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.

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.

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.

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.

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%.

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.

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.

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.

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.

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.

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.

Mobile genetic elements facilitate the transmission of antibiotic resistance genes in multidrug-resistant Enterobacteriaceae from duck farms

Multidrug-resistant(MDR)Enterobacteriaceae critically threaten duck farming and public health.The phenotypes,genotypes,and associated mobile genetic elements(MGEs)of MDR Enterobacteriaceae isolated from 6 duck farms in Zhejiang Province,China,were investigated.A total of 215 isolates were identified as Escherichia coli(64.65%),Klebsiella pneumoniae(12.09%),Proteus mirabilis(10.23%),Salmonella(8.84%),and Enterobacter cloacae(4.19%).Meanwhile,all isolates were resistant to at least two antibiotics.Most isolates carried tet(A)(85.12%),blaTEM(78.60%)and sul1(67.44%)resistance genes.Gene co-occurrence analysis showed that the resistance genes were associated with IS26 and integrons.A conjugative IncFII plasmid pSDM004 containing all the above MGEs was detected in Proteus mirabilis isolate SDM004.This isolate was resistant to 18 antibiotics and carried the blaNDM-5 gene.MGEs,especially plasmids,are the primary antibiotic resistance gene transmission route in duck farms.These findings provide a theoretical basis for the rational use of antibiotics in farms which are substantial for evaluating public health and food safety.

GNN Representation Learning and Multi-Objective Variable Neighborhood Search Algorithm for Wind Farm Layout Optimization

With the increasing demand for electrical services,wind farm layout optimization has been one of the biggest challenges that we have to deal with.Despite the promising performance of the heuristic algorithm on the route network design problem,the expressive capability and search performance of the algorithm on multi-objective problems remain unexplored.In this paper,the wind farm layout optimization problem is defined.Then,a multi-objective algorithm based on Graph Neural Network(GNN)and Variable Neighborhood Search(VNS)algorithm is proposed.GNN provides the basis representations for the following search algorithm so that the expressiveness and search accuracy of the algorithm can be improved.The multi-objective VNS algorithm is put forward by combining it with the multi-objective optimization algorithm to solve the problem with multiple objectives.The proposed algorithm is applied to the 18-node simulation example to evaluate the feasibility and practicality of the developed optimization strategy.The experiment on the simulation example shows that the proposed algorithm yields a reduction of 6.1% in Point of Common Coupling(PCC)over the current state-of-the-art algorithm,which means that the proposed algorithm designs a layout that improves the quality of the power supply by 6.1%at the same cost.The ablation experiments show that the proposed algorithm improves the power quality by more than 8.6% and 7.8% compared to both the original VNS algorithm and the multi-objective VNS algorithm.

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。

荷兰的有机农业（Organicfarming）

本文简要介绍了荷兰的有机农业状况。同时，介绍了荷兰的有机农业、有机农业农场及有机农产品等概念，并展望了有机农业在荷兰的发展前景。

韩国贝类养殖(Shellfish Farming)现状及展望

韩国是水产养殖业的主要国家之一。本文作者概述了韩国贝类养殖现状,并展望韩国贝类养殖发展前景。

Modeling the relationship of land use change and some geophysical indicators for the interlock area of farming and pasturing in China

This paper discusses land-use changes in the interlock area of farming and pasturing (IAFP)in northern China. It presents detailed analyses of land-use features in the IAFP, which are controlled by the macro geomorphic units and geophysical conditions-constraints or advantages. Additionally, it selects some indicators, according to the availability in acquiring and processing their quantitative data, to analyze the canonical correlations between the typical conversion of grassland and geophysical conditions. The preliminary study indicates that the physical conditions are of great advantages to the development of grassland. There exists significant correlation between land use change and some geophysical conditions.

Developmental Tendency of Dry Land Farming Technologies

The developmental tendency of dry land farming technologies in the semiarid area of China were reviewed based on the overview of recent progress in dry land farming researches from China and oversea. It was emphasized that conservation tillage, limited irrigation, genetic modification and chemical control are the important aspects for the dry land farming research and development of the future. In addition, some considerations and suggestions on above-mentioned aspects were proposed in this paper.