Modern Agricultural Technology Research Articles

[Effects of Controlled-release Blended Fertilizer on Crop Yield and Greenhouse Gas Emissions in Wheat-maize Rotation System].

The increasing use of nitrogen fertilizers exerts extreme pressure on the environment (e.g., greenhouse gas emissions, GHGs) for winter wheat-summer maize rotation systems in the North China Plain. The application of controlled-release fertilizers is considered as an effective measure to improve crop yield and nitrogen fertilizer utilization efficiency. To explore the impact of one-time fertilization of controlled-release blended fertilizer on crop yield and GHGs of a wheat-maize rotation system, field experiments were carried out in Dezhou Modern Agricultural Science and Technology Park from 2020 to 2022. Five treatments were established for both winter wheat and summer maize, including no nitrogen control (CK), farmers' conventional nitrogen application (FFP), optimized nitrogen application (OPT), CRU1 (the blending ratio of coated urea and traditional urea on winter wheat and summer maize was 5:5 and 3:7, respectively), and CRU2 (the blending ratio of coated urea and traditional urea on winter wheat and summer maize was 7:3 and 5:5, respectively). The differences in yield, nitrogen fertilizer utilization efficiency, fertilization economic benefits, and GHGs among different treatments were compared and analyzed. The results showed that nitrogen application significantly increased the single season and annual crop yields of the wheat-maize rotation system (P < 0.05). Compared with those of FFP, the CRU1 and CRU2 treatments increased the yields of summer maize by 0.4% to 5.6%, winter wheat by -5.4% to 4.1%, and annual yields by -1.1% to 3.9% (P > 0.05). N recovery efficiency (NRE), N agronomic efficiency (NAE), and N partial factor productivity (NPFP) were increased by -8.6%-43.4%, 2.05-6.24 kg·kg-1, and 4.24-10.13 kg·kg-1, respectively. Annual net income increased by 0.2% to 6.3%. Nitrogen application significantly increased the annual emissions of soil N2O and CO2 in the rotation system (P < 0.05) but had no effect on the annual emissions of CH4 (except for in the FFP treatment in the first year). The annual total N2O emissions under the CRU1 and CRU2 treatments were significantly reduced by 23.4% to 30.2% compared to those under the FFP treatment (P < 0.05). Additionally, nitrogen application significantly increased the annual global warming potential (GWP) of the rotation system (P < 0.05), but the intensity of greenhouse gas emissions was reduced due to the increase in crop yields. Compared with that under FFP, the annual GWP under the CRU1 and CRU2 treatments decreased by 9.6% to 11.5% (P < 0.05), and the annual GHGs decreased by 11.2% to 13.8% (P > 0.05). In summary, the one-time application of controlled-release blended fertilizer had a positive role in improving crop yield and economic benefits, reducing nitrogen fertilizer input and labor costs, and GHGs, which is an effective nitrogen fertilizer management measure to promote cleaner production of food crops in the North China Plain.

Smart Cultivation System: Innovation Concept for Designing a Modern and Automatic Shrimp Farming Technology System Powered by Renewable Energy

The research presents a comprehensive exploration of energy calculations and pond design for smart cultivation systems, with a focus on shrimp ponds. Through interviews and analysis, the energy consumption of various components such as lights, waterwheels, and pumps was determined, leading to the calculation of total power consumption and the specification of necessary equipment like inverters, batteries, and solar panels. Furthermore, the study proposes the integration of renewable energy sources, such as solar and wind power, into the pond system, enhancing sustainability and reducing environmental impact. The incorporation of IoT technology facilitates real-time energy monitoring and optimization. Additionally, innovative solutions like water filtration systems and solar-powered automatic feeders are introduced to improve water quality and feeding efficiency, respectively. The application of microcontroller-based solar street lighting enhances energy efficiency and maintenance ease. A SWOT analysis underscores the strengths, weaknesses, opportunities, and threats of the proposed smart cultivation system, emphasizing its potential for energy efficiency, environmental friendliness, and long-term cost savings despite challenges such as weather dependence and technological limitations. Overall, the research underscores the feasibility and benefits of integrating renewable energy and modern technology in shrimp pond management for sustainable and efficient aquaculture practices.

The effects of COVID-19 on agriculture supply chain, food security, and environment: a review.

COVID-19 has a deep impact on the economic, environmental, and social life of the global population. Particularly, it disturbed the entire agriculture supply chain due to a shortage of labor, travel restrictions, and changes in demand during lockdowns. Consequently, the world population faced food insecurity due to a reduction in food production and booming food prices. Low-income households face food security challenges because of limited income generation during the pandemic. Thus, there is a need to understand comprehensive strategies to meet the complex challenges faced by the food industry and marginalized people in developing countries. This research is intended to review the agricultural supply chain, global food security, and environmental dynamics of COVID-19 by exploring the most significant literature in this domain. Due to lockdowns and reduced industrial production, positive environmental effects are achieved through improved air and water quality and reduced noise pollution globally. However, negative environmental effects emerged due to increasing medical waste, packaging waste, and plastic pollution due to disruptions in recycling operations. There is extensive literature on the effects of COVID-19 on the environment and food security. This study is an effort to review the existing literature to understand the net effects of the pandemic on the environment and food security. The literature suggested adopting innovative policies and strategies to protect the global food supply chain and achieve economic recovery with environmental sustainability. For instance, food productivity should be increased by using modern agriculture technologies to ensure food security. The government should provide food to vulnerable populations during the pandemic. Trade restrictions should be removed for food trade to improve international collaboration for food security. On the environmental side, the government should increase recycling plants during the pandemic to control waste and plastic pollution.

A Study on Agricultural Loans offered by NABARD to Farmers

This study delves into the comprehensive landscape of agricultural loans disbursed by the National Bank for Agriculture and Rural Development (NABARD) to farmers in India. The research scrutinizes the varied purposes for which these loans are extended, encompassing crop cultivation, animal husbandry, dairy farming, poultry, fisheries, and agro-processing. Emphasizing the different loan types – short-term, medium-term, and long-term – the investigation explores the interest rates associated with each category and evaluates the role of government subsidies in enhancing affordability. Additionally, the study investigates the credit delivery mechanism facilitated by NABARD through cooperative banks, regional rural banks, and commercial banks, ensuring an inclusive approach to reach farmers across diverse strata. The research underscores the technological impetus provided by NABARD, encouraging farmers to adopt modern agricultural practices and technologies. Special attention is given to risk mitigation measures, including crop insurance, designed to shield farmers from losses arising due to unforeseen circumstances. Keywords: NABARD, Agricultural Loans, Farmer Financing, Credit Delivery, Government Subsidies, Rural Development, Risk Mitigation, Financial Inclusion, Technological Adoption, Indian Agriculture.

Trends in global sugar beet production and sugar consumption levels

Relevance. Sugar beet is one of the raw materials from which granulated sugar is produced, and it, in turn, is one of the indicators by which the food security of any country is assessed. In 2020, European countries produced 47.6% of the total global volume of sugar beet, Asian countries — 18.6%, America — 13.3%, the Russian Federation — 13.7%, African countries — 6.7%. At the same time, the share of sugar beet production in global production increased in Asian countries (from 15.9% in 2010 up to 18.6% in 2020), in the Russian Federation (from 10.1 to 13.7%), in African countries (from 4.6 to 6.7%). A decrease in sugar beet production was noted in European countries — from 55.4% in 2010 to 47.6% in 2020, in American countries — from 14 to 13.3%. In the Russian Federation, sugar production per capita generally meets not only rational consumption standards, but also all criteria for food self-sufficiency. The excess of actual consumption over rational consumption in Russia is 62.5%. The lowest sugar beet production volumes are observed in countries such as Greece, Portugal, North Macedonia, Pakistan, Azerbaijan, Turkmenistan, Kazakhstan, Moldova, Kyrgyzstan, and some others.Results. The results of the study showed that in order to increase the economic indicators of sugar beet production, Russian commodity producers need to implement a policy of intensification of agricultural production along with updating the material and technical base using modern agricultural technologies and the development of their own breeding and genetic centers.

Multipurpose, climate-resilient agroforestry in the Eastern Himalayas

Traditional, small-scale agroforestry systems offer a range of socioecological, sociocultural, and socioeconomic benefits for communities in the Eastern Himalayan region. Successfully managed by Indigenous farmers for generations, these systems involve intricate farming practices that integrate trees, shrubs, crops, and livestock, while avoiding any dependence on modern agricultural technologies like mechanisation or chemical inputs. The Eastern Himalayan region is home to seven agroforestry practices: farm-based, forest-based, large cardamom-based, mandarin-based, crops/mixed trees-based, slash-and-burn based, and tea-garden-based. The output-to-input ratio is highest for tea-based agroforestry and lowest for farm-based agroforestry. Farmers should carefully consider their choice of agroforestry system to suit their circumstances, but each system contributes to livelihood improvement, biodiversity conservation, and ecological sustainability. Several of the systems support high-value cash crops and they all provide a variety of functions and services, including maintaining soil fertility, conserving resources, enhancing productivity, and reducing erosion. They also support a remarkable level of crop diversity and preserve genetic resources, contributing to agrobiodiversity conservation. These traditional agroforestry systems, therefore, offer a sustainable approach to agriculture, balancing short-term food and livelihood needs with long-term environmental conservation. Research is now needed to assess gaps, especially related to multipurpose trees, to ensure the resilience and sustainability of these systems in the face of socioeconomic shifts.

The Application of Wheat Farmers to Modern Agriculture Technology Related to Improve Crop Production in Thi-Qar

The research aim is to determine the level of application farmers of Modern Agricultural Technology have in improving wheat crop production in Thi-Qar Province. A multistage sample probability proportionates of size (PPS) was used to conduct this study. The sample number was (75 farmers from the Qalat Sukkar district, 105 farmers from the AL-Rifai district, 45 farmers from the AL-Shatrah district, and 29 farmers from the AL-Nasr district) (15% of the total number of farmers) it was 254 farmers. Questionnaire techniques and interviews with the farmers were adopted to collect the data (March to May 2019). The study has revealed that the highest percentage (62.6 %) belonged to the medium category in applying modern agricultural technology to improve wheat crop production. The application level of modern agricultural technology was significant and positive at a 1% probability level under six variables. Multiple regression analyses have been studied with ten variables: social class, age, Education, Occupation, Farm power, Size of land holding, Family type, Family size, social participation, and source of information utilized. This research has contributed nine independent variables with significant levels of variation to the extent of the application level of modern agricultural technology in improving wheat crop production (R2= 0.759). The importance of farmers using modern agricultural technology with the parts (Soil preparation, Planting and crop service, harvesting processes and marketing) was high according to (72.12, 70.72, and 68.41) respectively. The data were used for analysis: Frequency, percentage, mean, Standard deviation, and multiple regression analysis. According to the result, farmers' application of modern technology in improving wheat crop production was good. Modern agricultural technology will reduce costs, increase productivity, and save soil quality. The importance of farmers with the parts (Soil preparation, Planting, crop service, harvesting processes, and marketing) was high according to (72.12, 70.72, and 68.41) respectively. Because of this, it is necessary to improve the cultivation of wheat crops to achieve high productivity and reduce the problems that happen during agricultural production. Keywords: Technology, Independent variables, Farmers, Harvesting, Size of land holding

The Application of Wheat Farmers to Modern Agriculture Technology Related to Improve Crop Production in Thi-Qar

The research aim is to determine the level of application farmers of Modern Agricultural Technology have in improving wheat crop production in Thi-Qar Province. A multistage sample probability proportionates of size (P.P.S.) was used to conduct this study. The sample number was (75 farmers from the Qalat Sukkar district, 105 farmers from the AL-Rifai district, 45 farmers from the AL-Shatrah district, and 29 farmers from the ALNasr district) (15% of the total number of farmers) it was 254 farmers. Questionnaire techniques and interviews with the farmers were adopted to collect the data (March to May 2019). The study has revealed that the highest percentage (62.6 %) belonged to the medium category in applying modern agricultural technology to improve wheat crop production. The application level of modern agricultural technology was significant and positive at a 1% probability level under six variables. Multiple regression analyses have been studied with ten variables: social class, age, Education, Occupation, Farm power, Size of land holding, Family type, Family size, social participation, and Source of information utilized. This research has contributed nine independent variables with significant levels of variation to the extent of the application level of modern agricultural technology in improving wheat crop production (R2= 0.759). The importance of farmers using modern agricultural technology with the parts (Soil preparation, Planting and crop service, harvesting processes and marketing) was high according to (72.12, 70.72, and 68.41) respectively. The data were used for analysis: Frequency, percentage, mean, Standard deviation, and multiple regression analysis. According to the result, farmers' application of modern technology in improving wheat crop production was good. Modern agricultural technology will reduce costs, increase productivity, and save soil quality. The importance of farmers with the parts (Soil preparation, planting, crop service, harvesting processes, and marketing) was high according to (72.12, 70.72, and 68.41) respectively. Because of this, it is necessary to improve the cultivation of wheat crops to achieve high productivity and reduce the problems that happen during agricultural production. Keywords: Technology, Independent variables, Farmers, Harvesting, Size of land holding

Relevancy of Modern Agriculture Education on Students’ Farming Practical Skills in Secondary Schools of Kabujogera Town Council, Kitagwenda District

Despite the importance of agriculture education, it has recently been approved that agriculture students still lack practical skills and this could be attributed to poor delivery of methods on modern agriculture education and other numerous challenge like retention rates of students, lack of interest from the learners, lack of practical time/opportunities, limited funding for agriculture practicals, and low passion by agriculture teachers. The study was about the relevancy of modern agriculture education on students’ farming practical skills in secondary schools in Kabujogera Town council, Kitagwenda district. It was guided by three specific objectives which were to; examine different methods of modern agriculture education taught in secondary schools, identify the challenges experienced in modern agriculture education in secondary schools, evaluate the strategies to enhance modern agriculture education in order to improve practical skills among secondary students. The study employed a cross-sectional study design that used both quantitative and qualitative approaches. The study used a sample size of 248. The study used questionnaires and interview guide to collect data. The data collected was analysed using Statistical Package for Social Scientists. The study concluded that modern agricultural education methods had significant relationship with improving students’ farming practical skills. These included; utilization of modern agricultural inputs (<i>x<sup>2</sup></i> = 8.305, p=0.005), Use of improved farm machines (<i>x<sup>2</sup></i> = 6.048, p=0.001), Pre and Post-harvest handling (<i>x<sup>2</sup></i> = 4.985, p= 0.026), and use of modern resistant crop varieties (<i>x<sup>2</sup></i> = 4.120, p=0.004). The study concluded that there were significant challenges experienced in modern agriculture education. These included; limited modern agricultural in puts at [p = 0.001], lack of resources to use [p = 0.005], poor motivation among students and teachers [p = 0.003], limited school farm size [p = 0.001] and poor learning environment [p = 0.004]. The study finally concluded that strategies to enhance modern agriculture education had significant association with improving student’s farming practical skills. Such as; agriculture tours and field trips (p=.027), class discussion student involvement (p=.029), use of practical demonstration method (p=.004) and recruitment of experienced agriculture teachers (p=.028). The study recommended that; there should be training and re-training among teachers and students of agricultural science on use of modern agricultural education technology. Secondary schools should ensure establishment of enough demonstration farms that students would constantly visit in order to copy much on how to do agriculture practical work to improve their skills and experience.

Smart agriculture for urban regions: Digital transformation strategies in the agro-industrial sector for enhanced compliance and economic growth

Research on this topic is becoming relevant due to the growing pressure on agriculture in urbanized regions due to population growth, climate change and the need for sustainable production, which requires the introduction of smart technologies to increase productivity and sustainability. The purpose of this paper is to investigate the impact of growing pressures on agriculture in urbanized regions due to population growth, climate change and sustainable production needs. The methods used include the analytical method, classification method, functional method, statistical method, synthesis method, and others. The study found that modern digital transformation technologies have great potential to improve agricultural productivity and sustainability in urbanized regions, particularly in Latvia and the European Union. The use of data analytics allowed identifying key trends and patterns, which contributed to informed decision-making in the agricultural sector. The study results confirmed the need to implement comprehensive strategies to achieve compliance with sustainable development standards and ensure economic growth. The introduction of modern agricultural technologies, such as aeroponics and hydroponics, has focused on innovative methods to increase productivity and ensure sustainability. The use of the Internet of Things (IoT), data analytics, and modern agricultural technologies has led to an increase in the efficiency of urbanized agriculture. The practical significance of the work lies in the development of specific recommendations aimed at optimizing the functioning of agriculture, which will increase the efficiency of resource use and ensure sustainable economic growth in urbanized regions

EXAMINING THE IMPACT OF FINANCIAL CAPITAL ACCESS ON TECHNICAL EFFICIENCY: EMPIRICAL INSIGHTS FROM CARROT FARMERS IN INDONESIA

Objective: This study investigates the interplay between financial capital access and technical efficiency in small-scale carrot farming in Indonesia, focusing on the regions of Malang and Probolinggo in East Java.   Methods: Employing a multistage random sampling method, data was collected from 100 farmers, and stochastic frontier analysis (SFA) was employed to measure technical efficiency.   Results: The results highlight the positive and significant impact of financial capital access on farmers' technical efficiency. Farmers with enhanced access to financial resources, including credit and loans, demonstrated higher levels of technical efficiency. Additionally, the study identifies the positive influence of larger cultivated land on technical efficiency, allowing farmers greater flexibility and opportunities for adopting modern agricultural technologies. Conversely, greater distances to cultivation lands were found to negatively impact technical efficiency due to increased transaction costs and difficulties in accessing information and markets.   Implication: These findings underscore the critical role of financial capital in shaping the success of small-scale carrot farming, emphasizing its implications for sustainable agricultural practices. The study's insights contribute to the formulation of targeted policies and interventions aimed at improving financial inclusion and reducing geographical barriers to enhance overall agricultural productivity and sustainability in small-scale farming communities.

The potential and prospects for the implementation of precision farming for soybean production in Indonesia

Precision farming is a modern agricultural technology using various ITs. This technology is considered very potential to be applied for developing soybean production in Indonesia. This is because with the use of conventional technology it is difficult to achieve maximal productivity as expected, especially with the limited facilities and infrastructure. Based on research results, precision farming is able to increase productivity and farming efficiency, reduce negative impacts on the environment and increase farmer’s income so that it can support sustainable farming management. Precision farming is very prospective to be developed in Indonesia to increase soybean productivity and production to support the achievement of soybean self-sufficiency. Support for the implementation of precision farming has been provided by the government, the private sector, and also farmers. The success of implementation of precision farming is greatly influenced by the development of IT technology, especially those related to various aspects of soybean cultivation.

The Impact of Cooperative membership on Adoption of Modern Technology by Bee farmers in Kenya.

The main aim of this research is to examine the impact of cooperative membership on adoption of modern technology by bee farmers in Kenya. This study’s data comes from a bee farmers survey in Baringo County, Kenya using a sampling size of 201 households. Probit, logit and Instrumental variable models were incorporated to test for the estimation of relationships and the information generated imported into the SPSS computer application (SPSS 2015) and STATA MP 17 for statistical analysis. The results show that education has a negative significant predictor of cooperative membership at a 5% significance level. Attaining secondary levels did not contribute to farmers’ decision to join cooperative membership. Older farmers were more likely to join cooperatives, unlike the young farmers. Using neighbors in cooperatives as an instrumental variable, the findings indicate that farmers with neighbors who were already in cooperative membership were more likely to join cooperatives. In addition, the majority of adopters of modern bee farming technologies had access to both credit and markets and reported to have experienced an increase in income from bee farming. The adoption of modern beekeeping technologies, such as protective gears, and honey extractors, enabled the farmers to produce more and better-quality honey, which fetched higher prices in the market. Cooperative membership increased the probability of adopting modern beekeeping technology. As such, the study recommends that cooperatives should provide more incentives and support to their members, such as training, subsidies, quality assurance, and market linkages to promote the adoption of modern bee farming technologies.

Dismantling Reductionism in the Green Revolution Project with Vandana Shiva’s Approach

<p>This research is philosophical research on actual problems. This study tries to present Vandana Shiva’s critique of the Green Revolution project. This research uses the philosophical hermeneutic method with methodological elements consisting of description, historical continuity, and critical reflection. After the Second World War ended, one of the major impacts experienced by various countries was the destruction of the agricultural industry and an increasing food crisis around the globe. The newly independent Indonesia also experienced the impact of the war on national agriculture. This condition triggers a new demand for modern agricultural technology to achieve maximum yields. The Green Revolution project promises to meet this new demand, this project brings modern agricultural technology with superior seeds and mass production systems. In reality, the Green Revolution project reduces local knowledge about sustainable food production and replaces it with mass production of food. The diversity of local people’s food is seen as unfavourable in the Green Revolution era. Vandana Shiva criticizes the impact of the Green Revolution project on life. Shiva explained the Green Revolution had the following impacts: creating a food monoculture, destroying the environment, promoting the capitalization of the agricultural industry, and displacing local knowledge. Therefore, local people are powerless as a result of reductionism in the Green Revolution project. Local knowledge is considered inferior compared to Western knowledge presented in the Green Revolution project.<br></p>

A deep learning-based algorithm for crop Disease identification positioning using computer vision

Food security is fundamental to a country. As the main risk factors, pests and diseases seriously restrict the normal growth of crops and the quality and safety of agricultural products. With the intensification of climate change and the continuous adjustment of farming methods, crop diseases and pests have become more frequent in recent years. Therefore, the agricultural production mode has gradually moved from family production to large-scale agricultural planting, and the production equipment has become more automated and intelligent. Agricultural intelligent robots can reduce labor costs in the process of agricultural production and improve the standardization of agricultural production. The application of computer vision in agriculture is rapidly becoming an important aspect of modern agricultural technology, especially in crop positioning and management. Through the use of advanced image processing algorithms and pattern recognition technology, computer vision systems are able to accurately identify and locate various crops in the field, enabling automated and precise management. This technology shows great potential for crop health monitoring, pest identification, and maturity assessment. For example, by analyzing images of plants, computer vision systems can spot signs of lesions or nutrient deficiencies in time and guide farmers to treat them accordingly. In addition, this technology can also be used to guide automated agricultural machinery, such as driverless tractors and harvesters, to improve the efficiency of crop harvesting and reduce labor costs. In general, the combination of computer vision and crops provides new technical means for the development of modern precision agriculture, which helps to improve the efficiency and sustainability of agricultural production.

AGRARIAN DISTRESS: A CASE STUDY OF INDEBTEDNESS AMONGST FARMERS IN HARYANA STATE

This study addresses the critical issue of farmer indebtedness as the primary cause of agrarian distress in Haryana, India. The pervasive challenge of debt negatively impacts farmers’ livelihoods and agricultural sustainability, creating a cycle that hampers investment in modern farming technologies and sustainable practices. The study highlights the disproportionate access to credit, with institutional lenders favoring semi-medium, medium, and larger farmers, while small and marginalized farmers resort to non-institutional sources with higher interest rates. This unequal access perpetuates financial strain on the latter group. The findings emphasize the urgent need for government intervention and institutional support to assist marginalized and small farmers. The study advocates for comprehensive measures, including risk mitigation strategies, enhanced credit access, minimum support prices, and sustainable agricultural policies, to break the cycle of farmer debt and ensure the well-being of those crucial to our food systems.

Smart Farming (Ai-Generated) as an Approach to Better Control Pest and Disease Detection in Agriculture: POV Agricultural Institutions

Purpose – The purpose of current study was to examine the role of smart farming through artificial intelligence (AI) (Data Integration; Machine Learning; Sensor Technologies; Image Processing and Computer Vision; Decision Support Systems and Scalability and Adaptability) in controlling pest and disease detection in agriculture.
 Methodology/ Design / Approach – Quantitative methodology was adopted and a questionnaire was self-administered online by (328) agricultural engineers working in private agricultural institutions in Jordan that are subject to the laws of the Jordanian Ministry of Agriculture. SPSS was employed in order to screen and analyze primary data.
 Findings – Study results indicated that acceptance of the main hypothesis that argued, “Smart Farming Agriculture has an effect on Control Pest and Disease Detection”. Results indicated an R-value (0.963) and an overall variance of 92.7%. In addition to that, among the chosen sub-variables of study, results revealed that scalability and adaptability scored that highest influence on disease detection and control with (r = 0.961) and an overall variance of 92.4%. Study recommended the necessity of training and qualifying agricultural staff to use modern agricultural technology and artificial intelligence.
 Originality –  The originality of the current study lies in its application within the Jordanian environment. In addition, there weren’t direct studies that took into perspective the idea of smart farming through AI and its uses in pests and disease detection and control in crops. 
 Implications – The implications of current study stems from its ability to present the AI potentials to enhance food production, increase the efficiency of agricultural materials that would be a source in guaranteeing food security, and create job opportunities for individuals in this sector. 

Factors Influencing Small-Holder Food Crops Farmers’ Adoption Intention Behaviour on Modern Agricultural Technology among the Non-Adopter in Sarawak’s Rural Areas

Factors Influencing Small-Holder Food Crops Farmers’ Adoption Intention Behaviour on Modern Agricultural Technology among the Non-Adopter in Sarawak’s Rural Areas

Application of Robotics, Artificial Intelligence and Deep Learning in Modern Agriculture Technology: A Review

In order to determine their potential impact in the field of agriculture, the proposed work aims to review the various artificial intelligence (AI) techniques, with a focus on expert systems, robots designed specifically for agriculture, and sensors technology for data collection and transmission. These techniques include fuzzy logic (FL), artificial neural network (ANN), genetic algorithm (GA), particle swarm optimisation (PSO), artificial potential field (APF), simulated annealing (SA), deep learning. The application of AI techniques and robots in cultivation, monitoring, and harvesting is not highlighted in any literature, making it difficult to compare each one simultaneously based on popularity and usefulness while also understanding how each contributes to the agricultural industry. With knowledge of the extent of AI engaged and the robots used, this paper compares three crucial agricultural phases: cultivation, monitoring, and harvesting. The current study offers a comprehensive analysis of over 200 publications that cover the use of automation in agriculture as of 1960 and 2021. It draws attention to the unmet research needs for developing intelligent, self-governing agricultural systems. The frequency of various AI, robotics and deep learning techniques for particular applications in the agriculture industry round out the article.

[Effect of single basal application of controlled-release blended fertilizer on reactive nitrogen loss, carbon and nitrogen footprint during summer maize growth period].

To elucidate the agronomic and environmental effects of single basal application of controlled-release blended fertilizer in summer maize, and optimize management measures of nitrogen fertilizer for grain production in North China Plain, we conducted a field experiment in Dezhou Modern Agricultural Science and Technology Park in Shandong Province. There were four treatments: CK (no N fertilizer), FFP (farmer's fertilizing practice, 240 kg N·hm-2), OPT (optimized nitrogen application, 210 kg N·hm-2), and CRBF (controlled-release blended fertilizer with single basal application, 210 kg N·hm-2). We compared maize yield and reactive nitrogen loss, and quantitatively evaluated the carbon and nitrogen footprints by using life cycle assessment method. The results showed that nitrogen application significantly increased summer maize yield. Compared with FFP, OPT and CRBF increased summer corn yield by 0.7% and 2.9%, respectively, decreased the total amount of ammonia volatilization, N2O emission, and nitrate leaching by 13.0% and 72.7%, 13.3% and 37.5%, 20.5% and 23.5% respectively. Compared with CK, nitrogen application significantly increased the global warming potential (GWP) of summer maize production. Compared with FFP, GWP and greenhouse gas emission intensity of OPT decreased by 3.8% and 4.2%, while the reduction of CRBF were 8.7% and 12.0%, respectively. Compared with CK, nitrogen application significantly increased the carbon and nitrogen footprint of summer maize production. The production and transportation of nitrogen fertilizer and soil greenhouse gas emission were the main contributing factors of the carbon footprint, with contribution rates of 54%-60% and 24%-31%, respectively. Nitrate leaching was the main contributing factor of nitrogen footprint, with contribution rate of 57%-94%. Compared with FFP, the carbon and nitrogen footprints of OPT and CRBF were reduced by 11.0% and 16.5%, 19.6% and 28.4%, respectively. Considering the yield, reactive nitrogen loss and carbon and nitrogen footprint, we recommended the single basal application of controlled-release blended fertilizer as an effective nitrogen fertilizer management measure to promote grain clean production in the North China Plain.