Journal articles on the topic 'Agricultural Economic Data'
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1
Ghosh, Sujit K. "Economic Implications of Imputation in Agricultural Economic Data: Discussion." American Journal of Agricultural Economics 93, no. 2 (January 2011): 627–28. http://dx.doi.org/10.1093/ajae/aaq165.
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Wrzaszcz, Wioletta, and Józef Stanisław Zegar. "Economic sustainability of agricultural holdings on the basis of the data of the Agricultural Census 2010." Wiadomości Statystyczne. The Polish Statistician 60, no. 6 (June 29, 2015): 41–53. http://dx.doi.org/10.5604/01.3001.0016.0827.
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Measuring the level of agriculture sustainability is very complex. Different proposals are presented and discussed, and still, there is no generally accepted measures of the sustainability of agriculture. This problem also concerns economic sustainability of agriculture. Sustainability of agricultural holdings determines the sustainability of agriculture, although these notions are not identical. The purpose of the article is to present proposals for measuring the economic sustainability of agricultural holdings on the basis of Agricultural Census 2010 data. This article sets the following indicators of the economic sustainability: land productivity, labour profitability, farms market activity and sources of households’ income and maintenance. The analysis concerns individual agricultural holdings with at least 1 ha of agricultural land and it is also carried out in four area groups.
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Herath, Janaranjana, and David Hill. "Harnessing Agricultural Potentials for Economic Growth in North Carolina." Sustainable Agriculture Research 2, no. 2 (March 5, 2013): 142. http://dx.doi.org/10.5539/sar.v2n2p142.
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Agriculture in North Carolina contributes to 19 percent of the state’s income and employs over 20 percent of the work force. Agricultural activities are significant in rural counties and nearly 30 percent of the total population of North Carolina lives in 85 rural counties. Individuals in these rural counties have less income, education, and employment opportunities eventually in high poverty and unemployment rates. The objective of this study is to examine the potential use of agriculture in economic growth of North Carolina using county level data. Data were gathered from U.S. Bureau of Labor Statistics, U.S. Department of Agriculture, and U.S. Census Bureau for the period of 2000 to 2010. A system of simultaneous equations is used for the analysis. Results highlight that increasing income increases agricultural activities and vise versa. Thus, the counties with high household income levels are more capable of incorporating agriculture in economic growth while the counties with significant agricultural activities are more competent of improving income levels. Overall, results conclude the importance of secured satisfactory level of income through agriculture to enhance economic growth.
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Rajagukguk, Wilson. "Agriculture and regional economic growth in Indonesia." E3S Web of Conferences 258 (2021): 06037. http://dx.doi.org/10.1051/e3sconf/202125806037.
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The Republic of Indonesia consists of 34 provinces in 514 districts with diverse economic characteristics. The objective of this research is to analyze the association between agriculture sector and regional economic growth in Indonesia. The data source was from the Indonesia Database for Policy and Economic Research (INDO-DAPOER) of the World Bank. The study covered the period between 2001 and 2008. The province total gross domestic product (GDP) excluding oil and gas was used as the outcome variable. The covariates were grouped into agricultural and development variables. The agricultural variables were total agricultural credit, number of people employed in agriculture, forestry and fishery, and agriculture function expenditure. Meanwhile, the development variables were percentage of household with access to safe water and literacy rate for population age 15 and over. The data analysis method was the generalized least square multiple regression with random effects. The results of the study indicate that the Indonesia’s province GDP increased every year. In addition, higher economic growth was associated with higher total agriculture credit, larger number of people employed in agriculture, forestry and fishery, higher agricultural function expenditure, higher percentage of household with access to safe water, and higher literacy rate for population age 15 and over.
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Wang, Lei, and Hongwei Tan. "Agricultural Economic Risk Forecast Based on Data Mining Technology." Computational Intelligence and Neuroscience 2022 (April 27, 2022): 1–9. http://dx.doi.org/10.1155/2022/3684736.
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In order to improve the effect of agricultural economic risk forecast, this paper studies the agricultural economic risk forecast combined with data mining technology and builds an intelligent agricultural economic risk forecast system. Moreover, this paper employs a dynamic factor model to estimate common factors that drive changes in target topics. In order to construct a sentiment index that can reflect the overall operating situation of the macroeconomy, this paper improves the agricultural economic risk mining algorithm and standardizes the sentiment value corresponding to the target theme. In addition, this article analyzes the sentiment changes of its individual topics one by one in combination with the specific economic environment. The simulation study shows that the agricultural economic risk forecast system based on data mining technology proposed in this paper has a good effect.
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Szabó, L., and Zsarnóczai JS. "Economic conditions of Hungarian agricultural producers in 1990s." Agricultural Economics (Zemědělská ekonomika) 50, No. 6 (February 24, 2012): 249–54. http://dx.doi.org/10.17221/5198-agricecon.
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The main aims of this study are to describe how much the economic role of agriculture decreased, and this decrease comes mainly from some economic difficulties, for example weak income position of producers based on weak capital accumulation. So agricultural producers need financial supports to improve their production and favourable credit conditions. In 1990s during the last decade, the role of agriculture in the national economy decreased, which contributed to its decreasing share in GDP and real value of agricultural GDP. In 2001, in spite of the fact that the plant production considerably increased and the animal husbandry stagnated, the whole agricultural production volume was by 20 percent under its level of 1989. Finally by the end of 2001, the share of agriculture declined to 4 percent of GDP and together with food industry, their share was about 7 percent. The agricultural scissors increased considerably, namely from 126.5 percent in 1992 to 138.4 percent in 2001.The income conditions made a significant influence on the capacity of the agricultural sector in fields of investments and accumulation. The main problem was the decline of real value of investments. For example the real value of investments in 2001 had not implemented half of investments realised in 1989. This situation showed the low level of technological and technical development in the agricultural sector during a longer period, than a decade. It was important to increase different kinds of supports for agricultural producers, for example: export subsidies, interests of credits, supports for establishing new farmland structure. The share of supports for agricultural production and food industry was 12–14 percent of the two sectors’ GDP in 1990s. The development of the main factors of agricultural incomes was determined by index calculations based on the data of the APEH (Hungarian Tax and Financial Supervising Office) and EAA (Economic Accounts for Agriculture). The supports are needed, which are as follows: based on the APEH data, the profit before tax of 23 billion HUF in 1997 decreased to the loss-level of 8 billion HUF by the end of 1990s. The main aim for agricultural producers was to increase their capital accumulation to implement improvement of production in order to be competitive on the world and domestic markets. There is a difficulty that at the end of 1990s, only about 30 percent of the supports was directly provided for agricultural producers. In Hungary, without taxes and other different deprivals, the current value of production supports was over the level of incomes obtained in agricultural sector, but according to the calculation methods of the OECD, the value of PSE (PSE= Producer Support Estimate) index was at a very low level and it had a decreasing tendency, which could not ensure enough income for agricultural producers in Hungary. So the development of agricultural production cannot be realised additionally to the unfavourable background conditions for the sector. Comparing the support structure experienced in the OECD with that in Hungary, it can be declared, that within the PSE (Producer Support Estimate) during 1997–2000, the MPS (Market Price Support) declined, similarly it was in Hungary. In the OECD, the 8–9 percent share of payments based on input use has remained at same level within the PSE. The subsidy based on input use in Hungary was a main element within the overall subsidy system, and its proportion within the producer subsidy increased from 9 percent to 27 percent during the same period. The payment based on the regulation on input use (environment friendly production) also decreased and shared 2 percent within producer subsidies. In the OECD, payments based on farming income totalled only 1 percent of the total producer subsidies, as well as it was experienced in Hungary. Hungarian market price subsidies by products reveal that milk, eggs and poultry enjoyed a high Market Price Support. On the other hand, Market Price Support to beef cattle remained low.
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Liu, Shu, and Yuting Wu. "Economic Benefit Evaluation and Analysis Based on Intelligent Agriculture Internet of Things." Journal of Mathematics 2021 (December 20, 2021): 1–7. http://dx.doi.org/10.1155/2021/9499197.
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There has been a consensus on the development of ecological agriculture to promote the leap from traditional agriculture to ecological agriculture, but the unavoidable fact is that the development of ecological agriculture is still relatively slow at the present stage and has not formed a major climate and great influence. The rise of the Internet is a technology that has promoted the transformation and upgrading of modern agriculture, changed the traditional agricultural production mode, and accelerated the scientific and technological integration of information. In view of the characteristics and difficulties of agriculture, this paper builds an Agricultural Internet of Things (IoT) management system to realize the integrated management of Internet equipment and realize the management of environmental data, video data, and agricultural expert knowledge. Then from perception technology, transmission technology, and the perspective of three intelligent information processing technologies, this paper introduces the present state of agricultural IoT, analyzes the Internet of Things to the economic benefits of agricultural production, to research the problems of China’s agricultural development of the Internet of Things, and puts forward China’s agricultural Internet of the future research emphasis and direction of development.
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Nohel, František, Daniela Spěšná, and Pavel Pospěch. "Regional markets with agricultural workforce based on Labour offices' data." Acta Universitatis Agriculturae et Silviculturae Mendelianae Brunensis 59, no. 4 (2011): 177–86. http://dx.doi.org/10.11118/actaun201159040177.
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The changes in Czech agriculture over the past twenty years have had their impact on the agricultural labour market, too. The regional differentiation of the chances of applicants on the labour market as well as the agricultural enterprises’ chances of hiring employees fitting their requirements, are, among others, influenced by the specific conditions of agricultural production. The aim of this paper pertains to two basic problem areas: first, the differentiation of respective regions based on the number of agricultural applicants and job vacancies, and second, the identification of disequilibrium on the agricultural labour market. The latter is based on a theoretical framework defined by approaches in economy dealing with labour market equilibrium. Due to the unavailability of economic data (including wages, economic performance, etc.) on the regional level, authors develop their own methodological approach, based on the number of applicants per job vacancy. A database of applicants and vacancies available from the Labour Offices is used as a source for the analysis and interpretation of data, enabling us to study the agricultural labour market not only sector-wise but also region-wise.
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Lerohl, M. L. "Issues in Canadian Agricultural Economic Data: A Selected Review." Canadian Journal of Agricultural Economics/Revue canadienne d'agroeconomie 36, no. 2 (July 1988): 175–86. http://dx.doi.org/10.1111/j.1744-7976.1988.tb03270.x.
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Marjudi, Suziyanti, Roziyani Setik, Mohamad Aizi Salamat, and Muhammad Fahruddin Irfan Yusfaidir. "The Design and Development of Smart Agriculture Data Analytics." International Journal of Emerging Technology and Advanced Engineering 13, no. 1 (January 3, 2023): 82–91. http://dx.doi.org/10.46338/ijetae0123_10.
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Agriculture is on the verge of entering the Smart Farming era, in which farming operations will become digitalized and data-driven, allowing for better decision support, smart analytics, and forecasting. Farming is the most diverse economic sector and is critical to a country's overall economic development. The Internet of Things (IoT) can potentially optimize agriculture and farming sector activities by reducing manpower through technology. Forecasts are central to most agricultural and agricultural-related operations. Smart Agriculture Data Analytics (SADA) was developed to address this issue. SADA is an embedded system with two components: data analytics and the Internet of Things (IoT). IoT in SADA also assists farmers in collecting data and learning more about the appropriate soil PH scale, fertilizer dataset, air humidity, and temperature. A prototyping model is used in software development. The farmer can provide real-time feedback, request project changes, and update model specifications. SADA will help farmers understand the trend of analytics crop production, allowing them to increase yield
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Shen, Danna, Wang-Fang Shi, Wei Tang, Yan Wang, and Jun Liao. "The Agricultural Economic Value of Weather Forecasting in China." Sustainability 14, no. 24 (December 19, 2022): 17026. http://dx.doi.org/10.3390/su142417026.
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Agriculture is one of the areas most sensitive to climate change. Extreme climate events can directly affect agricultural production and development. Based on the data from the statistical yearbooks of 30 provinces in China from 2009 to 2019 and the survey data of meteorological forecasting, this paper uses the fixed-effect model to empirically test the impact of meteorological forecasting on agricultural economic value. The results show that meteorological forecasting has a significant promoting effect on agricultural economic value, in that an increase in the accuracy of the meteorological forecast by one percentage point will increase agricultural economic value by 0.500 percentage points, and the results still hold after a series of robustness tests. Further study showed that there were some regional differences in the agricultural economic value of the meteorological forecasting, and the meteorological forecasting had the strongest promoting effect on the agricultural economic value of the western region, followed by the eastern region and the central region.
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Qiu, Xia, Daixue Xu, Zhixian Zeng, and Xuanzhou Yan. "A Study of the Economic Contribution Rate of Agricultural Mechanization in Jiangxi Province from the Perspective of Cobb-Douglas’ Production Function." Scientific and Social Research 4, no. 1 (January 20, 2022): 40–46. http://dx.doi.org/10.36922/ssr.v4i1.1313.
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With the gradual transformation of traditional agriculture into modern agriculture, agricultural mechanization has played a very important role in the contribution rate of the whole people’s economy in Jiangxi Province. Because of the wide application of Cobb-Douglas (C-D) production function in western economics, many scholars have used this method in practice in recent years. By establishing the C-D production function model, the agricultural mechanization data of Jiangxi Province from 2005 to 2019 are analyzed, and the factors such as agricultural output value, agricultural mechanization input, agricultural material consumption, labor input and land input play a key role in the economic growth of agricultural mechanization development.
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Denisova, Elena. "Geoinformation Methodology of Agricultural Land Evaluation for Agricultural Economic Growth." Agris on-line Papers in Economics and Informatics 13, no. 4 (December 30, 2021): 3–8. http://dx.doi.org/10.7160/aol.2021.130401.
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The formation of an economically developed management system for the country's agro-industrial complex cannot be considered only from the point of view of a separate science. Land resources are the source of profit, which is involved in almost all sectors of society. Land preservation and improvement is required to ensure an economic security and competitiveness of each region of the Russian Federation). The dynamics of changes in the areas of Svetloyarsky district of the Volgograd region in the context of municipalities is analyzed. The actual deviation of the area of Privolzhsky rural settlement amounts to 2,3 % of the statistical data. The boundaries and areas of the used plots of arable land in the Raigorod settlement do not coincide with the data of the state cadastral registration, the discrepancy of only one land plot is 422,44 hectares. By implementing GIS-technologies, the data were obtained for 2355 arable land plots, whereof the irrigated land area amounts to 52138 hectares, instead of the potentially possible 19455 hectares, that exceeds the settlement's capabilities by 2,7 times according to the statistical data.
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Jiang, Yangming, Tuo Wang, Huihui Zhao, Xiaodong Shao, Weihong Cui, Kun Huang, and Lingping Li. "Big Data Analysis Applied in Agricultural Planting Layout Optimization." Applied Engineering in Agriculture 35, no. 2 (2019): 147–62. http://dx.doi.org/10.13031/aea.12790.
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Abstract. Mile is a region in Yunnan Province, China. The planting-related industry is its pillar industry. Its agricultural population accounts for 59.3% of the total population. Temporal fluctuations of crop price and yield have a significant influence on farmers’ revenue. Farmers’ selection of crop species, crop planting strategy, and agricultural planting layout according to the market price is important in securing their revenue. In this study, we used a web crawler program to obtain a large amount of data on agricultural product prices from the Internet. Then, the price fluctuation trend of the main economic crops was analyzed by using the K-means clustering method. The net investment yield and the Sharpe ratio were used to compare the economic benefits and investment risks of 10 crops and five cultivation strategies in Mile. Furthermore, a comprehensive comparative advantage index, which integrates the net investment yield, Sharpe ratio, scale advantage index, productivity advantage index, and ecological suitability advantage index, was adopted to comprehensively measure the advantages of crop cultivation. Finally, we propose a spatial-temporal big data analysis model based on the cuckoo search algorithm to optimize the spatial layout of the main crops in Mile in 2017. Based on the comparative analysis of the remote sensing monitoring results and the spatial optimization layout results of the main crops in 2017, several suggestions were given. The results based on agricultural big data analysis, such as crop selection cluster analysis, economic benefit analysis, and crop planting layout optimization, can give suggests to farmers plant suitable crops on right lands, in right time. Thus, it can help farmers stabilize their revenue and minimize the risk by choosing the right crops and planting strategy in accordance with the local conditions. Keywords: Agriculture investment risk, Agricultural layout optimization, Cuckoo search algorithm, K-means clustering, Relative advantage analysis, Spatial-temporal big data analysis.
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Hartarska, Valentina, Denis Nadolnyak, and Xuan Shen. "Agricultural credit and economic growth in rural areas." Agricultural Finance Review 75, no. 3 (September 7, 2015): 302–12. http://dx.doi.org/10.1108/afr-04-2015-0018.
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Purpose – In this paper, the authors set out to establish if there is a link between finance and economic growth in rural areas. The purpose of this paper is to evaluate the relation between credit by major lenders in rural areas – commercial banks and Farm Credit System (FCS) institutions – and economic growth for the period 1991-2010. Design/methodology/approach – The motivation for this work comes from empirical studies showing a link between economic development and financial system development as well as from work which highlights the positive role of long-term finance provided by banks. The authors use two alternative panel data sets and fixed effects models to estimate the causal effect of credit supply (with lagged explanatory variables) on agricultural GDP growth per rural resident. Findings – The authors find a positive association between agricultural lending and agricultural GDP growth per rural resident with additional billion in loans (about a third of the actual average) associated with 7-10 percent higher state growth rate with this association stronger during the 1990s. Regional data confirm these results. The results point to a positive link between credit and economic growth in rural areas during that period, attributable to the lending by FCS institutions and by commercial banks. Research limitations/implications – Data availability limits the scope of this paper. The authors use state level balance sheet data available for the 1991-2003 period and annual data for 2003-2010 period. An additional regional data set is constructed for 1991-2010 with more aggregated data for the ten USDA agricultural production regions. The small number of panels limits the ability to use more sophisticated econometric models and the choice of dependent variables that captures economic growth. Practical implications – By provides evidence that agricultural finance and in particular lending contribute significantly to the growth of US agriculture, this paper contributes to the policy debate on weather support for agricultural finance initiatives is justified. Originality/value – The authors are not aware of another study that has linked agricultural lending by commercial banks and FCS institutions to growth in rural areas in the USA.
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Rosochatecká, E. "Economic efficiency of agricultural enterprises and its evaluation ." Agricultural Economics (Zemědělská ekonomika) 48, No. 3 (February 29, 2012): 97–101. http://dx.doi.org/10.17221/5455-agricecon.
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Agriculture as a sector of national economy shows a permanent loss (except the year 1995 and 2000). The investment volume and number of workers decreases. The necessary resources for businesses development are not created at the general level. Introducing of new technologies for restructuring appears as problematic from this point of view. The stated results of the sector of agriculture stem from the average data of the monitored set of enterprises collected by the RIAE. Evaluation objectivity of the agricultural enterprises economic results is influenced by the quality of the database and of the used evaluation method. In the contribution, the method of the financial analysis indices, economic normal and the indicators of the enterprise financial situation prediction were utilised for evaluation. For the analysis, own set of monitored enterprises is used and also its comparison with the selected results of the RIAE.
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Šapolaitė, Vaida. "Assessment of the agricultural activity in the EU-27 countries." Management Theory and Studies for Rural Business and Infrastructure Development 36, no. 3 (October 14, 2014): 653–62. http://dx.doi.org/10.15544/mts.2014.062.
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The rational use of land, capital and labor determine the growth of economic efficiency of agricultural production and income of farmers together. The aim is to estimate the use of production resources in the EU-27 agricultural sector, using macro-economic indicators. The analysis and assessment of the use of land resources in agriculture have been conducted on the basis of data on economic accounts for agriculture and agricultural census to describe agricultural production intensity by type of farming and its impact on farm income. This paper examines the use of land resources in agriculture, measured by using relative indicators of agricultural output, intermediate consumption per hectare of agricultural land, the revenue per average employee and the comparative analysis these indicators in the farms of the European Union (EU) is presented.
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Korotchenya, V. M., and G. I. Lichman. "THE TECHNICAL AND ECONOMIC LEVEL OF AGRICULTURAL UAVS: USING DATA ENVELOPMENT ANALYSIS METHODOLOGY." Экономика сельского хозяйства России, no. 9 (September 2020): 73–78. http://dx.doi.org/10.32651/209-73.
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Su, Yan, and Xianping Wang. "Innovation of agricultural economic management in the process of constructing smart agriculture by big data." Sustainable Computing: Informatics and Systems 31 (September 2021): 100579. http://dx.doi.org/10.1016/j.suscom.2021.100579.
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Cochrane, Logan, and Yeshtila W. Bekele. "Contextualizing Narratives of Economic Growth and Navigating Problematic Data: Economic Trends in Ethiopia (1999–2017)." Economies 6, no. 4 (December 3, 2018): 64. http://dx.doi.org/10.3390/economies6040064.
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There are common narratives about economic growth in Ethiopia. We analyze four common narratives, namely, that (1) the economy is transforming from agriculture to industry, (2) that national economic growth has been rapid and sustained, (3) that Ethiopia’s economy is largely agricultural, and (4) that there is a looming debt crisis, largely due to lending from China. In many instances, the justification for these narratives is based upon single years or specific data points. We examine these narratives over the long term, to assess if they are supported by available macroeconomic data. In doing so, we encountered significant issues with data quality and consistency. This article presents the available datasets from 1999 to 2017 and concludes that the commonly made claims about the Ethiopian economy are sometimes accurate, sometimes incomplete, and other times inaccurate. We call for greater attention to primary data, and primary datasets, as opposed to relying upon secondary summaries, single years, or specific data points to make generalized claims.
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Suwandaru, Agung, and Thamer Alghamdi. "Modelling Sustainability Agriculture and Economic Development in Indonesia." E3S Web of Conferences 316 (2021): 02049. http://dx.doi.org/10.1051/e3sconf/202131602049.
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Agriculture sustainability plays an essential role in country development. This paper aims to examine whether sustainable agriculture is beneficial to economic development in Indonesia. The empirical analysis employs the autoregressive distributed lag model over the data from 1961-2016. The results show that sustainable agriculture significantly contributes to economic development in the long run for both models. The gross fixed capital and rural population as endogenous variables show the positive relationship in the long run, but technical assistance shows negative results. In the short run, all variables show mixed results in different lags. These findings conclude that agricultural policies are broadly on the right track. However, the government needs to focus more on the agricultural bureaucracy and strengthen its infrastructure.
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Zang, Dungang, Zhijia Hu, Yunqi Yang, and Siyu He. "Research on the Relationship between Agricultural Carbon Emission Intensity, Agricultural Economic Development and Agricultural Trade in China." Sustainability 14, no. 18 (September 18, 2022): 11694. http://dx.doi.org/10.3390/su141811694.
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Under the interactive background of more emphasis on low-carbon and environmentally friendly agricultural production modes and the coordinated development of agricultural foreign trade, China is paying more and more attention to the coordination between agricultural trade, economic development and ecological agriculture development. This paper selects the relevant data of China from 2002 to 2020 as the research object. Taking the agricultural carbon emission intensity as an indicator of environmental pollution, measuring it and then constructing a time series model for analysis, the research finds that, in the long run, the increase in agricultural carbon emission intensity in China will reduce the level of agricultural trade by 2%, which will also lead to a decline in the overall development level of the agricultural economy by 2 to 4 percent. At the same time, this paper also finds that the current situation of China’s agricultural trade reduces the development of China’s agriculture by 1%, which will also lead to an increase in agricultural carbon emission intensity by about 0.5%. Finally, this paper finds that the development of the agricultural economy makes the overall increase in agricultural trade 2%, and with the development of the agricultural economy, the agricultural carbon emission intensity decreases by 0.1%, but the impact is small. Therefore, it is necessary to improve the construction of a leadership mechanism, implement the development strategy of low-carbon agriculture and provide corresponding financial security and other policy suggestions to promote the coordinated development of China’s agricultural trade and low-carbon agricultural production environment.
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Ahmad, Mumtaj, Pasarul Islam, and Shamsul Haque Siddiqui. "Role of Agricultural Technology on Socio-Economic Development in Hathras District, Uttar Pradesh." National Geographical Journal of India 66, no. 3 (September 30, 2020): 222–35. http://dx.doi.org/10.48008/ngji.1743.
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Agriculture in India has experienced a significant transformation in the past fifty years, with agriculture being more and more oriented to a productivist form of socio-economic production. Introduction of new agricultural technologies, high yielding varieties of seeds, improve access to irrigation, education, efficient use of fertilizers and extension services are capable of enhanced productivity per unit of land. Increased production further reflects on socio-economic transformation in rural communities. The study uses secondary data from various sources published by the Government of India and the Government of Uttar Pradesh. The study covers the period between 2000-01 and 2014-15 to analyze the role of agricultural technologies on socio-economic transformation in Hathras district. The methodology adopted for the present study are Data Interpolation or Extrapolation, Yang’s Crop Yield Index, Dayal’s Labour Productivity, Data Standardisation technique Z- score, and Composite Z score. The study concludes that the district has experienced tremendous technological changes in agricultural practices, agriculture induced better productivity and productivity further leads to overall socio-economic transformation.
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Sui, Yuan, and Jizhu Zhao. "Optimization Simulation of Supply-Side Structure of Agricultural Economy Based on Big Data Analysis in Data Sharing Environment." Journal of Environmental and Public Health 2022 (September 9, 2022): 1–10. http://dx.doi.org/10.1155/2022/1497357.
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Big data is transforming how people live their lives, and the widespread use of information technology has tremendously aided in the development and deployment of big data technologies. The use of big data technology can lower agricultural production and distribution costs, increase agricultural modernization’s effectiveness, and support the transformation and upgrading of the agricultural economy. Big data technology has garnered a lot of attention as a burgeoning technological area. Big data has revolutionised the service model for “agriculture, rural areas, and farmers” and given agricultural economy supply-side structure optimization new life. In the age of big data, we should reexamine the way agricultural economic information is currently released, propose more scientific techniques for doing so, and improve the effectiveness of implementation across the board. In light of the background of big data, this research investigates and evaluates the supply-side structure of the agricultural sector. The big data method is combined in this work to explore and analyse it. This study shows that the supply-side structure of the agricultural economy, when seen against the backdrop of big data, has a definite impact, with an impact as high as 56.56%. This essay lays the groundwork for future agricultural economy research and development.
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Murzin, Anton, and Li Yiru. "Comprehensive Socio-Ecologo-Economic Assessment of Agricultural Efficiency in China." IOP Conference Series: Earth and Environmental Science 937, no. 3 (December 1, 2021): 032063. http://dx.doi.org/10.1088/1755-1315/937/3/032063.
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Abstract Modern agriculture aims to coordinate the contradiction between the development and utilization of agricultural resources and environmental protection by using scientific and technological achievements and management methods, so as to obtain good ecological benefit, social benefit and economic benefit. In this paper, 12 indexes are selected to build an evaluation system of comprehensive agricultural benefit. The agricultural data from 2013 to 2019 are analyzed, and the evaluation results are obtained: China’s comprehensive agricultural benefit kept growing, social benefit and economic benefit continued to grow, and ecological benefit began to grow rapidly in 2018 after experiencing a small decline. According to the evaluation results, the problems existing in China’s agricultural development are found, and the corresponding countermeasures and suggestions are put forward.
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Pusra, Cut Miranda, Srinita Srinita, and Chenny Seftarita. "EFFECT OF SELECTED ECONOMIC SECTORS ON POVERTY." International Journal of Business, Economics, and Social Development 2, no. 1 (February 4, 2021): 37–49. http://dx.doi.org/10.46336/ijbesd.v2i1.116.
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This study analyzes the influence of certain economic sectors on poverty levels in districts/cities in Aceh Province. The determination of the economic sector is based on the 4 largest contributions to the economy in Aceh. The economic sector in question is the agriculture, trade, construction, and processing industry sectors. So that the purpose of this study is to analyze the influence of selected economic sectors, namely the agricultural sector, the trade sector, the construction sector, and the manufacturing sector on poverty levels in Aceh. This study uses panel data from 23 districts/cities in Aceh Province for the period 2010-2019 and the data used is the percentage of poverty and data on the distribution of the percentage of Gross Regional Domestic Product (GRDP) by business field. The results obtained from this study are that all independent variables, namely the agricultural sector, the trade sector, the construction sector, and the manufacturing sector have a significant negative effect on the poverty level. This can be seen from the F test probability of 0.00. partially the agricultural sector reduced the poverty rate by 0.71 percent. trade sector 0.48 percent. the construction sector reduces poverty by 0.51 percent and the manufacturing sector reduces poverty by 0.67 percent. Therefore, it is hoped that the government can work together with other policymakers to improve the manufacturing sector both in agriculture and other fields to increase the productivity of society to alleviate poverty.
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Gusmini, Gabriele, and Todd C. Wehner. "Fifty-five Years of Yield Improvement for Cucumber, Melon, and Watermelon in the United States." HortTechnology 18, no. 1 (January 2008): 9–12. http://dx.doi.org/10.21273/horttech.18.1.9.
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Yield data for the major cucurbit crops in the United States have been collected and summarized. Yield trends are presented for cucumber (Cucumis sativus; processing and fresh-market), melon (Cucumis melo; muskmelon and honeydew), and watermelon (Citrullus lanatus) for the period 1951–2005. Data have been obtained from the U.S. Department of Agriculture, as originally reported by six of its units: Agricultural Marketing Service, Agricultural Research Service, Bureau of Agricultural Economics, Economic Statistics Service, National Agricultural Statistics Service, and Statistical Reporting Service. For all crops yields have been increasing over time, except for processing cucumber, for which yields seem to have reached a plateau by the end of the 1990s.
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Karabasov, R. A., A. A. Piagay, and R. S. Bespaeva. "Economic efficiency of organic farming in Kazakhstan." Bulletin of "Turan" University, no. 4 (December 25, 2022): 39–49. http://dx.doi.org/10.46914/1562-2959-2022-1-4-39-49.
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In recent years in Kazakhstan, as elsewhere in the world, markedly increased interest in the development of organic agriculture, contributing to the creation of high-margin agricultural production and improve the quality of economic growth in the agricultural sector. The article is aimed at assessing the economic efficiency of agricultural enterprises with organic farming in Kazakhstan. An attempt is made to analyze the viability of organic farms and their contribution to agriculture and the environment. One of the purposes of the article is to analyze whether the latest databases of organic farms and their structure contribute to the achievement of the above objectives. In order to comprehensively assess the economic efficiency, the production base (equity, assets, liabilities) was analyzed. Profit indicator was used in the monitoring of different types of profits and selected financial ratios. Data on organic farms were taken from 2009. Primary data was taken from the materials of farms engaged in organic farming. For comparison, both the database of farms and annual statistical reviews of the Bureau of National Statistics of the Agency for Strategic Planning and Reforms of the Republic of Kazakhstan were used. Taking into account the accumulated experience and new technologies there is an opportunity to reanimate some of the abandoned land into arable land at a safe ecological level. Land with a higher fertility potential can be used for organic farming. To assess the economic and financial situation of agricultural enterprises the following financial ratios were adopted: return on assets, return on equity, liquidity, debt, interest coverage and total asset turnover.
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Zeng, Shaolong, Bingying Qi, and Minglin Wang. "Agricultural Insurance and Agricultural Economic Growth: The Case of Zhejiang Province in China." International Journal of Environmental Research and Public Health 19, no. 20 (October 11, 2022): 13062. http://dx.doi.org/10.3390/ijerph192013062.
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Based on the theories of welfare economics, this paper analyzed the mechanism of agricultural insurance (AI) affecting agricultural economic growth (AEG), theoretically, and carried out an empirical analysis by using the random effects model and thirteen years of panel data, which included the annual data of 11 cities in Zhejiang Province, China, from 2007 to 2019. The gross output value of agriculture, forestry, animal husbandry, and fishery (GOVA) of 11 cities in Zhejiang Province is selected as the explained variable, agricultural insurance premium income (AIPI) as an explanatory variable. We selected area of waterlogging removal (AWR), rural electricity consumption (REC), total power of agricultural machinery (TPAM), and crop-sown area (CSA) as control variables. The study shows that: (1) the AIPI has a significant positive impact on the growth of GOVA. When other conditions remain unchanged, a 1% increase in AIPI increases the GOVA by 0.166%, accordingly; (2) The control variables of REC, TPAM, and CSA are statistically significant for the growth of the GOVA. The elasticity coefficient of REC is 0.325, the elastic coefficient of the TPAM is 0.287, and the elasticity coefficient of CSA is −0.281.
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Carletto, Calogero. "Better data, higher impact: improving agricultural data systems for societal change." European Review of Agricultural Economics 48, no. 4 (July 6, 2021): 719–40. http://dx.doi.org/10.1093/erae/jbab030.
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Abstract The agricultural sector is undergoing a period of rapid transformation, driven by the powerful and interconnected impacts of climate change, demographic transitions and uneven economic growth around the world. For governments and the international community to navigate this period of upheaval to protect vulnerable populations and ensure positive societal change will require a similar degree of transformation within agricultural data systems. While technological innovation has resulted in substantive improvements in the availability, timeliness and overall quality of agricultural data, many technical and institutional challenges remain. This paper reviews recent developments in the agricultural data landscape, highlights existing constraints to further progress and argues for agricultural economists to take responsibility for building agricultural data systems equipped to respond to the diverse needs of a changing world.
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Yang, Ying. "Intelligent Informatization Early Warning Analysis of Agricultural Economy Based on Support Vector Sequential Regression Model." Journal of Mathematics 2021 (November 30, 2021): 1–9. http://dx.doi.org/10.1155/2021/6334444.
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The development of science and technology has laid a solid foundation for the economic informatization of agriculture, and at the same time it brought technical guarantee for the development of agriculture, and the development of agriculture has provided an important material foundation for the development of science and technology. How to identify and deeply study agricultural economic informatization, give early warning to risk information, and ensure the steady development of the whole industry has become a key issue in the application of Internet technology in the field of agricultural development. This paper studies the present situation of agricultural economy informatization development process and applies support vector machine to forecast regional economic development level. The warning limit of agricultural economic growth rate is obtained on the basis of warning situation and warning indicator in early warning index system. The economic early warning model is established based on the support vector sequential regression method, and then the data is trained by MATLAB software to verify the rationality of the early warning model, and the accuracy and corresponding error of the model are given. Experimental results show that the prediction accuracy is 99.3%, the error is less than 0.05, and the prediction effect is relatively ideal, for agricultural economic intelligence information to provide accurate warning and agricultural economic research agricultural commercial development to provide support.
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Neubauer, Sándor. "The place of data in precision agricultural data asset management." Institutiones Administrationis 1, no. 2 (November 17, 2021): 52–61. http://dx.doi.org/10.54201/iajas.v1i2.23.
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Data and information are both key players of the 21st century. Technology is rapidly changing, and the industrial revolution is represented in the field of agriculture as well. Precision farming helps farmers to maximise annual yields and use available data. Due to technological developments and data management, more and more information is available. Precision agriculture manages the variability in production agriculture in a more economic and environmentally efficient manner. It encompasses a suite of farm-level information technologies, monitors the major field crops and annual yields. Precision agriculture can survive only by using the data and information gained.
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Radivojevic, Biljana. "Economic structures of the rural population in Yugoslavia." Stanovnistvo 37, no. 1-4 (1999): 119–39. http://dx.doi.org/10.2298/stnv9904119r.
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The inter-dependence of demographic and economic development both determines and is reflected in the economic structure of the population. Industrialization and the process of deagrarization have strongly influenced the changes in rural population structures. The underdeveloped economy of Yugoslavia before the II World War of mostly agrarian character and underdeveloped industry was characterized by excess labor force in villages and substantial agrarian overpopulation. Preferential treatment of industry during the post-war period, based on the outpouring of savings from agriculture, hindered agricultural activity and created discrepancy in the level or industrial and agricultural development. This led to mass migration of rural population into cities and its engagement in non-agricultural activities. Hence, by changing the structure of the economy, the process of accelerated urbanization also changed the economic structure of the population. The transfer of rural population continued throughout the period following the II World War. It was very intensive during certain periods and far in excess of the natural growth in agricultural population. Abandoning agriculture and migration to cities has had numerous negative effects, particularly because of its immoderate and rapid development. Senilization and feminization of villages practically left them without labor force, while agriculture became a neglected economic activity. Based on the 1981 census, 45.5% of population in non-urban settlements of Yugoslavia were economically active, 4.9% were self-employed, while 49.6% were dependents. The rate of economically active population in these settlements was somewhat higher than for the total urban and non-urban population. The economically active population in non-urban settlements is still most highly concentrated in the agricultural sector, followed by industry and mining. Thus, in 1991, 77.6% of the economically active population of central Serbia were employed in these three sectors (of which 58.1 % in agriculture). The other three sectors with relative importance are construction, transport and communication, and trade. The decline in agricultural population is one of the most significant changes in the social and economic structure of population in Yugoslavia. In the period from 1953 to 1991, it declined by over 3 million persons, while its share in the total decreased almost four times. Based on the 1981 census, 93.9% of total agricultural population of Yugoslavia lived in villages. At the same time, it accounted for 43.9% of population in those settlements. The downward tendency in agricultural population has continued in recent years as is shown by the 1991 census data for territories in which it was fully conducted. With the decline in agricultural population there was also recorded a decline in the number of persons actively engaged in agriculture as well as a decline in their share in the work force of non-?urban settlements_ Based on the 1981 census, almost every second person living in these settlements was an agricultural producer. General rate of economic activity of agricultural population amounted to 59.7% and was higher than the rate for total non-urban population (45.5%) because of higher engagement of border age categories of the economically active population in agricultural activities.
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Harnani, Sri. "Carbon Dioxide and Agricultural Economics in the Sphere of Sustainable Economic Development." Tamansiswa Accounting Journal International 3, no. 1 (October 21, 2021): 4–11. http://dx.doi.org/10.54204/taji/vol312021002.
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This study uses annual time series data with a time period of 1985 to 2020. The data consists of various sources. The data is secondary data collected from the Global Footprint Network, Penn World, and World Bank. This research utilized the following two time-series models for the period from 1985 to 2020 for the following variables. The dependent variable in this study is the ecological footprint and CO2 as an indicator of environmental damage. The independent variables in this study are the human capital index (HC), economic growth (EG), infrastructure (Gx), and natural resource depletion (NR) as indicators of economic activity and environmental changes as a result of economic activity. We found that Indonesia is a country with a large enough open green space, especially on islands outside Java, so it is very important to preserve Indonesia's nature as a supplier of world oxygen. On the other hand, infrastructure development is quite massive in 2019-2021 in Indonesia to encourage economic growth. Therefore, this study examines how Natural Resources Depletion (NR), human capital (HC), Economic Growth (EG), and Infrastructure Investment (GX) affect environmental degradation from the perspective of two important indicators, namely, Ecological footprint (EF) and CO2 from 1985 to 2020. The results of the analysis using the ARDL approach show that in the long term human capital and natural resources have a negative relationship with CO2, while Economic Growth and infrastructure development have a positive relationship with CO2. Based on the ARDL results, it can be concluded that the role of human capital is very important in preserving nature and infrastructure development needs to be carried out while preserving nature or trying to minimize environmental damage
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Groenewald, J. A., and A. Frick. "South African farmers' needs of agricultural data." South African Journal of Economic and Management Sciences 4, no. 2 (June 30, 2001): 316–31. http://dx.doi.org/10.4102/sajems.v4i2.2645.
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Data on agriculture are required by decision-makers, including farmers, to solve problems and make business decisions. The needs of decision-makers have changed over time. Since information systems are designed to aid decisionmakers, their needs should be determined. A mail survey among farmers indicated that they are chiefly interested in information regarding producer prices, prices of field crop inputs and statistics on imports and exports of livestock products. There is also interest in employment data and statistics on economic, institutional and infrastructural matters.
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Wolf, Steven, David Just, and David Zilberman. "Between data and decisions: the organization of agricultural economic information systems." Research Policy 30, no. 1 (January 2001): 121–41. http://dx.doi.org/10.1016/s0048-7333(99)00096-7.
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Evangelista, Jewel Christian, Escalona, James Adriane S., and Pigao, Kevin. "The Correlational Analysis between the Industrial Sector and Agriculture Sector towards Economic Development." Journal of Economics, Finance and Accounting Studies 4, no. 2 (March 23, 2022): 44–54. http://dx.doi.org/10.32996/jefas.2022.4.2.4.
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The Correlational Analysis between the Industrial Sector and Agricultural Sector towards Economic Development. This research aims to determine the current situation of the Construction, Manufacturing and Agriculture industry in the Philippines and the significant relationship of the manufacturing and construction industry towards the agriculture sector. The researchers gathered data from the Philippine Statistics Authority Using the Manufacturing and Construction Industry as the Dependent variable and Agricultural Sector as the independent variable. The researchers used statistical methods and measurements using Pearson correlation and Multiple Regression to determine their results. The Pearson correlation results indicate that there is a strong positive relationship between Manufacturing-Agriculture and Construction-Agriculture Industry. Our findings from the regression analysis suggest that there is a positive effect between the manufacturing industry, construction industry and agricultural sector.
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Li, Bin, and Ni Yang. "Research on Innovative Strategies of Accurate Development Model of Regional Agricultural Economy under Big Data Coordination." E3S Web of Conferences 233 (2021): 01148. http://dx.doi.org/10.1051/e3sconf/202123301148.
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This article will analyze the correlation between big data and regional agricultural economic development on the basis of fully understanding the connotation and characteristics of big data technology. Then, we should use its concept and related technologies and operating models to realize the precise operation guidance of multiple links such as agricultural product planting, selection, planting, farm management, harvesting and storage, and marketing. Through the integration of big data and local advantageous agricultural resources, it is possible to build a fusion and innovation mechanism based on big data, and build an open, intelligent, and intensive precision agriculture development format. This can accelerate the realization of agricultural informatization and modernization, and promote the innovative development of regional agricultural economy.
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Manoppo, Kevin John, Benu Olfie L. S, and Lyndon ,. Pangemanan. "KAJIAN SEKTOR PERTANIAN TERHADAP PEREKONOMIAN DI KABUPATEN MINAHASA UTARA." AGRI-SOSIOEKONOMI 13, no. 3A (November 20, 2017): 15. http://dx.doi.org/10.35791/agrsosek.13.3a.2017.17971.
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This study aims to determine the size of the contribution to the agricultural sector and to determine whether the agricultural sector became the basic sector and any agricultural sub-sector that became the base sector. The data used were collected from Central Bureau of Statistics of North Minahasa District, Central Statistics Agency of North Sulawesi, North Minahasa BAPPEDA. The data is then analyzed by calculating how much the contribution of agriculture sector to the economi of North Minahasa District, LQ, and economic growth rate. The results showed that the contribution of the agricultural sector tends to decrease in the period 2010-2015, but the agricultural sector is still the sector that has the largest contribution in PDRB Kabupaten Minahasa Utara. Average growth rate of agriculture sector during the period of 2010-2015 was amounted to 4.48% the calculation of LQ indicates that the agricultural sector was still the base sector in North Minahasa Regency and agriculture sub-sector which is the base sub-sector was horticulture and the others, annual plantation sector such as the livestock sub sector and fishery sub-sector.
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Figari, Anelise Krauspenhar Pinto, Fabiano Guasti Lima, Rafael Confetti Gatsios, and Vinicius Medeiros Magnani. "Economic Value Drivers for Brazilian Agricultural Cooperatives." Base - Revista de Administração e Contabilidade da Unisinos 18, no. 1 (April 20, 2021): 56–77. http://dx.doi.org/10.4013/base.2021.181.03.
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This article aims to identify the economic value drivers for Brazilian agricultural cooperatives. To this end, we analyzed the potential value drivers for agricultural cooperatives in Paraná and Rio Grande do Sul using panel data regression, considering data from 2008 to 2016. The results showed that net margin, basic purchasing power, investment in fixed assets, circulating assets X sales margin, fixed asset turnover, net revenue, and number of members are the economic value drivers for Brazilian agricultural cooperatives. Moreover, a dynamic panel based on generalized method of moments (GMM) was used to check the robustness of the relationships. With these results, managers and members of agricultural cooperatives can focus their efforts and decisions on maximizing economic value for associated farmers.
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Očić, Vesna, Branka Šakić Bobić, and Mario Njavro. "Economic results of Croatian farms." Applied Studies in Agribusiness and Commerce 10, no. 1 (March 31, 2016): 53–58. http://dx.doi.org/10.19041/apstract/2016/1/7.
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The objective of the paper is to provide an overview of the situation and performance of Croatian farms. Croatian farmers rarely keep business books and therefore farm level business data are deficient. Croatian accession to the European Union in 2013 brought numerous innovations to agricultural sector. One is introduction of Farm Accountancy Data Network (FADN) which aims to determine the impact of the Common Agricultural Policy on national agriculture of EU member states. The sample of Croatian FADN comprises 1,250 commercial farms. The paper brings results of agricultural sector financial analysis for the period 2011-2013. Total farm output decreased, but since the stronger decrease trend occurred in total inputs, this led to positive trend of gross and net farm income in the year 2013. Positive results are also shown at efficiency and productivity of Croatian farms. In the years 2011 and 2012 farms operated below the efficiency level while in 2013 efficiency increased above the efficiency level. In the observed period there was a 70% increase in productivity. The analysis shows that the most efficient farms are those in vegetables and flowers type. It also has the highest debt ratio due to their capital intensiveness. The vegetable and floriculture farms have the largest gross farm income in all three analysed years, but with a large drop in 2013, while the farms in type pigs and poultry have largest increase of gross farm income in last observed year.
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Sira, Elena, and Ryszard Pukala. "Management of agriculture innovations: Role in Economic Development." Marketing and Management of Innovations, no. 2 (2020): 154–66. http://dx.doi.org/10.21272/mmi.2020.2-11.
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Agriculture has a significant economic position in each country, either historically or in terms of importance. Without the products of agriculture, there could be no life. That's the reason to analyze this industry. This industry is now, in the current global world, affected by new trends and new competition on the market. New management, innovations, and other challenges that occurred in this sector. It must face new threats. Especially, significant changes in the global world environment significantly affect this sector. Firstly, through the volume of crop production, respectively non-production due to significant climate changes. Secondly, due to stricter market conditions and its current regulation. Changes in these areas have a significant impact not only on the development in the agricultural sector itself but also on the development of the economy as a whole. Today, competitiveness plays a significant role in the world, as well as in agriculture. This paper summarizes the findings from the area of agriculture, nowadays trends in this sector, innovations. It analyses the competitiveness in this sector, which is characterized by its specific features. Then it summarizes the findings and main thesis about Common Agricultural Policy and its instruments. Another part of this article is dedicated to a very important topic - innovation in agriculture. Agricultural innovation is seen as a co-evolutionary process because it combined technological, social, economic, and institutional changes. The main aim of the article is to identify the impact of agriculture on the economic development of the Slovak Republic economy and to show the possibilities for innovation implementing into this sector. The selected indicators will analyze the description of the position of this sector in the past and today. The typical indicators for the agricultural sector were set. Methodological tools of the research methods were analyzing statistical methods as a regression model, and p-value. Through a regression model, we would like to know what is the dependence of crop and livestock productions on the GDP of agriculture. Finally, improvements to the current state will be suggested. To gain the representative data, more than 20 years of research were set. The object of research is the Slovak republic. The position of agriculture within this country was identified. The article shows the results of verification of dependencies between indicators in the agricultural sector, which showed that statistical significance is assumed, which of course is confirmed both in crop and livestock production. The systematization of domestic and foreign scientific studies and approaches to answering problems in the management of agricultural innovations and the low share of agriculture on GDP makes it possible to create suggestions for the innovative solutions in agriculture in Slovakia. Keywords: agriculture, management, innovation, crop production, livestock production, Slovak Republic.
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Ponomarenko, I., V. Tarasov, A. Ihnatchenko, Yu Khymchenko, and B. Kovalov. "ECONOMIC EFFICIENCY OF DRONE USE IN AGRICULTURE." Vìsnik Sumsʹkogo deržavnogo unìversitetu 2021, no. 4 (2021): 235–40. http://dx.doi.org/10.21272/1817-9215.2021.4-27.
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The article analyzes the market of drones for agricultural activities as part of the concept of precision farming; the classification of agricultural drones by structure, use and cameras installed on them is given; the analysis of the world market of drones for today is carried out, and efficiency of introduction of drones in agriculture (on an example of plant growing) is calculated. To analyze the global market for agricultural drones, data were taken from analytical reports and reviews of companies such as: PricewaterhouseCoopers, Markets and Markets, Mordor Intelligence, Fortune Business Insider. The authors used the following research methods: observation method, index analysis, economic-mathematical modeling and deductive method for drawing conclusions. The study was conducted in several stages. First, the classification of drones by structure, use and type of video cameras was studied. At the second stage, on the basis of analytical reports of reputable international companies analyzed the current state of the agricultural drone market and its capacity; identified the prerequisites for the development of the agricultural drone market and the factors that have the greatest impact on the industry; the forecast on the future possible development of the agricultural drone market is analyzed, and the main market players are identified, indicating the country of origin of the companies. At the third stage, the analysis of the introduction of drone technology in crop production for aerial photography and fertilizer application was carried out. The article develops two possible scenarios of farmer's behavior in relation to agriculture: 1) monitor the condition of fields and crop growth with their own vehicle and apply fertilizers using specialized agricultural machinery; 2) perform similar work using drones. The average tariff for fertilizer application in Ukraine and the average salary of a drone operator were used for the calculation. Drones have been shown to be more cost-effective if they increase crop yields by more than 3.85% over five years of using the technology.
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Muslim, Muhamad Hirzan Hadi, Jamhari Jamhari, and Dwidjono Hadi Darwanto. "Agriculture Category Advantages and Economic Structures in The Region of West Nusa Tenggara Province." Agro Ekonomi 28, no. 1 (June 28, 2017): 64. http://dx.doi.org/10.22146/jae.23854.
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This research aims to identify [1] the highest agricultural category contribution in the West Nusa Tenggara province; [2] basic or non-basic category in current and future; [3] economic structure changes in the agricultural category; [4] classifying agricultural category. This research by a descriptive method. The data analysis by Location Quotient, Dynamic Location Quotient, Shift-Share and Klassen Typology. The results with the highest contribution to the West Nusa Tenggara GRDP is the agriculture category of 23.5%. The highest contribution of an agricultural category to the agricultural category GRDP in West Nusa Tenggara is a Bima Regency of 46.8%. Based on LQ analysis, forestry and logging categories by 2.41% and fisheries category by 1.16% are categorized as a base, and the agriculture category* (agriculture, farming, hunting and agricultural services) is non-base categories of 0.96%. Based on the DLQ analysis, there is a repositioning structure in agriculture category* that Originally non-base 0.96% to a base 1.00%, as for forestry and logging categories and fishery categories remain base. Based on the shift-share analysis, all categories are positive values, the highest category is agriculture category* 1,528,544,064,778.96 (million) influenced by provincial economic growth, industry mix and the influence of competitive advantage. Based on the Klassen Typology analysis, there are two classifications of agriculture category that is the prime classifi cation (forestry and logging category and fishery category) and potential classifi cation (agriculture category*).
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Upendra, R. S., I. M. Umesh, R. B. Ravi Varma, and B. Basavaprasad. "Technology in Indian agriculture - a review." Indonesian Journal of Electrical Engineering and Computer Science 20, no. 2 (November 1, 2020): 1070. http://dx.doi.org/10.11591/ijeecs.v20.i2.pp1070-1077.
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Optimization of agricultural practices for enhanced crop yield is considered to be essential phenomena for the countries like India. In order to strengthen the economy and also to meet the food demand for the exponentially growing population, optimizing the agricultural practices has become necessity. In India, weather and geographical conditions are highly variable and were thought to be the major bottleneck of agricultural practices to achieve improved crop yield. Agricultural practices in India are facing many challenges such as change in climatic conditions, different geographical environment, conventional agricultural practices; economic and political scenario. Economic loss due to the lack of information on crop yield productivity is another major concern in the country. These hurdles can be overcome by the implementation of advanced technology in agriculture. Some of the trends observed are smart farming, digital agriculture and Big Data Analytics which provide useful information regarding various crop yields influencing factors and predicting the accurate amounts of crop yield. The exact prediction of crop yield helps formers to develop a suitable cultivation plan, crop health monitoring system, management of crop yield efficiently and also to establish the business strategy in order to decrease economic losses. This also makes the agricultural practices as one of the highly profitable venture. This paper presents insights on the various applications of technology advancements in agriculture such as Digital Agriculture, Smart Farming or Internet of Agriculture Technology (IoAT), Precision Agriculture, Crop Management, Weed and Pest control, Crop protection and Big data analytics.
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Umehruo, C. H., O. A. Owolabi, B. Aderounmu, M. O. Rotimi, and E. S. Osabuohien. "Environmentally sustainable socio-economic welfare and agricultural employment: evidence from ECOWAS." IOP Conference Series: Earth and Environmental Science 993, no. 1 (March 1, 2022): 012006. http://dx.doi.org/10.1088/1755-1315/993/1/012006.
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Abstract Environmental sustainability considerations in socio-economic welfare has been argued in recent welfare literature. With an emphasis on the role of agricultural employment, this present study explores environmentally sustainable socio-economic welfare in ECOWAS, which features countries abundant in agriculture resources, although with low levels of socio-economic welfare and low carbon emissions. The study utilises a balanced panel data set of observations in respect of all fifteen ECOWAS countries over the period of 2010 to 2019. The Human Sustainable Development Index (HSDI) was used to measure environmentally sustainable socio-economic welfare. On the other hand, agricultural employment was measured using the percentage of the employed population earning their livelihoods from agricultural employment. Panel data fixed effects estimation was used to estimate the model for the study, and the findings were that agricultural employment had a significant adverse influence on environmentally sustainable socio-economic welfare as measured by HSDI, while a further comparison of the findings with that of welfare measured using HDI indicated that agricultural employment also adversely affected HDI. The study recommends that socio-economic welfare be assessed from the view point of environmental sustainability, and the governments of ECOWAS member countries provide strong governance including strong laws and policies to ensure that socio-economic welfare that is environmentally sustainable is realised as abundant agricultural resources as well as agricultural employment are well managed.
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Xiao, Jing, Wenlan Wang, and Sang-Bing Tsai. "Coupling of Agricultural Product Marketing and Agricultural Economic Development Based on Big Data Analysis and “Internet+”." Mobile Information Systems 2021 (October 18, 2021): 1–10. http://dx.doi.org/10.1155/2021/3702064.
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In the era of “Internet+,” the increase of agricultural products sales can be achieved by creating and joining e-commerce platforms. Most of the farmers in China are self-employed and cannot form an industrial scale. With the rise of “Internet+” background research, the combination of this technology and the marketing of agricultural products has become a new marketing model under the deep integration of different fields. Based on the marketing of products under the background of “Internet+” and using marketing theories, this paper reviews the development of marketing of agricultural products under the background of “Internet+,” including the Internet infrastructure, the establishment of logistics system, the formation of branding, and the deep processing of agricultural products. The paper reviews the development of agricultural marketing under the background of “Internet+,” including the Internet infrastructure, establishment of logistics system, branding, and deep processing of agricultural products. The marketing mode of agricultural products under the background of “Internet+” is proved, and the development of agricultural products marketing under the background of “Internet+” is discussed from various angles, and insights into how to improve it are proposed from five aspects. After excluding the influence of environmental factors through the improved three-stage SE-DEA model, the mean value of TE of comprehensive efficiency of agricultural information allocation increases from 0.773 to 0.832, the mean value of SE of scale efficiency increases from 0.844 to 0.9219, and the mean value of PTE of pure technical efficiency adjusts from 0.9087 to 0.9058. The mean value of pure technical efficiency (PTE) was adjusted from 0.9087 to 0.9058. Compared with the parametric method, DEA does not require a specific production function to be set in advance, and it is also difficult to select a suitable production function in advance for complex problems.
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Sun, Yu, Zhe Zhao, and Mingquan Li. "Coordination of agricultural informatization and agricultural economy development: A panel data analysis from Shandong Province, China." PLOS ONE 17, no. 9 (September 16, 2022): e0273110. http://dx.doi.org/10.1371/journal.pone.0273110.
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With the continuous development of the world economy, science, and technology, the era of intelligence and information is upon us. Through the implementation of the digital rural construction project in China, agriculture is developing rapidly in the direction of informatization. As a major agricultural province in China, Shandong Province has been ranked first in China for many years in terms of gross agricultural product and the import and export of agricultural products. According to the current situation of agricultural informatization in Shandong Province, this study uses relevant evaluation index data of Shandong Province from 2011 to 2019 and applies the entropy value method, coupling degree analysis model, and coupling coordination degree analysis model to deeply evaluate the mutual influence and coordination degree between the agricultural informatization level and agricultural economic development in Shandong province in each year. We identify the possible problems in the development of agricultural informatization in Shandong province. Finally, in terms of talent construction, infrastructure construction, the main role of government, policies, and farmers’ awareness of informatization, we propose some countermeasures and suggestions that are conducive to the coordinated development of agricultural informatization and the agricultural economy.
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Stepnykh, N. V., S. D. Gilev, E. V. Nesterova, A. M. Zargaryan, and S. A. Kopylova. "Assessment of the effectiveness of agricultural technologies based on production data." BIO Web of Conferences 36 (2021): 08009. http://dx.doi.org/10.1051/bioconf/20213608009.
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Modern agriculture is characterized by a variety of technologies associated with a multivariance of means of production. Due to the fact that the forces of scientific organizations do not allow to study most of the innovations in agriculture, the analysis of the effectiveness of technologies is possible directly in agricultural enterprises, where a large amount of agronomic and economic information obtained in the specific conditions of the introduction of agricultural practices is accumulated. The purpose of the study was to analyze the effectiveness of modern technologies for growing grain crops according to accounting and agronomic reports of agricultural enterprises of the Kurgan region. The methods of monographic, mathematical, and statistical analysis of data from literary sources, annual reports of agricultural enterprises of the region, as well as data from production fields of the Kurgan Research Institute of Agricultural Sciences were used. The results of the study showed the possibility of obtaining high results in crop production due to different methods of tillage (with and without surface tillage), the use of optimal doses of fertilizers. The reserves of profitability growth are associated with a more accurate use of resources, which is possible when considering the data of each field, thanks to the maintenance of electronic books of the field history, as a variant of a digital management tool in crop production.
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Oyewale Peter Oluwaseun. "The Role of Agriculture in the Economic Development of Idofin-Igbanna, Kwara State Nigeria." Economit Journal: Scientific Journal of Accountancy, Management and Finance 2, no. 3 (January 4, 2023): 274–82. http://dx.doi.org/10.33258/economit.v2i3.819.
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The study focus on the role of agriculture in the economic development of Idofin-Igbanna, agriculture remains one the major economic activities of Idofin, agriculture as an engine of growth and poverty reduction, because it assured food security. This paper however, focuses on the development of agriculture, the gender role in agricultural activities, it also attempts the role and impact of government in the prospect agricultural economy of Idofin-Igbanna. The paper obtained it's data from both primary and secondary sources which are made up of oral interview, books, journal articles, newspaper reports and government publications relevant to the topic.