Addressing the challenges of low resource-use efficiency and supply–demand mismatch in Hami melon production, this study investigated the interactive effects of irrigation and fertilization to identify an optimal regime that balances yield, water conservation, and resource-use efficiency (i.e., water use efficiency and fertilizer partial factor productivity). A greenhouse experiment was conducted in Hami, Xinjiang, employing a two-factor design with five irrigation levels (W1–W5: 60–100% of full irrigation) and three fertilization levels (F1–F3: 80–100% of standard rate), replicated three times. Growth parameters, yield, water use efficiency (WUE), and partial factor productivity of fertilizer (PFP) were evaluated and comprehensively analyzed using the entropy-weighted TOPSIS method, regression analysis, and the NSGA-II multi-objective genetic algorithm. Results demonstrated that irrigation volume was the dominant factor influencing growth and yield. The W4F3 treatment (90% irrigation with 100% fertilization) achieved the optimal outcome, yielding 75.74 t ha⁻¹—a 9.71% increase over the control—while simultaneously enhancing WUE and PFP. Both the entropy-weighted TOPSIS evaluation (C = 0.998) and regression analysis (optimal irrigation level at w = 0.79, ~90% of full irrigation) identified W4F3 as superior. NSGA-II optimization further validated this, generating Pareto-optimal solutions highly consistent with the experimental optimum. The model-predicted optimal regime for greenhouse Hami melon in Xinjiang is an irrigation amount of 3276 m³ ha⁻¹ and a fertilizer application rate of 814.8 kg ha⁻¹. This regime facilitates a 10% reduction in irrigation water and a 5% reduction in fertilizer input without compromising yield, alongside significantly improved resource-use efficiencies.

Triterpenoids are the primary bioactive constituents responsible for the medicinal efficacy of Ziziphus jujuba Mill. cv. ‘Junzao’ (Junzao) fruits, and there are significant differences in their functional composition depending on the harvest period. However, the metabolic characteristics and dynamic accumulation patterns of triterpenoids during fruit development remain poorly understood. This study represented the first systematic integration of transcriptomic and metabolomic analysis combined with weighted gene co-expression network analysis (WGCNA) to elucidate the biosynthetic pathways of triterpenoids during the harvest times of Junzao fruits, and provide a scientific basis for the future development of functional foods. Total triterpenoid content exhibited a stage-specific accumulation pattern, peaking at the YG (young fruit) stage of fruit development, declining sharply by 37% at the PD (expansion) stage, rebounding at the BS (white-ripe) stage, and gradually decreasing through the CS (crispy-ripe) stage and WS (full-ripe) stages. A total of 347 terpenoid differentially accumulated metabolites (DAMs) and 18,925 differentially expressed genes (DEGs) were identified, among which 224 triterpenoids were predominant. A total of 347 terpenoid differentially accumulated metabolites (DAMs) and 18,925 differentially expressed genes (DEGs) were identified, among which 224 triterpenoids were predominant. WGCNA identified six key modules (salmon, midnightblue, black, blue, yellow, and brown modules) strongly correlated with the accumulation of methyl oleanolate, 3-oxopomolic acid, hederagenin, and other triterpenoids. Furthermore, integrated correlation analysis revealed that cytochrome P450 family genes, particularly CYP716, CYP72A and CYP88, were likely the hub genes governing triterpenoid biosynthesis and RT-qPCR validation of eight key genes confirmed the transcriptome expression trends. These findings provide a comprehensive framework for understanding triterpenoid biosynthesis and offer theoretical foundations for optimizing harvest timing and advancing metabolic engineering in Junzao fruits.