Greenhouse vegetable production provides significant quantities of vegetables throughout the year and improves farmers’ income. However, over-fertilization with mineral fertilizer causes soil secondary salinization and decreases the stability of the soil structure. To improve aggregate formation and decrease salt accumulation in the soil profile, bio-organic fertilizers (Protaetia brevitarsis larvae frass with Bacillus amyloliticus and/or Trichoderma harziensis) were applied to partially substitute mineral fertilizer in a salinized vegetable soil. Soil nutrient condition, aggregate stability, and salt movement in the soil profile were measured in a greenhouse double-cucumber system. The results showed that soil organic matter (SOM), total nitrogen (TN), and available phosphorus (AP) increased significantly under bio-organic fertilizer treatments compared with control. Soil electrical conductivity (EC) and total salt content (TSC) decreased by 15.74–24.20% and 19.15–29.05%, respectively, with bio-organic fertilizers (p < 0.05). Cl⁻, NO₃⁻, and SO₄²⁻ content under double inoculation with B. amyloliticus and T. harziensis reduced by 31.19%, 26.30%, and 53.11%, respectively, compared to CK (p < 0.05). In addition, double inoculation was more efficient in reducing nitrate content in the soil profile than single inoculation. Soil microaggregates of 0.25–0.053 mm increased by 75.87–78.51% with bio-fertilizers compared with control, and double inoculation was the best for aggregate formation. In conclusion, the inoculation of plant-growth-promoting and salt-tolerant microorganisms with high humic acid larvae frass can alleviate salinization in vegetable soil, enhance soil nutrient content, and improve the soil structure.

Greenhouse vegetable production in China not only increases farmers’ income, but also increases the risk of nitrogen losses due to excessive water and fertilizer input. Nitrogen losses, including the potent greenhouse gas nitrous oxide (N₂O), are driven by water content, soil temperature and pH; regulated by available organic carbon and inorganic nitrogen (N); and affected by management. Therefore, a process-based model was applied to explain the complex interaction of the factors affecting N losses in the form of N₂O, NH₃ and NO₃⁻ from a greenhouse vegetable production system in a northeast suburb of Beijing, China. We designed four treatments: two equal N input treatments with one flooding (FP) and the other drip irrigation (FPD) and two equal water input treatments (drip irrigation) with one 100% chemical N input (FPD) and the other 50% N input (OPTD). The last one was CK treatment (flooding without chemical N). We calibrated the WHCNS-veg model using year-round measurements of soil temperature, N₂O emission, NH₃volatilization, NO₃⁻ distribution and yields for greenhouse cucumber–tomato cultivation under farmers’ practice (flooding + 100% chemical N, FP). Then, we validated the model using the data sets under drip irrigation (70% of flooding amount + 100% chemical N, FPD), reduced chemical N by 50% (drip + 50% chemical N, OPTD) and CK treatment. The WHCNS-veg model was able to capture the above processes under different treatments. Annual N₂O emissions were 5.47 and 3.76kg N ha⁻¹ for the cucumber and tomato seasons under FP, respectively. Compared to FP, drip irrigation (FPD) decreased N₂O emissions by 19.0% and 45.5% in the two seasons, respectively. Compared to FPD, applying a lower rate of N (OPTD) further reduced N₂O emissions by 13.7% and 40.5%, respectively. According to the model simulation, N₂O emission was mainly controlled by nitrification/denitrification in the cucumber/tomato seasons, respectively. Compared to FP, drip irrigation (FPD) increased NH₃ volatilization by 54.2% in the cucumber season, while in the tomato season, there were no significant differences inNH₃ volatilization under the three fertilizer treatments. The nitrate leaching levels were 48.5 and 81.0 kg N ha⁻¹ for the two seasons under FP treatment. Drip irrigation (FPD) decreased NO₃⁻ leaching by 20.6% in the cucumber season. Drip irrigation (FPD) and/or reducing chemical N (OPTD) did not compromise vegetable yields. In all, WHCNS-veg performed well in simulating N₂O, NH₃ and NO₃⁻ dynamics from the greenhouse vegetable field, which means that the model can be used to manage water and nitrogen precisely in greenhouse vegetable production systems by scenario analysis, and drip irrigation and/or lower N input can be applied in this area to secure yield and reduce N losses.

Microbial-mediated nitrogen (N) dynamics is not only a key process for crop productivity, but also a driver for N losses. Therefore, a better understanding of N dynamics and controlling factors in different soil types is needed to better manage N fertilization in crop fields. To achieve this, a ¹⁵N tracing approach was used to quantify simultaneously occurring N transformation rates in four agricultural trials (>20 years chemical fertilizer application) with contrasting climatic and edaphic types (three upland soils and one paddy soil). The results showed that recalcitrant soil organic carbon (SOC) mineralization was the main source of NH₄⁺ at all the sites, with rates ranging from 0.037 in fluvo-aquic soil to 3.096 mg kg⁻¹ day⁻¹ in paddy red soil. Autotrophic nitrification (O_NH4) was the predominant NO₃⁻ production mechanism in the black and fluvo-aquic soils, whereas it was negligible in the upland and paddy red soils. Nitrification capacity, as an indicator of nitrate leaching risk, was in the order: upland red soil (1%) < paddy red soil (8%) < black soil (235%) < fluvo-aquic soil (485%), implying a high nitrate leaching risk in the last two soils. However, high microbial immobilization (41%) and abiotic adsorption (6%) decreased NO₃⁻ leaching in black soil. The partial least squares path modeling (PLS-PM) showed that SOC, temperature and pH were the main factors controlling nitrate immobilization, N mineralization and nitrification. In summary, even under similar chemical fertilization conditions, N transformation dynamics are expected to differ with respect to soil type. Therefore, N management strategies should be adjusted to soil type to control N losses and increase crop yield.