modeling with a comprehensive morphological index, local crowding and overall structural compactness of fruit clusters were jointly quantified. Finally, a two-level fruit-thinning priority strategy was constructed at both the cluster and fruit levels. Experimental results showed that, under limited fruit removal, this strategy reduced the fruit contact ratio by 44.8%, increased the minimum normalized fruit spacing by approximately 21.2%, and decreased cluster density by approximately 24.6%. This framework provides an interpretable visual phenotypic analysis approach for fruit-thinning strategy formulation in the middle and late stages of cherry production.