Ovarian maturity in live female mud crabs (Scylla paramamosain) strongly affects harvest decisions and market value. Current ovarian maturity assessment relies mainly on expert-dependent methods that are subjective and destructive. Therefore, this study aimed to develop an interpretable, non-destructive image-based framework to classify crab ovarian maturity as immature or mature. A total of 240 crab image sets acquired using ventral external-view, dorsal external-view, and dorsal transillumination imaging were retained for analysis. Six primary morphometric features were semi-manually extracted from these views. External-view images quantified carapace width (CW), abdomen width (AW), abdomen area (AA), and sternum area (SA). Dorsal transillumination images yielded carapace area (CA) and ovary area (OA), an internal cue visualized through the intact carapace. To mitigate body-size variation, three ratio-based features—abdomen–carapace width ratio (ACWR), abdomen–sternum area ratio (ASAR), and ovary–carapace area ratio (OCAR)—were calculated. Between-class comparisons and correlation analyses were performed to guide candidate feature-set construction. Because OA and OCAR were strongly correlated, two reduced feature sets (Reduced 1 and Reduced 2) were designed to compare absolute ovary area with normalized ovary occupancy. Five feature sets—Raw, Ratio, Combined, Reduced 1, and Reduced 2—were evaluated using logistic regression (LR), support vector machine (SVM), and random forest (RF) classifiers. The Combined feature set, integrating all primary and ratio-based features, achieved the strongest mean cross-validated performance when paired with LR. On the held-out test set (n = 40), the final Combined-LR model achieved 0.950 accuracy and 0.997 ROC–AUC. On an independent practical implementation set (n = 40), the model correctly classified 39 specimens, achieving 0.975 accuracy. These findings may support non-destructive ovarian maturity screening and commercial grading in mud crab aquaculture.
Huang et al. (Mon,) studied this question.