Agricultural Environmental Protection Research Articles

Microagroecosystem models and their landscape ecological risk evolution in karst mountainous areas

Micro-spatial agroecosystem (AES) changes in karst mountain areas are a response to the human-land relationship of the human activity center. However, the changes and linkages between AESs and landscape ecological risks (LER) from a micro perspective in karst mountain areas (KMA) have not yet attracted in-depth attention from the academic community. This paper proposes the concept of microagroecosystems (MAESs) and constructs the MAES model based on the landscape development intensity (LDI) to evaluate the systematic landscape evolution rules and the LER intensity, which reflects the human-land relationship in KMA. We used the buffer ring with a 200 m cultivation range interval to categorize the MAES model into six models, namely, High-Mid-Low, High-Low-Medium, Medium-High-Low, Medium-Low-High, Medium-High-High, Low-Medium-High and Low-Medium-High, and the different models not only reflect the regional conditions but also represent the different stages of the evolution of AESs in KMAs. We found that AESs in karst mountainous areas are transforming from traditional food crop systems to economic fruit forest ecosystems, and at the same time, the gravity center of human activities is migrating from high to low altitude areas, and the ecological vitality of MAESs is showing a trend of enhancement. In addition, the regions with high altitudes and steep slopes in karst mountainous areas have a single landscape structure and are dominated by traditional food cultivation, while the regions with low altitudes and gentle slopes have a diverse landscape structure and are dominated by modern and sustainable agricultural development. Finally, we reveal that the LER in KMAs shows a trend of initial increase followed by subsequent decrease, the influence of the human-land relationship on the LER in the micro perspective is significant, and the coordination and trade-off between agricultural development and environmental protection is the key direction of development in the future. The study results can provide a reference for the rational allocation of landscape, ecological environment restoration, and optimization of regional human-land relationships in KMAs worldwide.

Green Finance Helps Rural Revitalization under the New Institutional Economics

Based on the theoretical basis of new institutional economics, this paper discusses and analyzes the role of green finance in helping rural revitalization. Rural revitalization is an important strategy for China's economic development, while green finance is an important means to achieve sustainable development. This paper first introduces the basic concepts of new institutional economics and green finance, then analyzes the problems faced by rural revitalization and the advantages of green finance, and points out the relationship between green finance and institutional economics. Secondly, this paper expounds the specific application of green finance in rural revitalization from two aspects of agricultural production and environmental protection. Then, this article evaluates the benefits of green finance for rural revitalization. Finally, this paper summarizes the significance of green finance to help rural revitalization under the new institutional economics.

The fate of antibiotic resistance genes during anaerobic digestion of sewage sludge with ultrasonic pretreatment.

This study investigated the effect of ultrasonic (US) pretreatment at three different contact times (30, 45, and 60 min) with a power of 240 W and frequency of 40 kHz on the fate of antibiotic resistance genes (ARGs), mobile genetic elements (MGEs), and enteric pathogens during anaerobic digestion (AD) of sludge. By using real time-qPCR, three MGEs (int1, int2, and tnpA) and seven ARGs (sul1, sul2, tetW, tetA, tetO, ermF, and aac(6')-lb) were quantified that have serious human health impacts and represent the most widely used antibiotics (tetracycline, sulfonamide, macrolide, and aminoglycoside). Results indicated that US pretreatment under different contact times improved the removal of ARGs and MGEs. Compared to 30 and 45 min of US pretreatment, 60 min of US pretreatment resulted in a higher reduction of ARGs with total ARG reduction of 41.70 ± 1.13%. Furthermore, the relative abundance of ARGs and MGEs after US pretreatment was reduced more effectively in anaerobic reactors than in a control AD without US pretreatment. The total ARGs and MGEs removal efficiency of control AD was 44.07 ± 0.72% and 63.69 ± 1.43%, and if US pretreatment at different times were applied, the total ARGs and MGEs removal efficiency of the whole pretreatment AD process improved to 59.71 ± 2.76-68.54 ± 1.58% and 69.82 ± 2.15-76.84 ± 0.22%. The highest removal of total ARGs (68.54 ± 1.58%) and MGEs (76.84 ± 0.22%) was achieved after AD with US pretreatment at 45 min. However, US pretreatment and AD with US pretreatment were not effective in inactivation of enteric pathogens (total coliforms and E. coli), suggesting that posttreatment is needed prior to land application of sludge to reduce the level of enteric pathogens. There was no detection of the studied ARGs and MGEs in the enteric pathogens after US pretreatment in subsequent AD. According to this study, long contact times of US pretreatment can mitigate ARGs and MGEs in AD processes, offering valuable insight into improving environmental safety and sustainable waste management. Additionally, the study highlights the need to investigate posttreatment techniques for reducing enteric pathogens in AD effluent, a crucial consideration for agricultural use and environmental protection.

Should environmental taxes be imposed on agriculture? Analysis from the welfare perspective

IntroductionEnvironmental taxation is an essential regulatory tool for governments seeking to optimize agricultural production, enhance the environment, and guarantee food safety. Concerns exist, however, regarding the imposition of environmental taxes on agriculture, as this could be detrimental to the interests of agricultural producers and consumers. To address these challenges, it is essential to integrate agricultural production, environmental protection, and economic development, which can better comprehend the effects of agricultural environmental taxes on production decisions, the environment, the economy, and society.MethodsTo better comprehend the effects of agricultural environmental taxes on production decisions, the environment, the economy, and society, this paper constructs a mathematical model and analyzes optimal outcomes from a welfare perspective. The study examines the structure of consumer groups, classifying them as either green or non-green.Results and discussionFirst, when both consumer groups coexist on the market, imposing environmental taxes on non-green agricultural producers does not always result in a reduction in social welfare. Within a specific tax range, it is possible to accomplish a tripling of social welfare, agricultural producer welfare, and environmental benefits. Second, as the tax rate rises, the environment progressively improves while consumer surplus diminishes. Within a particular tax range, producer surplus and social welfare both increase. Third, as the proportion of green consumers in the market and ordinary consumers’ awareness of green agricultural foods increases, the positive impact of taxation on the environment decreases, while its positive impact on producer surplus and consumer surplus increases. Taxation can also have a positive effect on the social welfare under certain conditions.ContributionsFirst, we comprehensively investigate the feasibility of agricultural environmental taxation from a welfare perspective, considering market competition and segmentation, which fills a gap in previous studies. Second, we establish a reasonable range for taxation that simultaneously enhances social welfare, producer welfare, and environmental benefits. Third, we explore the relationship between market segmentation structure, ordinary consumers’ awareness of green agricultural foods, and welfare, providing insights into the different attitudes of countries and regions toward agricultural environmental taxation.

A timing self-cleaning nanoherbicide: Design of triple-structure nanovectors for weed control and pesticide residues treatment

Pesticide residues treatment is a crucial issue for both agricultural production and environmental protection. In recent years, designing self-cleaning nanoformulations has emerged as a promising strategy for reducing pesticide residues in a convenient and cost-effective manner. However, traditional physical blending methods of photodegradation reagents with nanocarriers have limitations in terms of pesticide residue degradation efficiency and active ingredient efficacy. Here, a new type of timing self-cleaning nanoherbicide dicamba@mSiO2/ATA/TiO2 with a triple structure was fabricated. Dicamba, a widely used herbicide that was attracting increasing concern over its high efficiency and broad spectrum, was selected as the model herbicide and loaded on the mSiO2 shell. In the stage of pesticide release, the TiO2 and dicamba were separated by the timing-barrier. Therefore, the efficacy of dicamba was not affected by the photocatalyst. During the release process, the ATA layer continuously absorbed the reactive oxygen species (ROS) produced by TiO2 and was gradually degraded. Finally, the barrier was destroyed, and the residual dicamba in the carrier was degraded by TiO2. Compared with the traditional physical blending method, this triple structure avoided the degradation of active ingredients by photocatalysts during the pesticide release period. The experimental results suggested that this nanoformulation improved the efficacy of the herbicide, and reduced the pesticide residues, providing a new approach for self-cleaning nanopesticides research.

Geospatial Artificial Intelligence (GeoAI) and Satellite Imagery Fusion for Soil Physical Property Predicting

This study aims to predict vital soil physical properties, including clay, sand, and silt, which are essential for agricultural management and environmental protection. Precision distribution of soil texture is crucial for effective land resource management and precision agriculture. To achieve this, we propose an innovative approach that combines Geospatial Artificial Intelligence (GeoAI) with the fusion of satellite imagery to predict soil physical properties. We collected 317 soil samples from Iran’s Golestan province for dependent data. The independent dataset encompasses 14 parameters from Landsat-8 satellite images, seven topographic parameters from the Shuttle Radar Topography Mission (SRTM) DEM, and two meteorological parameters. Using the Random Forest (RF) algorithm, we conducted feature importance analysis. We employed a Convolutional Neural Network (CNN), RF, and our hybrid CNN-RF model to predict soil properties, comparing their performance with various metrics. This hybrid CNN-RF network combines the strengths of CNN networks and the RF algorithm for improved soil texture prediction. The hybrid CNN-RF model demonstrated superior performance across metrics, excelling in predicting sand (MSE: 0.00003%, RMSE: 0.006%), silt (MSE: 0.00004%, RMSE: 0.006%), and clay (MSE: 0.00005%, RMSE: 0.007%). Moreover, the hybrid model exhibited improved precision in predicting clay (R2: 0.995), sand (R2: 0.992), and silt (R2: 0.987), as indicated by the R2 index. The RF algorithm identified MRVBF, LST, and B7 as the most influential parameters for clay, sand, and silt prediction, respectively, underscoring the significance of remote sensing, topography, and climate. Our integrated GeoAI-satellite imagery approach provides valuable tools for monitoring soil degradation, optimizing agricultural irrigation, and assessing soil quality. This methodology has significant potential to advance precision agriculture and land resource management practices.

Measurement and temporal and spatial characteristics of agricultural eco-efficiency under climate change: a case study of Anhui, China

IntroductionAgricultural eco-efficiency is an important index to evaluate the agricultural sustainable development and ecological economics, while simultaneously providing a metric for improvements to the rural environment and the stability of agricultural ecosystems.MethodsThis study took Anhui province as a case, and applied unit survey and list analysis methodologies to quantify rural agricultural non-point source pollution (NPS). Input-oriented super-efficient DEA-SBM was used to measure agricultural eco-efficiency in the typical North-South Transition Zone, and evaluated spatial correlations and differences.ResultsThis study showed that NPS was relatively stable, with less than 5% local variation in Chemical Oxygen Demand (COD), Total Nitrogen (TN), and Total Phosphorus (TP) pollutants. The environmental pressure caused by livestock breeding and the use of chemical fertilizers was very substantial, and the differences of rural agricultural NPS in Anhui Province had obvious north-south characteristics. The agricultural eco-efficiency exhibited an “inverted N” trend. Affected by the “Spatial proximity effect” and the “Matthew effect”, it presented spatial agglomeration and positive spatial correlation. The regional differences were significant, and the heterogeneity increased in our study areas. The southern region had the greatest variation, followed by the northern region, with the smallest variation in the central region, although inter-regional differences were consistent.DiscussionThough the rational allocation of resources, coordination between agricultural economic and environmental protection would be realized, and better conditions for the sustainable development of agricultural ecology and the long-term stability of agricultural ecosystem would be created.

Bulanık Mantık Yaklaşımı Kullanılarak Kızılırmak Nehri Aylık Ortalama Akımlarının Tahmini

River flow values are used in the design and operation of hydraulic structures. Determining the correct flow value is important in terms of controlling water movements in the operation of hydraulic structures, irrigation of agricultural lands, hydroelectric production, environmental protection and flood control. In the literature, different methods are used to predict possible river flows using the available data. The fuzzy logic approach is a kind of intelligent system method used in solving problems involving uncertainty. The method has been widely used in the modeling of hydrological data for 2000’s. In this study, the fuzzy logic method was applied to estimate the flow data of Yamula Station on the Kızılırmak River in the Kızılırmak basin, one of the largest basins in Turkey. In addition to these flow station data, the monthly average temperature and monthly total precipitation data of the Kayseri meteorology station, which affects the station flows, were also used for modeling. Three different models were created for the flow estimates. In these models, temperature and precipitation data were selected as input values and river flow data were chosen as output values. In the models, 1982-2012 data of the stations were used. Model output data were tested with data set of 2013, 2014 and 2015. As a result, it has been seen that the fuzzy logic approach gave healthy results when both temperature and precipitation data were used as inputs.

Decoupling relationship between greenhouse gas emissions from cropland utilization and crop yield in China: implications for green agricultural development.

Developing low-carbon utilization of cropland is critical to coordinate agricultural production and environmental protection. Based on a theoretical analysis of greenhouse gas (GHG) emissions and crop production, this study examined the GHG emissions from cropland utilization in China and the decoupling process from crop yields with consideration of different sources and then explored the driving factors in different regions. The results showed that the GHG emissions from cropland utilization in China rose first and then fell between 2003 and 2020, and the decoupling process has undergone three stages, namely "expansive coupling", "weak decoupling", and "strong decoupling". And the eastern and southern provinces are relatively ahead of the western and northwestern provinces. Additionally, crop yields have been basically decoupled from GHG emissions caused by agricultural inputs, but they were still not decoupled from GHG emissions from cropland in Northeastern and Northern China. Among the influencing factors, utilization efficiency has promoted the decoupling progress, the input structure has played a promoting role in the early stage and hindered it later, and the input intensity and the scale have worked as hindering factors. Policy implications have been proposed to support the sustainable development of agriculture.

Design Optimization of Hammer Blade Crusher to Improve the Crushing Performance

China is a large agricultural country, each year will produce a large number of straw. The recycling of straw to China's agricultural development and environmental protection are very helpful, the recycling of straw is mainly energy, fertilizer, feed several uses, different uses need different crushing fineness, so adjust the crushing fineness can improve the recycling rate of straw. This paper mainly on the impact of straw crushing fineness factors for This paper focuses on the theoretical analysis and study of the factors affecting the fineness of straw crushing, and provides a general design plan for the crushing chamber.Firstly, the effect of different hammer and sieve gaps on the pulverisation fineness is studied and the straw pulverisation fineness is changed by changing the hammer and sieve gaps. The effect of hammer blade material, structure, arrangement, distribution density and hammer blade speed on the fineness of the straw is studied. Study the effect of the aperture size and arrangement of the sieve on the fineness of the crushing, and adjust the fineness of the crushing by changing the aperture size of the sieve. The study of the material in the crushing process generated by the "ring flow layer" mechanism, and by changing the shape of the crushing chamber structure to destroy the "ring flow layer" on the impact of the crushing performance of the crusher.Secondly, according to the production requirements of the hammer mill, the structure and material of the hammer blade and screen plate are designed and selected, and the hammer blade is analysed statically using Ansys, the rotor is analysed modally, a complete model of the crushing chamber is designed, and a three-dimensional model of the crushing chamber is built using SolidWorks.Finally, after simulation calculations, the design of the rotor headquarters structure is reasonable. An adjustable hammer and sieve clearance was achieved, reducing costs and improving the efficiency of the pulveriser crushing.

Combining Multi-Source Data and Feature Optimization for Plastic-Covered Greenhouse Extraction and Mapping Using the Google Earth Engine: A Case in Central Yunnan Province, China

Rapidly increasing numbers of the plastic-covered greenhouse (PCG) worldwide ensure food security but threaten environmental security; thus, accurate monitoring of the spatiotemporal pattern in plastic-covered greenhouses (PCGs) is necessary for modern agricultural management and environmental protection. However, many urgent issues still exist in PCG mapping, such as multi-source data combination, classification accuracy improvement, spatiotemporal scale expansion, and dynamic trend quantification. To address these problems, this study proposed a new framework that progressed layer by layer from multi-feature scenario construction, classifier and feature scenario preliminary screening, feature optimization, and spatiotemporal mapping, to rapidly identify large-scale PCGs by integrating multi-source data using Google Earth Engine (GEE), and the framework was first applied to Central Yunnan Province (CYP), where PCGs are concentrated but no relevant research exists. The results suggested that: (1) combining the random forest (RF) classifier and spectrum (S) + backscatter (B) + index (I) + texture (T) + terrain (Tr) feature scenario produced the highest F-score (95.60%) and overall accuracy (88.04%). (2) The feature optimization for the S + I + T + B + Tr scenario positively impacted PCG recognition, increasing the average F-score by 1.03% (96.63% vs. 95.60%). (3) The 6-year average F-score of the PCGs extracted by the combined RF algorithm and the optimal feature subset exceeded 95.00%, and its spatiotemporal mapping results indicated that PCGs were prominently agglomerated in the central CYP and continuously expanded by an average of 65.45 km2/yr from 2016 to 2021. The research reveals that based on the GEE platform, multi-source data can be integrated through a feature optimization algorithm to more efficiently map PCG spatiotemporal information in complex regions.

Determinants of adoption of multiple sustainable agriculture practices among mandarin producing farmers in Salyan District of Karnali Province, Nepal

Sustainable agriculture practices (SAPs) are eco-friendly farming techniques, which ensure the agricultural production and environmental protection simultaneously. The aim of this study was to identify the potential SAPs being adopted by farmers, their adoptability, and to assess the determinant factors for multiple SAPs adoption. For this, face-to-face interview with 120 mandarin producing farmers, six focus groups, and 11 key informants was conducted in Salyan District of Karnali Province, Nepal. Farms were categorized into four categories on the basis of sustainability score and required inferences on quantitative and qualitative data were made by descriptive statistics and probit regression. Results revealed that majority of the mandarin farms were categorized as fairly low and fairly high categories. Factors such as age, gender, and schooling of household head, access to the Internet, distance of market for farm inputs, and availability of human labor had significantly increased the probability of multiple SAPs adoption at varied level of significance. Farm level policies regarding dissemination of integrated nutrient and pest management tactics, subsidization on eco-friendly farm inputs via cooperatives, trainings, demonstration, and field workshops should be formulated and implemented effectively.

Crop Production and Security in Ningjin County of the North China Plain

Stable growth in grain production is a critical challenge to ensure food security in North China Plain (NCP), an area dominated by smallholder farming. Food production and security of NCP largely depend on how smallholders farm their land. This study took Ningjin County of the NCP as an example to describe the characteristics of crop planting structure and the changes in crop production based on household surveys, statistics, various documents, and literature by descriptive statistics, calculation of crop self-sufficiency, and curve fitting, and aimed to reveal crop security and the influencing factors of crop production at the household level. The results were as follows: (1) Wheat and maize sown area accounted for 61.69% and 47.96% of the total sown area of crops during 2000–2020, increasing at a rate of 3.42% and 5.93%, respectively. Their planted areas increased from 27.52% and 15.54% in 2000 to 47.82% and 44.75% in 2020, respectively. (2) The self-sufficiency rate of maize showed a significant upward trend and reached its peak in 2019. the self-sufficiency rate of wheat also showed an increasing trend, from 192.87% to 617.37%, which indicates that wheat and maize can meet food self-sufficiency and the per capita grain yield is in a safe state. (3) The trends on wheat yield and fertilizer initially grew, then decreased, closely resembling an inverted “U”, while the maize yield showed a pattern of increasing first and then basically remaining stable, similar to an “S” shape. A turning point for fertilizer use (550 kg/ha) was identified, indicating the limits of fertilizer use to increase yield. The national agricultural production and environmental protection policies, continuous improvement of crop varieties, as well as the farmers’ traditional practices have significant impacts on crop production. This study will enhance management practices for improved yield, which can support the integrated management of agricultural production in intensive agricultural areas.

An Overview of the Impact of Tillage and Cropping Systems on Soil Health in Agricultural Practices

There is currently a demand to grow more crops in less area as a result of urbanization’s reduction of agricultural land. As a result, soil fertility is gradually declining. To maintain soil fertility, various management methods are used in modern times. The conventional tillage method is a traditional tillage method that damages soil structure, but zero tillage can improve soil quality. By maintaining soil structure with no-tillage, biological processes are frequently improved and microbial biodiversity is increased. This review helps to understand the role of tillage as well as cropping systems in increasing crop production by maintaining soil fertility. For agricultural production and environmental protection to be sustained for future generations, soil quality must be maintained and improved in continuous cropping systems. The nodulation, nitrogen fixation, and microbial community are all impacted by different cropping systems and tillage methods. They also alter soil properties including structure, aeration, and water utilization. The impact of tillage and cropping system practices such as zero and conventional tillage systems, crop rotation, intercropping, cover cropping, cultivator combinations, and prairie strip techniques on soil fertility is carefully summarized in this review. The result highlights that conservational tillage is much better than conventional tillage for soil quality and different aspects of different tillage and their interaction. On the other hand, intercropping, crop rotation, cover cropping, etc., increase the crop yield more than monocropping. Different types of cropping systems are highlighted along with their advantages and disadvantages. Using zero tillage can increase crop production as well as maintain soil fertility which is highlighted in this review. In terms of cropping systems and tillage management, our main goal is to improve crop yield while minimizing harm to the soil’s health.

Food security and overuse of agrochemicals: evidence from China's major grain-producing areas policy.

China's major grain-producing areas (MGPA) policy is the core policy to ensure national food security. While achieving long-term stable growth of grain production, assessing the impact of MGPA policy on agrochemical application has important practical significance in sustainable agricultural development and environmental protection. Based on panel data of 31 provinces in China from 1997 to 2020 and taking the MGPA policy introduced in 2004 as a quasi-natural experiment, we construct a difference-in-difference (DID) model to evaluate the overall impact and dynamic effect of MGPA policy. It is found that the MGPA policy do not exacerbate chemical overuse as a whole, but significantly reduce the fertilizer use by 11% and the pesticide use by 6%. Using the event study to decompose the policy effect year by year, we find that the MGPA policy significantly increased the fertilizer and pesticide use in a short period of time. Its influence on the application amount of two chemicals began to turn negative until the fourth and sixth years of the policy implementation and became more and more obvious. We conclude the intermediate paths of MGPA policy to change planting structure, deepen agricultural division of labor, and reduce the use of agrochemicals, which were verified by the intermediary effect model. From the perspective of provincial differences, MGPA policy reduced chemical use more in provinces with large output contribution and northern provinces. In addition, the MGPA policy has reduced the amount of fertilizer application in major rice-growing provinces, but not the amount of pesticide application. Our research can provide implications for other developing countries and emerging economies where agricultural production is highly dependent on chemicals and has green agricultural transition plans.

Agricultural production and environmental protection

Agricultural production and environmental protection is a science-based study of the agrarian sector of economy. Dictionary gave data and the origin of agricultural crops, their growing and varieties development, geographical distribution, food safety and security, food and feed processing technologies, rational use and consumption of natural resources. Definition of terms in the book explains all the terms that are used in the modern agrarian sector and environmental protection. These two directions are important for increasing crops yield and minimizing the negative "impact" on the ecological environment, preventing genetic erosion of soil and vegetation for the obtaining ecologically clean and safety products. The mentioned publication will contribute to the raising of public awareness of the population, dissemination of the latest advance technologies and development conditions, and will increase guarantees of food security and safety.

Study on the Coupling Effect of Agricultural Production, Road Construction, and Ecology: The Case for Cambodia

Agricultural development is a necessary component of national development efforts to fight food crises and promote poverty reduction in many developing countries. However, many developing countries have fallen into a stalemate between modernization and development—modernized areas are less capable of driving regional development despite their abundant land and rich population. Striking a balance between agricultural technology and environmental protection is a key feature of sustainable land development. Based on the social–ecological resilience theory, this study takes Cambodia as an example and aims to establish a comprehensive evaluation index system to measure the agricultural production, regional road construction, and agricultural eco-environment in Cambodia. The coupled coordination model and gray relation analysis model are utilized to explore the interaction between agriculture, roads, and the agricultural eco-environment. The results show that (1) Cambodia has road environmental risks, and there is a need for rural labor migration in areas with higher levels of economic development. (2) The main agricultural production areas are faced with the dilemma of lagging infrastructure development, such as roads, and a huge potential for agricultural development. (3) In the plains areas, the growing population has caused tension between food security, fertilizer abuse, and deforestation, which intensified the disturbance of the agricultural ecological environment. In summary, based on their own developmental needs, developing countries at different stages of development can explore the interaction between agricultural production, infrastructure development, and the agricultural eco-environment in the process of agricultural development. This study attempts to provide a set of practical development policy implications for developing countries that are seeking to enhance the coupling relationship between agricultural production, infrastructure, and the agricultural eco-environment.

Multitemporal greenhouse mapping for high-resolution remote sensing imagery based on an improved YOLOX

Plastic greenhouses (PGs), as safeguard agricultural facilities, have changed the cultivation structure of agriculture, to a certain extent, and can seriously impact the environment. Exploring the temporal characteristics of greenhouses in terms of quantity and area is significant for sustainable agricultural development and environmental protection. Pixel or object-based large-scale greenhouse mapping has difficulty meeting the demand for the simultaneous extraction of greenhouse quantity and area. Multibranch task model can provide the number and area information of greenhouse. However, there are various labeling methods and model between different branches, which lead to the deviation between quantity and area results. This paper proposes a model that is based on improved you only look once X (YOLOX) and kullback–leibler divergence (KLD), called YOLOX and KLD plus (YXLD + ), to obtain spatiotemporally consistent greenhouse mapping. The new model still has stable performance in dense scenes, with a 5.7 % improvement in average precision compared to BBAVectors. Finally, a multitemporal greenhouse map of Zhoukou City was obtained using imagery provided by Google Earth (GE). Overall, the distribution of greenhouses in Zhoukou City remained stable between 2012 and 2017. However, the number and area of greenhouses in local areas has increased rapidly in the past five years, with the number of greenhouses increasing by 47.08 % and the area expanding by 41.38 %. Greenhouses' distribution and changing characteristics concentrate on the gently sloping areas from the northwest to the southeast. These results provide an objective perspective on the development of the local agricultural cultivation structure, which is of significant importance for the promotion of agricultural modernization.

Study of Designing Technology-Driven Solutions for Holistic Environmental Protection in Agriculture

Study of Designing Technology-Driven Solutions for Holistic Environmental Protection in Agriculture

Assessment and mechanism analysis of plant salt tolerance regulates soil moisture dynamics and controls root zone salinity and sodicity in seasonally irrigated agroecosystems

Soil water deficit and saline-alkaline stress impose severe constrains to agriculture and vary across different salt-tolerant crops. Yet, the effects and mechanisms of plant salt tolerance on long-term soil water budget and future root zone (both primary and secondary) salinization and alkalization trends under changing environments in irrigated agroecosystems have not been fully understood, particularly driven by seasonal irrigation practices and stochastic climate conditions. Here, we introduce a robust species-dependent soil water, salinity, and sodicity coupled model that enables explicitly simulation to the feedback between evapotranspiration and salinity being shaped by plant salt tolerance and saturated hydraulic conductivity as affected by salinization and alkalization in seasonally irrigated agroecosystems. Using this model in conjunction with field comprehensive measurements from a typical arid inland river basin in Northwest China, we find that the species-dependent model performed well in simulating the root zone moisture (s), salinity (Cs) and sodicity (Ex) dynamics as driven by seasonal irrigation and random precipitation under different salt-tolerant crops, with average consistency measure (CM) reaching to 0.825 ± 0.017, 0.819 ± 0.027 and 0.728 ± 0.033, respectively. Stochastic simulations indicate that plant salt tolerance plays a predominant role in regulating the feedback of vegetation on soil water budget and root zone salinity and sodicity levels over time in seasonally irrigated agroecosystems. In contrast to salt-sensitive species, salt-tolerant plants seems to exhibit higher efficiency in water extraction from soil, with higher evapotranspiration rates, less frequent leaching events and greater capillary upflow fluxes, thereby lowering soil moisture and boosting salinization and alkalization in the root zone, particularly in arid climates. Sensitivity analysis revealed that plant salt tolerance, together with climatic forcing and anthropogenic perturbations, can significantly modulate the soil water balance and determine the possible trends of root zone salinization and alkalization in future, thus controlling potential risks of soil degradation related to reducing soil hydraulic conductivity Ks(Cs, Ex) in irrigated agroecosystems. Notably, since Ks(Cs, Ex) decreases with plant salt tolerance increases, salt-resilient species have the potential to exacerbate soil degradation. Our results emphasize the importance of comprehensively considering plant salt tolerance for assessing the sustainability of agricultural management practices and environmental protection measures, as well as proposing adaptive strategies under global changes.