Autophagy, an evolutionarily conserved mechanism for cellular homeostasis, is essential for plant adaptation to abiotic stresses. DNA methylation is well-established as an epigenetic regulator of development and stress responses; however, its direct modulation of autophagy under salt stress remains unexplored. In this study, we found that a salt-sensitive cucumber (Cucumis sativus L.) cultivar exhibited higher accumulation of ubiquitinated proteins correlating with a lower level of autophagic activity compared to a salt-tolerant cucumber cultivar under salt stress. Whole-genome bisulfite sequencing analysis revealed that salt stress induced CG hypomethylation in the coding sequence (CDS) region of Autophagy-related gene 6 (CsATG6) in cucumber, coinciding with its upregulation and autophagy activation. The CDS hypomethylation of CsATG6 was induced by DNA methylation inhibitor 5-azacytidine (5-Aza), resulting in its transcriptional upregulation, which was accompanied by increased autophagic activity and decreased accumulation of ubiquitinated proteins. Silencing of CsATG6 decreased autophagic activity and salt tolerance, whereas its overexpression enhanced both. Loss of function of CsATG6 compromised 5-Aza-induced autophagic activity and salt tolerance. Furthermore, salt stress and 5-Aza co-induced Repressor of silencing 1b (CsROS1b) expression, which actively demethylated CsATG6 at CG sites and increased CsATG6 transcript abundance, enhancing autophagosome formation and reducing ubiquitinated protein accumulation. Our study reveals a mechanism by which CsROS1b-mediated CG hypomethylation of CsATG6 activates autophagy to enhance salt stress tolerance in cucumber.

Chinese wolfberry (CW) is a medicinal-food homologous fruit. Key mineral elements are important indicators of the nutritional quality and geographical authenticity of CW. Rapid and non-destructive evaluation of key mineral elements remains challenging because inductively coupled plasma mass spectrometry (ICP-MS) is accurate but destructive and laboratory-dependent. In this study, 120 CW batches from Ningxia, Qinghai, Gansu, and Xinjiang were analyzed by combining ICP-MS reference measurements of Cu, Fe, Mn, and Zn with standardized RGB image features. Visible-color proxy curves were reconstructed from RGB/L*a*b* information and Gaussian fitting, and frequency-domain texture descriptors were extracted from Fourier-derived angle–energy curves. Multivariate analysis showed that mineral profiles, the 570–593 nm visible-color proxy band, and the 0–40° and 63–140° texture-angle ranges contributed to regional differentiation. A Dung Beetle Optimizer-radial basis function (DBO-RBF) regression model was then used for internal prediction of mineral element contents and compared with nine baseline regression algorithms. DBO-RBF achieved test-set R² values of 0.949, 0.965, 0.951, and 0.913 for Cu, Fe, Mn, and Zn, respectively, with corresponding test RPD values of 2.9017, 3.2419, 3.0175, and 2.8416. These results indicate that image-derived visible-color and texture features can provide useful screening information for mineral quality assessment in CW, offering a rapid, low-cost, and non-destructive approach for preliminary batch evaluation.