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.

Analysis and Innovative Strategies of Tax Preferential Policies to Promote the Sustainable Development of Small-Scale Individual Businesses

This study conducted an in-depth analysis of the current tax preferential policies for small-scale individual businesses and compared them with similar policies both domestically and internationally,aiming to reveal the advantages and disadvantages of the current system.After examining the impact of these tax preferential policies on the economic status of individual business owners and the broader social economy,this article proposes a set of innovative tax preferential strategies based on theoretical foundations.By developing these innovative strategies and clarifying their implementation paths,the aim is to promote the sustainable and healthy development of small-scale individual businesses,thereby fostering comprehensive socio-economic progress.The conclusion of this study not only summarizes policy recommendations with practical significance but also provides theoretical support for the optimization and innovation of future related systems.

Development of an Integrated Tool for Small-Scale Maize Farming in Uganda

About 62% of the maize produced in developing countries is cultivated manually owing to limited access to appropriate technology. Available technologies perform a single operation, necessitating farmers to buy multiple implements, which is expensive. In this study, an ox-drawn tool integrating a plough, planter and cultivator for small-scale maize farming was developed and its performance evaluated. Planting and cultivating units were designed and fabricated for assembly onto an existing standard ox-plough beam. The integrated tool was tested in the field to assess the effectiveness and efficiency of cultivation and planting of maize. Results showed that the planting unit had an average seed rate of 35.4 kg/ha with a seed damage of 4% and an effective field capacity of 0.15 ha/h at a field efficiency of 87.3%. The cultivating unit had an effective field capacity of 0.1 ha/h and a weeding efficiency of 86%. The efficiency, effectiveness and reliability for field operations are superior to manual operations currently used by farmers and are comparable to single-unit prototypes developed in other countries. This demonstrates the technical feasibility of integrating planting and cultivation units onto an existing mould board plough instead of buying multiple tools.

Case Study:Productive Performance and Prediction of Operating Income of Small-Scale Contract Farming of Swine in Lampang,Thailand

The objective of this study was to examine productive performance and predict factors affecting operating income of small-scale contract farming of swine(SCFS)in Lampang,Thailand.Ten SCFSs were selected by purposive sampling as primary data sources for two consecutive fattening cycles during the year 2015-2017.Data indicated that the SCFS was feeder pig finishing system which herd size(HS)averaged 502 head/farm.The animals consumed approximate 1.59 kg of feed/head/d.The average daily gain(ADG)was 675.22 g/d and feed conversion ratio(FCR)was 2.42.The mean of fattening time(FT)averaged 158 d/cycle.The culling rate(CR)and mortality rate(MR)were 0.17%and 2.50%,respectively.The predicted operating income(POI)was estimated by multiple linear regressions.The equation was:POI=2,700.912+0.027HS–7.119CR–18.225MR+16.885ABW+806.466FI–4.142ADG–420.281FCR–9.719FT(ABW=average body weight;FI=feed intake)with r=0.899,r2=0.808,p-value=0.009.According to stepwise procedure,the potential equation was:POI=323.664FI–9.769MR–22.635 with r=0.837,r2=0.701,p-value=0.000.This predicted equation would benefit as a monitoring index for SCFS to manage their expected operating income and proper farm management to be further profitable and sustainable.

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.

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.

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%.

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.

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.

Factors affecting technical efficiency of small-scale apple farms in Balochistan Plateau, Pakistan

In Balochistan, Agriculture is dominated by small-scale farmers and the apple production sector is confronted with the chronic constraint of low output per unit of input. Although some agricultural policies have been implemented in this province, studies on effectiveness and impacts of such policies over apple production and farmers' performance are still limited. This study is an effort to bridge the research gap on this potential crop in the plateau by investigating technical and scale efficiency of 181 officially designated small-scale apple farmers in mountainous district Mastung in Balochistan; then explored factors that underlie differences in production inefficiency. A two-stage input-oriented Data Envelopment Analysis(DEA) methodology was employed to evaluate technical and scale efficiency followed by truncated bootstrapped regression framework to analyze the correlative determinants to efficiency. Average technical and scale efficiencies of larger landholders were higher than medium and small landholders. Analysis indicated that there is still ample scope for inefficient sample farmers to reduce the input use by 33% without compromising the given yield level. Maximum contributions to the total input savings were from the use of urea, farm yard manure(FYM) and labor-use. Farmer's experience, farm ownership, irrigation constraints, and farmer's access to trainings, credit and extension services significantly affected apple farmers' technical efficiency. Based on the findings of this study, strategies are suggested to enhancing efficiencies by farmers' capacity development through effective extension services and trainings and provision of adequate credit.

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.

Enhancing Access to Bank Credit for Small-Scale Farmers in Kisumu and Kiambu Districts, Kenya Through Public-Private Partnership Initiative

In Kenya, small-scale fanning has immense potential in poverty reduction. The growth of farming activities requires sustainable access to affordable credit to boost and sustain production. This study is initiated to investigate factors influencing access to bank credit by small-scale farmers in Kisumu and Kiambu Districts, Kenya. It is necessitated by lack of a comprehensive study documenting the effectiveness of the partnership initiative in improving access to credit for small-scale farmers. The study seeks to address the following concerns： what factors influence access to bank credit by small-scale farmers under the initiative？ Are small-scale farmers in various parts of the country accessing bank credit equally？ Through which sources do farmers get to know about credit products provided through the initiative？ Primary data was collected from 144 farmers in Kiambu and 127 farmers in Kisumu, sampled using systematic random procedure. The cross-sectional survey design was applied to guide the research process. Quantitative analysis generated cross-tabulations with chi-square and binary logistic regression. The study found that out of 144 credit applicants in Kiambu about 56.3% were successful, while in Kisumu only 37.8% were successful. Access to bank credit was significantly associated with farmers＇ gender, education level, income level, farm size, and farming experience. Besides, women were 1.3 times less likely to access bank credit than men. In terms of regional variation, a Kiambu farmer was 2.7 times more likely to obtain bank credit than a Kisumu farmer. The initiative is an innovative approach for enhancing access to bank credit; however, its potential has not been fully exploited. The study recommends the need： to inform farmers about credit products to clear misconceptions and myths associated with bank credit; develop innovative financing packages for small-scale farmers that are also gender-sensitive; and to initiate a training program targeting farmers with appropriate information.

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.

Mechanized cover crop farming:Modern methods,equipment and technologies

Cover crops are important for covering the soil and fixing nutrients in order to manage soil erosion and improve soil quality.This paper discusses some of the modern methods,equipment and technologies used in carrying out cover crop farming.This is important because modern agricultural and farming operations work a lot differently from those of the past as a result of the improvements in technological advancements over the past decades.The paper explains the usefulness of the various classes of cover crops known as grasses,legumes,brassicas and non-legume broadleaves.It also explains the role of smart farming technologies such as artificial intelligence and big data,satellites,drones and robotic systems as well as Internet of Things(IoT).Some of the benefits of these advanced technologies are high crop productivity,efficient use of water,fertilizer and pesticides,and improvement in farmer safety and growing conditions,as well as reduced impact on the natural environment and ecosystem.Mechanized cover crop farming equipment are also discussed,and grouped into preparation,planting,termination and incorporation equipment,based on the stage they are used during the cover crop farming process.Clearly,these advanced equipment and technologies are aiding the cover crop farming process by making it safer and environmentally friendly while helping farmers to be more efficient.

The Impacts and Causes of Land Fragmentation on Farm Productivity: Case Review of East African Countries

This report provides an overall assessment of land fragmentation problems in East Africa. Many parts of East Africa have become highly fragmented, putting development systems and activities in these areas at risk of complete collapse. Land fragmentation occurs when land gets converted for agriculture, industrialization, or urbanization, invaded by non-local plants, or enclosed for individual use and by subdividing farmlands into subsequent smaller units called parcels with varying average farm sizes. Fragmentation results from inappropriate agricultural development processes and ineffective land use planning that fails to recognize how farmland is used, and the importance of its interconnected areas. Insecurity of tenure and resource rights are key factors in making this possible. Land fragmentation is one of the key reasons why the ability of most resources in East Africa becomes scarcer, and those remaining become “privatized” by more powerful community members—keen to maintain their access to them. Such individualistic attitudes are new and disadvantage the poorest even further by affecting the traditional customary safety nets and agricultural outputs. Neither the government nor customary governance systems effectively protect resource access for the poorest. This review summary report identifies the key causes, measures, and implications, government interventions, and the common remedies to land fragmentation problems in the East African Countries of Kenya, Uganda, Rwanda, and Tanzania including neighboring Ethiopia, and the Sudan. The findings indicated from 2005 to 2015, the population kept increasing for all the named countries in East Africa with Rwanda and Uganda having a substantial increase in population density. The study review further explores the trend in the performance of agriculture by average farm sizes within the intervals of five years by highlighting their strong linkages and found that the average farm size has declined drastically, especially for Kenya. This can only mean that small farms kept becoming smaller and smaller and that there were more small-scale farmers. The results further depicted that the major and commonly cultivated food crops among the East African countries include maize, sorghum, rice, cassava, sweet potatoes, bananas, Irish potatoes, beans, peas, etc., with maize yields (Mt/ha) in 2003 for Uganda being the highest (1.79 Mt/ha) and the lowest in Rwanda (0.77 Mt/ha) respectively. Therefore, from the review results, recommendations are being made as to how the negative impacts of land fragmentation on agricultural productivity can be reduced or mitigated. One way is by community sensitization and awareness about the importance of land consolidation and its proposition on farm productivity.

Wind farms increase land surface temperature and reduce vegetation productivity in the Inner Mongolia

Wind power has been developing rapidly as a key measure to mitigate human-driven global warming.The under-standing of the development and impacts of wind farms on local climate and vegetation is of great importance for their rational use but is still limited.In this study,we combined remote sensing and on-site investigations to identify wind farm locations in Inner Mongolia and performed landscape pattern analyses using Fragstats.We explored the impacts of wind farms on land surface temperature(LST)and vegetation net primary productivity(NPP)between 1990 and 2020 by contrasting these metrics in wind farms with those in non-wind farm areas.The results showed that the area of wind farms increased rapidly from 1.2 km2 in 1990 to 10,755 km2 in 2020.Spatially,wind farms are mainly clustered in three aggregation areas in the center.Further,wind farms increased nighttime LST,with a mean value of 0.23℃,but had minor impacts on the daytime LST.Moreover,wind farms caused a decline in NPP,especially over forest areas,with an average reduction of 12.37 GC/m^(2).Given the impact of wind farms on LST and NPP,we suggest that the development of wind farms should fully consider their direct and potential impacts.This study provides scientific guidance on the spatial pattern of future wind farms.