Artykuły w czasopismach: „AGRICULTURAL DATABASE”

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Bunin, M. S., I. A. Kolenchenko i L. N. Pirumova. "Digital agriculture informational resources in local and international databases". Dokuchaev Soil Bulletin, nr 108 (19.10.2021): 157–74. http://dx.doi.org/10.19047/0136-1694-2021-108-157-174.

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The article reviews informational resources on precision and digital agriculture in international cross-disciplinal and sectoral international and local databases. The databases Web of Science, Scopus, AGRIS (by FAO UN) and Engineering infrastructure of Agriculture, Rosinformagrotech, AGROS (by Central Scientific Agricultural Library) with the retrieval requests “Digital agriculture”, “Precision Agriculture” were analyzed. The authors estimated the dynamics of document flows to the AGROS database and confirmed strong growth of volume of local publications on precision agriculture to the level demonstrating technology adoption of precision agriculture. Meanwhile the level of document flow on digital agriculture is at the starting level. Analysis of most frequent publications on the topic showed that there’s no local specialized journals on precision agriculture, most frequently publications appeared in local journals such as “Machinery and equipment for rural areas”, “Soil science and agrochemistry”, “Agricultural machinery and technology”. Predominantly materials were published in specialized foreign journals “Computers and electronics in agriculture” and “Precision agriculture”. Most of the documents were obtained from WOS and Scopus databases, but a lot of them are irrelevant. While searching for foreign documents it makes sense to use all the databases available, but most of the full-size texts in open access are available in the AGRIS database. In the same way AGROS database provide a wide range of full-size texts in the Russian language. Both AGROS and AGRIS databases showed high efficiency of search with most relevant documents in search results since both databases use thesaurus as a linguistic tool.

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Goertzen, Melissa. "Multidisciplinary Databases Outperform Specialized and Comprehensive Databases for Agricultural Literature Coverage". Evidence Based Library and Information Practice 14, nr 2 (13.06.2019): 140–42. http://dx.doi.org/10.18438/eblip29561.

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A Review of: Ritchie, S. M., Young, L. M., & Sigman, J. (2018). A comparison of selected bibliographic database subject overlap for agricultural information. Issues in Science and Technology Librarianship, 89. http://doi.org/10.5062/F49Z9340 Abstract Objective – To determine the most comprehensive database(s) for agricultural literature searching. Design – Data collection and analysis was conducted using a modified version of the bibliography method, overlap analysis, chi square tests, and data visualization methods. Setting – An academic library in the U.S. Subjects – Eight commonly used bibliographic databases, including comprehensive agricultural indexes (AGRICOLA, AGRIS, and CAB Abstracts), specialized databases (BIOSIS Previews and FSTA), and multidisciplinary databases (Google Scholar, Scopus, and Web of Science). Methods – The researchers selected three review articles that represented sub-topics within the field of agriculture. Sources listed in the bibliographies of the three review articles were used to build a bibliographic citation set for analysis. Using a modified version of the bibliography method, 90 citations were randomly selected from the above-mentioned citation set. Researchers then turned to the 8 selected databases and searched for all 90 citations in each platform. Search queries were crafted in two ways: unique title strings in quotation marks and combinations of terms entered into the “title”, “keyword”, “journal source”, and “author” fields. Citations were considered to be covered in a database if the full bibliographic record was located using the above-mentioned search strategy. Next, chi square tests were used to evaluate if the expected number of citations from the sample group were found in each database or if the frequency differed between the eight databases. The overlap analysis method provided numerical representation of the degree of similarity and difference across the eight databases. Finally, data visualizations created in Excel and Gephi enhanced comparisons between the eight databases and highlighted differences that were not obvious based solely on the analysis of numerical data. Main Results – Researchers found that comprehensive databases (AGRICOLA, AGRIS, and CAB Abstracts) were not in fact comprehensive in their coverage of agricultural literature. However, the results suggested that CAB Abstracts was more comprehensive than AGRICOLA or AGRIS, particularly in regard to its coverage of the sub-topics “agronomy” and “meat sciences”. However, coverage of the sub-topic “sustainable diets” lagged behind multidisciplinary databases, which may be explained by the fact that the topic is interdisciplinary in nature. The superior coverage of CAB Abstracts over other comprehensive databases is consistent with findings reported by Kawasaki (2004). The analysis of specialized databases (BIOSIS Previews and FSTA) suggested that citations within the scope of the database were covered very well, while those out of scope were not. For instance, the sub-topics “sustainable diets” and “meat science” are out of scope of the biological sciences and thus, were not well covered in BIOSIS. The multidisciplinary databases (Google Scholar, Scopus and Web of Science) provided the most comprehensive coverage agricultural literature. All three databases covered most citations included in the data set. However, researchers noted that all three databases provided weak coverage of trade published items, books, or older journals. Conclusion – The study found that multidisciplinary databases provide close to full coverage of agricultural literature. In addition, they provide the best access to content that is interdisciplinary in nature. Specialized and comprehensive databases are recommended when research topics are within the scope of the database. Also, they best support in-depth projects such as bibliographies or comprehensive review articles.

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McKean, John R., R. Garth Taylor i Wen Lin Liu. "Inadequate agricultural database for American Indians?" Society & Natural Resources 8, nr 4 (lipiec 1995): 361–66. http://dx.doi.org/10.1080/08941929509380928.

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Ngwira, Margaret. "Developing an agricultural database in Malawi". Information Development 7, nr 2 (kwiecień 1991): 89–92. http://dx.doi.org/10.1177/026666699100700207.

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Afxentiou, Nicolas, Phoebe-Zoe Morsink Georgali, Angeliki Kylili i Paris A. Fokaides. "Greenhouse agricultural plastic waste mapping database". Data in Brief 34 (luty 2021): 106622. http://dx.doi.org/10.1016/j.dib.2020.106622.

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Romaschenko, M. I., V. P. Kovalchuk, Y. O. Tarariko, Y. V. Soroka, A. V. Krucheniuk i O. S. Demchuk. "Information management system for agricultural production on the Internet". Міжвідомчий тематичний науковий збірник "Меліорація і водне господарство" 104, nr 2 (27.11.2016): 87–92. http://dx.doi.org/10.31073/mivg201602-64.

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The analysis of information support in the agricultural production has been done. IWPLR is developing now a «System of information support for agriculture», which has a two-level structure of decision-making and contains a database. At the level of «economy» the system, taking into account both the economic priorities and the wishes of the farms as well as soil-climatic and environmental constraints helps the agricultural producers (the users of the system) to define a set of priority crops using a subsystem «crop rotation». At the level of «field» the system, using the database helps the users to calculate the flow process charts for identified priority crops. The database of the system consists of five sections: «agriculture», «agri-resource potential» «reclamation», «mechanization and processing», «animal production» and provides some background information for agricultural producers.

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Wang, Shu Rong, Jin Song Zhao i Song Ze Lei. "The Research on the Intelligent Control of Geographic Information System Design to Agricultural Production". Advanced Materials Research 605-607 (grudzień 2012): 1705–9. http://dx.doi.org/10.4028/www.scientific.net/amr.605-607.1705.

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Agricultural geographic information system could use the agriculture information database, agricultural resources dynamic monitoring, agricultural management, analysis and decision support, "precision agriculture" demonstration, realizes the intelligent control of agricultural production management, could realize rapid investigation and monitoring in each link of agricultural production, timely diagnosis and analysis, high decision-making and management, thus promoting agricultural modernization.

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Sanches, I. D., R. Q. Feitosa, B. Montibeller, P. M. Achanccaray Diaz, A. J. B. Luiz, M. D. Soares, V. H. R. Prudente i in. "FIRST RESULTS OF THE LEM BENCHMARK DATABASE FOR AGRICULTURAL APPLICATIONS". ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLIII-B5-2020 (24.08.2020): 251–56. http://dx.doi.org/10.5194/isprs-archives-xliii-b5-2020-251-2020.

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Abstract. Applying remote sensing technology to map and monitor agriculture and its impacts can greatly contribute for the proper development of this activity, promoting efficient food, fiber and energy production. For that, not only remote sensing images are needed, but also ground truth information, which is a key factor for the development and improvement of methodologies using remote sensing data. While a variety of images are current available, inclusive cost-free images, field reference data is scarcer. For agricultural applications, especially in tropical regions such as Brazil, where the agriculture is very dynamic and diverse (recent agricultural frontiers, crop rotations, multiple cropping systems, several management practices, etc.), and cultivated over a vast territory, this task is not trivial. One way of boosting the researches in agricultural remote sensing is to stimulate people to share their data, and to foster different groups to use the same dataset, so distinct methods can be properly compared. In this context, our group created the LEM Benchmark Database (a project funded by the ISPRS Scientific Initiative project - 2017) from the Luiz Eduardo Magalhães (LEM) municipality, Bahia State, Brazil. The database contains a set of pre-processed multitemporal satellite images (Landsat-8/OLI, Sentinel-2/MSI and SAR band-C Sentinel-1) and shapefiles of agricultural fields with their correspondent monthly land use classes, covering the period of one Brazilian crop year (2017–2018). In this paper we present the first results obtained with this database.

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Li, Haizhou, François Pinet i Farouk Toumani. "Towards The Use of Probabilistic Spatial Relation Databases in Business Process Modeling". International Journal of Agricultural and Environmental Information Systems 6, nr 3 (lipiec 2015): 50–62. http://dx.doi.org/10.4018/ijaeis.2015070104.

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In this paper, the authors combine the methods of probabilistic databases, GIS (Geographical Information Systems) and business process modelling to evaluate the agricultural activities. The authors provide a technique to evaluate the risk of agricultural activities among the hydrological objects (lakes, rivers, etc.) and agricultural plots. The spatial relation is an important information needed in the evaluation processes. This type of information is usually uncertain and the available data are often not precise. Consequently, probabilistic database is used to capture the uncertainty of the spatial objects in order to estimate the level of possible water and soil contamination (by agricultural inputs). Probabilistic spatial relations provide information on the layout of spatial objects. Probabilities are stored in a probabilistic database. Probabilistic database is a finite number of complete databases that are assigned with a set of probabilities. Probabilistic data-aware business processes integrate the theory of probabilistic database with business processes modeling methods. This new formalism of business processes helps the experts to model the environmental risks in terms of probabilistic spatial relations.

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Mohd Nizar, Nur Marahaini, Ebrahim Jahanshiri, Anil Shekar Tharmandram, Ayman Salama, Siti Sarah Mohd Sinin, Nurul Jannah Abdullah, Husna Zolkepli i in. "Underutilised crops database for supporting agricultural diversification". Computers and Electronics in Agriculture 180 (styczeń 2021): 105920. http://dx.doi.org/10.1016/j.compag.2020.105920.

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Pavlova, A. I., i V. K. Kalichkin. "DATABASE FOR AGROECOLOGICAL ASSESSMENT OF AGRICULTURAL LAND". Siberian Herald of Agricultural Science 48, nr 1 (4.04.2018): 80–88. http://dx.doi.org/10.26898/0370-8799-2018-1-11.

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Hyman, Glenn, Herlin Espinosa, Paola Camargo, David Abreu, Medha Devare, Elizabeth Arnaud, Cheryl Porter, Leroy Mwanzia, Kai Sonder i Sibiry Traore. "Improving agricultural knowledge management: The AgTrials experience". F1000Research 6 (24.03.2017): 317. http://dx.doi.org/10.12688/f1000research.11179.1.

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Background: Opportunities to use data and information to address challenges in international agricultural research and development are expanding rapidly. The use of agricultural trial and evaluation data has enormous potential to improve crops and management practices. However, for a number of reasons, this potential has yet to be realized. This paper reports on the experience of the AgTrials initiative, an effort to build an online database of agricultural trials applying principles of interoperability and open access. Methods: Our analysis evaluates what worked and what did not work in the development of the AgTrials information resource. We analyzed data on our users and their interaction with the platform. We also surveyed our users to gauge their perceptions of the utility of the online database. Results: The study revealed barriers to participation and impediments to interaction, opportunities for improving agricultural knowledge management and a large potential for the use of trial and evaluation data. Conclusions: Technical and logistical mechanisms for developing interoperable online databases are well advanced. More effort will be needed to advance organizational and institutional work for these types of databases to realize their potential.

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Hyman, Glenn, Herlin Espinosa, Paola Camargo, David Abreu, Medha Devare, Elizabeth Arnaud, Cheryl Porter, Leroy Mwanzia, Kai Sonder i Sibiry Traore. "Improving agricultural knowledge management: The AgTrials experience". F1000Research 6 (9.10.2017): 317. http://dx.doi.org/10.12688/f1000research.11179.2.

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Background: Opportunities to use data and information to address challenges in international agricultural research and development are expanding rapidly. The use of agricultural trial and evaluation data has enormous potential to improve crops and management practices. However, for a number of reasons, this potential has yet to be realized. This paper reports on the experience of the AgTrials initiative, an effort to build an online database of agricultural trials applying principles of interoperability and open access. Methods: Our analysis evaluates what worked and what did not work in the development of the AgTrials information resource. We analyzed data on our users and their interaction with the platform. We also surveyed our users to gauge their perceptions of the utility of the online database. Results: The study revealed barriers to participation and impediments to interaction, opportunities for improving agricultural knowledge management and a large potential for the use of trial and evaluation data. Conclusions: Technical and logistical mechanisms for developing interoperable online databases are well advanced. More effort will be needed to advance organizational and institutional work for these types of databases to realize their potential.

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Pashkov, Sergey V., i Gulnur Z. Mazhitova. "DEVELOPING GEOINFORMATION SUPPORT FOR AGRICULTURAL LANDSCAPE DESIGN AT AN AGRICULTURAL ENTERPRISE". Географический вестник = Geographical bulletin, nr 4(63) (2022): 167–79. http://dx.doi.org/10.17072/2079-7877-2022-4-167-179.

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In the paper, we discuss application of geoinformation systems in agriculture and their advantages in studying and mapping agricultural landscapes. We analyzed geoinformation support at agricultural enterprises in the Republic of Kazakhstan and its regions. The paper presents methodology for the development of GIS technologies to be applied at an agricultural enterprise. The study was conducted for the North Kazakhstan Agricultural Experimental Station LLP, which is a farm located in the North Kazakhstan Region. The GIS was developed based on the application of systemic and integrated approaches to agricultural landscape research and mapping. The GIS creation included several stages: determining the structure and content of the GIS; designing the GIS model; collecting, scanning, converting, and processing the data; developing a digital map base and a database; inputting information into the system. We created a digital map base and a database including information about the natural conditions and agricultural activities of the farm. The GIS developed by us can be used for production tasks; for performing spatial analysis of farmland; evaluating the effectiveness of agricultural technologies used; modeling, designing, and managing agricultural production; for predictive analytics based on an array of high-quality agro-information.

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Krechetnikovа, Evgeniya, Viktor Krechetnikov, Igor Titov i Vladimir Kuznetsov. "Database of the results of radioecological monitoring of contaminated agricultural lands of the Tula NIISH". Geoinformatika, nr 2 (6.07.2021): 53–58. http://dx.doi.org/10.47148/1609-364x-2021-2-53-58.

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For the radioactively contaminated territory of the Tula Research Institute of Agriculture, a database has been created for storing spatially oriented information. The created database contains information about the location of agricultural areas; crop rotation structure; distribution of values of specific activity of 137Cs on agricultural lands; agrochemical indicators of soils of agricultural territories (content of humus, potassium, phosphorus, acidity); soil types; relief. It also contains a calculation module for assessing the content of 137Cs in crop and livestock products. The accumulated data array will be used for designing adaptive landscape farming systems using information on the 137Cs content in the soil generalized over a long-term period.

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Oda, Masato. "Interface System between Climate-Database and Agricultural Researcher". Agricultural Information Research 3, nr 2 (1994): 97–107. http://dx.doi.org/10.3173/air.3.97.

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Eremina, I. G., i N. V. Kutkina. "Database of agricultural soils of the Western Sayan". IOP Conference Series: Earth and Environmental Science 862, nr 1 (1.10.2021): 012004. http://dx.doi.org/10.1088/1755-1315/862/1/012004.

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&NA;. "Flavonoid Database Started by USDAʼs Agricultural Research Service". Nutrition Today 38, nr 3 (maj 2003): 90. http://dx.doi.org/10.1097/00017285-200305000-00007.

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Johnston, R. M., S. J. Barry, E. Bleys, E. N. Bui, C. J. Moran, D. A. P. Simon, P. Carlile i in. "ASRIS: the database". Soil Research 41, nr 6 (2003): 1021. http://dx.doi.org/10.1071/sr02033.

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The Australian Soil Resources Information System (ASRIS) database compiles the best publicly available information available across Commonwealth, State, and Territory agencies into a national database of soil profile data, digital soil and land resources maps, and climate, terrain, and lithology datasets. These datasets are described in detail in this paper. Most datasets are thematic grids that cover the intensively used agricultural zones in Australia.

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Syp, Alina. "Emisje gazów cieplarnianych z rolnictwa w latach 1990-2014". Zeszyty Naukowe SGGW w Warszawie - Problemy Rolnictwa Światowego 17(32), nr 2 (30.06.2017): 244–55. http://dx.doi.org/10.22630/prs.2017.17.2.43.

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Agriculture is the second, after energy sector, emitter of greenhouse gasses (GHG), of which increased concentrations in the atmosphere are caused by human activities. In order to reduce GHG, parties ratifying the Kioto protocol have committed to prepare annual emission reports and pledged to reduce emissions. The aim of the study was to analyse changes of agricultural emissions in the World, the European Union (EU) and Poland in 1990-2014. The research uses the United Nations Food and Agricultural database (FAOSTAT), United Nations Framework Convention on Climate Chang (UNFCCC) and World Resources Institute (CAIT) databases. The analysis shows that in the World, in the examined period the total GHG emissions increased by 85%, whereas in agriculture by 15%. However, the EU as a member of Annex I parties had reduced total and agricultural emissions by 24% and 23%, respectively. The reduction of emissions was the result of the implementation of pro-environmental regulations.

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Thornton, P. K. "ISNAR Agricultural Research Indicator Series: A Global Database on National Agricultural Research Systems". Agricultural Systems 35, nr 2 (styczeń 1991): 229–30. http://dx.doi.org/10.1016/0308-521x(91)90088-r.

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Baráth, Lajos, i Imre Fertő. "Accounting for TFP Growth in Global Agriculture - a Common-Factor-Approach-Based TFP Estimation". Agris on-line Papers in Economics and Informatics 12, nr 4 (30.12.2020): 3–13. http://dx.doi.org/10.7160/aol.2020.120401.

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There is no consensus about trends in agricultural productivity among agricultural economists. The aim of this paper is to contribute to the investigation of this issue by estimating a Total Factor Productivity (TFP) index for global agriculture and global agricultural regions. One of the biggest challenges with analysing global productivity trends is the lack of price data or cost shares, especially in developing countries. We apply recently introduced econometric models that permit accounting for technology heterogeneity and the time-series properties of data to estimate cost shares. Aggregate sectoral data from the USDA ERS database are investigated for the period 1990 to 2013. Although we used a different method, our results are in line with earlier findings that used USDA or FAO database. TFP growth has accelerated in world agriculture, largely due to better performance in transition countries. Although TFP growth has accelerated in world agriculture, it has slowed down in industrialized countries. TFP growth in the EU has increased, but at slower rate in recent years. In the Old Member States the growth rate has decreased, whereas in the New Member States it has increased. The results highlight that insufficient spending on productivity-enhancing agricultural R&D in industrialized countries may put future agricultural productivity growth at risk.

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Zhao, Yongzhi, i Yangfen Chen. "Global Patterns of Agricultural Investment and Food Security: Evidence from the fDi Markets Database". Foods 12, nr 9 (28.04.2023): 1827. http://dx.doi.org/10.3390/foods12091827.

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The number of hungry people is on the rise and more efforts are needed to improve the global food security status. The Food and Agriculture Organization (FAO) proposes more investment in the agricultural sector to boost production and alleviate hunger. However, there are fewer papers that distinguish enterprises investment from public investment. In this case, we take advantage of detailed investment data in the fDi Markets database to explore the global patterns of agricultural investment. In particular, we identify the top destination countries based on aggregate and sub-sectoral agricultural investment data. Then we investigate the relationship between agricultural investment and food security, which is measured by per capita protein intake. Finally, we propose some suggestions from the investment motivation perspective to help food-insecure countries to attract overseas investment. We find that developed countries are the primary sources of global agricultural investment and these sources have been becoming more diverse in the past decade. It implies the trend towards a more inclusive investment environment worldwide. However, the global distribution of agricultural investment is uneven as food-insecure countries only receive 20% of the global agricultural investment. The top three destination countries, USA, China, and Russia, have a relatively high food security level. In contrast, countries suffering from food insecurity receive fewer investment projects, and most of which are on a small scale. Given the limited socio–economic development status in food-insecure countries, it is essential for all levels of society to help them and contribute to ending hunger.

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Vopravil, J., V. Podrázský, M. Batysta, P. Novák, L. Havelková i M. Hrabalíková. "Identification of agricultural soils suitable for afforestation in the Czech Republic using a soil database". Journal of Forest Science 61, No. 4 (3.06.2016): 141–47. http://dx.doi.org/10.17221/123/2014-jfs.

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Afforestation of agricultural lands may be a positive action in many cases. Especially, it is a beneficial feature for waterlogged soils, stony soils or for soils which are less fertile for any other reason and thus unsuitable for farming. Afforestation can be a very important action even in the agricultural landscape – afforested belts of agricultural land divide large farm blocks into smaller ones, or act as windbreakers and biological corridors. The value, quality and fertility of soil can be assessed in different ways. The study aims to determine the identification soil criteria of agricultural land which is suitable for afforestation. This evaluation process is based on Evaluated Soil Ecological Units (ESEU), in the Czech Republic known as BPEJ, database which is available for all agricultural land in the Czech Republic. The results are represented by a complete list of ESEU codes suitable for afforestation. The list of codes is supplemented by an explanation why such an ESEU code, representing a soil group with similar properties, is suitable to afforestation.

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Kolesnik, O. A., P. M. Demidova i A. P. Sannikova. "Creation of a geospatial database of particularly valuable productive agricultural land taking into account geodetic data in order to provide land monitoring". Vestnik SSUGT (Siberian State University of Geosystems and Technologies) 27, nr 6 (2022): 39–48. http://dx.doi.org/10.33764/2411-1759-2022-27-6-39-48.

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A geospatial database is the best way to systematize and present attributive and spatial data. Currently, there is no single geospatial database of particularly valuable agricultural land for the entire territory of the country. Most of the land plots belonging to such lands have not yet been registered in the Unified State Register of Real Estate or do not have the coordinates of the borders and, respectively, are not marked on the Public Cadastral Map. Monitoring of such lands is not carried out properly, there is no information about the composition and quality of such lands. But the primary issue when creating a geospatial database is the source data – the basis of the object's coordinate reference. The article ana-lyzes the normative legal acts on the research topic, provides an overview of geoinformation systems and geoinformation resources in the field of agriculture and for comparison in the field of forestry. The creation of a geospatial database of especially valuable agricultural lands is considered on the example of the Volosovsky district of the Leningrad region. The insufficiency (incompleteness) of the coordinated boundaries of the lands was noted. The geospatial database of especially valuable agricultural lands will allow you to have a complete picture of the quantity, area, composition, condition and use of especially valuable agricultural lands, for which it is important to keep records and monitor in order to preserve, protect and develop them.

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Mohan, Geetha, Hirotaka Matsuda, Samuel A. Donkoh, Victor Lolig i Gideon Danso Abbeam. "Effects of Research and Development Expenditure and Climate Variability on Agricultural Productivity Growth in Ghana". Journal of Disaster Research 9, nr 4 (1.08.2014): 443–51. http://dx.doi.org/10.20965/jdr.2014.p0443.

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This paper examines the effects of agricultural research expenditure and climate change on agricultural productivity growth by region in Ghana. A panel dataset is constructed for 2000-2009 from the Food and Agriculture Organization of the United Nations; the Ministry of Food and Agriculture, Ghana; and the Agriculture Science and Technology Indicators (ASTI) database of the International Food Policy Research Institute. A Malmquist index was used to compute agricultural productivity growth, including decomposition components efficiency change and technical change. The determinants of productivity growth are examined using a fixed effects regression model. The results specify that significant causal factors impact positively on Ghana’s agricultural productivity growth, include climate variability, infrastructure, and agricultural research and development expenditure. The study confirms there is a need to strengthen and develop new technological progress for sustainable agricultural production in Ghana.

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Shen, Yao. "Construction of a Wireless Sensing Network System for Leisure Agriculture for Cloud-Based Agricultural Internet of Things". Journal of Sensors 2021 (13.11.2021): 1–11. http://dx.doi.org/10.1155/2021/3021771.

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This paper provides an in-depth study and analysis of the construction of a cloud-based agricultural Internet of Things system for a wireless sensing network system for leisure agriculture. Using more mature agricultural sensor technology, compliant economy designed for indoor feeding and planting of distributed and integrated two sensor collection and transmission scheme, analysis of environmental factors selected high-performance various types of sensors and regulation equipment, between nodes based on SI4432 for wireless communication, and controller nodes selected STM32 as a microprocessor, through the W5500-based network port access module or ESP8266-based WiFi module for broadband access. In response to the development of mobile technology and the reality of diversified types of mobile terminals, to make all kinds of terminals accessible to the leisure agriculture system, the server software adopts the SOA software architecture, which makes the system have good openness and scalability. The NoSQL database MongoDB is used for the cloud storage of massive data, and the data structure design is completed after analyzing the database requirements, including collections, documents, and fields. The autosharding technology is used to build a database sharding cluster in the cloud, which realizes the high-speed cloud elastic storage of massive data and rewrites the database access object DAO to ensure that the WEB application is normal. Traditional leisure agriculture is mostly based on field tourism and agritourism methods, and the model is developing slowly and has increasingly failed to attract the interest of urban residents. The introduction of IoT technology in traditional leisure agriculture can increase the interest of leisure agriculture and improve the interest of urban residents in leisure agriculture.

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Sanches, I. D., R. Q. Feitosa, P. Achanccaray, B. Montibeller, A. J. B. Luiz, M. D. Soares, V. H. R. Prudente, D. C. Vieira i L. E. P. Maurano. "LEM BENCHMARK DATABASE FOR TROPICAL AGRICULTURAL REMOTE SENSING APPLICATION". ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-1 (26.09.2018): 387–92. http://dx.doi.org/10.5194/isprs-archives-xlii-1-387-2018.

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<p><strong>Abstract.</strong> The monitoring of agricultural activities at a regular basis is crucial to assure that the food production meets the world population demands, which is increasing yearly. Such information can be derived from remote sensing data. In spite of topic’s relevance, not enough efforts have been invested to exploit modern pattern recognition and machine learning methods for agricultural land-cover mapping from multi-temporal, multi-sensor earth observation data. Furthermore, only a small proportion of the works published on this topic relates to tropical/subtropical regions, where crop dynamics is more complicated and difficult to model than in temperate regions. A major hindrance has been the lack of accurate public databases for the comparison of different classification methods. In this context, the aim of the present paper is to share a multi-temporal and multi-sensor benchmark database that can be used by the remote sensing community for agricultural land-cover mapping. Information about crops in situ was collected in Luís Eduardo Magalhães (LEM) municipality, which is an important Brazilian agricultural area, to create field reference data including information about first and second crop harvests. Moreover, a series of remote sensing images was acquired and pre-processed, from both active and passive orbital sensors (Sentinel-1, Sentinel-2/MSI, Landsat-8/OLI), correspondent to the LEM area, along the development of the main annual crops. In this paper, we describe the LEM database (crop field boundaries, land use reference data and pre-processed images) and present the results of an experiment conducted using the Sentinel-1 and Sentinel-2 data.</p>

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Matsuyama, Hidekazu, i Teruya Yamada. "Development of Hokkaido Agricultural Statistic Database with "Excel VBA"". Agricultural Information Research 7, nr 2 (1998): 81–95. http://dx.doi.org/10.3173/air.7.81.

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Kim, ChangKug, DongSuk Park, YoungJoo Seol, UngHan Yoon, GangSeob Lee i JangHo Hahn. "An online database for genome information of agricultural plants". Bioinformation 8, nr 21 (31.10.2012): 1059–61. http://dx.doi.org/10.6026/97320630081059.

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Sato, Takeshi, Asako Imai, Tomoaki Murakami, Yukinaga Nishihara, Ryosuke Kikushima, Shinsaku Nakajima, Taro Takahashi i Yasuhiro Nakashima. "Geo-Agricultural Database as a Platform for Mechanism Design". Journal of Agricultural & Food Information 14, nr 4 (październik 2013): 334–47. http://dx.doi.org/10.1080/10496505.2013.825567.

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Vernon, R. "The Pacific Pest List Database for agricultural trade facilitation". EPPO Bulletin 33, nr 3 (grudzień 2003): 501–4. http://dx.doi.org/10.1111/j.1365-2338.2003.00682.x.

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Janssen, Sander, Erling Andersen, Ioannis N. Athanasiadis i Martin K. van Ittersum. "A database for integrated assessment of European agricultural systems". Environmental Science & Policy 12, nr 5 (sierpień 2009): 573–87. http://dx.doi.org/10.1016/j.envsci.2009.01.007.

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Nanseki, Teruaki, i Shigehiro Honda. "Prototype of A Simple Web Database for Agricultural Systems". Agricultural Information Research 11, nr 3 (2002): 273–78. http://dx.doi.org/10.3173/air.11.273.

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PRADITHA, ARDHIA AYU, INDAYATI LANYA i MADE SRI SUMARNIASIH. "Database Sumberdaya Lahan Pertanian Pangan Berkelanjutan Berbasis Remote Sensing dan Sistem Informasi Geografis di Subak Temaga Kecamatan Denpasar Timur". Agrotrop : Journal on Agriculture Science 11, nr 2 (17.11.2021): 210. http://dx.doi.org/10.24843/ajoas.2021.v11.i02.p10.

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Database of Sustainable Food Agricultural Land Resources Based on Remote Sensing and Geographical Information System at Subak Temaga East Denpasar Subdistricts. Subak Temaga doesn’t yet have a database according to Government Regulation No. 25 of 2012 concerning Information System for Sustainable Food Agriculture Land (SFAL). A geospatial-based database needs to be compiled to implement these regulation. The research aims: compile a database of artificial resources, agricultural resources, land resources and human resources to support SFAL in Subak Temaga, create land ownership maps in Subak Temaga, compile an information system of SFAL and land ownership based on remote sensing and Geographic Information System (GIS). This research uses a survey method to obtain primary data, then doing the mapping to compile the information system based on geospatial. The research results: artificial resources (irrigation, jogging track/farm road), land resources (soil family, landform, slope, rainfall, land suitability, soil fertility), agricultural resources (types of farm commodities, productivity, agriculture tools and machinery, cropping pattern, types and dosage of fertilizer), human resources (name, address, age, last education, farmer status, ownership status, ownership large and boundary, profit-sharing system). Farmer status consists of 56 owner farmers (30,9%) and 125 sharecropers (69,1%). Land ownership status consist of 432 freehold polygons (92,7%) and 34 non freehold polygons (23.8%). Remote sensing is used to determine the boundaries of land ownership, GIS is used to compile a geospatial-based information system for LP2B and land ownership.

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Cai, Xi. "Agricultural Environment Information Management". International Journal of Agricultural and Environmental Information Systems 11, nr 3 (lipiec 2020): 48–60. http://dx.doi.org/10.4018/ijaeis.2020070104.

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ZigBee communication technology was used to design the internal information transmission system of intelligent gateway in the monitoring system. Finally, the system was used to detect the changes of temperature and humidity in the environment in real time for verification. The results showed that Amazon AWS cloud service platform was used to build the monitoring system, while the application layer used Spring MVC system framework in J2EE platform to realize the storage of perception data, control of equipment, and analysis of data, and developed the DEMO system by using Amazon DynamoDB NoSQL database and RDS database to jointly store data. The results of this study show that the agricultural environment IOT monitoring system based on cloud computing can better realize the monitoring of relevant parameters in the crop environment, and can lay a foundation for the development of agricultural technology of follow-up facilities.

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Zouberakis, M., C. Chandras, M. Swertz, D. Smedley, M. Gruenberger, J. Bard, K. Schughart i in. "Mouse Resource Browser--a database of mouse databases". Database 2010 (20.05.2010): baq010. http://dx.doi.org/10.1093/database/baq010.

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Li, Y. R., G. H. Huang, Y. F. Li, J. Struger i J. D. Fischer. "A pesticide runoff model for simulating runoff losses of pesticides from agricultural lands". Water Science and Technology 47, nr 1 (1.01.2003): 33–40. http://dx.doi.org/10.2166/wst.2003.0010.

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An integrated modeling system was developed to predict runoff losses of pesticides from agricultural lands. The system is an integration of a mathematical model, a database system, and a geographic information system. Information on soil type, land use, land slope, watershed boundaries, precipitation, pesticide usage, as well as physical and chemical properties of pesticides have been input to a GIS, managed through a database, and used for further modeling studies. The modeling outputs were in turn put into the database, such that runoff patterns along with pesticides losses could be further simulated by using a database management system. The final results could then be visualized through GIS. The developed modeling system was applied to the Kintore Creek Watershed, Ontario, Canada, for simulating losses of atrazine from agricultural lands. A water quality monitoring project was carried out from 1988 to 1992 in the watershed to detect conditions of surface water pollution due to the use of pesticides. The modeling outputs were verified through the monitoring data, demonstrating reasonable prediction accuracy. The result indicated that the model provides an effective means for forecasting pesticide runoff from agriculture lands.

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Liu, Yang, Chunyu Liu i Mi Zhou. "Does digital inclusive finance promote agricultural production for rural households in China? Research based on the Chinese family database (CFD)". China Agricultural Economic Review 13, nr 2 (14.01.2021): 475–94. http://dx.doi.org/10.1108/caer-06-2020-0141.

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PurposeThe development of digital inclusive finance appears to be able to solve the difficulty of traditional finance, which cannot completely cover agriculture and farmers and provides better financial services and products to Chinese farmers. Thus, it improves the farmers' enthusiasm for agricultural production. The purpose of this paper is to clarify whether this goal is indeed being achieved.Design/methodology/approachThis paper theoretically analyzes the mechanism that influences the effect of digital inclusive finance on rural households' agricultural production decisions and conducts an empirical study based on a sample from the Chinese family database (CFD).FindingsFirst, the development of digital financial inclusion in general can encourage rural households to reduce agricultural production. Second, the negative effect of digital inclusive finance on households' agricultural output is realized by widening the gap between the efficiency of non-agricultural economic activities and the efficiency of agricultural production. The wider the gap is, the lower the enthusiasm of households for agricultural production. Third, the mediating effect of “digital financial inclusion – difference in efficiency – agricultural output” has a significant negative effect on households with low agricultural production efficiency, but not households with high agricultural production efficiency. Digital inclusive finance has no significant effect on the difference in efficiency between the two economic activities of high-efficiency households, but a greater difference in efficiency between the two economic activities corresponds to higher enthusiasm of households for agricultural production.Originality/valueTo the best of our knowledge, this paper is the first to analyze the impact of digital financial inclusion on Chinese farmers' agricultural production. The findings of this study can provide policy-related insights to help local governments promote the development of digital finance in China's agricultural economy.

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MIHALACHE, DUMITRU BOGDAN, N. A. VANGHELE, A. A. PETRE i MARIUS NICOLAE CIOBOATA. "INTELIGENT SYSTEMS USED IN MODERN AGRICULTURE". "Annals of the University of Craiova - Agriculture Montanology Cadastre Series " 51, nr 2 (20.12.2020): 367–72. http://dx.doi.org/10.52846/aamc.2021.02.44.

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Digital agriculture is the perfect integration of digital technologies in crop and animal management and other agricultural processes. For farmers, digital farming offers the opportunity to increase production, save long-term costs and eliminate risk. Agricultural researchers see it as a data collection tool that has the ability to simplify data collection and analysis, improving predictive skills when it comes to crop management, animal behavior and production. A digital agricultural system is a database that includes not only different types of data relevant to agriculture, from soil conditions to market assessment, but also optimal decision-making functions that help to take the best measures in a series of processes. The paper presents a brief summary of new technologies in agriculture.

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Kamenidou, Sophia, Ravi Jain, Kumar Hari, James M. Robertson i Jacqueline Fletcher. "The Microbial Rosetta Stone Central Agricultural Database: An Information Resource on High-Consequence Plant Pathogens". Plant Disease 97, nr 8 (sierpień 2013): 1097–102. http://dx.doi.org/10.1094/pdis-03-12-0263-re.

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Microbial pathogens of humans, animals, and plants can serve as potential agents of biowarfare, bioterrorism, and biocrime. Previously, the Microbial Rosetta Stone (MRS) Central database, an easily accessible informational resource tool, was developed to assist law enforcement personnel in the event of a disease investigation by providing key information on pathogens of concern. Although the database already contained information on a few high-profile plant pathogens, the coverage was insufficient considering the large number of plant pathogens that pose a threat, not only to agricultural production but also to natural plant resources such as forests and rangelands. In this project, 100 plant pathogens of high consequence were selected for study, existing literature on these agents was reviewed, and both the sources and key pathogen information provided therein were curated in the new Agricultural Database (AgDB), an accessory to the existing MRS Central Database. Chosen for inclusion in the MRS Central AgDB were plant pathogens having significant potential for damage to U.S. agricultural and natural ecosystems. The selection process included review of several previously developed plant-pathogen threat lists and recommendations from experts within the U.S. plant biosecurity community. Pathogen information was collected by searching a number of relevant literature databases, sites on the World Wide Web, and other resources. For inclusion in the MRS, the information was curated into categories: pathogen taxonomy, nomenclature synonyms, disease symptoms and geographic distribution, plant hosts, insect vectors, detection and diagnostic methods, laboratory and field protocols, sample collection, and epidemiology. The resulting AgDB enhances the MRS Central Database by summarizing and linking key information on high-threat plant diseases and their causal agents to relevant scientific literature and internet resources. The AgDB contains critical, key information on high-consequence plant pathogens, curated in a format that is readily accessible and easily searched. The resource enhances the existing MRS Central Database and provides law enforcement, forensic, and investigative personnel with an additional tool with which to respond to microbial emergencies, particularly those affecting the agricultural and environmental sectors.

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Et.al, Sun-Ae Park. "Implementation of Returning Farmers Database Set Using Characteristics Information And Local Environment Information". Turkish Journal of Computer and Mathematics Education (TURCOMAT) 12, nr 6 (10.04.2021): 680–86. http://dx.doi.org/10.17762/turcomat.v12i6.2070.

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In recent years, returning farms are attracting attention as a new way of life from urbanites who are about to retire. Returning farming means that the population living in the city leaves the city and continues a new form of life in rural areas. In other words, the fever of returning farming and returning villages is increasing, and the present is called the era of returning farming. As interest in returning farms increases, it is essential to provide accurate information for a successful return to farming life. Therefore, in this paper, a set of returned farmers database was constructed to provide information related to returning farmers with improved reliability and accuracy. To this end, personal characteristic information of returnees and local environmental information were linked. In addition, a set of databases for returning farmers was constructed using population movement statistics and agricultural management database. In this paper, data necessary for service development were selected and collected. In addition, a total of three types of service scenarios were created according to the type of use of returnees, and information on customized policy projects for returnees were constructed. Finally, an exploratory analysis of the collected data was conducted. In other words, refinement work was carried out to build the utilized database set, and the database set was constructed according to the purpose of use. As a result, the agricultural support information and the agricultural management body database were used based on the basic characteristic information of the returnees to provide selective customized information and establish a database set to improve reliability. Through this, it is possible to provide a customized service for anyone interested in returning to farming to easily access the farming information database set and obtain related information.

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Xu, H., R. De Jong, S. Gameda i B. Qian. "Development and evaluation of a Canadian agricultural ecodistrict climate database". Canadian Journal of Soil Science 90, nr 2 (1.05.2010): 373–85. http://dx.doi.org/10.4141/cjss09064.

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Spatially representative climate data are required input in various agricultural and environmental modelling studies. An agricultural ecodistrict climate database for Canada was developed from climate station data using a spatial interpolation procedure. This database includes daily maximum and minimum air temperatures, precipitation and incoming global solar radiation, which are necessary inputs for many agricultural modelling studies. The spatial interpolation procedure combines inverse distance squared weighting with the nearest neighbour approach. Cross-validation was performed to evaluate the accuracy of the interpolation procedure. In addition to some common error measurements, such as mean biased error and root mean square error, empirical probability distributions and accurate rates of precipitation occurrence were also examined. Results show that the magnitude of errors for this database was similar to those in other studies that used similar or different interpolation procedures. The average root mean square error (RMSE) was 1.7°C, 2.2°C and 3.8 mm for daily maximum and minimum temperature, and precipitation, respectively. The RMSE for solar radiation varied from 16 to 19% of the climate normal during April through September and from 21 to 28% of the climate normal during the remainder of the year.Key words: Maximum and minimum temperature, precipitation, solar radiation, ecodistrict, interpolation, cross validation

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ChangKug Kim, DongSuk Park, YoungJoo Seol, SooChul Park i JangHo Hahn. "An Integrated Genome Database for Agricultural Crops and Web Service". International Journal of Information Processing and Management 1, nr 2 (31.10.2010): 25–29. http://dx.doi.org/10.4156/ijipm.vol1.issue2.3.

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Kim, Chang-Kug, Gang-Seob Lee, Ji-Su Mo, Seon-Hwa Bae i Tae-Ho Lee. "Molecular marker database for efficient use in agricultural breeding programs". Bioinformation 11, nr 9 (30.09.2015): 444–46. http://dx.doi.org/10.6026/97320630011444.

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Sun, Pei Feng, i Yong He. "Study on Remote Distributed Fault Diagnosis System in Modern Agricultural Machinery". Advanced Materials Research 225-226 (kwiecień 2011): 356–59. http://dx.doi.org/10.4028/www.scientific.net/amr.225-226.356.

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A remote distribution based agricultural mechanical fault diagnosis system was proposed against the characteristics of high technology and difficult fault diagnosis in the modern agriculture and the time-sensitive requirements in agricultural production. The paper introduced the overall system architecture and working principle, analyzed the development of site monitoring and diagnostic system, remote diagnosis center, network communication systems, and software systems development, and investigated the system’s main implementation techniques, which include network database technology, data compression and transmission technology and system security technology.

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Xue, Yan, Ye Ping Zhu i Yue E. "Construction and Application of County-Level Database of Basic Rural Economic Information". Applied Mechanics and Materials 651-653 (wrzesień 2014): 1547–51. http://dx.doi.org/10.4028/www.scientific.net/amm.651-653.1547.

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This paper describes data cleaning and reporting to effectively improve data quality in the construction of County-level Database of Basic Rural Economic Information. Modeling and GIS, as well as relevant design and development software are also incorporated, so that the database can fulfill the potential and serve for agricultural production, agricultural policy development, and agricultural management.

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Zhang, Xiao Xian, Fang Ma i Li Wang. "Application of Life Cycle Assessment in Agricultural Circular Economy". Applied Mechanics and Materials 260-261 (grudzień 2012): 1086–91. http://dx.doi.org/10.4028/www.scientific.net/amm.260-261.1086.

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Life cycle assessment is a technique to assess potential environmental impacts associated with all the stages of a product, process or service. This paper introduces life cycle assessment into the full process of agricultural circular economy. There are increasing environmental risks associated with agricultural circular economy; however, no appropriate assessment and analysis techniques on environmental impact are available. Due to the lack of special life cycle assessment database and available methodology in agricultural circular economy, we proposed a life cycle assessment technical framework with emphasis on problems associated with traditional agricultural circular economy life cycle assessment. This paper is aimed to produce reliable information on the environmental impact assessment for agriculture policy-makers, producers and consumers to help them choose sustainable development agricultural products and processes.

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Stoica, Gabriela-Dalila. "The Evolution of Agricultural Holdings – Bibliometric Analysis". Proceedings of the International Conference on Business Excellence 17, nr 1 (1.07.2023): 581–89. http://dx.doi.org/10.2478/picbe-2023-0055.

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Abstract The survey of the structure of farms is carried out by all the member states of the European Union, with agricultural holding as the statistical unit of measure. Thus, all the member states of the European Union are based on the definition of agricultural exploitation where it is mentioned that “agricultural exploitation means a single unit, both from a technical and economic point of view, with a single management, which carries out its agricultural activities on the economic territory of the EU, either as a primary activity or as a secondary activity”. The purpose of the paper is to highlight the evolution and importance of studying agriculture, more specifically agricultural holdings, by performing a qualitative and quantitative analysis of the specialized literature. Thus, to achieve the proposed goal, the web of science database was accessed in order to perform a bibliometric analysis. Thus, following the application of the bibliometric analysis, it can be argued that this sector has been given considerable interest, as evidenced by the high number of articles published recently, regarding the analysis of agricultural holdings. By querying the mentioned database, 26,804 scientific articles were found after the phrase “agricultural farms”. Most such papers were published by authors from the US (28.4% of the total number of papers) and China (18.7% of the total number of papers) in the Journal of agricultural and food chemistry (1.52%) and Acta horticulture (1.39%). Because this topic of agricultural holdings is vast and many countries are involved in approaching it in different ways, further studies are recommended on analyzing the evolution and importance of agricultural holdings in different countries and identifying the discrepancies between them.

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Saheed, Farouq Enesi, Fikri Rida Pebriansyah, Parlindungan Sitorus, T. George Michael i Arjon Turnip. "Development and Implementation of Smart Irigation for Precision Farming". IOP Conference Series: Earth and Environmental Science 1083, nr 1 (1.09.2022): 012066. http://dx.doi.org/10.1088/1755-1315/1083/1/012066.

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Abstract The agricultural sector is one of the important sectors in people’s lives as well as an important role in Indonesia’s economic growth. However, agriculture in Indonesia is not a few who still use conventional technology, so an agricultural system that can make it easier for farmers to manage their agricultural land is needed. In this system, a smart irrigation system is developed which is implemented for precision farming, by utilizing IoT technology as a means of connection between devices as well as monitoring and controlling irrigation. Parameter values such as air humidity, air temperature, soil moisture, and soil pH measured on the sensor will be sent to the database server to be displayed on the front end of the website so that users can access them using their respective devices. In addition, the soil moisture value stored in the database will later be used by the solenoid controller component to carry out the watering process.

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Artykuły w czasopismach na temat „AGRICULTURAL DATABASE”

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