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Considering the high demand for air quality, the development of biomass-based air filtration membranes with high air filtration efficiency and good stability is an urgent task. In this work, polyvinyl alcohol (PVA), gelatin (GA), and cellulose nanocrystals (CNC) were mixed and prepared into a membrane through an electrospinning method for air filtration. After a hydrophobic modification, the modified PVA/GA/CNC composite membrane showed excellent filtration efficiency for PM2.5 (97.65%) through the internal three-dimensional structure barrier and the electrostatic capture effect of the CNC with a negative charge, as well as a low-pressure drop (only 50 Pa). In addition, the modified PVA/GA/CNC composite membrane had good mechanical properties (maximum tensile fracture rate of 78.3%) and high stability (air filtration efficiency of above 90% after five wash-filter cycles and a high-temperature treatment at 200 °C). It is worth noting that the whole preparation process is completed without organic solvents, putting forward a new strategy for the construction of green air filtration membranes. [ABSTRACT FROM AUTHOR]

Nitrogen (N) is an essential macronutrient for crop growth; therefore, N deficit can greatly limit crop growth and production. In the North China Plain (NCP), winter wheat (Triticum aestivum L.) is one of the main food crops, and its yield has increased from approximately 4000 kg ha−1 to 6000 kg ha−1 in the last two decades. Determining the proper N application rates at different growth stages and in all seasons is very important for the sustainable and high production of wheat in the NCP. A field experiment with five N application rates (250, 200, 150, 100, and 40 kgN·ha−1, designated as N250, N200, N150, N100, and N40, respectively) was conducted during the 2017–2018 and 2018–2019 winter wheat seasons to investigate the effects of the N application rate on water- and fertilizer-utilization efficiency and on the crop growth and yield of winter wheat under sprinkler fertigation conditions. The results showed that in the N application range of 40–200 kg ha−1, crop yield and water- and fertilizer-use efficiencies increased as the N application rate increased; however, further increases in the N application rate (from N200 to N250) did not have additional benefits. The N uptake after regreening of winter wheat linearly increased with crop growth. Considering the wheat yield and N-use efficiency, the recommended optimal N application rate was 200 kg ha−1, and the best topdressing strategy was equal amounts of N applied at the regreening, jointing, and grain-filling stages. The results of this study will be useful for optimizing field N management to achieve high wheat yield production in the NCP and in regions with similar climatic and soil environment conditions. [ABSTRACT FROM AUTHOR]

Timely and accurate estimation of Above-Ground-Biomass (AGB) in cotton is essential for precise production monitoring. The study was conducted in Shaya County, Aksu Region, Xinjiang, China. It employed an unmanned aerial vehicle (UAV) as a low-altitude monitoring platform to capture multispectral images of the cotton canopy. Subsequently, spectral features and textural features were extracted, and feature selection was conducted using Pearson's correlation (P), Principal Component Analysis (PCA), Multivariate Stepwise Regression (MSR), and the ReliefF algorithm (RfF), combined with the machine learning algorithm to construct an estimation model of cotton AGB. The results indicate a high consistency between the mean (MEA) and the corresponding spectral bands in textural features with the AGB correlation. Moreover, spectral and textural feature fusion proved to be more stable than models utilizing single spectral features or textural features alone. Both the RfF algorithm and ANN model demonstrated optimization effects on features, and their combination effectively reduced the data redundancy while improving the model performance. The RfF-ANN-AGB model constructed based on the spectral and textural features fusion worked better, and using the features SIPI2, RESR, G_COR, and RE_DIS, exhibited the best performance, achieving a test sets R2 of 0.86, RMSE of 0.23 kg·m−2, MAE of 0.16 kg·m−2, and nRMSE of 0.39. The findings offer a comprehensive modeling strategy for the precise and rapid estimation of cotton AGB. [ABSTRACT FROM AUTHOR]

Industrial water electrolysis requires highly-active and ampere-current-bearing oxygen evolution reaction (OER) catalysts, but achieving such a large operating current density at low overpotentials in available OER catalysts still remains a grand challenge. Herein, we report a facile and conventional strategy to grow vertically non-metallic modified nickel ferrite nanosheets on Fe foam (S-NiFe2O4/IF) as largecurrent-density OER catalysts. The vertically aligned nanosheet arrays can offer large electrochemical surface area, and the spacing between nanoarrays can allow for effective electrolyte access to the active sites. The introduction of S enhanced the adsorption and dissociation to water and optimized the adsorption of OER intermediates. As a result, S-NiFe2O4/IF exhibits superior OER activity with an overpotential of 287 and 326 mV to achieve 100 and 500 mA cm−2, respectively, and displays robust stability in alkaline media. In addition, the synthesis strategy developed here can be applied to other mixed transition metal oxides with similar selfsupported earth-abundant nanoarrays for advanced electrocatalysis in energy-related reactions.