Growth Of Agricultural Sector Research Articles

The relationship between CO2 emissions and macroeconomics indicators in low and high-income countries: using artificial intelligence

AbstractThis paper aims to unravel the driving forces behind carbon dioxide emissions in low- and high-income countries by applying gradient boosting and random forest algorithms. The study reveals that gradient boosting demonstrates superior accuracy over random forests in low-income countries, whereas the opposite pattern is observed in high-income countries. Additionally, the study demonstrates that, according to the gradient boosting algorithm-based feature selection, the major influencers of carbon dioxide emissions in low-income countries are the agriculture sector (49.9%), the industry sector (17%), the services sector (10.4%), population size (9.8%), gross domestic product growth (7%), and foreign direct investment inflow (5.3%). Furthermore, random forest algorithm-based feature selection reveals that, in high-income countries, the key drivers of carbon dioxide emissions are the services sector (30.8%), the agriculture sector (27.1%), the industry sector (21.5%), population size (19%), foreign direct investment inflow (1.2% - A different working methodology than low-income countries), and gross domestic product growth (0.4%). Moreover, the study corroborates that low carbon dioxide emissions in low-income countries correlate positively with industrial sector growth, foreign direct investment inflow, gross domestic product, and population size but negatively correlate with the agricultural and service sectors. In the case of high-income countries, carbon dioxide emissions positively correlate with foreign direct investment inflow, industrial and agricultural sector growth, and gross domestic product while exhibiting a negative correlation with population size and service sector growth.

VEGSHELL

The Agricultural sector provides employment to over two third of the population of our country. This project aims at building a community for the farmers, educating them about high margin crops, practices to follow increase their profitability. Every now and then we hearing about the pathetic condition about our farmers. And despite employing more than 50% of the workforce the condition of the Indian agricultural section has been very bad. Every time we listen to this, we curse the government and we just move on until another news comes in. And because of this shallow activity we never understand the problem of our farmers at the ground level. The consistent high growth of agriculture sector is a prerequisite for India to become a globally economic superpower. Our application has been designed in such a way that farmers with no much education could easily adapt to our application. During the time of green revolution to make India ‘food self-sufficient’ we started farming major crops like wheat, rice etc. Even today we continue the same. It requires a change; it is also needed to concentrate equally on crops with higher margin.

The impacts of widespread agricultural interventions on yields and food security in Ethiopia☆

In the past decades, the Government of Ethiopia implemented widespread interventions with the objective of modernizing the agricultural sector and stimulating transformative growth. This paper assesses the agricultural yields and food security impacts of those interventions. Combining project and remote-sensing data with a nationally representative household panel survey, we identify impacts by exploiting the temporal and geographic variation in the roll-out of the interventions implemented by the Ethiopian Agricultural Transformation Agency from 2011 to 2016. Results show that large-scale agricultural interventions are associated with higher agricultural yields and better food security outcomes. These outcomes underscore the linkages that persist between agricultural development and food security for rural households living in mostly agrarian economies and the potential for systems-wide interventions to catalyze agricultural transformation.

Regional Disparity in the Growth Performance of the Agricultural Sector: Evidence from Indian States

This research study investigated regional disparity in agricultural sector growth performance in 15 states from 1991 to 2020. The study confirmed the existence of ? and ? convergence using the convergence hypothesis and suggested reduced income disparity between states and higher growth in poorer states than richer states. Further insights into club convergence came from forming two clubs, with three states approaching the national average while twelve did not converge. The economic reforms of 1991 strengthened Indian agriculture, but only a few states prospered, and the majority did not follow a common development path, which is a cause for concern. The government should make policies to bring these states up to national averages, which will pave the way for the government's goal of doubling farmers' income.

Land use land cover simulations using integrated CA-Markov model in the Tawi Basin of Jammu and Kashmir India

Land use and land cover (LULC) changes are important indicators of environmental and socio-economic changes made by the natural and anthropogenic sources. The present study is based on the Cellular Automata (CA) Markov model for predicting the LULC changes in the Tawi Basin. To decipher the spatio-temporal distributions of LULC, the Landsat images of 2010 and 2020 were used to analyse the LULC classification. Further, CA Markov model simulations of various scenarios of eight decades (2030 to 2100) were generated based on LULC of 2010 and 2020 data to know the LULC perspective changes in the Tawi Basin, which has witnessed the enormous developmental activities such as growth in settlement, population, and agriculture sector over the years. The model predicts that a population explosion leading to rapid urbanization and rural expansions.Settlement is expected to increase from 5.29% of the total area in 2020 to 13.975% in the year 2100. The CA–Markov model results paint a picture of significant changes in land use and settlement patterns in the Tawi Basin. The study serves as a crucial tool for guiding future planning efforts, urging environmentalists, planners, and decision-makers to prioritize sustainable practices and make informed decisions for the well-being of the region.

Tapping the Potential of Agriculture Transformation in Tanzania Under the BBT-YIA Program: the Case of Organic Waste Management

This study assess the available potential that can be tapped from organic waste generated under the BBT-YIA program. The study motivated by the ongoing Agriculture transformation in the Tanzania which aimed at increasing: the area under block farming; area under irrigation; and agriculture sector growth from currently, 41,000 acres to one million acres, 10% to 50% and 4% to 10% by 2030 respectively. However, every step of agricultural production, transportation, and processing generates wastes. Ineffective management of such waste cause social, economic and environmental concern. Despite that, there is potential of turning such waste into valuable resources. The study analyses the available potential that can be tapped from organic waste mostly crop residues generated in the block farms. The methodology involved purposeful selection of the Ministry of Agriculture, Ministry of Livestock and Fisheries, Ministry of Energy and Local Government authorities. Interviews, direct observations and documentary reviews were part of data collection techniques and the collected data were analysed using descriptive analysis. The findings show that the BBT-YIA program has a potential of producing 200,000 tons of animal feed annually; 14,129 tons of compost per month; creating about 56,490 jobs through organic waste recycling; generating 1.44 MW of electricity per day; and reducing Greenhouse gas by diverting 734,375 tons of crop residue disposal sites. The study recommends; establishment of biomass plants; organic waste recycling program; and compost production initiatives.

Assessing the efficacy of agricultural cold chain facility expansion in China

This study determines the effectiveness of agricultural cold chain facilities in preserving quality and extending storage time of vegetables and fruits in China. National data were collected through interviews with 10,263 farmers across all provinces except Tibet. Using ordinary least squares regression analysis, several conclusions and policy implications emerge. First, cold chain facilities significantly reduce loss ratios (about 2% on average) and extend storage days for fruits (up to 28 days), but some facilities fail to demonstrate significant effects for vegetables. This implies that stakeholders, especially vegetable producers, must strategically select storage methods. Second, regional disparities exist, with the less developed Northwest facing more acute post-harvest losses, underscoring the need for tailored interventions addressing infrastructure gaps. Third, cold chain transportation distinctly influences vegetable preservation, decreasing losses and storage time. Improving vegetable transport efficiency benefits farmers and consumers. Fourth, supporting facilities like packing houses extend storage days for fruits and vegetables, highlighting the need to construct such infrastructure especially where shipping is limited. Moreover, with the projected expansion of cold chain facilities in China, these findings offer crucial guidance for policymakers, agencies, and farmers in selecting and distributing infrastructure to mitigate losses and support agricultural sector growth. As China advances its cold chain capabilities, this study demonstrates the vital role of such facilities in enhancing food security, reducing waste, and providing fresh produce to consumers.

Application of Universal Cooperative Principles in Agricultural Cooperatives: A Case Study from Nepal

This study examines the use of universal cooperative principles by agricultural cooperatives in Nepal, highlighting their importance and the challenges they face. Data from 45 cooperatives, including savings and credit cooperatives (n=17) and multipurpose cooperatives (n=28), and 135 respondents in Tulsipur Sub-Metropolitan City, Nepal were analyzed quantitatively and qualitatively. The study suggests that principles such as democratic member control, voluntary and open membership, and member economic participation are critical to the effective and sustainable operation of agricultural cooperatives in Nepal. These principles promote members' sense of responsibility and ownership by ensuring transparency, fairness, and democratic decision-making. However, the research also identifies several constraints facing Nepal's agricultural cooperatives, including limited access to finance, inadequate infrastructure, governance issues, lack of technical expertise, and political interference. These challenges could hinder cooperatives' ability to expand into new markets, provide essential services to members, and support the long-term growth of Nepal's agricultural sector. The study concludes that addressing these issues and promoting the adoption of universal cooperative principles are essential to strengthening agricultural cooperatives in Nepal and enabling them to significantly improve the livelihoods of farmers and rural communities.

Factors Affecting Farmers’ Access to Agricultural Subsidy in Makwanpur and Dhading Districts of Nepal

The government of Nepal has been providing high priority to subsidy programs to support farmers and boost the national economy. Increasing access to and effectiveness of the subsidy program is important to enhance growth of agricultural sector. However, there has always been a concern about access to and effectiveness of the subsidy programs to address the problem of farmers in Nepal. This study was carried out to determine the factors affecting farmers' access to the agricultural subsidy. For this, a multi-stage sampling method was employed, and altogether 120 commercial vegetable growers from Dhading and Makwanpur districts of Nepal were selected using simple random technique. Descriptive statistical tools and binary logistic regression were used to analyze the data. Out of the total sampled households, 55.83% had accessed at least one agricultural subsidy program, and the highest number of sampled households (39.17%) received the subsidy for agricultural tools. The result of binary logistic regression revealed that factors like ethnicity, membership in agricultural groups or co-operatives, farm visit by extension agents, and participation in agricultural training were significantly (p<0.01) influencing farmers' access to agricultural subsidy. Hence, the farmers are suggested to operate through agricultural groups or co-operatives, and the concerned authorities and policymakers should emphasize agricultural extension services and agricultural subsidy simultaneously for synergistic effects. SAARC J. Agric., 21(2): 263-276 (2023)

Recent Trends of Machine Learning Techniques on The Growth of Agricultural Sector of Assam

The agricultural sector in Assam, India, holds immense potential for economic growth and rural development. However, harnessing this potential requires tackling challenges like low productivity, resource scarcity, and climate change. Machine learning (ML) emerges as a promising tool to address these hurdles and transform Assam’s agricultural sector. This review investigates the potential of machine learning (ML) techniques in driving agricultural growth within the specific context of the Assam’s economy. Utilizing comprehensive search within Scopus and Web of Science databases from 2015 to 2023, and following the PRISMA guidelines, we analyzed 37 relevant articles. Our examination focuses on the multifaceted applications of ML across various agricultural domains in Assam, encompassing crop yield prediction, soil health analysis and economic growth. The review highlights successful ML- driven interventions in Assam’s agricultural sector, showcasing their ability to improve resource efficiency, optimize crop management, and enhance market access. This review provides valuable insights for policymakers, researchers, and farmers seeking to leverage the power of ML for a more sustainable and prosperous Assam’s agricultural landscape.

Inclusive Regional Value Chains: Blockchaining Perishable Agricultural Products in Southern Africa

Abstract In Southern Africa due to unsystematically and uncoordinated regional value chain (RVCs), plenty of perishable agricultural products are lost because of spoilage and poor postharvest system misaligning upstream and downstream partners. Although appeal for increasing trade in Southern Africa region may seem plausible, there are strictly speaking no well-grounded economic reasons why perishable agricultural products trade should be an obsession. Broad-based inclusive RVCs through blockchaining perishable agricultural products could enable far more effective responses to region’s sustainable developmental challenges as it does in developed and emerging economies. Recently, the rise and expansion of inclusive RVCs and emphasis on blockchain has spurred major paradigm shift on revamping postharvest system. The investigate relevance of blockchaining initiatives towards inclusive RVCs to perishable agricultural products in Southern Africa. Through a quantitative research approach involving quantitative data collection methods, the research aims to assess the current challenges, opportunities, and perceptions regarding blockchain technology in the agricultural sector. Study findings practically and empirically contribute to excel blockchain for supporting development of inclusive and resilient value chains, providing insights for policymakers and stakeholders in promoting sustainable economic growth in Southern Africa’s agricultural sector.

Impact of Minimum Wage and Sectoral Growth on Inflation

Inflation is one of the macroeconomic problems faced by every country. Inflation reduces the purchasing power of money. Inflation occurs due to cost-push inflation, demand-pull inflation, and rising expectations. The main objectives of this study are to analyze the impact of the minimum wage on inflation, evaluate the effect of agricultural sector growth on inflation, examine the impact of industrial sector growth on inflation, and identify the impact of service sector growth on inflation. In order to attain these goals, an examination was conducted utilizing Eviews with panel data spanning from 2013 to 2022 across 38 regions in East Java. After conducting tests on different models, it has been determined that the REM model is the most optimal. Analyzing the results obtained through the REM model reveals that the impact of minimum wage on inflation is positive but not statistically significant. The growth of the agricultural sector has a positive and significant effect on inflation. The growth of the industrial sector has a positive and insignificant effect on inflation. Growth in the service sector has a positive and significant effect on inflation.

Effect of External Debt on Performance of the Agricultural Sector in Kenya

Agriculture forms the backbone of the economy in most developing and developed countries. Its production has increased significantly over the last three to four decades. In 2018, it contributed to about 4% of global gross domestic product (GDP), and in 2020, it accounted for 35 percent of the gross domestic product (GDP) and 65 percent of foreign exchange earnings in Kenya. It’s also a primary source of raw materials for both national and international industries. However, its performance has been declining over the years, and there is a dearth of information with regard to how external debt has affected the sector’s performance. Thus, this study sought to investigate the effect of external debt on the performance of the agricultural sector in Kenya. A correlational research design was adopted. The time series data used in the study was obtained from the databases of World Development Indicators and Statista, covering the period from 2012 to 2020. The data was analyzed using EViews software. The findings revealed that external debt had a significant positive effect on the performance of the agricultural sector in Kenya. Therefore, according to the study, the government of Kenya needs to invest more external debt in agriculture to spur agricultural sector growth.

The Effect of Per Capita Income and the Agricultural Sector on Goods and Services Tax Receipts with Economic Growth as Moderation in BRICS Countries

The purpose of this research is to analyze the effect of per capita income and the agricultural sector on goods and services tax revenues with economic growth as the moderation in the combined economy countries, BRICS (Brazil, Russia, India, China, and South Africa). The variables used in this study are the ratio of goods and services tax revenue, per capita income, the contribution of the agricultural sector, and the percentage of economic growth. The data source comes from the World Bank Data for the period 2010 to 2018. The research method used is quantitative using panel data and multiple linear regression analysis techniques. The Random Effect Model is a model selected based on panel model testing. Simultaneously, all variables have a significant effect on goods and services tax revenues. Partially, per capita income, agricultural sector, and economic growth have a significant negative effect on goods and services tax revenues. This research is expected to provide insight to the governments of the BRICS countries in making policies to optimize goods and services tax revenues through per capita income, the agricultural sector, and economic growth.

Human Resource Management Practices and Entrepreneurship Performance in the Agricultural Sector: Indonesia Study

Entrepreneurship is driving growth in Indonesia's agricultural sector, but the link between it and Human Resource Management (HRM) practices is largely unknown. A quantitative study aims to investigate this relationship. This research surveyed 355 agricultural companies in different areas and sub-sectors using a questionnaire designed for cross-sectional research. on their HR practices and entrepreneurial performance. Using Smart-PLS 4, a strong correlation between HRM strategies and entrepreneurial behavior and performance founded. HRM practices like hiring qualified staff, providing training, fair compensation, and promoting engagement can encourage entrepreneurial behavior among employees, leading to better agricultural enterprise performance. Prioritizing HRM strategies that support an entrepreneurial culture can increase productivity, promote sustainability, and motivate the workforce to tackle industry challenges.

Development of the agro-industrial complex of the Republic of Moldova, ways to improve the sphere and management system

Relevance of the research. The agro-industrial complex is the most important component of the economy of the Republic of Moldova. The protracted crisis of the agrarian sphere was, first of all, the result of the weakening of the role of state regulation and the management system of the agro-industrial complex. The effective economic development of the agricultural sector of the Republic of Moldova at the macro and micro levels requires the improvement of the system of management of the agricultural sector at all levels. Formulation of the problem. Related to the improvement of management at all levels of the country's agro-industrial complex, namely the competitiveness of enterprises under the influence of various risk factors, the correct formation of strategic management at the level of the state and enterprises, the use in the production of certain models of rational placement of production infrastructure for the effective development of enterprises, which ultimately ensure the sustainable economic growth of the country's agricultural sector. Setting the task, the purpose of the study. The purpose and objectives of the article are to study the structure of the agro-industrial complex management system, the dynamics of the main indicators characterizing the state of agriculture of the Republic of Moldova; identify problems, and develop recommendations for improving the management system of the agro-industrial complex of Moldova. Material and methodology. During the writing of the article, general scientific and special methods were used, namely the abstract-logical, statistical-economic, and graphic methods. The information and empirical base of the study are based on data from the National Bureau of Statistics of the Republic of Moldova. Presentation of the main material (results of work). The article conducted a study of the composition of the agro-industrial complex of the Moldavian SSR; the current state management system of the agro-industrial complex was analyzed; the degree of impact of reforms on the management structure of the agro-industrial complex was determined; in-depth analysis of the main indicators characterizing the state of this industry was carried out; proposed are directions of market infrastructure development through suitable channels of agricultural products distribution. Field of application of results. The materials, results, and conclusions of the study can be used by government bodies, higher education institutions, and student organizations. Conclusions according to the article. The results of the reforms carried out in the agricultural sector of the country's economy were summarized, problems that arose as a result of the ongoing reorganizations in the agro-industrial complex system were identified, and a deep analysis of the development of the agricultural economy was made. The authors also presented recommendations for improving the processes of management of the agricultural sector of the Republic of Moldova, and presented the author's conceptual approaches to the formation of the composition of the agro-industrial complex.

Applications of Emerging Smart Technologies in Farming Systems: A Review

The future of farming systems depends mainly on adopting innovative, intelligent, and smart technologies. The agricultural sector's growth and progress are more critical to human survival than any other industry. Extensive multidisciplinary research is happening worldwide for adopting intelligent technologies in farming systems. Nevertheless, when it comes to handling realistic challenges in making autonomous decisions and predictive solutions in farming, applications of Information & Communications Technologies (ICT) need to be utilized more. Information derived from data worked best on year-to-year outcomes, disease risk, market patterns, prices, or customer needs and ultimately facilitated farmers in decision-making to increase crop and livestock production. Innovative technologies allow the analysis and correlation of information on seed quality, soil types, infestation agents, weather conditions, etc. This review analysis highlights the concept, methods, and applications of various futuristic cognitive innovative technologies along with their critical roles played in different aspects of farming systems like Artificial Intelligence (AI), IoT, Neural Networks, utilization of unmanned vehicles (UAV), Big data analytics, Blok chain technology etc.

Sectoral Growth Analysis in Determining the Okun’s Law in Indonesia

This study aims to analyze the effects of agricultural sector growth, industrial sector growth, and service sector growth on economic growth, analyze the effects of agricultural sector growth, industrial sector growth, service sector growth, and economic growth on the unemployment rate, as well as analyze the indirect effects of agriculture sector growth, industrial sector growth, and service sector growth through economic growth on the unemployment rate. Using panel data in Indonesia for the 2017-2022 period. Analyzed with Smart PLS, the results of the analysis show that the growth of the agricultural sector, the growth of the industrial sector, and the growth of the services sector have a significant positive impact on economic growth. Directly, growth in the agricultural sector and growth in the services sector have a significant negative impact on the unemployment rate. while the growth of the industrial sector has no significant negative impact, and economic growth has no significant positive impact on the unemployment rate. Indirectly, the growth of the agricultural sector, the growth of the industrial sector, and the growth of the service sector have a not significant positive impact on the unemployment rate. The enactment of Okun's Law on the impact of agricultural sector growth, industrial sector growth, and service sector growth on the unemployment rate. The inapplicability of Okun's Law on the impact of economic growth on the unemployment rate.

Innovation, natural resources abundance, climate change and green growth in agriculture

The growing concerns over climate change and the existence of the resource curse hypothesis in several resource-rich countries highlight the importance of green growth. Similarly, promoting green growth in agriculture is essential for addressing environmental problems, realizing sustainable development, and building a sustainable future. However, none of the studies emphasized the specific phenomena of the agriculture sector. Therefore, the core objective of this paper is to explore the role of innovation, natural resource abundance, and climate change in promoting green growth in the agriculture sector of China. The study used time series data ranging from 1970 to 2021 and applied cointegration and spectral causality techniques for empirical investigation. Robustness of the results was ensured using Bayesian regression. The findings of the study indicated that innovation significantly improves green growth in agriculture. It is also found that the proxy of climate change also plays a significant positive role in the green growth of agriculture. Conversely, the role of natural resource abundance in green agricultural growth has been found to be negative, which confirms the existence of a resource curse in the agriculture sector of China. Notably, all variables in the model demonstrated a positive impact on green growth in agriculture, except for natural resource abundance. The findings provide reasonable insights for policy development related to innovation, natural resources, and agriculture sector growth. The study concludes with key suggestions for policy formulation.

Digital inclusive finance and green total factor productivity growth in rural areas

Transitioning to environmentally friendly economic growth is crucial for achieving sustainable development. Digital inclusive finance (DIF) can promote environmentally friendly economic activities and play a crucial role in fostering green and low-carbon development. In this context, a fundamental research question revolves around the theoretical foundations of how DIF impacts the growth of green total factor productivity (GTFP) and whether this relationship can be empirically verified. This question is particularly relevant for rural areas where financial innovations are necessary for the advancement of businesses and society as a whole. Additionally, expanding DIF can bring benefits to the environment, which is affected by agricultural activities. Therefore, it is important to assess the mechanisms behind the development of DIF and its impact on agricultural productivity growth. This paper presents an analysis of the interaction between DIF and GTFP growth in China's agricultural sector. Panel data from 2012 to 2019 at the province level are used for this analysis. The results reveal that GTFP and DIF demonstrate similar growth patterns, with DIF significantly contributing to GTFP growth. DIF can enhance GTFP by promoting information channels and fostering innovation in green technologies.