Smart Farming for Sustainable Rice Production:An Insight into Application,Challenge,and Future Prospect

Rice has a huge impact on socio-economic growth,and ensuring its sustainability and optimal utilization is vital.This review provides an insight into the role of smart farming in enhancing rice productivity.The applications of smart farming in rice production including yield estimation,smart irrigation systems,monitoring disease and growth,and predicting rice quality and classifications are highlighted.The challenges of smart farming in sustainable rice production to enhance the understanding of researchers,policymakers,and stakeholders are discussed.Numerous efforts have been exerted to combat the issues in rice production in order to promote rice sector development.The effective implementation of smart farming in rice production has been facilitated by various technical advancements,particularly the integration of the Internet of Things and artificial intelligence.The future prospects of smart farming in transforming existing rice production practices are also elucidated.Through the utilization of smart farming,the rice industry can attain sustainable and resilient production systems that could mitigate environmental impact and safeguard food security.Thus,the rice industry holds a bright future in transforming current rice production practices into a new outlook in rice smart farming development.

Contour Farming Suitability of the Black Soil Region in Northeast China and Its Spatial Characteristics

Contour farming technology plays a key role in reducing soil erosion,enhancing water use efficiency,and fostering sustain-able agricultural development,Despite being a straightforward yet efficacious farming technique,it has not seen widespread implement-ation in China.Considering the deteriorating quality of arable lands in the Black Soil Region of Northeast China(BSR-NEC),it is ne-cessary to investigate spatial patterns and identify suitable areas for contour farming in this region.To achieve this objective,spatial autocorrelation and grouping analysis methods were employed to classify the land into four categories of suitability for contour farming:highly suitable,moderately suitable,generally suitable,and unsuitable.The results reveal that:1)the contour farming suitable area in BSR-NEC covers 89861.32 km^(2),accounting for 21.59%of arable land as of 2020.Heilongjiang Province owns the largest suitable area of 32853.68 km^(2),and Inner Mongolia has the highest proportion of 28.89%.2)In terms of the spatial distribution,regions with higher suitability for contour farming are concentrated in the Da Hinggan Mountains region,particularly Nenjiang City(Heilongjiang Province),which has the highest area of 2593.07 km^(2).Areas with a high proportion of suitable arable lands for contour farming are mainly found in the Da Hinggan Mountains and Changbai Mountains regions,with Ergun City(Inner Mongolia)having the highest pro-portion at 47.2%.Regions with higher suitability and proportion are concentrated in the Da Hinggan Mountains region,primarily cover-ing the Inner Mongolia and Heilongjiang.3)Regarding spatial clustering,both the area and proportion of suitable contour farming areas exhibit noticeable clustering effects,though not entirely consistent.4)Group analysis results designate 148 counties in BSR-NEC as highly suitable areas,predominantly located in the Changbai Mountains region,Liaodong Peninsula,Hulun Buir Plateau,and the north and south regions of the Da Hinggan Mountains.The zoning of suitable areas for contour farming in BSR-NEC informs the strategic de-velopment of policies and measures,allowing for the implementation of targeted policies in distinct areas suitable for contour farming.This provides a valuable reference for promoting contour farming technology more effectively and efficiently.re effectively and effi-ciently.

Technical efficiency of cocoa farms at varying elevation levels in Davao City, Philippines: implications to sustainable upland farming systems

Elevation is one of many components that influence agriculture, and this in turn affects the level of both inputs and outputs of farmers. This article focuses on the productivity and technical efficiency of 100 cocoa farms using cross-sectional data from areas ranging from 190 to 1021 m above sea level which were classified as low, medium, and high elevation in Davao City, considered as the chocolate capital of the Philippines. Using stochastic frontier analysis, the results showed that the cost of inputs per ha and the number of cocoa trees per ha significantly increase yield. Farms at high elevations were less technically efficient, as this entails lower temperatures and increased rainfall, and cocoa farming in those areas and conditions can be more challenging, especially with changes in farming practices, terrain, and distance to markets. Other significant variables were age of cocoa farms, married farmers, and age of the farmers. Older farms may be more developed, farmers who are married benefit from their spouses being able to readily contribute as farm labor, and lastly, older farmers' inefficiency may likely stem from nonadaptation of newer farming practices. With an average technical efficiency of 0.61, 0.63, and 0.26 in low, medium, and high elevation areas, respectively, farmers therefore have an incentive to improve farm practices and consider topographical variations found in high elevation areas. Recommendations for the improvement of technical efficiency of cocoa farms are better connectivity to markets, enhancing farm practices, and continuation and improvement of government programs on cocoa with an added emphasis on research. For farmers in high elevation areas, mitigating solutions such as sustainable agriculture practices and ecolabelling are key to improving efficiency and minimizing the potential negative impact on upland farming systems. Moreover, such adaptation measures may also contribute to sustainability of cocoa farming in high elevation areas.

The role of time preferences in contract breach:Evidence from Chinese poultry farmers participating in contract farming

Farmers’contract breach behavior is cited as one of the major stumbling blocks in the sustainable expansion of contract farming in many developing countries.This paper examines farmers’contract breach decisions from the perspective of time preferences.The empirical analysis is based on a household survey and economic field experiments of poultry households participating in contract farming conducted in Jiangsu Province,China.A discounted utility model and a maximum likelihood technique are applied to estimate farmers’time preferences and the effect of time preferences on contract breach in the production and sales phases are explored with a bivariate probit model.The results show that,on average,the poultry farmers in the sample are generally present biased and impatient regarding future utility.The regression results show that farmers with a higher preference for the present and a higher discount rate are more likely to breach contracts,and time preferences play a greater role in the production phase than in the sales phase.When considering heterogeneity,specific investments and transaction costs promote contract stability only for farmers with a low degree of impatience.Moreover,compared with large-scale farmers,small-scale farmers’contract breach decisions are more significantly affected by their time preferences.These results have implications for contract stability policies and other issues that are impacted by the linking of behavioral preferences to agricultural decisions.

Information-Centric IoT-Based Smart Farming with Dynamic Data Optimization

Smart farming has become a strategic approach of sustainable agriculture management and monitoring with the infrastructure to exploit modern technologies,including big data,the cloud,and the Internet of Things(IoT).Many researchers try to integrate IoT-based smart farming on cloud platforms effectively.They define various frameworks on smart farming and monitoring system and still lacks to define effective data management schemes.Since IoT-cloud systems involve massive structured and unstructured data,data optimization comes into the picture.Hence,this research designs an Information-Centric IoT-based Smart Farming with Dynamic Data Optimization(ICISF-DDO),which enhances the performance of the smart farming infrastructure with minimal energy consumption and improved lifetime.Here,a conceptual framework of the proposed scheme and statistical design model has beenwell defined.The information storage and management with DDO has been expanded individually to show the effective use of membership parameters in data optimization.The simulation outcomes state that the proposed ICISF-DDO can surpass existing smart farming systems with a data optimization ratio of 97.71%,reliability ratio of 98.63%,a coverage ratio of 99.67%,least sensor error rate of 8.96%,and efficient energy consumption ratio of 4.84%.

Enhanced Water Quality Control Based on Predictive Optimization for Smart Fish Farming

The requirement for high-quality seafood is a global challenge in today’s world due to climate change and natural resource limitations.Internet of Things(IoT)based Modern fish farming systems can significantly optimize seafood production by minimizing resource utilization and improving healthy fish production.This objective requires intensive monitoring,prediction,and control by optimizing leading factors that impact fish growth,including temperature,the potential of hydrogen(pH),water level,and feeding rate.This paper proposes the IoT based predictive optimization approach for efficient control and energy utilization in smart fish farming.The proposed fish farm control mechanism has a predictive optimization to deal with water quality control and efficient energy consumption problems.Fish farm indoor and outdoor values are applied to predict the water quality parameters,whereas a novel objective function is proposed to achieve an optimal fish growth environment based on predicted parameters.Fuzzy logic control is utilized to calculate control parameters for IoT actuators based on predictive optimal water quality parameters by minimizing energy consumption.To evaluate the efficiency of the proposed system,the overall approach has been deployed to the fish tank as a case study,and a number of experiments have been carried out.The results show that the predictive optimization module allowed the water quality parameters to be maintained at the optimal level with nearly 30%of energy efficiency at the maximum actuator control rate compared with other control levels.

Influences of large-scale farming on carbon emissions from cropping:Evidence from China

Reducing agricultural carbon emissions is important to enable carbon emission peaking by 2030 in China.However,China's transformation towards large-scale farming brings uncertainties to carbon emission reduction.This study quantifies the carbon emissions from cropping based on life cycle assessment and estimates the effects of farm size on carbon emissions using a fixed effects model.Furthermore,the variations of the carbon emissions from cropping driven by the changes in farm size in future years are projected through scenario analysis.Results demonstrate an inverted U-shaped change in total carbon emission from cropping as farm size increases,which is dominated by the changes in the carbon emission from fertilizer.Projections illustrate that large-scale farming transformation will postpone the peak year of total carbon emission from cropping until 2048 if the change in farm size follows a historical trend,although it is conducive to reducing total carbon emission in the long run.The findings indicate that environmental regulations to reduce fertilizer usages should be strengthened for carbon emission abatement in the early stage of large-scale farming transformation,which are also informative to other developing countries with small farm size.

Current Implementation and Experience of Natural Farming in Japan

The natural farming in Japan mainly includes Mokich Okadas natural farming theory and Masanobu Fukuokas natural farming theory in terms of genre.Natural farming was proposed and implemented to deal with the anabatic soil degradation and food safety problems.Among themꎬMokich Okadas natural farming theory advocates the restoration of the agricultural tradition of the past and combination with modern agricultural science and technologyꎻMasanobu Fukuokas natural farming theory advocates a complete return to natural and traditional farming and puts forward a set of green agricultural cultivation methods focusing on injurious insect control with beneficial insectꎬweed control with green herbaceous plantsꎬsoil reclamation with grassꎬnontoxic and cost￣reducing method based on the Japanese ancient agricultural books.Their natural farming theories have been widely popularized and applied in Japanꎬand its successful experience is worthy of study and reference for China.

Effect of Combined Application of Organic Farming Aid (OFA) and Inorganic Fertilizers on the Growth and Yield of Maize and Soil Microbial Properties in the Guinea Savannah Agro-Ecological Zone of Ghana

The aim of the study was to evaluate the effect of different rates of organic farming aid (OFA) and inorganic fertilizer on the productivity of maize, chemical and microbial properties of soil for higher economic value. Field experiments were conducted during the 2020 and 2021 cropping seasons at the research fields of CSIR-Savanna Agricultural Research Institute located at Nyankpala in the Guinea savannah agroecology of Ghana. The study consisted of five treatment combinations: full rate of OFA, full rate of NPK, 1/2 OFA + 1/2 NPK, full OFA + 1/2 NPK and a control (no OFA and no NPK) which were arranged in a randomized complete block design with four replications. Analysis of variance indicated significant (P 0.05) treatment and year interaction effect for all the growth parameters except for plant height, leaf area and leaf area index. Apart from hundred seed weight, treatment and year interaction effect for all the yield and yield components was significant (P 0.05). Application of full rate of NPK (90:60:60) resulted in the highest grain yield of 4960 kg·ha-1, however it was statistically similar to those obtained by the combined application of full rate of OFA (250 ml·ha-1) + 1/2 NPK and 1/2 OFA + 1/2 NPK with grain yield of 4856 kg·ha-1 and 4639 kg·ha-1 respectively. There was also a yield advantage of 197. 5%, 191.3%, 178.3 and 79.1% over the control for full NPK rate, full OFA rate + 1/2 NPK rate, 1/2 OFA rate + 1/2 NPK and full OFA rate respectively. Application of full OFA rate + 1/2 NPK enhanced soil basal respiration (evolved CO2) and mineralizable C, implying that, combination of full OFA rate and NPK fertilizer would be necessary to boost soil microbial activity and soil labile nutrient pool (labile C pool). This suggests that combined use of full OFA rate + 1/2 NPK fertilizer can be a better strategic tool for improving soil quality. The highest benefit cost ratios (BCR) of 2.58 and 3.77 were obtained following the application of full OFA rate + 1/2 NPK and 1/2 OFA rate + 1/2 NPK respectively. Hence, it could be concluded that complementary use of OFA and NPK is more profitable than using single inputs (either OFA or NPK). Thus, in promoting technology packages to farmers, development practitioners must carefully consider the complementary of inputs that are cost-effective but economically rewarding.

Cultivation of Core Competencies of History in Middle Schools:Taking the Lesson of Primitive Farming Life as an Example

The cultivation of history teaching in middle schools involves many aspects and multi-level teaching factors such as classroom teaching objectives,teaching methods and teaching means.Taking the Lesson of Primitive Farming Life in the seventh grade volume 1 of People’s Education Press as an example,this paper discussed the cultivation of core competencies of history in middle schools,to improve the implementation process of history courses and promote the cultivation of students’discipline competencies.

Gender Perspectives of Vulnerability to Climate Change: A Descriptive Evidence from Farming Households at Ikpayongo Community in Gwer Lga, Benue State, Nigeria

Climate change impact and risks on agricultural livelihood affect women and men disproportionately and often to the disadvantage of women and girls. Consequently, this study assessed gender perspectives of vulnerability to climate change of farming households at Ikpayongo community in Gwer local government area, Benue State, Nigeria using descriptive approach. The study identified a total of 120 male-headed and female-headed farming households across four neighbourhoods and administered structured questionnaire on them using simple random sampling method, while data analysis was done using descriptive statistics. The results indicate lower education and income status among female-headed households, though male-headed households have high household size. Both sexes have relatively equal access to land for farming, however men have large farm size compared to women. The major crops cultivated by men were rice and yam, while women cultivated largely groundnut and cassava. Women are more exposed and sensitive to climate-related hazards such as floods and heat stress due to the location of their farms. The result further shows that males possess better adaptive capacity given their higher incomes, social networks and more access to training/capacity building programmes and credit facilities. The study concludes that female-headed farming households are more vulnerable to climate change and variability than male-headed farming households due to higher exposure and a lower adaptive capacity. Programme and policies to improve women access to credit facilities and relevant training to boost their adaptive capacity and build resilience are highly recommended. This would also limit exposure with attendant reduction in vulnerability.

On the Rice Farming in the Shu Area During the Can Cong Period

The Bashu area was one of the most civilized agricultural areas in ancient China.Since the late Eastern Han Dynasty,it has been reputed as the“Land of Abundance”due to its abundant resources.Archaeological data show that the Shu area cultivated millet as early as the prehistoric period.The legend goes that Can Cong was the first ruler of the Shu area during the pre-Qin period,indicating that agricultural production at that time had made great progress compared with the prehistoric period.During this period,the agricultural pattern of the Shu area experienced profound changes,from dryland millet farming originating from the Western Sichuan Plateau to rice farming that is more suitable for Sichuan Basin,especially for the Chengdu Plain,where there are abundant rainfalls and high temperatures.Since then,rice farming has become a long-established farming tradition in the Shu area.The agricultural production tools and grain crop seeds unearthed from the Baodun site,where the archaeological remains of Can Cong Culture were discovered,show the prosperity of early agriculture in the Shu area.During the Baodun Culture period,the accelerated economic and social development in the Shu area promoted complicated and hierarchical changes in the social organization structure of settlements,which gradually evolved into early states.

Can Natural Farming Help to Combat Climate Variability? A Comparison of Natural and Chemical Farming in Andhra Pradesh, India

A study was conducted to compare the potential of natural farming versus conventional chemical farming to withstand adverse climate effects. The study investigated two cyclones, namely cyclone Pethai and cyclone Titli of 2018, which caused significant damage to Andhra Pradesh’s coastal corridor. In addition, the impact of heavy rainfall in 2021 on two different farming systems was studied. The worst-affected Paddy crop regions where these cyclones caused severe damage were surveyed. Multiple linear regression was utilized to investigate predictors including crop damage, wind damage, submergence, and yield loss in these two agricultural systems during these two cyclonic and heavy rainfall events. The study indicated that natural farming practices were more resilient to climate variability than conventional chemical farming techniques. The study showed a statistically significant difference (p < 0.001) between these two farming systems in terms of damage caused due to climate variabilities.

上游风力机偏航对于下游风力机气动特性的影响

针对倾斜尾迹导致下游风力机受到不平衡的气动载荷,疲劳载荷显著增加的问题,文章基于FAST.Farm开源软件,研究了在NREL 5 MW风力机错列布局下,上游风力机偏航对于下游风力机气动特性的影响。研究结果表明:随着上游风力机偏航角度的增加,下游风力机逐渐处于尾流风速亏损的核心区域,其风轮输出功率的减少量显著增大,风轮所承受的推力逐渐降低;相较于上游风力机未偏航的情况,当上游风力机偏航角度为40°时,下游风力机叶根处倾覆力矩的标准差增加了50.5%,波动性显著增大。该研究结果可为整场控制协同优化和偏航入流下的风力机气动特性分析提供参考。

Fenlong Cultivation-the Fourth Set of Farming Methods Invented in China

The basic theory and effect of the new farming method of ＂Fenlong＂ cultivation which has been included in the main extension technology of Ministry of Agriculture of the People＇s Republic of China is fully illustrated for the first time, and it is the fourth set （generation） of farming modes and methods following manpower, animal and mechanical （tractor） farming. It follows the natural law to achieve soil activation, water saving, oxygen increase, warming and desalination through the active use of natural resources like soil, rainfall and solar energy, thereby promoting a new round of natural agricultural production and quality improvement and water con- servation, which has crop yield increase by 10%-30%, quality improvement of 5%, natural precipitation retaining increase by100%. The characteristics and mechanism are the use of spiral drill for one-time completion of the land preparation by drilling vertically to 30-50 cm of soil layer through high speed peeling. After instant high temperature and many fierce impacts, mechanical frictions, it could achieve the multiplication of the number of loose soil, soil physical modification and expansion of the soil nutrients, reservoirs, oxygen, microorganisms （＂Four pools＂）. Fenlong cultivation can give birth to new farming culture and civilization, and it can achieve the physical ＂desalinized＂ transformation and utilization of saline soil. The formation of Fenlong green farming technology system makes it possible to invent the farming tools of ＂serf-propelled Fenlong machinery＂ that has got the patent, and it is the method for farmland （dry land, paddy field） Fenlong cultivation, saline-alkali soil smash-ridging cultivation and for the abundance of grass ecology on degraded grassland. The application of Fenlong ＂4＋1＂ （arable, saline-alkali soil, grasslands, Sponge City＋rivers） green development in China can achieve the ＂double safety＂ of food and living space.

基于遗传Data Farming的公共政策优化仿真模型

为了解决公共政策优化仿真时考察点不全面及耗费时间大的问题,提出了基于遗传Data Farming的公共政策优化仿真模型。所提出的模型中,Data Farming被用于全面地考察输入参数空间中各输入参数水平对应的输出响应,通过把仿真过程的输出过程看作适应度的计算,遗传算法被用于优化仿真过程,提高优化效率。分析了公共政策作用效果的影响因素,并介绍了传统的Data Farming技术,然后从仿真目标、模型框架、算法等三方面介绍了所提出的优化仿真模型。最后进行了实验,证明了所提出模型的有效性。

区域经济发展Data Farming决策支持技术及其应用

为解决现有的决策支持技术不能解决的区域经济历史数据稀少的问题,提出了区域经济发展Data Farming决策支持技术。所提出的技术采用基于智能体仿真的Data Farming技术,对参数空间进行遍历搜索,以利用各个参数值对应的仿真结果来获取大量的数据,使决策者可以有效地识别到系统的最优控制值,并了解在控制值下的系统风险性。最后,以江门市社会消费品零售总额的控制优化为例,说明了该技术的有效性。

Determination of Selected Toxic Elements in Apples from Organic Farming

Due to the elevated ecological awareness nowadays the consumption of products of organic agriculture is increasing. Organic farming means excluding the use of synthetic inputs, such as synthetic fertilizers and pesticides or genetically modified organisms, but there are only a few regulations regarding heavy metal concentrations in soils. Thus a not negligible uptake of metals from the soil where the apple trees are grown may occur. Furthermore inorganic copper compounds being traditional fertilizers for apple trees are not considered as synthetic fertilizers, thus they are still used in organic apple farming for soil or foliar application. Thus also apples produced by organic agriculture may contain toxic elements, such as cadmium, chromium, copper, and lead. The concentrations of these elements were determined in whole apples, as well as in the flesh and peel in order to estimate the possible risk for human health. Prior to analysis using ICP-AES samples underwent a microwave assisted digestion. The LODs obtained are below the recommended maximum levels in vegetables/fruits by WHO. In all samples no Cu, Cr, and Pb could be detected. Only Ca was found in the peel of about a third of samples investigated in concentrations between LOD and LOQ （1-3 μg/g）.

Refining the Factors Affecting N_(2)O Emissions from Upland Soils with and without Nitrogen Fertilizer Application at a Global Scale

Nitrous oxide(N_(2)O)is a long-lived greenhouse gas that mainly originates from agricultural soils.More and more studies have explored the sources,influencing factors and effective mitigation measures of N_(2)O in recent decades.However,the hierarchy of factors influencing N_(2)O emissions from agricultural soils at the global scale remains unclear.In this study,we carry out correlation and structural equation modeling analysis on a global N_(2)O emission dataset to explore the hierarchy of influencing factors affecting N_(2)O emissions from the nitrogen(N)and non-N fertilized upland farming systems,in terms of climatic factors,soil properties,and agricultural practices.Our results show that the average N_(2)O emission intensity in the N fertilized soils(17.83 g N ha^(-1)d^(-1))was significantly greater than that in the non-N fertilized soils(5.34 g N ha^(−1) d^(−1))(p<0.001).Climate factors and agricultural practices are the most important influencing factors on N_(2)O emission in non-N and N fertilized upland soils,respectively.For different climatic zones,without fertilizer,the primary influence factors on soil N_(2)O emissions are soil physical properties in subtropical monsoon zone,whereas climatic factors are key in the temperate zones.With fertilizer,the primary influence factors for subtropical monsoon and temperate continental zones are soil physical properties,while agricultural measures are the main factors in the temperate monsoon zone.Deploying enhanced agricultural practices,such as reduced N fertilizer rate combined with the addition of nitrification and urease inhibitors can potentially mitigate N_(2)O emissions by more than 60%in upland farming systems.

A nonlinear wake model of a wind turbine considering the yaw wake steering

Duo to fluctuations in atmospheric turbulence and yaw control strategies,wind turbines are often in a yaw state.To predict the far wake velocity field of wind turbines quickly and accurately,a wake velocity model was derived based on the method of momentum conservation considering the wake steering of the wind turbine under yaw conditions.To consider the shear effect of the vertical incoming wind direction,a two-dimensional Gaussian distribution function was introduced to model the velocity loss at different axial positions in the far wake region based on the assumption of nonlinear wake expansion.This work also developed a“prediction-correction”method to solve the wake velocity field,and the accuracy of the model results was verified in wake experiments on the Garrad Hassan wind turbine.Moreover,a 33-kW two-blade horizontal axis wind turbine was simulated using this method,and the results were compared with the classical wake model under the same parameters and the computational fluid dynamics(CFD)simulation results.The results show that the nonlinear wake model well reflected the influence of incoming flow shear and yaw wake steering in the wake velocity field.Finally,computation of the wake flow for the Horns Rev offshore wind farm with 80 wind turbines showed an error within 8%compared to the experimental values.The established wake model is less computationally intensive than other methods,has a faster calculation speed,and can be used for engineering calculations of the wake velocity in the far wakefield of wind turbines.