## 2 Materials and Methods  
### Sample Preparation  
The prune samples used in this study were harvested on 10 August 2024, from a commercial orchard in Kashgar, Xinjiang, China. All fruits were collected from the same batch to ensure uniformity in maturity and tissue properties. A total of 200 prunes were selected based on the following criteria: intact skin, uniform shape, and absence of visible external defects. These samples exhibited an average fruit weight of 46 \(\pm\) 10.5 g and mean dimensions of a = 45.1 \(\pm\) 3.9 mm, b = 38.84 \(\pm\) 3.2 mm, and c = 50.31 \(\pm\) 4.3 mm, approximating an ellipsoidal geometry. Prior to testing, all samples were equilibrated at room temperature (23 \({}^{\circ}\)C, 15-25% relative humidity) for 24 h to stabilize their physiological conditions and reduce moisture-induced spectral variation. Subsequently, the 200 prunes were randomly divided into four equal groups (50 samples per group) to create different levels of cumulative mechanical damage: intact (0 impacts), mild (1 impact), moderate (2 impacts), and severe (3 impacts). This ensured balanced group sizes for classification modeling and facilitated systematic comparisons across damage levels. Due to quality issues such as postharvest deterioration or abnormal bruising patterns, 3 samples from the intact group and 1 sample from the moderate group were excluded from further analysis. As a result, the final dataset consisted of 196 samples. Mechanical damage was simulated using a custom-designed impact device developed in-house to ensure precise control over impact energy and location (Figure 1). The device was based on the commonly used free-fall principle in fruit bruise simulation [16; 17] but introduced significant structural improvements for repeatability and experimental consistency. Specifically, the system incorporated a 370 g solid metal ball (45 mm diameter) mounted on a lightweight rod, guided through a vertical bearing frame for stable trajectory control. The ball was released from a fixed height of 15 cm, generating an estimated impact energy of approximately 0.544 J per drop (calculated using the formula E = mgh). Each prune was positioned in equator-up orientation in a high-density foam holder with a concave groove to cradle the fruit and minimize secondary bouncing or rotational displacement during impact. Compared with conventional setups that rely on simple inclined planes or fixed-height brackets, this apparatus offers enhanced adjustability, improved energy consistency, and modularity for changing impact conditions. However, it also has limitations--primarily in replicating the complex, multidirectional forces encountered during real-world fruit handling and transportation. Despite this, the design provides a standardized and controllable method to simulate cumulative low-energy impacts, which is critical for isolating the spectral effects of progressive tissue damage without introducing confounding variables such as angular momentum or random contact points. Based on the number of impacts administered, the samples were divided into four experimental groups:  
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After the impact, all samples were left undisturbed for another 24 h under the same ambient conditions to allow bruise development and stabilization prior to spectral acquisition. It is important to clarify that the damage classification of the samples was not determined by visual or tactile inspection but rather by the predefined number of impacts applied using a standardized device (0, 1, 2, or 3 impacts). Each fruit's damage level was thus assigned a priori based on controlled treatment. The subsequent tactile and visual descriptions serve only to illustrate the limited perceptibility of bruises in dark-skinned prunes and were not used to define or verify class labels. This approach ensured objective, repeatable grouping, while highlighting the need for spectroscopic methods to detect internal damage that may not be externally visible.