Review on the Impact of Climate Change on Great Lakes Region’s Agriculture and Water Resources

This study investigates the multifaceted impacts of climate change on the Midwest region of the United States, particularly the rising temperatures and precipitation brought about by hot weather activities and technological advances since the 19th century. From 1900 to 2010, temperatures in the Midwest rose by an average of 1.5 degrees Fahrenheit, which would also lead to an increase in greenhouse gas emissions. Precipitation is also expected to increase due to increased storm activity and changes in regional weather patterns. This paper explores the impact of these changes on urban and agricultural areas. In urban areas such as the city of Chicago, runoff from the increasing impervious surface areas poses challenges to the drainage system, and agriculture areas are challenged by soil erosion, nutrient loss, and fewer planting days due to excessive rainfall. Sustainable solutions such as no-till agriculture and the creation of grassland zones are discussed. Using historical data, recent climate studies and projections, the paper Outlines ways to enhance the Midwest’s ecology and resilience to climate change.

Performance of a Horizontal Flow Constructed Reed Bed Filter for Municipal Wastewater Treatment: The Case Study of the Prototype Installed at Gaston Berger University, Saint-Louis, Senegal

In Saint-Louis, Senegal, a constructed wetland with horizontal flow reed beds (FHa and FHb) has demonstrated significant efficacy in treating municipal wastewater. Analyzing various treatment stages, the system showed only a slight temperature variation, from an influent average of 26.3°C to an effluent of 24.7°C. Electrical conductivity decreased from 1331 mS/cm to 974.5 mS/cm post-primary treatment, with suspended solids (SS) dramatically reduced from 718.9 mg/L to 5.7 mg/L in the final effluent. Biochemical oxygen demand (BOD5) and chemical oxygen demand (COD) saw a notable decrease, from initial levels of 655.6 mg/L and 1240 mg/L to 2.3 mg/L and 71.3 mg/L, respectively. Nitrogenous compounds (N-TN) and phosphates () also decreased significantly, indicating the system’s nutrient removal capacity. Microbiological analysis revealed a reduction in fecal coliforms from 7.5 Ulog/100ml to 1.8 Ulog/100ml and a complete elimination of helminth eggs. The presence of Phragmites and Typha was instrumental in enhancing these reductions. The system’s compliance with the Senegalese standards for disposal into natural environments, WHO recommendations for unrestricted water reuse in irrigation, and the European legislation for water reuse was established. The effluent quality met the stringent criteria for various classes of agricultural reuse, illustrating the system’s potential for sustainable water management. This wetland model presents a robust solution for water-stressed regions, ensuring environmental protection while supporting agricultural needs. The study calls for ongoing research to further refine the system for optimal, reliable wastewater treatment and water resource sustainability.

Modeling of Sensor Enabled IrrigationManagement for Intelligent Agriculture Using Hybrid Deep Belief Network

Artificial intelligence(AI)technologies and sensors have recently received significant interest in intellectual agriculture.Accelerating the application of AI technologies and agriculture sensors in intellectual agriculture is urgently required for the growth of modern agriculture and will help promote smart agriculture.Automatic irrigation scheduling systems were highly required in the agricultural field due to their capability to manage and save water deficit irrigation techniques.Automatic learning systems devise an alternative to conventional irrigation management through the automatic elaboration of predictions related to the learning of an agronomist.With this motivation,this study develops a modified black widow optimization with a deep belief network-based smart irrigation system(MBWODBN-SIS)for intelligent agriculture.The MBWODBN-SIS algorithm primarily enables the Internet of Things(IoT)based sensors to collect data forwarded to the cloud server for examination purposes.Besides,the MBWODBN-SIS technique applies the deep belief network(DBN)model for different types of irrigation classification:average,high needed,highly not needed,and not needed.The MBWO algorithm is used for the hyperparameter tuning process.A wideranging experiment was conducted,and the comparison study stated the enhanced outcomes of the MBWODBN-SIS approach to other DL models with maximum accuracy of 95.73%.

Irrigation and nitrogen fertiliser optimisation in protected vegetable fields of northern China:Achieving environmental and agronomic sustainability

Globally,sub-optimal use of nitrogen (N) fertiliser and elevated N irrigation groundwater have led to high leached nitrate (NO_(3)^(–)) losses from protected vegetable field systems.Optimising fertiliser and irrigation management in different soil types is crucial to reduce future N loads from such systems.The present 4-year study examined leached N loads from lysimeter monitoring arrays set up across 18 protected vegetable system sites encompassing the dominant soil types of northern China.The treatments applied at each field site were:1) a high N and high irrigation input treatment (HNHI);2) a low N but high irrigation input treatment (LNHI) and 3) a low N with low irrigation input treatment (LNLI).Results showed that the mean annual leached total nitrogen loads from the HNHI,LNHI and LNLI treatments were 325,294 and 257 kg N ha^(–1) in the fluvo-aquic soil,114,100 and 78 kg N ha^(–1) in the cinnamon soil and 79,68 and 57 kg N ha^(–1) in the black soil,respectively.The N dissolved in irrigation water in the fluvo-aquic soil areas was 8.26-fold higher than in the cinnamon areas.A structural equation model showed that N fertiliser inputs and leaching water amounts explained 14.7 and 81.8%of the variation of leached N loads,respectively.Correspondingly,reducing irrigation water by 21.5%decreased leached N loads by 20.9%,while reducing manure N and chemical N inputs by 22 and 25%decreased leached N loads by only 9.5%. This study highlights that protected vegetable fields dominated by fluvo-aquic soil need management to curtail leached N losses in northern China.

Decoding the inconsistency of six cropland maps in China

Accurate cropland information is critical for agricultural planning and production,especially in foodstressed countries like China.Although widely used medium-to-high-resolution satellite-based cropland maps have been developed from various remotely sensed data sources over the past few decades,considerable discrepancies exist among these products both in total area and in spatial distribution of croplands,impeding further applications of these datasets.The factors influencing their inconsistency are also unknown.In this study,we evaluated the consistency and accuracy of six cropland maps widely used in China in circa 2020,including three state-of-the-art 10-m products(i.e.,Google Dynamic World,ESRI Land Cover,and ESA WorldCover)and three 30-m ones(i.e.,GLC_FCS30,GlobeLand 30,and CLCD).We also investigated the effects of landscape fragmentation,climate,and agricultural management.Validation using a ground-truth sample revealed that the 10-m-resolution WorldCover provided the highest accuracy(92.3%).These maps collectively overestimated Chinese cropland area by up to 56%.Up to 37%of the land showed spatial inconsistency among the maps,concentrated mainly in mountainous regions and attributed to the varying accuracy of cropland maps,cropland fragmentation and management practices such as irrigation.Our work shed light on the promotion of future cropland mapping efforts,especially in highly inconsistent regions.

Artificial Intelligence for Maximizing Agricultural Input Use Efficiency: Exploring Nutrient, Water and Weed Management Strategies

Agriculture plays a crucial role in the economy,and there is an increasing global emphasis on automating agri-cultural processes.With the tremendous increase in population,the demand for food and employment has also increased significantly.Agricultural methods traditionally used to meet these requirements are no longer ade-quate,requiring solutions to issues such as excessive herbicide use and the use of chemical fertilizers.Integration of technologies such as the Internet of Things,wireless communication,machine learning,artificial intelligence(AI),and deep learning shows promise in addressing these challenges.However,there is a lack of comprehensive documentation on the application and potential of AI in improving agricultural input efficiency.To address this gap,a desk research approach was used by utilizing peer-reviewed electronic databases like PubMed,Scopus,Goo-gle Scholar,Web of Science,and Science Direct for relevant articles.Out of 327 initially identified articles,180 were deemed pertinent,focusing primarily on AI’s potential in enhancing yield through better management of nutrients,water,and weeds.Taking into account researchfindings worldwide,we found that AI technologies could assist farmers by providing recommendations on the optimal nutrients to enhance soil quality and deter-mine the best time for irrigation or herbicide application.The present status of AI-driven automation in agricul-ture holds significant promise for optimizing agricultural input utilization and reducing resource waste,particularly in the context of three pillars of crop management,i.e.,nutrient,irrigation,and weed management.

Variations in Soil Organic Matter Content in Cultivated and Uncultivated Calcareous Soils from the Mediterranean Island of Malta after 15 Years of Cultivation

The soils of Malta are calcareous and generally undeveloped. Organic matter (OM) in these soils is low and farmers are constantly urged to increase it. The objective of this study was to evaluate any temporal variation in soil OM after 15 years of cultivation, and determine whether soil series, soil depth, and cultivation influence variation. OM was determined in the topsoil and subsoil of 7 agricultural and 4 non-agricultural sites. The sites represented 7 different soil series that are present on the island. In sampling periods 1 (t = 0 years) and 2 (t =15 years), the OM content in the collective (all soil series) bulk (topsoil and subsoil) uncultivated soil was 3.9 % and 3.8 % respectively. This was significantly greater than that of the collective bulk cultivated soil (2.4% and 2.3%). The OM in the collective uncultivated topsoil was 5.4% and 5.2% in periods 1 and 2 and was significantly higher than that of the cultivated topsoil (2.5% in both periods). The OM content in the collective uncultivated subsoil was 2.3% and 2.5% in periods 1 and 2 respectively but only that measured in period 2 was significantly higher than that of the cultivated subsoil (2.2% in both periods). On an individual soil series basis, the OM in the uncultivated topsoils was significantly higher than that of their cultivated counterparts. The differences in the subsoils were not significant. Across the uncultivated soil series, OM was significantly higher in the topsoil than in the subsoil but in the cultivated soil series the differences between topsoil and subsoil were not significant. There was no significant difference in OM between the uncultivated soils of different series, but in the cultivated the OM content was higher in soils that were more mature. After 15 years, no significant change in OM occurred in both the collective cultivated and uncultivated bulk soils, the collective topsoil and subsoil, and in most of the individual series. The OM content of each soil series was also similar to what was reported 60 and 50 years earlier by other researchers.

Advanced biosensing technologies for monitoring of agriculture pests and diseases:A review

The threat posed to crop production by pests and diseases is one of the key factors that could reduce global food security.Early detection is of critical importance to make accurate predictions,optimize control strategies and prevent crop losses.Recent technological advancements highlight the opportunity to revolutionize monitoring of pests and diseases.Biosensing methodologies offer potential solutions for real-time and automated monitoring,which allow advancements in early and accurate detection and thus support sustainable crop protection.Herein,advanced biosensing technologies for pests and diseases monitoring,including image-based technologies,electronic noses,and wearable sensing methods are presented.Besides,challenges and future perspectives for widespread adoption of these technologies are discussed.Moreover,we believe it is necessary to integrate technologies through interdisciplinary cooperation for further exploration,which may provide unlimited possibilities for innovations and applications of agriculture monitoring.

Analysis of the Dynamic Relationship among Financial Fund for Agriculture, Agricultural Output Value and Farmers' income

By using the methods of co-integration, impulse response function and variance decomposition, I conduct the empirical research on the dynamic relationship among China's financial fund for agriculture, agricultural output value, and farmers' income from the year 1978 to the year 2009. The results indicate that the government's financial fund for agriculture plays the significant role in promoting agricultural output value and farmers' income in the long run, but this role of promoting is not prominent in the short run; in the mean time, agricultural output value plays insignificant role in promoting farmers' income and the government's financial fund for agriculture; farmers' income plays the significant role in promoting agricultural output value and the government's financial fund for agriculture.

Research on Financial Support for the New Types of Agricultural Management Entities from the Perspective of the Rural Revitalization Strategy

Both the escape from the predicament of traditional financial support in rural areas and the cultivation of new types of agricultural management entities underlie,at a micro level,the improvement of a new-type of agricultural management system,and offer an important guarantee for the implementation of a rural revitalization strategy.In reference to the demands of carrying out reform,activating factors,invigorating entities and stimulating markets during the implementation of this rural revitalization strategy,we are applying a financing preference theory that infers and analyzes the excessive preference for new-type agricultural management entities(family farms,specialized farmer cooperatives,specialized large family farms,and modern agricultural enterprises)regarding government subsidies(quasi-equity financing).Our analysis has identified crucial factors in the issue and predicts that government subsidies(quasi-equity financing)will crowd out financial support funding(quasi-debt financing),and we offer empirical proof obtained through statistical modeling.As our results indicate,financing costs,free cash flows,and the perceived income adequacy(PIA)of new-type agricultural management entities all have significant influence upon decision-making for debt financing by such entities.Therefore,with the concrete contents of the formulation of policies concerning the financial support for rural agricultural strategy,one not only needs to consider the further decrease of financing costs,but also should take into account both the designing of cash flow mechanism in the process of paying both principal and interest,and the improvement of bankruptcy rules for agricultural management entities to accelerate the transformation of family farms,specialized farmer cooperatives,and specialized large family farms,towards modern agricultural enterprises.Meanwhile,upgrades to the supply chains of the agriculture industry,improvements to the construction of the rural financial information system,building an accounting system that meets the requirements of the rural revitalization strategy,and giving full play to the policies for financial support,which assume an important role in activating factors and markets during the implementation of the rural revitalization strategy,are also anticipated.

The Relation between Performance and Flows of Mutual Funds: Case of the Croatian Fund Market

With pre 2008 euphoria and present depression, inflows to open investment funds and outflows from it shaped general market conditions on the Croatian fund market. This article studies the relationship between performance of open ended investment funds and inflows (outflows) to them on Croatian funds data in an environment without long fund data history, with small number of funds and relatively illiquid underlying equity market. The results suggest that the driving forces behind funds’ flows encompass the combined influence of present month fund’s performance and persistency of past performances. At the end of our analysis we test the significance of the introduced explanatory variables on the data sets that include data for each particular fund. The significance of the introduced explanatory variables varies among different funds, although a general level of the explanatory power is maintained on average.

‘Smart’copycat mutual funds:on the performance of partial imitation strategies

Using a novel measure of stock-level trade imitation,we uncover‘smart’copycats:fund managers that use their own information when beneficial,and otherwise imitate other managers’better trades.Contrary to previous research,we find that these partial imitation strategies lead to outperformance.Our‘Copycat Score’combines the propensity to imitate and to lead trades.Funds at the high and low ends of the score outperform all others.The Copycat Score is persistent in time,related to other measures of skill,and a good predictor of fund performance.We conclude that smart copycatting is another skill of successful fund managers.

Educational Reform in Management Courses of Agricultural & Forestry Higher Vocational Schools from the Perspective of Microblog

At present there are many socialized microblog platforms.With powerful mobility,real-time information,fragment of information dissemination,and innovation of interaction,the microblog has become a socialized interaction mode in recent years.Since microblog is very popular with students of agricultural and forestry higher vocational schools,with the rising and development of network education,the microblog as a new information platform will be used by more and more teachers in education.From the perspective of microblog,this paper studied educational reform in management courses of agricultural and forestry higher vocational schools,in the hope of providing certain reference and help for current education practice of agricultural and forestry management courses.

Influence of Outflow of Rural Funds on Financial Support for Agriculture

Since the reform and opening-up,rural finance has made enormous contribution to rural economic development.However,with commercialization reform of financial institutions,the conflict between outflow of large funds and shortage of funds for rural economic development becomes prominent,leading to serious degradation of agricultural support function of rural finance.From the perspective of outflow of rural funds,this paper analyzes the problem of"deviation from agriculture"of rural financial business,and derives the conclusion that it is necessary and urgent to restore agricultural support function of rural finance.Then,it discusses restoration path for agricultural support function of rural finance.Finally,it comes up with some effective paths in accordance with existing problems in agricultural support function of rural finance.

Construction of the All-region Linkage System for Emergency Management of Agricultural Product Quality and Safety in West China

Quality and safety of agricultural products are significant for national socioeconomic development,sustainable development,and vital interests of people.To safeguard quality and safety of agricultural products in west China is to safeguard economic safety and ecological safety of the country,public health and social stability,of which an important task is to properly handle emergencies concerning quality and safety of agricultural products.Considering actual conditions of west China,suggestions are given to construct the all-region linkage system for emergency management of agricultural product quality and safety in the local area,enhance the all-region linkage,and improve the linkage efficiency.

How to Optimize the Management of Science and Technology Funds in Colleges and Universities Based on the Policy of Streamlining Administration,Delegating Powers,Improving Regulation,and Strengthening Services

To advance the field of science and technology,we need to revitalize the development of science and technology through innovation.The development of science and technology has many beneficial implications on the revitalization of the country.For this reason,universities in China should give full attention to their role as the main propeller of science and technology.“Streamlining administration,delegating powers,improving regulation,and strengthening services”is a policy issued by the Chinese government for the management of science and technology funds in colleges and universities.Based on the policy of“streamlining administration,delegating powers,improving regulation,and strengthening services,”colleges and universities must optimize the management of science and technology funds for their efficient use.In this paper,we analyzed the importance of the policy and put forward an effective management strategy,aiming to improve the management of science and technology funds in colleges and universities.

The Relationship between Customer Knowledge Management and Performance of Agricultural Product Innovation

This paper takes an overview of the CKM and the performance of agricultural product innovation from contents of agricultural product innovation and customer knowledge management (CKM) ,the relation between CKM and agricultural product innovation. On the basis of the overview, it builds the theoretical framework of CKM and agricultural product innovation. It points out that enterprises can satisfy demands of customers through acquisition,share,utilization and innovation of customer knowledge,and improve performance of agricultural product innovation through speeding up agricultural product innovation.

Construction of the Ontology-Based Agricultural Knowledge Management System

Ontology is the formal representation of concepts and their mutual relations. It has wide application potential in the classification of agricultural information, the construction of information and knowledge database, the research and development of intelligent search engine, as well as the realization of cooperative information service, etc. In this research, an ontology-based agricultural knowledge management system framework is proposed, which includes modules of ontology-based knowledge acquisition, knowledge representation, knowledge organization, and knowledge mining, etc. The key technologies, building tools and applications of the framework are explored. Future researches on the theoretical refinement and intelligent simulation knowledge service are also envisioned.