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Nanotechnology has attracted the interest of scientists due to its wide range of application specifically in agriculture. Nanoparticles (NPs) may act as a promising materials to alleviate cadmium (Cd) stress in plants. This study aims to assess the impact of multiple nanoparticles including nSiO2 (50 mg L−1:100 mg L−1), nTiO2 (20 mg L−1:60 mg L−1), nZnO (50 mg L−1:100 mg L−1), nFe3O4 (100 mg L−1:200 mg L−1), nCuO (50 mg L−1:100 mg L−1), and nCeO2 (50 mg L−1:100 mg L−1) in combination with CdCl2 (5 µM) to mitigate Cd toxicity in lettuce through foliar application in hydroponic solution. Current findings indicate that foliar application of nSiL + Cd (50 mg L−1), nZnL + Cd (50 mg L−1), and nTiL + Cd (20 mg L−1) is more effective in improving growth, biomass, root architecture, and elevated photosynthetic efficiency, which might be attributed to the increasing uptake of essential micronutrient (K, Mg, Ca, Fe, Zn) under Cd stress. Similarly, treatment with nanoparticles leads to reduced accumulation of ROS and MDA in lettuce, while enhancing the SOD, POD, CAT, and APX activities. The results showed that nanoparticles have high tolerance against Cd as depicted by the inhibition in Cd accumulation by 3.2–58% and 10–72% in roots as well as edible parts of lettuce, respectively. In addition, Cd alone reduces the morphological traits, antioxidant enzyme activity, and photosynthetic activity, while increasing the ROS, MDA, and Cd accumulation in lettuce. This comprehensive study suggests the role of nanoparticles in reducing Cd toxicity in lettuce, signifying their importance as stress mitigation agents. However, long-term pot, priming, and field trials are needed to identify the optimal nanoparticle for the lettuce under variable environmental conditions. [ABSTRACT FROM AUTHOR]

The accurate prediction of environmental Se (selenium) adsorption levels is critical for sustainable development and management perception. The concept of sorting massive quantities of data to find important information using machine learning (ML) has recently been applied to environmental remediation, particularly the science-based design of a 'green' carbonaceous and an effective functional material (e.g., biochar and Fe modified biochar) with high Selenium (Se) removal capacity. The present study focuses on presenting ML models that utilize the random-forest (RF) support vector regression (SVR) and SHAP (SHapley Additive exPlanations) models to forecast the adsorption of Se by modified biochar. The RF, SVR and SHAP models, which were constructed using basic surface properties of Fe-modified biochar and environmental conditions showed accuracy and predictive performance for Se (removal capacity in the test group with R2 of 0.98, 0.98 and 0.95 and RMSE of 0.35, 0.14 and 0.23 mg-kg−1, respectively). The SVR model was highly effective for predicting Se adsorption, indicating potentially higher accuracy than the RF and SHAP models. This may be due to the small size of our data. According to the feature analysis and partial dependence plot analysis of all three models, the most significant component regulating Se adsorption was oxygen (%) followed by carbon (%), temperature, pH and Fe in all three models. The relative importance of variables may offer guidance for researchers to develop improved Se treatment of actual water and wastewater. Moreover, the ML models developed in this study took into account the surface functionalities of biochar and Fe-modified biochar to provide a more accurate prediction of Se removal, and offer a comprehensive guideline for the long-term development of biochar adsorbents for Se removal. Highlights: ML can predict Se adsorption by Fe-modified biochar (with O being most significant factor), improving Se treatment of water and wastewater. Researchers can use the relative importance of factors to improve Se treatment of real water and wastewater ML in environmental remediation can promote sustainability and protect the environment by reducing harmful pollutants. [ABSTRACT FROM AUTHOR]

Phosphorus (P) is limiting nutrient in many soils, and P availability may often depend on iron (Fe) speciation. Colloidal iron phosphate (FePO4coll) is potentially present in soils, and we tested the hypothesis that phytate exudation by Pteris vittata might dissolve FePO4coll by growing the plant in nutrient solution to which FePO4coll was added. The omission of P and Fe increased phytate exudation by P. vittata from 434 to 2136 mg kg−1 as the FePO4coll concentration increased from 0 to 300 mM. The total P in P. vittata tissue increased from 2880 to 8280 mg kg−1, and the corresponding increases in the trichloroacetic acid (TCA) extractable P fractions were inorganic P (860–5100 mg kg−1), soluble organic P (250–870 mg kg−1), and insoluble organic P (160–2030 mg kg−1). That is, FePO4-solubilizing activity was positive correlated with TP, TCA P fractions in P. vittata, TP in growth media, and root exudates. This study shows that phytate exudation dissolved FePO4coll due to the chelation effect of phytic acid on Fe; however, the wider question of whether phytic acid excretion was prompted by deprivation of P, Fe, or both remains to be answered. [ABSTRACT FROM AUTHOR]

Purpose: The present study aimed to assess the synergistic effects of superabsorbent polyacrylamide hydrogel (SPH) and gypsum on colloidal phosphorus (CP) release from different farmlands (i.e. tea, vegetable, and paddy soils). Materials and methods: A laboratory experiment was carried out to examine the effects of SPH at different rates of 0.00, 0.01, 0.05, and 0.1% (w/w) and gypsum at the rates of 0 and 0.005% (w/w) on CP released from different farmland soils. For this purpose, CP, colloidal molybdate–reactive P (MRPc), and colloidal molybdenum–unreactive P (MUPc) were measured in soil solutions. Results and discussion: The results revealed that the release of CP, MRPc, and MUPc ranged respectively from 5.20 to 56.65, 1.62 to 39.09, and 0.33 to 37.10% of total P (TP) in soil solutions across three farmland soils. Besides, the soils treated with SPH and gypsum (0.1%) mitigated CP release respectively by 51.75%, 62.64%, 24.13%, and 62.74% for tea, vegetable, silt loam paddy, and loam paddy soils. However, the MRPc release dropped respectively by 40.22%, 41.04%, 38.55%, and 63.70% in tea, vegetable, silt loam paddy, and loam paddy soils, and similar trends were observed in MUPc, namely, 43.72%, 49.37%, 35.71%, and 56.17% respectively in tea, vegetable, silt loam paddy, and loam paddy soils. The results indicated that gypsum could make a binding in the carboxyl group of polyacrylamide (PAM)/SPH and anion CP because of decreased CP release. Conclusions: The major form of P was CP, and co-application of PAM/SPH and gypsum could be a promising management approach to moderate CP release from agricultural soils. [ABSTRACT FROM AUTHOR]

Colloidal phosphorus (CP) as an additional route of P mobilization in soil solution has gained much attention. A batch experiment was conducted to investigate the effect of sheep manure-derived biochar (SMB) on CP release from various land uses (paddy, vegetable, tea, and citrus) at a rate of 0% as a control treatment (CK), 1% as a low (L) level, 2% as a middle (M) level, and 4% as a high (H) level of SMB application. The CP and MRPcoll in the solution increased from 30.58 to 88.97% and from 2.45 to 55.54% of total P (TP), respectively. The SMB enhanced CP release in all the soils and all the treatments (except CK and L levels in tea soil; CK, L, and M levels in vegetable soil; and L and M levels in citrus soil). Multiple linear regression revealed a significant correlation between CP and MRPcoll and between colloidal iron, aluminum, calcium, and total organic carbon (Fecoll, Alcoll, Cacoll, and TOCcoll) and pH, which may play an important role as CP carriers that could depend on the pH. This study suggests that the application of SMB in the soil at an appropriate rate of 1 and 2% for tea and vegetable soils, respectively, could be beneficial to avoid the risk of CP release in water bodies. [ABSTRACT FROM AUTHOR]