Regulating the Electronic Structure of Ni Sites in Ni(OH)2 by Ce Doping and Cu(OH)2 Coupling to Boost 5-Hydroxymethylfurfural Oxidation Performance.

Biomass is a sustainable and renewable resource that can be converted into valuable chemicals, reducing the demand for fossil energy. 5-Hydroxymethylfurfural (HMF), as an important biomass platform molecule, can be converted to high-value-added 2,5-furandicarboxylic acid (FDCA) via a green and renewable electrocatalytic oxidation route under mild reaction conditions, but efficient electrocatalysts are still lacking. Herein, we rationally fabricate a novel self-supported electrocatalyst of core-shell-structured copper hydroxide nanowires@cerium-doped nickel hydroxide nanosheets composite nanowires on a copper mesh (CuH_NWs@Ce:NiH_NSs/Cu) for electrocatalytically oxidizing HMF to FDCA. The integrated configuration of composite nanowires with rich interstitial spaces between them facilitates fast mass/electron transfer, improved conductivity, and complete exposure of active sites. The doping of Ce ions in nickel hydroxide nanosheets (NiH_NSs) and the coupling of copper hydroxide nanowires (CuH_NWs) regulate the electronic structure of the Ni active sites and optimize the adsorption strength of the active sites to the reactant, meanwhile promoting the generation of strong oxidation agents of Ni3+ species, thereby resulting in improved electrocatalytic activity. Consequently, the optimal CuH_NWs@Ce:NiH_NSs/Cu electrocatalyst is able to achieve a HMF conversion of 98.5% with a FDCA yield of 97.9% and a Faradaic efficiency of 98.0% at a low constant potential of 1.45 V versus reversible hydrogen electrode. Meanwhile, no activity attenuation can be found after 15 successive cycling tests. Such electrocatalytic performance suppresses most of the reported Cu-based and Ni-based electrocatalysts. This work highlights the importance of structure and doping engineering strategies for the rational fabrication of high-performance electrocatalysts for biomass upgrading.

Evaluation of Dianhong black tea quality using near-infrared hyperspectral imaging technology.

BACKGROUND: Tea (Camellia sinensis L) is a highly nutritious beverage with commercial value globally. However, it is at risk of economic fraud. This study aims to develop a powerful evaluation method to distinguish Chinese official Dianhong tea from various other categories, employing hyperspectral imaging (HSI) technology and chemometric algorithms. RESULTS: Two matrix statistical algorithms encompassing a gray-level co-occurrence matrix (GLCM) and a gradient co-occurrence matrix (GLGCM) are used to extract HSI texture data. Three novel spectral variable screening methods are utilized to select wavenumbers of near-infrared (NIR) spectra: iteratively retaining informative variables (IRIV), interval random frog, and variable combination population analysis. Feature fusion of image texture characteristics and spectra data are the eigenvectors for model building. Authentic classification models are constructed using the extreme learning machine approach and the least squares support vector machine (LSSVM) approach, coupling them with features from wavelength extraction techniques for assessing the quality of Dianhong black tea. The results demonstrate that the LSSVM model using fused data (IRIV + GLGCM) provides the best results and achieves a predictive precision of 99.57%. CONCLUSION: This study confirms that HSI coupled with LSSVM is effective in differentiating authentic Dianhong black tea samples. © 2020 Society of Chemical Industry.

Cognitive spectroscopy for evaluating Chinese black tea grades (Camellia sinensis): near-infrared spectroscopy and evolutionary algorithms.

BACKGROUND: Grading represents an essential criterion for the quality assurance of black tea. The main objectives of the study were to develop a highly robust model for Chinese black tea of seven grades based on cognitive spectroscopy. RESULTS: Cognitive spectroscopy was proposed to combine near-infrared spectroscopy (NIRS) with machine learning and evolutionary algorithms, selected feature information from complex spectral data and show the best results without human intervention. The NIRS measuring system was used to obtain the spectra of Chinese black tea samples of seven grades. The spectra acquired were preprocessed by standard normal variate transformation (SNV), multiplicative scatter correction (MSC) and minimum/maximum normalization (MIN/MAX), and the optimal pretreating method was implemented using principal component analysis combined with linear discriminant analysis algorithm. Three feature selection evolutionary algorithms, which were a genetic algorithm (GA), simulated annealing (SA) and particle swarm optimization (PSO), were compared to search the best preprocessed characteristic wavelengths. Cognitive models of Chinese black tea ranks were constructed using extreme learning machine (ELM), K-nearest neighbor (KNN) and support vector machine (SVM) methods based on the selected characteristic variables. Experimental results revealed that the PSO-SVM model showed the best predictive performance with the correlation coefficients of prediction set (Rp ) of 0.9838, the root mean square error of prediction (RMSEP) of 0.0246, and the correct discriminant rate (CDR) of 98.70%. The extracted feature wavelengths were only occupying 0.18% of the origin. CONCLUSION: The overall results demonstrated that cognitive spectroscopy could be utilized as a rapid strategy to identify Chinese black tea grades. © 2020 Society of Chemical Industry.

Applicability of multifunctional preprocessing device for simultaneous estimation of spreading of green tea, withering of black tea and shaking of oolong tea.

BACKGROUND: Preprocessing technologies of fresh tea leaves have a great influence on tea quality. A multifunctional preprocessing device for tea raw materials has been designed and utilized as a novel item of equipment to synchronously meet the process needs of spreading of green tea, withering of black tea and shaking of oolong tea. RESULTS: The preprocessing parameters of fresh tea leaves for spreading of green tea, withering of black tea and shaking of oolong tea were optimized by orthogonal experiments. Sensory assessment combined with statistical tools was employed as an analytical method to evaluate the pretreatment effect of processing different sorts of tea. The range analysis and variance analysis of tea sensory evaluation combined with chemical components (total polyphenols, free amino acids and soluble sugar) showed that A3 B2 C3 (70%, 25 °C, 8 h), A1 B3 C1 (60%, 28 °C, 18 h) and A1 B1 C3 (5 min, 20 °C, discontinuous leaf turning c) were considered to be the optimum schemes for the best pretreatment conditions of the above three major processing types of tea, respectively. The verification experiment of the proposed schemes was performed with satisfactory performance. CONCLUSION: This study demonstrated that a multifunctional preprocessing device for fresh tea leaves can be successfully applied to simultaneously estimate spreading of green tea, withering of black tea and shaking of oolong tea. © 2019 Society of Chemical Industry.

Analysis of the environmental behavior of farmers for non-point source pollution control and management: An integration of the theory of planned behavior and the protection motivation theory.

Agricultural non-point source (NPS) pollution in water source protection areas poses serious challenges for governments in developing countries. It is important to consider the environmental behavior of farmers when exploring the causes of NPS pollution as well as when establishing scientific controls and management measures. However, the poor understanding of factors influencing the environmental behavior of farmers and the lack of a suitable environmental socio-psychological model limit the application of the environmental behavior of farmers in NPS pollution management. In this study, we therefore integrated the theory of planned behavior (TPB) and the protection motivation theory (PMT) to identify the main determinants of the NPS pollution-related environmental behavior and intention of farmers in the Water Source Area of the Middle Route of the South-to-North Water Diversion Project in China. Results indicated that the integrated model provided a better understanding of the environmental behavior and intention of farmers than that provided by each component when used individually, and revealed that farmers perceived that the susceptibility and severity of threats caused by water deterioration influenced environmental intention through the mediating effects of subjective norm and attitude toward adopting pro-environmental behavior. At the same time, the perceived vulnerability of farmers was relatively high and their perceived severity was relatively low. Furthermore, the subjective norm, attitude, self-efficacy (i.e., the perceived behavioral control), and response efficacy positively and significantly influenced intention. However, response cost had a significantly negative effect on intention. Among them, subjective norm had the largest effect on intention. Intention was the key determinant for the actual environmental behavior of farmers, while self-efficacy also had a significantly positive effect on behavior. Managing and controlling agricultural NPS pollution requires a multi-disciplinary and comprehensive approach. Therefore, an integrated theoretical framework was developed in this study by integrating TPB and PMT to gain insight into the environmental behaviors and intention of farmers. The results provided a theoretical basis for NPS pollution control.

Research on the food security condition and food supply capacity of Egypt.

Food security is chronically guaranteed in Egypt because of the food subsidy policy of the country. However, the increasing Egyptian population is straining the food supply. To study changes in Egyptian food security and future food supply capacity, we analysed the historical grain production, yield per unit, grain-cultivated area, and per capita grain possession of Egypt. The GM (1,1) model of the grey system was used to predict the future population. Thereafter, the result was combined with scenario analysis to forecast the grain possession and population carrying capacity of Egypt under different scenarios. Results show that the increasing population and limitations in cultivated land will strain Egyptian food security. Only in high cultivated areas and high grain yield scenarios before 2020, or in high cultivated areas and mid grain yield scenarios before 2015, can food supply be basically satisfied (assurance rate ≥ 80%) under a standard of 400 kg per capita. Population carrying capacity in 2030 is between 51.45 and 89.35 million. Thus, we propose the use of advanced technologies in agriculture and the adjustment of plant structure and cropping systems to improve land utilization efficiency. Furthermore, urbanization and other uses of cultivated land should be strictly controlled to ensure the planting of grains.

Rapid detection of ash content in black tea using a homemade miniature near-infrared spectroscopy.

Ash is a testing index with both health inspection value and quality decision value, and it is an essential detection item in the import and export trade of tea. To realize the rapid and effective quantitative analysis of ash content in tea, this study proposed the use of a homemade miniature near-infrared (NIR) spectroscopy combined with multivariate analysis for the rapid detection of ash content in black tea. First, NIR data of black tea samples from different countries were acquired and optimized by the spectral preprocessing method. Then, the optimized pre-processed spectral data were used as features, and four feature wavelength selection algorithms, such as competitive adaptive reweighted sampling, iteratively retaining informative variables (IRIV), variable combination population analysis (VCPA)-IRIV, and interval variable iterative space shrinkage approach (IVISSA), were utilized to optimize the feature spectra. Finally, the support vector machine regression (SVR) algorithm was employed to construct the quantitative models of ash content in black tea by combining the optimal wavelengths obtained from the four feature selection methods mentioned above. The experimental results showed that the IVISSA-SVR model had the best performance, with correlation coefficient (Rp), root mean square errors of prediction (RMSEP), and relative prediction deviation (RPD) of 0.9546, 0.0192, and 5.59 for the prediction set, respectively. The results demonstrate that a miniature NIR sensing system combined with chemometrics as an effective analytical tool can realize the rapid detection of ash content in black tea.

Straw Retention with Reduced Fertilization Enhances Soil Properties, Crop Yields, and Emergy Sustainability of Wheat-Soybean Rotation.

Cereal + legume rotation is an integrated system that facilitates soil fertility and sustainable agricultural production. However, research on the management compatibility affecting soil physico-chemical properties yields overall agro-ecosystem sustainability, but profitability is lacking, especially under straw retention and potential reductions in fertilizer application. An 11-year field experiment investigated three treatments: no straw retention + traditional mineral fertilization (TNS), straw retention + traditional mineral fertilization (TS), and straw retention + reduced mineral fertilization (DS). Compared with TNS, TS significantly improved soil physico-chemical properties, including macro-aggregates (R > 0.25 mm), porosity, field water capacity (FWC), soil organic carbon (SOC) storage, total nitrogen storage, microbial biomass carbon (MBC), and microbial biomass nitrogen (MBN) by 17.3%, 3.2%, 13.0%, 5.5%, 3.2%, 15.5%, and 13.8%, respectively. TS also significantly increased total (wheat + soybean) yields (TYs), economic profits, and emergy sustainability index (ESI) by 15.8%, 25.0%, 3.7 times that of TNS, respectively. Surprisingly, compared with TS, DS further significantly improved R > 0.25 mm, porosity, FWC, SOC storage, MBC, MBN, TY, economic profits, and ESI by 11.4%, 1.5%, 6.1%, 3.0%, 10.6%, 7.2%, 5.7%, 11.1%, and 36.5%, respectively. Overall, retaining straw with reduced fertilization enhances soil properties, yields, and emergy sustainability in wheat-soybean rotation systems.

Changes in Soil Aggregate Carbon Components and Responses to Plant Input during Vegetation Restoration in the Loess Plateau, China.

Vegetation restoration is an effective measure to cope with global climate change and promote soil carbon sequestration. However, during vegetation restoration, the turnover and properties of carbon within various aggregates change. The effects of plant source carbon input on surface soil and subsurface soil may be different. Thus, the characteristics of carbon components in aggregates are affected. Therefore, the research object of this study is the Robinia pseudoacacia forest located in 16-47a of the Loess Plateau, and compared with farmland. The change characteristics of organic carbon functional groups in 0-20 cm, 20-40 cm, and 40-60 cm soil layers were analyzed by Fourier near infrared spectroscopy, and the relationship between the chemical structure of organic carbon and the content of organic carbon components in soil aggregates was clarified, and the mechanism affecting the distribution of organic carbon components in soil aggregates was revealed in the process of vegetation restoration. The results show the following: (1) The stability of surface aggregates is sensitive, while that of deep aggregates is weak. Vegetation restoration increased the surface soil organic carbon content by 1.97~3.78 g·kg-1. (2) After vegetation restoration, the relative contents of polysaccharide functional groups in >0.25 mm aggregates were significantly reduced, while the relative contents of aromatic and aliphatic functional groups of organic carbon were significantly increased. The opposite is true for aggregates smaller than 0.25 mm. (3) With the increase in soil depth, the effect of litter on organic carbon gradually decreased, while the effect of root input on the accumulation of inert carbon in deep soil was more lasting.

Response surface optimization of methane potentials in anaerobic co-digestion of multiple substrates: dairy, chicken manure and wheat straw.

Dairy manure (DM), chicken manure (CM) and wheat straw were used to investigate the possibility of optimizing the methane (CH4) potentials in anaerobic co-digestion of multiple substrates. Response surface methodology (RSM) was used to evaluate the individual and interactive effects of four variables [carbon/nitrogen (C/N) ratio, the feeding composition (DM/CM), initial substrate loading and inoculum-to-substrate ratio (ISR)] in the digestion process. All four variables had significant effects on CH(4) potentials. Interactive effects of C/N and DM/CM ratios, C/N ratio and ISR, initial substrate loading and ISR were significant The optimum conditions were a C/N ratio of 26.31, a DM/CM ratio of 42.96:57.04, an initial loading of 15.90 g volatile solids (VS)/l and an ISR ratio of 2.34, with the maximum CH4 potential being 394 ml/g VS. The RSM model was appropriate for optimizing CH4 production in the process of anaerobic co-digestion of multiple substrates.

Rapid Characterization of Black Tea Taste Quality Using Miniature NIR Spectroscopy and Electronic Tongue Sensors.

The taste of tea is one of the key indicators in the evaluation of its quality and is a key factor in its grading and market pricing. To objectively and digitally evaluate the taste quality of tea leaves, miniature near-infrared (NIR) spectroscopy and electronic tongue (ET) sensors are considered effective sensor signals for the characterization of the taste quality of tea leaves. This study used micro-NIR spectroscopy and ET sensors in combination with data fusion strategies and chemometric tools for the taste quality assessment and prediction of multiple grades of black tea. Using NIR features and ET sensor signals as fused information, the data optimization based on grey wolf optimization, ant colony optimization (ACO), particle swarm optimization, and non-dominated sorting genetic algorithm II were employed as modeling features, combined with support vector machine (SVM), extreme learning machine and K-nearest neighbor algorithm to build the classification models. The results obtained showed that the ACO-SVM model had the highest classification accuracy with a discriminant rate of 93.56%. The overall results reveal that it is feasible to qualitatively distinguish black tea grades and categories by NIR spectroscopy and ET techniques.

Combining Straw Mulch with Nitrogen Fertilizer Improves Soil and Plant Physio-Chemical Attributes, Physiology, and Yield of Maize in the Semi-Arid Region of China.

Mulching and nitrogen (N) fertilization are the main drivers for sustainable crop production. The sole use of nitrogen fertilizer threatened both the physiology and production of maize in rain-fed areas. Therefore, we proposed that wheat straw mulching with N fertilization would increase maize yield by improving soil fertility, physiology, and nitrogen use efficiency. A two-year field study evaluated the effects of CK (control), N (nitrogen application at 172 kg ha-1), HS (half wheat straw mulch, 2500 kg ha-1), HS+N (half wheat straw, 2500 kg ha-1 plus 172 kg N ha-1), FS (full wheat straw, 5000 kg ha-1), and FS+N (full wheat straw, 5000 kg ha-1 plus 172 kg N ha-1) on maize growth, physiology, and biochemistry. Compared with the control, the FS+N treatment resulted in the increase of 56% photosynthetic efficiency, 9.6% nitrogen use efficiency, 60% nitrogen uptake, 80% soluble sugar, 59% starches, 48% biomass, and 29% grain yield of maize. In addition, the FS+N regime increased 47%, 42%, and 106% of soil organic carbon and available P and N content in comparison with the control. Maize grain and biomass yields were positively correlated with N uptake, photosynthesis, soil organic carbon, and soil available N and P contents. Conclusively, the use of wheat straw at 5000 kg ha-1, along with 172 kg N ha-1, is a promising option for building a sustainable wheat-maize cropping system to achieve optimal crop yield and improved plant and soil health in a semi-arid region of China.

[Mineralization Characteristics of Soil Organic Carbon and Its Relationship with Organic Carbon Components in Artificial Robinia pseudoacacia Forest in Loess Hilly Region].

In order to explore the characteristics of organic carbon mineralization and the variation law of organic carbon components of an artificial forest in a loess hilly area, an artificial Robinia pseudoacacia forest restored for 13 years and the adjacent slope farmland were selected as the research objects, and indoor culture experiments under three different temperature treatments (15, 25, and 35℃) were carried out. The results indicated that the mineralization rate of soil organic carbon decreased sharply at first and then stabilized. The cumulative release of organic carbon increased rapidly in the initial stage of culture and gradually slowed in the later stage. Soil organic carbon mineralization in sloping farmland was more sensitive to temperature change, and its temperature sensitivity coefficient Q10 was 1.52, whereas that in R. pseudoacacia forest land was only 1.38. According to the fitting of the single reservoir first-order dynamic equation, the soil mineralization potential Cp of R. pseudoacacia forest land and slope farmland was between 2.02-4.32 g·kg-1 and 1.25-3.17 g·kg-1, respectively, that is, the mineralization potential of the R. pseudoacacia forest was higher. During the cultivation period, the content of various active organic carbon components decreased with time, and that in the R. pseudoacacia forest land was greater than that in the slope land. The cumulative carbon release of soil was significantly positively correlated with the contents of MBC and DOC (P<0.05), and Q10 (15-25℃) was negatively correlated with the contents of SOC, EOC, and SWC (P<0.05). These results could provide some reference for the study of soil carbon sequestration in loess hilly regions under climate change.

Differential effects of petroleum-based and bio-based microplastics on anaerobic digestion: A review.

The number of plastics is increasing owing to the rapid development of the plastics industry. Microplastics (MPs) are formed during the use of both petroleum-based plastics and newly developed bio-based plastics. These MPs are inevitably released into the environment and are enriched in wastewater treatment plant sludge. Anaerobic digestion is a popular sludge stabilization method for wastewater treatment plants. Understanding the potential impacts of different MPs on anaerobic digestion is critical. This paper provides a comprehensive review of the mechanisms of petroleum-based MPs and bio-based MPs in anaerobic digestion methane production and compares their potential effects on biochemical pathways, key enzyme activities, and microbial communities. Finally, it identifies problems that must be solved in the future, proposes the focus of future research, and predicts the future development direction of the plastics industry.

Changes in the material characteristics of maize straw during the pretreatment process of methanation.

Pretreatment technology is important to the direct methanation of straw. This study used fresh water, four bacterium agents (stem rot agent, "result" microbe decomposition agent, straw pretreatment composite bacterium agent, and complex microorganism agent), biogas slurry, and two chemical reagents (sodium hydroxide and urea) as pretreatment promoters. Different treatments were performed, and the changes in the straw pH value, temperature, total solid (TS), volatile solid (VS), and carbon-nitrogen ratio (C/N ratio) under different pretreatment conditions were analyzed. The results showed that chemical promoters were more efficient than biological promoters in straw maturity. Pretreatment using sodium hydroxide induced the highest degree of straw maturity. However, its C/N ratio had to be reduced during fermentation. In contrast, the C/N ratio of the urea-pretreated straw was low and was easy to regulate when used as anaerobic digestion material. The biogas slurry pretreatment was followed by pretreatments using four different bacterium agents, among which the effect of the complex microorganism agent (BA4) was more efficient than the others. The current study is significant to the direct and efficient methanation of straw.

Assessing the determinants of teachers' job happiness in the private universities.

Teachers' job happiness in private universities is an important element for the healthy and orderly development of universities and an inevitable requirement for the construction of university faculty, and it has become a hot topic of research in the field of private higher education at present. However, there is still a lack of empirical studies on the factors influencing job happiness in private universities. This study constructs a theoretical model between professional identity, job competence, professional motivation, professional prospects, perceived fairness, job achievements and job happiness, and explores the specific drivers of teachers' job happiness in private universities based on empirical research. The results of the data analysis showed that professional identity, job competence, professional prospects, perceived fairness, job achievements, and professional motivation all had significant effects on teachers' job happiness, and the effects were decreasing. This study examined the effects of job happiness in practice in private universities, which helped private universities to enhance teachers' professional identity, strengthen organizational support for teacher development, promote teachers' teaching ability, improve job competence, and build a developmental teacher evaluation mechanism.

Landscape Ecological Risk Assessment Based on Land Use Change in the Yellow River Basin of Shaanxi, China.

The Yellow River Basin in Shaanxi (YRBS) has a relatively fragile ecological environment, with severe soil erosion and a high incidence of natural and geological disasters. In this study, a river basin landscape ecological risk assessment model was constructed using landscape ecology principles to investigate the temporal and spatial evolution, as well as the spatial autocorrelation characteristics of landscape ecological risks in the YRBS over a 20-year period. The main findings from the YRBS were that the land use types changed significantly over the span of 20 years, there was spatial heterogeneity of the landscape pattern, and the ecological risk value was positively correlated. The threat of landscape ecological risks in YRBS is easing, but the pressure on the ecological environment is considerable. This study provides theoretical support administrative policies for future ecological risk assessment and protection, restoration measures, and control in the Yellow River Basin of Shaanxi Province.

Soil microbial nitrogen-cycling gene abundances in response to crop diversification: A meta-analysis.

Single planting structure has a significant impact on the maintenance of nitrogen in managed ecosystems. Although the effect of crop diversity on soil nitrogen-cycling microbes is mainly related to the influence of environmental factors, there is a lack of quantitative research. This study aims to determine the effect of diversified cropping mode on the abundance of functional genes in the soil nitrogen cycle based on the quantitative integration of a meta-analysis database containing 189 observation data pairs. The results show that the soil nifH (nitrogenase coding gene), nirS and nirK (nitrite reductase coding gene), and narG (nitrate reductase coding gene) abundances are positively affected by the diversity of plant species, whereas the amoA (ammonia monooxygenase coding gene) and nosZ (nitrous oxide reductase coding gene) show no response. Diversification duration and ecosystem type are important factors that regulate soil nitrogen fixation and nitrification gene abundances. Denitrification genes are mainly affected by categorical variables such as the planting pattern, soil layer, application species, duration, and soil texture. Among them, the long-term continuous diversification is mainly manifested in the reduction of soil nifH and increase of nirK abundances. Soil organic carbon and nitrogen linearly affect the responses of nifH, amoA, nirS, and nirK. Therefore, to maintain the soil ecological function, diversity of planting patterns needs to be applied flexibly by regulating the abundance of nitrogen-cycling genes. Our study draws conclusions in order to provide theoretical references for the sustainability of nitrogen and improvement of management measures in the process of terrestrial managed ecosystem diversification.

Redeploy manure resources to enhance the agro-pastoral cycle.

Returning manure to the land is a critical link in the internal cycle of agricultural systems, but excess manure leads to water eutrophication. The traditional manure re-use method brings pathogenic microorganisms, heavy metals, antibiotic resistance genes (ARGs), insect eggs, and other contaminants into the soil, posing a great threat to the ecological environment and human health. Clarifying the spatial distribution patterns of manure nutrient supply and farmland nutrient demand can help guide a more efficient and harmless way to return manure to farmland. This work counted data on cultivation and breeding in 356 cities on the Chinese mainland from 2015 to 2019 and calculated the livestock breeding volume (LB), total environmental capacity (C), and remaining environmental capacity (RC) accordingly. The Spatial Autocorrelation Model (SAC) was used to analyze the distribution patterns of the three. Data results show that China currently has the potential to double LB, but most cities in the west have excess manure due to the mismatched distribution of LB and C. The hot spot analysis results demonstrate the priority/general areas of manure management and the export/import areas of manure resources. The results of the outlier analysis show that some cities located at the boundary of RC Cold/Hot spot areas (e.g., Chengdu City) can perform resource replacement nearby to relieve local environmental pressure. This study analyzes the potential and realistic resistance to utilizing manure as an organic nutrient resource and provides a reference for developing manure management links.

[Effects of Straw Returning and Fertilizer Application on Soil Nutrients and Winter Wheat Yield].

In order to explore the effects of straw returning combined with fertilizer on soil nutrients and winter wheat yield in the Guanzhong area, an experimental split plot design was utilized. The main plot consisted of no straw returning (S0) and straw returning (S). The sub-regions consisted of no fertilizer (WF), nitrogen fertilizer (NF), and nitrogen and phosphate fertilizer (NPF). Ecological stoichiometry was used to study the relationship between soil carbon, nitrogen, phosphorus content, and yield under straw returning combined with nitrogen and phosphorus fertilizer conditions. The results showed that straw and fertilization interactions had significant effects on soil organic carbon, total nitrogen, and total phosphorus contents in the surface layer (0-20 cm) (P<0.05). Compared with that in the S0WF treatment, the SNPF treatment significantly increased soil organic carbon and total nitrogen contents in the surface layer (0-20 cm) (P<0.05). The interaction between straw and year had significant effects on soil total nitrogen content in the surface layer (0-20 cm) (P<0.05). With the increase in straw returning time, the total nitrogen content of soil 0-20 cm under the SWF treatment was significantly higher than that under the S0WF treatment (P<0.05). Straw and fertilization and their interaction had no significant effects on organic carbon and total nitrogen contents in the 20-40 cm soil layer (P>0.05). Straw and straw interaction with fertilization significantly affected total P content in 20-40 cm soil (P<0.05). Compared with that in the SWF treatment, the SNPF treatment significantly increased the total phosphorus content in the 20-40 cm soil layer (P<0.05). Straw returning combined with chemical fertilizer also had a significant effect on soil stoichiometry. Compared with that in the S0WF treatment, the S0NPF treatment decreased soil C:N in the surface layer (0-20 cm) and increased soil C:P and N:P in the surface layer (0-20 cm). Compared with that in the SWF treatment, the SNF treatment reduced soil C:N in the surface layer (0-20 cm). Straw returning combined with chemical fertilizer also had a significant effect on winter wheat yield. In 2020 and 2021, the SNPF treatment increased production by 24.23% and 28.9%, respectively, compared with that of the S0WF treatment. Correlation analysis showed that yield was significantly positively correlated with C:N (P<0.05) and C:P (P<0.01). At the same time, total nitrogen and N:P were positively correlated with treatment years (P<0.001). In conclusion, straw returning and that combined with nitrogen and phosphate fertilizer (SNPF) can improve soil nutrient characteristics, change soil stoichiometric characteristics, and increase yield in the Guanzhong area. Therefore, the results of this study indicate that straw returning combined with nitrogen and phosphate fertilizer (SNPF) is an effective way to optimize regional farmland nutrient management and improve grain production capacity.