Continual Reinforcement Learning for Intelligent Agricultural Management under Climate Changes

Climate change poses significant challenges to agricultural management,particularly in adapting to extreme weather conditions that impact agricultural production.Existing works with traditional Reinforcement Learning(RL)methods often falter under such extreme conditions.To address this challenge,our study introduces a novel approach by integrating Continual Learning(CL)with RL to form Continual Reinforcement Learning(CRL),enhancing the adaptability of agricultural management strategies.Leveraging the Gym-DSSAT simulation environment,our research enables RL agents to learn optimal fertilization strategies based on variable weather conditions.By incorporating CL algorithms,such as Elastic Weight Consolidation(EWC),with established RL techniques like Deep Q-Networks(DQN),we developed a framework in which agents can learn and retain knowledge across diverse weather scenarios.The CRL approach was tested under climate variability to assess the robustness and adaptability of the induced policies,particularly under extreme weather events like severe droughts.Our results showed that continually learned policies exhibited superior adaptability and performance compared to optimal policies learned through the conventional RL methods,especially in challenging conditions of reduced rainfall and increased temperatures.This pioneering work,which combines CL with RL to generate adaptive policies for agricultural management,is expected to make significant advancements in precision agriculture in the era of climate change.

Effects of Different Agricultural Managements on Characteristics of Soil Microbial Community under Continuous Cropped Strawberry(Fragaria ananassa Duchesne)

[Objective] The objective of this study was to investigate the effects of different agricultural managements on soil microbial population,activity,functional diversity and soil enzyme activity in continuous mono-cropping field of strawberry.[Method]A field plot experiment was carried out to evaluate characteristics of soil microbial community by soil enzyme analysis,microbial cultivation and Biolog analysis.[Result]The results showed that bacteria population proportion,the ration of bacteria to fungi,microorganism amount,AWCD,soil dehydrogenase activity,the Shannon,Simpson,and Mcintosh indices of soil microbial communities were obviously increased under strawberry-rice rotation,soil solarization with rice bran,and calcium cyanamide（CaCN2）treatments,in addition,soil urease activity was significantly increased under strawberry-rice rotation and soil solarization with rice bran treatment,when compared with no fertilization.When compared with conventional fertilization treatment,strawberry-rice rotation and soil solarization with rice bran both significantly increased AWCD and Mcintosh index of soil microbial communities,meanwhile respectively increased soil urease and dehydrogenase activity.PCA analyses suggested that carbon utilization of soil microbial communities under strawberry-rice rotation,soil solarization with rice bran,and calcium cyanamide treatment was obviously different from that of conventional fertilization and no fertilization treatment.[Conclusion] strawberry-rice rotation and soil solarization with rice bran were effective agricultural managements to control soil biological degradation under Continuous Cropped Strawberry.

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.

Research on the Optimization Paths for Outstanding Agricultural Economics and Management Talents under the Background of Curriculum Ideology and Politics

The article aims to discuss how to cultivate outstanding agricultural economics and management talents to meet the needs of agricultural and rural economic development in the new era,within the context of ideological and political education.Through literature review and field research,a series of innovative talent training optimization paths are proposed,and specific suggestions are made for policymakers and educational practitioners.

Establishment of the Agricultural Knowledge Management System in the Knowledge-oriented Government

In order to optimizing the process of the government agricultural decision-making, based on the theories and technologies of the knowledge management, the meaning of the knowledge-based government is firstly analyzed. Combining with the detailed requirements of government for agricultural knowledge management, an agricultural knowledge management system including the agricultural knowledge sharing system, the agricultural Web data-mining system and the agricultural expert decision system is established in the paper.

A Study on the Agricultural Scientific Research Management in the New Situation

As the core of the management of agricultural institutes,scientific research management plays a vital role in strategic development,and also affects the strategic development of agricultural research institutes. This paper expounds the connotation and characteristics of agricultural scientific research management as well as management ability requirements of management personnel. This paper puts forward the recommendations for improving agricultural scientific research management from the view of management personnel.

Research on Application of information technology in agricultural economic management

In the current social, agricultural development is heavily influenced by the level of agricultural information development, so, it is necessary to pay attention to the development of information technology in order to maintain a sustained, steady and rapid development of agriculture, as well as we use information technology in all aspects of agricultural production, so as to make more rapid and stable development of Chinese agriculture. In Agricultural Economics and Management should focus on the help of information technology. The main author makes a brief analysis on the role of information technology in the agricultural economy and the management of specific applications, which is designed to promote the further development of Chinese agriculture.

Reflections on the management of agricultural economy in transition time of agricultural economy

In recent years, although farmers＇ income from agriculture is declining year by year, but the agricultural one is still the most important source of income. Factors determining the size of the total agricultural income are two sides： one is agricultural prices and the other is agricultural production. Obviously, because enhancements of China agricultural production capacity and several price increases of agricultural products, market saturation occurs in China＇ s major agricultural products and the price is close to or above the average level of international market. Simply relying on production increase and price hike has no longer satisfied growth needs of agricultural income.

Strategies for improving crop comprehensive benefits via a decision-making system based on machine learning in the rice‒rape,rice‒wheat and rice‒garlic rotation systems in Southwest China

Rice‒rape,rice‒wheat and rice‒garlic rotations are common cropping systems in Southwest China,and they have played a significant role in ensuring ecological and economic benefits(EB)and addressing the challenges of China’s food security in the region.However,the crop yields in these rotation systems are 1.25‒14.73%lower in this region than the national averages.Intelligent decision-making with machine learning can analyze the key factors for obtaining better benefits,but it has rarely been used to enhance the probability of obtaining such benefits from rotations in Southwest China.Thus,we used a data-intensive approach to construct an intelligent decision‒making system with machine learning to provide strategies for improving the benefits of rice-rape,rice-wheat,and rice-garlic rotations in Southwest China.The results show that raising the yield and partial fertilizer productivity(PFP)by increasing seed input under high fertilizer application provided the optimal benefits with a 10%probability in the rice-garlic system.Obtaining high yields and greenhouse gas(GHG)emissions by increasing the N application and reducing the K application provided suboptimal benefits with an 8%probability in the rice-rape system.Reducing N and P to enhance PFP and yield provided optimal benefits with the lowest probability(8%)in the rice‒wheat system.Based on the predictive analysis of a random forest model,the optimal benefits were obtained with fertilization regimes by reducing N by 25%and increasing P and K by 8 and 74%,respectively,in the rice-garlic system,reducing N and K by 54 and by 36%,respectively,and increasing P by 38%in rice-rape system,and reducing N by 4%and increasing P and K by 65 and 23%in rice-wheat system.These strategies could be further optimized by 17‒34%for different benefits,and all of these measures can improve the effectiveness of the crop rotation systems to varying degrees.Overall,these findings provide insights into optimal agricultural inputs for higher benefits through an intelligent decision-making system with machine learning analysis in the rice-rape,rice‒wheat,and rice-garlic systems.

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.

Reasons and Improving Strategies of Slow Development of Agricultural Insurance System in China

In order to establish modern agriculture and reduce harmful effects of natural disasters to agriculture, developing agricultural insurance and improving agricultural management system are essential. This paper firstly elaborated the feasibility and importance of improving agricultural economy, and analyzed some reasons which restricted China agricultural insurance developing speed, and then gave some improving suggestions in the end.

Construction of Ideological and Political Micro-Courses of Western Economics in Agricultural Economics Major

As a new means and way of combining media convergence and ideological and political education,ideological and political micro-courses play an important role in the process of cultivating the socialist core values of college students and qualified successors of the socialist cause.For western economics as the core course of agricultural economics major,how to construct ideological and political micro-courses in the era of media convergence to give full play to the effective function of micro-courses in ideological and political education in western economics has good practical significance at present.

Research on the Logistics Model of Agricultural Material

The paper states something about the characteristic of agricultural material, product and agricultural material market, and searches for the new agricultural material logistics model. In .addition, some proper strategies are provided for logistic companies.

Diversity and Dynamics of Soil Free-Living Nematode Populations in a Mediterranean Agroecosystem

To determine the effect of agricultural management on the dynamics and functional diversity of soil nematode communities in a carrot field at Kibbutz Ramat Hakovesh, Israel, soil samples from 0-10 cm and 10-20 cm depths were collected during the growing season of carrot. Indices were used to compare and assess the response of soil free-living nernatode communities to agricultural management. Eighteen nematode families and 20 genera were observed during the growing period, with Cephalobus, Rhabditidae, Aphelenchus, Tylenchus, and Dorylaimus being the dominant genera/families. During the planting, mid-season and post-harvest periods the total number of nematodes at both depths was significantly lower (P < 0.01) in the carrot treatment than in the control plots, while during the harvest period at both depths total nematodes and bacterivores were significantly higher in the treatment plots (P < 0.01). The values of the maturity index (MI) at both depths were found to be significantly lower in the treatment plots than in the control plots during the pre-planting period (P < 0.05). Overall, WI, MI and PPI were found to be more sensitive indicators than other ecological indices for assessing the response of nematode communities to agricultural management in a Mediterranean agroecosystem

Agricultural Land Contract and Management Rights:Transferring Price and Countermeasures in Typical Agricultural Areas of China

Henan is a large agricultural province and one of China’s major grain-producing areas. Agricultural land transfer and large-scale operations will have a profound impact on regional economic development and food security. This is a case study taken in Xiwan village in Qinyang city, Henan. This paper builds a transferring pricing model using land use rights assessment and characteristic correction of land contract and management rights. Results show that the transferring price of land contract and management rights should include the economic price, social price and corrected price. The use of a price model should focus on the distinction of theory and practical application. If there is no change in agricultural project,the actual transferring price should be the sum of the economic price and social security price. If there is a change in agricultural projects,such as cropland into cash crops,the actual transferring price should be the sum of the economic price, social price and corrected price. Because of the complexity of income distribution following the transfer, transferring gains should follow a rational distribution in the outflow side, inflow side, managers and land owner. The government should establish reasonable and orderly contracted management of land circulation transferring and use this to build a land transferring price system.

Spatio-temporal Distributions of Tropospheric NO_2 over Oases in Taklimakan Desert, China

Soil biogenic NO emission is one of the most important sources of atmospheric nitrogen oxides(NOx) worldwide. However, the estimation of soil source, especially in arid areas presents large uncertainties because of the substantial lack of measurements. In this study, we selected the Ruoqiang oases on the southeastern edge of the Taklimakan Desert, China as the study area and applied Ozone Monitoring Instrument(OMI) NO2 retrievals(DOMINO v2.0, 2005–2011) to investigate the spatial distribution and seasonal variations in tropospheric NO2 vertical column density(VCD). High NO2 VCDs were observed over the oases(farmlands and natural vegetation), with the highest value obtained during summer, and lowest during winter. Pulses were observed during spring. We conducted in-situ measurements in June 2011 in Milan oasis and employed ground-based multi-axis differential optical absorption spectroscopy(MAX-DOAS) instruments to validate satellite NO2 retrievals. The findings are as follows: 1) in the study area soil biogenic NO emission is the dominant source of tropospheric NO2; 2) oases(farmlands) are hotspots of tropospheric NO2, and a higher increase in tropospheric NO2 is found in oases from winter to summer; and 3) enhancement of soil biogenic NO emission due to soil managements is predictable. Given the rapid agricultural development in the southern Uygur Autonomous Region of Xinjiang, researches on soil biogenic NO emission and increase in tropospheric NOx should be given more importance.

Cross-Validation of a Mobile N20 Flux Prototype （IPNOA） Using Micrometeorological and Chamber Methods

Within a LIFE＋ project IPNOA （improved flux prototype for n2o emission from agriculture）, LIFE11 ENV/IT/302 is a mobile prototype was developed to evaluate at field scale N20 emissions using a fast chamber technique. Main challenge was to develop a mobile system capable of moving on various field surfaces, equipped with very reliable N20 gas analyser （Los Gatos Research Inc.）, electrically autonomous （with batteries） and enough robust to face up to field conditions. In this paper, we report the major features of this prototype studied during two field campaigns. The N20 flux IPNOA prototype was compared with other methodological implementations： first, during an INGOS （integrated non-CO2 greenhouse gas observing systems） campaign on a grazed grassland at Easter Bush （Scotland） by Eddy correlation method, and then after on an arable crop at Grignon （France） using automatic and manual chambers fitted with QC-TILDAS （Quantum Cascade Tunable Infrared Laser Differential Absorption Spectrometer, Aerodyne Research Inc.）, with the 46C model of thermo-instrument analyser or with a GC （gas chromatography） analysis.

DeCASA in AgriVerse: Parallel Agriculture for Smart Villages in Metaverses

The demand for food is tremendously increasing with the growth of the world population,which necessitates the development of sustainable agriculture under the impact of various factors,such as climate change.To fulfill this challenge,we are developing Metaverses for agriculture,referred to as Agri Verse,under our Decentralized Complex Adaptive Systems in Agriculture(De CASA)project,which is a digital world of smart villages created alongside the development of Decentralized Sciences(De Sci)and Decentralized Autonomous Organizations(DAO)for Cyber-Physical-Social Systems(CPSSs).Additionally,we provide the architectures,operating modes and major applications of De CASA in AgriVerse.For achieving sustainable agriculture,a foundation model based on ACP theory and federated intelligence is envisaged.Finally,we discuss the challenges and opportunities.

Multispectral imaging systems for airborne remote sensing to support agricultural production management

This study investigated three different types of multispectral imaging systems for airborne remote sensing to support management in agricultural application and production.The three systems have been used in agricultural studies.They range from low-cost to relatively high-cost,manually operated to automated,multispectral composite imaging with a single camera and integrated imaging with custom-mounting of separate cameras.Practical issues regarding use of the imaging systems were described and discussed.The low-cost system,due to band saturation,slow imaging speed and poor image quality,is more preferable to slower moving platforms that can fly close to the ground,such as unmanned autonomous helicopters,but not recommended for low or high altitude aerial remote sensing on fixed-wing aircraft.With the restriction on payload unmanned autonomous helicopters are not recommended for high-cost systems because they are typically heavy and difficult to mount.The system with intermediate cost works well for low altitude aerial remote sensing on fixed-wing aircraft with field shapefile-based global positioning triggering.This system also works well for high altitude aerial remote sensing on fixed-wing aircraft with global positioning triggering or manually operated.The custom-built system is recommended for high altitude aerial remote sensing on fixed-wing aircraft with waypoint global positioning triggering or manually operated.

Using fuzzy-AHP and parametric technique to assess soil fertility status in Northeast of Iran

A good understanding of the levels and distribution patterns of soil properties and/or quality indicators is a prerequisite for developing sustainable agricultural land management programs. Traditional assessments of these parameters of soil fertility status are somewhat costly, in both economics and time aspects. Different modelling techniques have been proposed as a useful tool for determination of soil quality indicators and development of soil fertility maps, but to what extent these results are reliable remains under-quantified in many regions worldwide. To address this uncertainty, Fuzzy-Analytical Hierarchy Process(Fuzzy-AHP) and Parametric analyses were conducted to ascertain the soil fertility status of a semiarid region in the Northeast of Iran for some selected crops: alfalfa, corn silage, potato, sugar beet, tomato and wheat. The Fuzzy-AHP and Parametric techniques using soil suitability indices were estimated for each crop and each soil delineation was achieved by Ordinary Kriging. The Technique for Order of Preference by Similarity to Ideal Solution(TOPSIS) was used as a compensatory method to allow tradeoffs among the selected criteria. Our results demonstrated that from the Fuzzy-AHP analysis, the soil fertility indices ranged from moderate to high for production of alfalfa;from low to high for production of corn silage and sugar beet;moderate to high for production of potato and tomato;and from low to moderate for production of wheat. However, the parametric analysis showed soil fertility classes ranging from very low to high for production of all the selected crops. High correlations were also observed between soil fertility indices predicted by both models. Similarly, the capacities of both models to predict soil fertility status for production of the selected crops were also highly correlated. The preference for the cultivation of the selected crops based on the Fuzzy-AHP analysis was sugar beet > corn silage > wheat > alfalfa > tomato > potato. On the other hand, using Parametric techniques, the crops preferences for cultivation ranked as corn silage > wheat > alfalfa > sugar beet > tomato > potato. We concluded that the findings would help to develop sustainable plans of cultivation based on patterns related to soil fertility classes depending on each crop’s requirement.