Soil salinization is a significant threat to agricultural production, making accurate salinity prediction essential. This study addresses key challenges in the Yellow River Delta (YRD) soil salinity inversion, including (1) determining which Landsat 8 OLI level performs better, (2) identifying the most suitable month for salinity inversion, and (3) improving model performance and identifying important variables in modeling. Thus Landsat 8 OLI images (Level-1 and Level-2) for 12 months were collected, then images having less than 10% cloud cover were selected and processed to extract spectral values. A total of 86 sampled points were processed to measure soil salinity. Using Pearson correlation and expert insights, January 15 and August 26 were identified as suitable dates for inversion. Then, seven original bands, 29 spectral indicators, and 39 derived variables which created through six mathematical transformations, were used to construct the following three models: partial least squares regression (PLSR), random forest (RF), and backpropagation neural network (BPNN). The results showed the following: (1) The Level-1 data, after FLAASH atmospheric correction, outperforms Level-2 data. (2) January is optimal for salinity inversion. (3) Among the three models, RF outperformed the others, achieving test set R² = 0.55, RMSE = 3.4, suggesting that the combination of spectral indicators and mathematically transformed variables can effectively enhance model accuracy for predicting soil salinity in the YRD. Furthermore, SWIR1, SWIR2, CLEX, second-order difference of SWIR1, and first-order difference of SWIR2 along with NIR played a key role in modeling.

In this study, sodium alginate–chitosan composite microspheres (S-C Ms) were prepared by ionic gelation to encapsulate Ziziphus jujuba pulp from wild jujube pulp. The effects of sodium alginate (SA) concentration, chitosan (CS) concentration, and core-to-wall ratio on encapsulation efficiency (EE%) and loading capacity (LC%) were systematically investigated. The results showed that both EE% and LC% were maximized when the SA concentration was 2.0% (w/v) and the CS concentration was 1.5% (w/v). The FTIR and XRD analyses confirmed the successful encapsulation of a phenolic-rich extract from Z. jujuba pulp (PRE) and its transformation into an amorphous state, while the SEM observations revealed that the composite microspheres possessed a well-defined morphology and a dense internal structure. Particle size analysis further indicated a narrow and uniform size distribution. Thermogravimetric analysis (TGA) and in vitro simulated digestion demonstrated that S-C Ms exhibited a pH-responsive release profile, characterized by slow, limited release in the gastric phase and markedly enhanced release in the intestinal phase. The release mechanism in simulated gastric fluid was dominated by Fickian diffusion, whereas it shifted to an erosion-controlled process in simulated intestinal fluid. Consistently, the swelling ratio of the microspheres was low at pH 1.2 but increased sharply at pH 7.0, reflecting a “gastric protection–intestinal release” behavior. Antibacterial assays showed that P-loaded microspheres exerted significant inhibitory effects against Staphylococcus aureus and other test strains, with the antibacterial activity possibly associated with the controlled release during the in vitro digestion of compounds with antimicrobial potential, such as phenolic compounds. Overall, SA-CS composite microspheres exhibited favorable encapsulation performance, structural stability, and controlled-release potential, making them a promising delivery and protection system for Ziziphus jujube pulp bioactive compounds.