Yunxia Cheng

The tomato (Solanum lycopersicum L.) is widely cultivated in yellow sand substrate-based systems in Northwest China, contributing significantly to regional agriculture. However, suboptimal water and fertilizer management hinders the balanced optimization of yield, fruit quality, and resource efficiency. In this two-year solar greenhouse experiment (2023–2024), we employed a four-factor, three-level orthogonal design [L9(3⁴)] to examine three irrigation regimes—full irrigation (FI 100% of crop evapotranspiration, [ET_c]), mild deficit irrigation (DIM 75% ET_c), and severe deficit irrigation (DIS 50% ET_c)—in combination with staged fertilizer applications at the seedling, flowering/fruit-set, and peak-fruit stages. A multi-objective decision-making framework, integrating an improved entropy weight method with a virtual-ideal-solution-based TOPSIS model, was established to address the complexity of water–fertilizer interactions. The results indicated that irrigation amount (IA) was the primary determinant of yield and water use efficiency (WUE), followed by fertilizer application in the second stage (FII). For fruit quality indices (moisture content, vitamin C (VC), lycopene (LC), soluble sugars (SSs), and soluble solids content (SSC)), IA remained the most influential factor, followed by FIII, FII, and FI; IA also had the largest impact on fruit hardness (Hd), soluble protein (SP), and titratable acidity (TA). An integrated scoring analysis revealed that treatment T5 achieved the highest yield, WUE, and partial factor productivity (PFP), whereas T7 excelled in fruit quality (VC, LC, SSC, and SP). Moreover, TOPSIS confirmed T5 as the optimal water–fertilizer strategy to achieve high yield, improved quality, and efficient resource utilization. Overall, these findings underscore a robust approach for optimizing water–fertilizer coupling in tomato cultivation under yellow sand substrate conditions, thereby enhancing resource use efficiency, promoting sustainable greenhouse agriculture in arid regions, and contributing to national water-saving and yield-increasing priorities.

Background: Ethyl methyl sulfonate (EMS) mutagenesis is widely used because of its advantages of inducing point mutations and no need for genetic transformation. To identify germplasm resources of processed tomatoes with superior comprehensive traits suitable for cultivation in Xinjiang. Methods: In this study, tomato seeds were treated with 2% EMS reagent for 12 h, 21 quality traits and 20 quantitative traits of 33 processed tomatoes derived from EMS-mutagenized“M82”were evaluated. Results: The results indicated that for traits such as hypocotyl color, growth habit, plant type, leaf type, and leaf shape, the range of quantitative trait variation was 8.45–37.25%, with a genetic diversity index ranging from 1.25 to 2.07. Conclusions: Cluster analysis of quantitative traits categorized the 33 EMS-mutagenized “M82” processed tomato resources into five groups: Group I contained 22 robust germplasm samples; Group II consisted of a single potential high-quality germplasm; Group III comprised five germplasm with a small and extreme plant type; Group IV included four high-yield germplasm; and Group V represented one moderate, conventional germplasm. Raw data from 15 quantitative traits across the 33 accessions were standardized using the “extreme method” to extract six comprehensive factors. The top 10 germplasm resources based on the comprehensive score were 76, 137, 97, 102, 19, 104, 21, 108, 17, and 147. It provides some theoretical basis for realizing the high-yield and high-quality cultivation and variety breeding of processed tomatoes in Xinjiang.

The chloroplast, the energy organelle unique to plants and green algae, performs many functions, including photosynthesis and biosynthesis of metabolites. However, as the most critical tuber crop worldwide, the chloroplast proteome of potato (Solanum tuberosum) has not been explored. Here, we use Percoll density gradient centrifugation to isolate intact chloroplasts from leaves of potato cultivar E3 and establish a reference proteome map of potato chloroplast by bottom-up proteomics. A total of 1834 non-redundant proteins were identified in the chloroplast proteome, including 51 proteins encoded by the chloroplast genome. Extensive sequence-based localization prediction revealed over 62% of proteins to be chloroplast resident by at least one algorithm. Sixteen proteins were selected to evaluate the prediction result by transient fluorescence assay, which confirmed that 14 were distributed in distinct internal compartments of the chloroplast. In addition, we identified 136 phosphorylation sites in 61 proteins encoded by chloroplast proteome. Furthermore, we reconstruct the snapshots along starch metabolic pathways in the two different types of plastids by a comparative analysis between chloroplast and previously reported amyloplast proteomes. Altogether, our results establish a comprehensive proteome map with post-translationally modified sites of potato chloroplast, which would provide the theoretical principle for the research of the photosynthesis pathway and starch metabolism.