The rate of chemical fertilizers’ utilization by crops does not exceed 40%. Environmental pollution and resource waste caused by the excessive application of chemical fertilizers have led to increased interested in using organic fertilizers as replacements for chemical ones. The present study investigated the impact of the combined application of chemical and organic fertilizers on the growth and nutrient utilization efficiency of highland barley (Hordeum vulgare L.). Compared to the application of 100% chemical fertilizers (OFR0), the substitution of chemical fertilizer with 40% organic fertilizer (OFR40) resulted in a significant increase in root length by 4% and improved the nutrient absorption capacity. The crop yields at harvest were not diminished in the combined fertilizer group compared to the OFR0 treatment group, while simultaneously achieving a 60% reduction in chemical fertilizer application. However, a complete substitution with 100% organic fertilizer (OFR100) resulted in a lower yield. This suggests that appropriate proportions of organic fertilizer replacement can maintain yield by increasing root length and enhancing the crop’s nutrient absorption capacity. In order to elucidate the mechanisms by which organic fertilizer modulates crop growth and nutrient utilization efficiency, combined transcriptomic and metabolomic analysis revealed that as the concentration of organic fertilizer increased, the differentially expressed genes (DEGs) and differentially accumulated metabolites (DAMs) shifted from secondary metabolite synthesis toward nitrogen metabolism. In addition, the gene expression and enzymatic activity of NR (nitrate reductase), GS (glutamine synthetase), and GOGAT (glutamine oxoglutarate aminotransferase) (key genes in the nitrogen metabolism pathways) were significantly enhanced in the OFR40 group. This study’s omics-based approach demonstrates that the combined use of chemical and organic fertilizers enhances nitrogen absorption and utilization through an increased expression of key genes and enzymatic activities within the nitrogen metabolic pathways. This synergistic effect not only maintains crop yields but also reduces the reliance on chemical fertilizers, offering a sustainable strategy for agricultural production.

Species distribution models (SDMs) grapple with uncertainty. To address this, a parameter-optimized MaxEnt model was used to predict habitat suitability for Elsholtzia densa, a predominant agricultural weed on the Tibetan Plateau. Through multiparameter optimization with 149 occurrence points and three climate variable sets, we systematically evaluated how the three MaxEnt extrapolation approaches (Free Extrapolation, Extrapolation with Clamping, No Extrapolation) influenced model outputs. The results showed the following: (1) Model optimization using the Kuenm R package version (1.1.10) identified seven critical bioclimatic variables (Feature Combinations = LQTH, Regularization Multipliers = 2.5), with optimized models demonstrating high accuracy (Area Under Curve > 0.9). (2) Extrapolation approaches exhibited negligible effects on variable selection, though four bioclimatic variables “bio1 (annual mean temperature)”, “bio12 (annual precipitation)”, “bio2 (mean diurnal range)”, and “bio7 (temperature annual range)” predominantly drove model predictions. (3) Current high-suitability areas are clustered in the eastern and southern regions of the Tibetan Plateau, and with Free Extrapolation yielding the broadest current distribution. Climate change projections suggest habitat expansion, particularly under conditions of No Extrapolation. (4) Multivariate Environmental Similarity Surface (MESS) and Most Dissimilar Variable (MoD) are not affected by the extrapolation method, and extrapolation risk analyses indicate that future climate anomalies are mainly concentrated in the western and southern parts of the Tibetan Plateau and that future warming will further increase the unsuitability of these regions. (5) Variance analysis showed that the extrapolation methods did not significantly affect the 10-replicate results but influenced the parameter and emission scenarios, with No Extrapolation methods showing minimal variance changes. Our findings validate that multiparameter optimization improves species distribution model robustness, systematically characterizes extrapolation impacts on distribution projections, and provides a conceptual framework and early warning systems for agricultural weed management on the Tibetan Plateau.

Highland barley (Hordeum vulgare var. nudum), a member of the genus Hordeum in the family Poaceae, represents a unique cultivated crop adapted to the Qinghai–Tibet Plateau. Weed infestation has long posed a serious threat to the yield and quality of highland barley, and the lack of effective weed management strategies has become a major constraint in its production. Pyroxsulam is an acetolactate synthase (ALS)-inhibiting herbicide widely used for weed control in highland barley fields. This study investigated the molecular mechanisms underlying the response of highland barley to pyroxsulam by integrating physiological, biochemical, and transcriptomic analyses. ALS activity assays showed that the resistant variety ‘Qing0306’ exhibited a significant increase in relative ALS activity within 1–4 days after pyroxsulam treatment. qRT-PCR analysis revealed a rapid induction of HvnALS expression, which was significantly higher in ‘Qing0306’ than in ‘Qing0160’ on the first day after treatment (p < 0.01), indicating that resistance is primarily associated with target-enzyme overexpression rather than target-site mutations. Moreover, transgenic Arabidopsis lines overexpressing HvnP450 and HvnGSTs displayed enhanced tolerance to pyroxsulam, as evidenced by an increased root length and fresh weight compared with wild-type plants. This study provides mechanistic insights that support the genetic improvement of pyroxsulam-resistant highland barley.

From 2019 to 2021, pepper viruses were investigated in pepper planting areas and collected a total of 333 samples were in Qinghai (The central district, Datong, Huangzhong in Xining; Ledu district, Pingan, Huzhu, Minhe in Haidong, and Jianzha in Huangnan). RT-PCR and molecular cloning were conducted for virus detection in 333 suspected viral samples, the results revealed that viruses infecting pepper mainly included 11 capsicum viruses. Tomato spotted wilt tospovirus （TSWV）has the highest detection rate (36%) in Datong County, and Pepper cryptic virus 1 (PCV1) has the highest detection rate (57%) in Huangzhong County. In the Haidong, 86.3% of the peppers were Broad bean wilt virus 2（BBWV2）, virus-infected Pepper cryptic virus 2 (PCV2), TSWV and Cucumber mosaic virus （CMV） were detected in Xunhua, among which PCV1 and CMV had the highest detection rate (30.4%); PCV1, TSWV, and PCV2 were detected in Ledu and PCV2 had the highest detection rate (50%). There were 17 kinds of co-infection and the co-infection of two viruses occurred often. There were only 5 kinds of co-infection of three. Combined infection contained PCV1 and TMV was the most common. The distribution and species of pepper viruses from the pepper planting areas were clarified and it laid the foundation for preventing and controlling pepper viruses across Qinghai province.