Modern Agricultural Technology Research Articles

Meta-Analysis on Farmers’ Adoption of Agricultural Technologies in East Africa: Evidence from Chinese Agricultural Technology Demonstration Centers

Farmers’ low agricultural productivity in East African countries is attributed to among other factors, the low application of modern agricultural technologies. Using meta-analysis this study intended to examine the determinants of adoption of agricultural technologies in East African countries recipients of Chinese Agricultural Technology Demonstration Centers (ATDCs). A comprehensive review employed to gather 22 studies addressing the determinants of adoption of agricultural technologies such as improved varieties, agricultural mechanization, soil conservation, and animal breeding from Ethiopia, Tanzania, Uganda, and Rwanda. The collected data were analyzed using STATA 17 software. The study used a random-effect model to estimate the determinants of agricultural technologies adoption. The findings demonstrated that access to credit, age, education, farming experience, farmer group membership, household size, and off-farm income have a significant influence on farmers ‘adoption of improved varieties. Age, farm size, and education have a significant influence on the adoption of agricultural mechanization. Soil conservation practices are influenced by age, household size, and sex. Moreover, age, education, extension services, and farming experience have a significant impact on the adoption of animal breeding. It is recommended that East African governments, policymakers, and agricultural practitioners to focus on these common variables when planning for the intervention of new agricultural technologies.

Feasibility Study of Snail Farming in Indonesia

This study evaluates the economic feasibility of snail cultivation in Indonesia by analyzing the impact of market demand, cultivation technology, and environmental conditions. A quantitative approach was employed, surveying 150 respondents using a Likert scale (1-5), with data analyzed via SPSS version 26. The results reveal that market demand is the most significant factor influencing economic feasibility, followed by cultivation technology and environmental conditions. All three variables positively and significantly affect the viability of snail farming. These findings suggest that increasing market demand, adopting modern farming technologies, and maintaining favorable environmental conditions are essential for promoting snail cultivation in Indonesia. This study provides valuable insights for policymakers, investors, and farmers interested in developing snail farming as a sustainable agricultural business.

Assessing the impact of financial resources on Sorghum yield in Al-Qadarif State, Sudan

The sorghum agricultural sector in Al-Qadarif State, Sudan, plays a pivotal role in ensuring regional food security. However, its productivity is hindered by significant constraints. Substantial improvements in sorghum yield are impeded by the intricate complexities that characterize this sector's financial resources, and agricultural practices. This study in Al-Qadarif State, Sudan, explores the relationship between financial resources and sorghum agrarian productivity. Data were collected from 200 sorghum farmers using standardized questionnaires during the 2022 season, and regression analysis was employed to investigate the association between financial factors and sorghum productivity. The findings indicate that financial accessibility considerations significantly influence sorghum productivity. This emphasizes the importance of improved financial resources for farmers to adopt innovative farming technologies and practices, leading to higher sorghum productivity levels. The study recommends the integration of digital financial services and precision agriculture technologies as a creative solution to enhance financial accessibility and sorghum productivity. By leveraging mobile money platforms and digital credit services, farmers can conveniently access financial resources, enabling them to invest in modern agricultural inputs and technologies. Additionally, the adoption of precision agriculture techniques, such as soil moisture sensors, drone-based crop monitoring, and variable rate application of inputs, can optimize resource utilization, increase yield, and reduce production costs. The combination of these innovative approaches has the potential to bridge the financial and knowledge gaps, promoting the widespread adoption of sustainable agricultural practices. This synergistic approach could significantly improve sorghum productivity, enhance farmer livelihoods, and contribute to regional food security.

The Inheritance and Development of Agricultural Culture in the Yellow River Basin: A Case Study of the Hetao Region

The agricultural culture of the Yellow River Basin is an essential component of Chinese civilization. The Hetao region, as a representative area of the upper and middle reaches of the Yellow River, possesses unique agricultural traditions and cultural characteristics. However, influenced by modernization, globalization, and ecological changes, traditional agricultural culture faces challenges in inheritance and development. This paper analyzes the natural environment, historical development, and uniqueness of agricultural culture in the Hetao region, exploring the dilemmas and development paths of agricultural culture in modern society. It suggests that integrating agricultural culture with modern agricultural technology, cultural tourism, education, and digital technologies can effectively promote its inheritance and innovative development, providing practical recommendations for the sustainable development of agricultural culture in the Yellow River Basin.

Research on the Strategies for Integrating Moral Education in the Teaching Practice of Modern Agricultural Technology

With the acceleration of agricultural modernization, the demand for cultivating talent in modern agricultural technology has become increasingly urgent. In this context, moral education, as an essential component of comprehensive talent development, needs to be effectively integrated and implemented during teaching practice. The teaching practice of modern agricultural technology is characterized by strong practicality and skill orientation. The integration of moral education not only helps enhance students' professional qualities and sense of social responsibility but also strengthens their mission to serve the "three rural issues" (agriculture, rural areas, and farmers). This paper discusses the difficulties and current status of moral education integration based on the characteristics of modern agricultural technology teaching practice, proposing strategies such as setting moral education goals based on professional skills, designing modular and scenario-based moral education content, and fostering mentor guidance and internship culture. The research results indicate that the organic combination of moral education and professional education can effectively enhance students' comprehensive qualities and provide important references for the cultivation of agricultural technology talent.

The Role of Agricultural Technology in Attaining Food Security among Small Farmers in Char Area in Mymensingh District

Farmers in the char areas of Bangladesh are frequently affected by food insecurity due to their low engagement in modern agriculture such as less use of modern agricultural technology. This study evaluates the socio-demographic characteristics of the sample farmers to assess their nutritional status and the factors influencing char dwellers' dietary diversity. Survey data were collected from 70 households, and focus group discussions were conducted using a semi-structured questionnaire from Nilokhiya char under the Mymensingh District of Bangladesh. An OLS regression model was used to estimate the influence of socioeconomic characteristics of sample households on the decision on factors influencing dietary diversity. The farming type of the farmers is another concern of this study where results show that 90% of farmers in the char areas rely on rice and vegetable farming, whereas more than 60% of the farmers are also involved in livestock and poultry farming at the same time. The nutritional status of char farmers shows that their diet includes a variety of foods but is deficient insufficient protein and healthy fats, which could have an impact on their overall nutrition. Cereals are a staple in the diet, as indicated by the high consumption rate (97.1%) and the substantial average intake (2.30 kg/day). Every household consumes fruits, though in smaller quantities (0.28 kg/day). Eggs are less frequently consumed (57.1%) despite a higher intake (2.64 kg/day). Dietary diversity has a strong positive correlation with supply (.913) at a 1 % significant level which means that efficient supply chains minimize delays, reduce spoilage, and ensure a continuous flow of food to markets to ensure food security. A positive correlation with total income (.373) leads to a higher total income also supports greater dietary diversity. Credit was significant at a 5% level (.267) indicating that a 1 % increase in credit leads to an increase in dietary diversity by 267%. On the contrary, Experience has a negative relationship with dietary diversity which means that experience does not influence food security. Lack of transport and communication, environmental hazards, and natural disasters are the most significant problems faced by the farmers in the char area.

Progress and Potential Drawbacks of Modern Agricultural Technologies: A Literature Review

The production of agriculture has undergone new modifications as a result of agricultural technologies. These not only boost agricultural output but may also significantly raise the caliber of produced food, cut labor expenses, boost farmers' incomes, and achieve agricultural modernization. The use of precision agriculture (PA) is expanding due to the rapid socioeconomic changes that are occurring in certain developing nations. There are enormous ramifications for urbanization, energy consumption, and economic growth in certain developing nations when fundamental changes occur. The research status and current agricultural technology achievements are carefully summarized in this study. In-depth discussions of thirteen significant agricultural technologies are provided in this article. All significant technologies from developed countries are discussed so that under-developed and lower-developed countries will benefit from this paper. Finally, some fresh concepts for each technology are offered, and potential issues in establishing such sophisticated technologies are identified. The main objective of this review is to increase knowledge of modern agriculture and the development process in the agricultural field.

Development of a hydroponic device using potassium Ion-Selective electrode and neural network technology

The rapid development of modern agricultural biotechnology and information technology has become a key driver of modern agricultural growth. The demand for ion detection is prevalent in all aspects of agriculture. This study details the research on an ion sensor agricultural system using potassium (K) ion-selective electrodes (ISEs). The main emphasis is on the application of artificial neural networks (ANNs) for driving ISE development of accuracy. ISEs based on solid contact with metal oxides, specifically manganese dioxide, are studied. Moreover, the design details of an ion signal acquisition device using the NI-9205 acquisition card and LabVIEW are presented. Finally, based on experimental results of nutrient solution samples, ANNs show better performance than the multiple linear regression method. The mean relative error of K-ISE detection was maintained within 4%. This study thoroughly discusses ISE technology to promote its adoption in agriculture.

Training on the Use of Appropriate Technology to Increase Agricultural Production in Villages in Indonesia

This Community Service activity aims to improve the knowledge and skills of farmers in Indonesia's villages by using appropriate technology through online training. In this series of activities, villages with adequate internet infrastructure and a low rate of technology adoption are identified. The training was conducted online using the Zoom application and attended by farmers from various regions. The results of the pre-test show that the majority of farmers have limited knowledge about agricultural technology. After participating in the training, the final assessment (post-test) showed a significant improvement in farmers' knowledge and skills, with an average increase in knowledge scores of 60% and skills of 55%. High participation and positive feedback from participants indicate the effectiveness of online training as a method to increase farmers' capacity. However, challenges such as limited access to equipment and cost remain obstacles to implementing appropriate technology in the field. In conclusion, online training has improved farmers' knowledge and skills. Still, additional support is needed to ensure the sustainability of the application of technology in the field. These findings make an important contribution to the development of farmer capacity-building programs in Indonesia, especially in the context of the adoption of modern agricultural technology.

Is adoption of modern dairy farming technologies interrelated? A case of smallholder dairy farmers in Meru county, Kenya

Attempts have been made to promote the adoption of modern dairy farming technologies (MDFT). However, the adoption of these technologies largely remains underutilized. This study aimed to analyze the determinants of the adoption of MDFTs in Meru County. Using purposive and proportionate sampling techniques from 355 smallholder dairy farmers in Meru County, Kenya, this study analyzed the factors that facilitate or impede the adoption of MDFTs. We use a Multivariate probit (MVP) to evaluate adoption decisions by dairy farm households facing multiple MDFTs. The results reveal a significant correlation among the eight MDFTs suggesting that modern technologies are interrelated. The MVP model results indicate that household income, education level, number of extension contacts, access to credit, farmer group membership, farming experience and livestock monetary value had positive effect on the adoption of MDFTs. Education level and extension contacts had a positive influence on the adoption of fodder establishment and preservation technologies. Farming experience in dairy farming had a positive effect on the adoption of well-structured and clean sleeping areas, and the growth of Rhodes grass. Household income had a positive effect on the growth of Rhodes grass and feed mixture. This work illustrates a need for a policy implication and insight into a need for the county government and private milk processing companies to increase extension frequency to enhance the adoption of MDFTs. Additionally, there is a need to increase access to affordable credit, this should be considered by the government by establishing strengthening a smallholder low-interest and efficient local credit schemes and institutions.

Penerapan IoT dengan Algoritma Fuzzy dan Mikrokontroler ESP32 dalam Monitoring Penyiraman

Smart farming has become a major focus in the development of modern agricultural technology. In this context, the Internet of Things (IoT) offers innovative solutions to increase productivity and efficiency in crop management. This research introduces an IoT-based plant watering monitoring system that uses a fuzzy algorithm and an ESP32 microcontroller. This system is designed to automatically regulate plant watering based on environmental conditions and plant needs. The ESP32 microcontroller acts as the brain of the system, collecting environmental data such as soil moisture, air temperature, and relative humidity. This data is analyzed using a fuzzy algorithm to determine plant watering needs in real-time. Based on the output of the fuzzy algorithm, the system automatically controls the water pump to water the plants according to the specified needs. The application of fuzzy algorithms allows the system to overcome uncertainty in plant watering decisions, especially in the face of complex variations in environmental conditions. With the adoption of IoT technology, farmers can monitor and control crop watering efficiently through web interfaces or mobile applications, even remotely. This research shows that the integration of IoT with fuzzy algorithms and ESP32 microcontrollers can be an effective solution in managing crop watering, increasing overall agricultural productivity, while reducing water and energy consumption.

Language Barriers, Technology Adoption and Productivity: Evidence from Agriculture in India

Abstract We study the effect of language barriers on the ability of farmers to access information about agricultural technologies in rural areas of India. We use the introduction of government-sponsored call centers (Kisan Call Centers) which offer agricultural advice in the official language of each Indian state. For identification, we compare geographically contiguous areas that sit across state borders, and exploit differences in the language spoken by farmers and call center advisors. We document that language barriers limit the adoption of modern agricultural technologies – such as high-yielding variety seeds – and negatively affect crop yields.

Sustainable practices for cotton production in Bangladesh: economic and environmental perspectives

Cotton is a major cash crop in the agriculture of Bangladesh, primarily fueling its substantial textile industry. Although local production is limited, cotton has the potential to bolster the country’s economic growth by supporting local economies and improving agricultural sustainability. An in-depth sustainability assessment of this integral crop is essential to ensure its long-term economic and environmental viability. This study aims to evaluate the sustainability of cotton production in Bangladesh and suggest strategic enhancements and policy measures to improve its environmental, economic, and social aspects. Data were collected from 60 farmers in two villages of Jashore district using a simple random sampling technique. A combination of descriptive, mathematical and statistical techniques was used to analyze the data. The findings highlighted a profitable benefit–cost ratio of 1.88 for cotton production. Positive impacts on cotton profitability were notably linked to the costs of labor, land preparation, and insecticides and pesticides. Despite this, 60% of farmers faced substantial challenges, including financial barriers, limited access to modern agricultural technologies, and a lack of training in sustainable practices. Economic constraints were a major barrier, although the environmental benefits of sustainable practices were widely acknowledged. To address these issues, the study recommends optimizing inputs like labor, land preparation, and pest management, and advocates for policy actions such as subsidies, tax incentives, and enhanced training programs to support the widespread adoption of sustainable practices across Bangladesh.

The Importance of Input-Output Analysis in Advancing Sustainable Agricultural Development in Hulu Sungai Selatan Regency

This study explores the role of input-output (I-O) tables in promoting sustainable agricultural sector development in Hulu Sungai Selatan Regency, Indonesia. The agricultural sector is a critical component of the local economy, contributing significantly to the Gross Regional Domestic Product (GRDP) and providing employment for the majority of the population. However, the sector faces challenges such as climate change, unsustainable farming practices, and limited access to modern agricultural technologies. By utilizing I-O tables, this research analyzes the interdependencies between the agricultural sector and other economic sectors, identifying opportunities for growth and the potential impact of sustainable practices. The findings reveal that integrating sustainable agricultural practices can enhance productivity, increase farmers' income, and contribute to environmental preservation. Policy recommendations are provided to support the adoption of sustainable methods, including incentives for environmentally friendly practices, education and training for farmers, and the development of supporting infrastructure. The study underscores the importance of data-driven approaches in formulating effective policies that promote both economic growth and sustainability in the agricultural sector.

Community Empowerment through Rang Mudo Farmers Group: Efforts to Improve the Economy in Nagari Paninjauan

The community service program through the Rang Mudo Farmers Group in Nagari Paninjauan aims to improve farmers' economic well-being through community-based empowerment. The method employed is a participatory approach involving the government, private institutions, and the local community in various stages, including needs assessment, training, and program implementation. This service focuses on enhancing farmers' technical capacities, strengthening social networks, and expanding market access. The results indicate that farmers have increased productivity and income through the adoption of modern agricultural technologies, the use of subsidized fertilizers, and marketing collaboration. The program also successfully built solidarity among group members, created new job opportunities, and improved the competitiveness of agricultural products in regional markets. In conclusion, this community service not only boosted farmers' economic well-being but also strengthened social capital that supports the sustainability of farming communities in Nagari Paninjauan.

KELURAHAN PETANI HIJAU MODERN: SMART FARMING MENGGUNAKAN TEKNOLOGI PANEL SURYA UNTUK MEWUJUDKAN KAWASAN PERTANIAN MODERN DI KELURAHAN BAKUNG JAYA

The development of automatic plant watering devices has become a major focus in increasing efficiency and effectiveness in plant cultivation. In this context, automatic plant watering devices that use electrical energy sources from solar panels have shown great potential in saving energy and reducing environmental impacts. This tool is designed to replace manual work in watering plants, both in hydroponic systems and sprinkler systems. In hydroponic systems, automatic plant watering devices use soil moisture sensors to detect soil moisture and send commands to the water pump to water periodically. This allows hydroponic plants to receive nutrients continuously and maintain air humidity with automatic fogging. Meanwhile, in sprinkler systems, automatic plant watering devices use solar panels as a source of electrical energy. These solar panels generate electrical energy that is used to power the water pump and sprinkler, thus watering plants automatically without the need for human intervention. The advantages of using solar panel in automatic plant watering devices include the use of renewable energy, easy maintenance, and no greenhouse gas emissions. However, this tool also has disadvantages, such as dependence on sunlight intensity. Thus, the development of automatic plant watering devices using solar panel can help increase plant productivity, save energy, and reduce environmental impacts. This tool can also be integrated with various types of plant cultivation systems, thus providing many benefits in the development of modern agricultural technology.

Greenhouse farming: Hydroponic vertical farming- Internet of Things (IOT) Technologies: An updated review

This review paper of literature highlights the importance of greenhouse urban farming technology, hydroponics, aeroponics, aquaponics, vertical farming and applications of Internet of Things (IOT) technologies. The greenhouse farming is a well known modern agriculture technology for optimal plant growth. Hydroponics, a soilless cultivation technique using nutrient solutions under controlled conditions, is used for growing vegetables, high-value crops, and flowers. Vertical farming is a popular trend in hydroponics that involves stacking multiple layers of plants in a vertical arrangement. This farming method saves space, reduces water usage, and increases yields per square foot of growing area. In comparison to conventional greenhouse cultivation, hydroponics requires less fertilizer, pesticides, and water due to the precise control over their distribution. The term “Internet of Things (IOT)” is a system of interconnected computing devices, sensors, objects, microcontrollers, and cloud servers that can transmit data across a network and control other devices remotely without human intervention. A better management of nutrient solution in hydroponic systems requires optimum pH, electrical conductivity (EC), or ions concentration. The three main greenhouse farming gases (GHGs) emissions in hydroponics hi-tech urban farming are nitrous oxide, methane and carbon dioxide (CO2). To measure the levels of CO2 in hydroponics, the more intermediate to advanced grower can use a CO2 monitoring and controllers system. Hydroponic vertical farming is in infancy in India. Although hydroponic vertical farming units for production of crops like strawberry, lettuce and other leafy vegetables, foliage and flowers are functioning in major metros of India. However, the organized hydroponic vertical farms for production of food crops are not available in India. Therefore, only a few successful hydroponic vertical farms have been built in India mainly due to the initial high price tag on construction and the cost of maintaining them afterwards. Another disadvantage is carbon footprint of hydroponic vertical farming is very high, and discourages its applications.

Education, Risk-attitude and Agricultural Innovation: Farm Level Investigation in North India

This paper explores the role of farmers’ education in promoting farming innovation, that is, contract farming (CF). Applying the Tobit model on cross-sectional data of 754 wheat growers in Haryana, it has been found that education directly and indirectly (by reducing risk aversion) stimulates the participation intensity of farmers in CF. It directly enhances farmers’ capacity to absorb and comprehend CF complexities and indirectly reduces farmers’ risk-aversion attitude. It fosters a positive attitude and willingness to adopt modern technologies. Hence, both the education and risk-taking attitudes of farmers are found to be significant for CF adoption probability and intensity. Other factors like farm size, non-farm income, asset ownership and access to credit, media and contact with extension services are all positive stimuli of CF participation intensity. The study suggests promoting field school and awareness programmes to help farmers both acquire and disseminate information on modern farm practices and technologies. JEL Codes: C01, I25, Q16

Enhancing food crop classification in agriculture through dipper throat optimization and deep learning with remote sensing

Remote sensing images (RSIs), a keystone of modern agricultural technology, refer to spectral or visual data captured from drones, satellites, or aircraft without direct physical contact with the Earth's surface. These images provide a wide-ranging view of agricultural landscapes, providing valuable insights into land use, crop health, and environmental conditions. Agricultural food crop classification, a vital application within precision agriculture, includes the detection and classification of different crops cultivated in a certain region. Traditionally reliant on manual techniques, the development of technologies, particularly the incorporation of RSIs, has revolutionized this process. Agricultural food crop classification has become more sophisticated and automated by harnessing the wealth of data received from RS, which facilitates precise management and monitoring of crops on a large scale. Deep learning (DL), a branch of artificial intelligence, plays a more effective role in these synergies. The incorporation of DL into the RSI analysis enables high-precision and efficient detection of various crop types, assisting more informed decision-making in agriculture. This study proposes a new Dipper Throat Optimization Algorithm with Deep Learning based Food Crop Classification (DTOADL-FCC) algorithm using Remote Sensing Imaging for Agricultural Resource Management. The DTOADL-FCC method aims to apply DL algorithms for the classification of different crop types. In the DTOADL-FCC method, fully convolutional network (FCN) based segmentation process is performed. Next, the DTOADL-FCC method exploits the SE-ResNet model for learning intrinsic and complex features. The DTOADL-FCC method makes use of DTOA for the hyperparameter tuning process. Lastly, the classification of crop types takes place using the extreme learning machine (ELM) model. The study utilizes mathematical formulations including activation functions, loss functions, fitness calculations, and iterative update processes. A brief set of simulations showcases that the DTOADL-FCC method achieves remarkable performance over other techniques with much improved results.

Living Conditions of the Gond Community in Veerdandi Village of Adilabad District in Telangana

The Gond community, one of India’s most prominent tribal groups, boasts a rich history and cultural heritage that dates back to the 9th century AD. Their vibrant art, traditional practices, and festivals were renowned, and they once ruled several prominent kingdoms in the hill Gondwana region. However, the British colonial period disrupted their traditional rule, leading to the current socioeconomic profile of Veerdandi village in Telangana’s Adilabad district, revealing significant challenges. Predominantly male (80%), with a large segment in the 25-35 age group (36.7%), the village faces problems such as low literacy rates (55%), lack of education and health facilities, and heavy reliance on agriculture and labour. Modern agricultural technology is limited despite infrastructure such as roads and emergency transport. Demographic and socioeconomic conditions highlight significant challenges in health, education, and living standards. 56.7% of households don’t possess sanitation facilities in their houses and 78.3% are suffering from nutritional deficiency. This underscores the urgent need for government schemes to address the multifaceted problems faced by tribal communities in Telangana. The Pearson Chi-Square value is 18.400. The p-value (.000) was statistically significant in the government support schemes and in preventing tribes’ malnutrition, health issues, and poverty in the study.