Rapid and cost-effective estimation of soil total nitrogen (TN) is essential for soil fertility assessment and nutrient management. However, the performance of laboratory visible–near-infrared (Vis–NIR) models is shaped not only by preprocessing and modeling strategy but also by sample preparation and the soil’s compositional background. In this study, TN prediction was evaluated using 376 topsoil samples from two contrasting datasets: Mollisols from the black-soil region of Northeast China and Ultisols from Qiyang County, Hunan Province, southern China. Spectra acquired over 350–2500 nm for three particle-size fractions were preprocessed using Savitzky–Golay smoothing combined with standard normal variate (SNV), first-derivative, or second-derivative transformations, and modeled using partial least squares regression (PLSR), support vector regression (SVR), and extreme gradient boosting (XGBoost). Model development used a 5 × 5 nested cross-validation followed by evaluation on a sample-grouped held-out test set. Among all combinations, XGBoost with first-derivative preprocessing on the 0.25 mm fraction produced the best performance, with test R² values of 0.91 for Mollisol and 0.78 for Ultisol. Shapley additive explanations (SHAP) and principal component analysis (PCA) consistently identified informative spectral regions at 430–480 and 1330–1450 nm for Mollisol and at 585–635, 820–900, and 2180–2240 nm for Ultisol. Prediction errors were larger in the sampled Ultisol dataset and increased with DCB-extractable Fe and mineral backgrounds. A second-stage log-domain residual correction incorporating ancillary soil properties further reduced the Ultisol RMSE from 0.30 to 0.27 g kg⁻¹. These findings support the 0.25 mm, first-derivative, XGBoost workflow as a robust laboratory Vis–NIR approach for TN prediction and indicate that composition-aware residual correction can improve prediction in oxide- and mineral-rich soils.

To alleviate the constraints of coastal saline-alkali soil on crop production and explore efficient and low-carbon planting patterns for vulnerable saline land ecosystems, a three-year continuous field experiment was carried out in the coastal saline-alkali farmland of the Yellow River Delta, Dongying City, Shandong Province, China. Using sole maize cropping (CM) as the control, this study systematically compared productivity, energy budget, economic benefit, carbon footprint (CF), and the carbon sustainability index (CSI) of maize–soybean intercropping (M/S) and maize–peanut intercropping (M/P), and further evaluated their comprehensive benefits based on the net ecosystem economic benefit (NEEB). The results showed that compared with CM, the three-year average economic yield of M/S and M/P decreased by 14.6% and 14.0%, with corresponding energy yield reductions of 12.0% and 9.1%. Notably, M/S and M/P significantly increased the maize equivalent yield by 9.4%. Relative to CM, the three-year average net income of M/S and M/P increased by 18.3% and 29.9%, respectively. For carbon-related environmental benefits, M/S and M/P reduced CF per unit maize equivalent yield by 14.0% and 18.1% and CF per unit economic benefit by 13.9% and 18.0%, while increasing the CSI by 6.0% and 8.4%, respectively. Comprehensive evaluation using the Z-score method demonstrated that M/P improved the NEEB by 9.4% and obtained a higher comprehensive score than CM, while M/S produced a marginally lower Z-score than CM. Overall, M/P exhibited the optimal multi-dimensional performance and represents a promising eco-friendly planting pattern for coastal saline-alkali regions.

Plants commonly encounter spatially heterogeneous distributions of nitrogen (N) forms and iron (Fe) in soils, but how N form modifies plant responses to heterogeneous Fe availability remains poorly understood. Using a split-root system, we examined the phenotypic responses of Arabidopsis thaliana and wheat to contrasting Fe availability combined with ammonium (NH₄⁺) or nitrate (NO₃⁻) supply. Plants were exposed to high (100 μM) or low (5 μM) Fe in combination with NH₄⁺ or NO₃⁻, either under homogeneous or spatially heterogeneous conditions. Within each species, NH₄⁺ and NO₃⁻ treatments were supplied at equivalent total N concentrations. In both species, high Fe combined with sole NH₄⁺ supply resulted in pronounced reductions in shoot and root growth, whereas spatial presence of NH₄⁺ and NO₃⁻ between root compartments was associated with improved growth. Under high-Fe conditions, sole NH₄⁺ supply to both root compartments (HAHA) resulted in pronounced reductions in shoot and root growth, whereas supplying NH₄⁺ and NO₃⁻ to separate root compartments (HAHN) was associated with improved growth. Under these conditions, shoot fresh weight in HAHN was 178% higher than that in HAHA in Arabidopsis and 231% higher in wheat. In wheat, root fresh weight under HAHN was 471% higher than under HAHA. Wheat exhibited stronger spatial differentiation of root growth between contrasting nutrient compartments, whereas Arabidopsis showed greater variation in whole-plant growth in response to N form. Chlorophyll accumulation also showed species- and Fe-dependent responses to N form. Overall, these results indicate that N form modifies plant phenotypic responses to heterogeneous Fe–N supply and that wheat exhibits greater root plasticity under spatially heterogeneous Fe–N conditions. The roles of plant Fe and N status, rhizosphere pH, and long-distance signaling in these responses remain to be determined.

The global food processing industry generates substantial volumes of wastewater characterized by elevated ammonia nitrogen concentrations, presenting both significant environmental challenges and opportunities for nutrient recovery. Conventional biological treatment consumes substantial energy for aeration and sludge handling. Algal–bacterial symbiosis represents a promising circular-economy strategy that combines wastewater purification with biomass production. This review synthesizes current knowledge on the application of algal–bacterial consortia for treating ammonia-rich food wastewater, with emphasis on the synergistic mechanisms underpinning nitrogen removal, biomass production, and the generation of high-value products. It examines microalgae–bacteria interactions—mediated by oxygen–carbon dioxide exchange, nutrient conversion, extracellular polymeric substance dynamics, and quorum sensing signaling. Among these mechanisms, quorum sensing acts as one of several key regulatory pathways, modulating microbial community succession, biofilm formation, metabolic pathway expression, and stress tolerance, thereby contributing to pollutant removal efficiency and biomass resource quality, together with gas exchange, nutrient assimilation, and microbial metabolism. The review also evaluates recent advances in reactor configurations that facilitate scalable implementation. Furthermore, it discusses the valorization of harvested biomass into aquafeed, biofertilizers, biofuels, and bioactive compounds, alongside the principal barriers to commercialization. Finally, it highlights emerging research directions involving synthetic biology, artificial intelligence-assisted process control, and a biorefinery that may accelerate the transition of algal–bacterial symbiosis systems from laboratory research toward practical food wastewater treatment and resource recovery applications.

A systematic elucidation of soil ammonia (NH₃) volatilization (SAV) and the underlying drivers is imperative for evaluating NH₃ pollution mitigation strategies and advancing sustainable agricultural practices. Currently, no scientific consensus has been established on the effects of maize–soybean intercropping on SAV across varying nitrogen (N) application rates. A consecutive field experiment was conducted over a 2-year period from 2024 to 2025 with a split-plot design. The experiment comprised three cropping systems (maize monocropping (MM), soybean monocropping (MS), and maize–soybean intercropping (IMS)) and three N application rates (no N application (NN), 20% reduced N application (20%RN), and conventional N application (ConN)). The results demonstrated that N application markedly increased SAV. Accumulative SAV was 4.94–6.01 kg ha⁻¹ under NN treatment, whereas it was 8.21–27.89 kg ha⁻¹ under ConN treatment, 7.25–21.52 kg ha⁻¹ under 20%RN treatment. Under ConN treatment, the accumulative SAV in IMS was 21.34 kg·ha⁻¹ and 27.89 kg·ha⁻¹ in 2024 and 2025, respectively, which were significantly higher than those in MM by 16.80% and 13.33%. Under 20% RN treatment, the accumulative SAV in IMS was 15.46 kg·ha⁻¹ and 19.24 kg·ha⁻¹ in 2024 and 2025, respectively, which were lower than those in MM by 3.07% and 10.59%. SAV was positively correlated with soil ammonium N concentration. Moreover, within an appropriate range, SAV increased in response to rising soil water content and temperature. Collectively, maize–soybean intercropping integrated with a 20% nitrogen reduction mitigated environmental risks associated with reactive nitrogen losses. This system constitutes a stable yield, resource-efficient, and ecologically sustainable cropping practice.