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Knowledge service technology of soil testing formula based on the integration of knowledge map and location service

Published: 20 December 2022 Publication History

Abstract

CCS CONCEPTS • Information systems∼Information systems applications∼Decision support systems∼Expert systems
Abstract: As a large agricultural country, agricultural fertilizer reduction has great carbon emission reduction potential and environmental contribution, which is of great significance to national carbon neutralization and carbon peak, ecological environment protection, comprehensive treatment of river basin water environment and so on. In the process of agricultural production, due to the marginal effect of agricultural inputs, excessive application of chemical fertilizer can not only increase production, but also cause soil hardening, environmental pollution and other problems, and directly affect the quality of agricultural products. In this paper, combined with the geographic information system of soil fertility and the knowledge map technology of soil testing and fertilizer blending, the knowledge service system of soil testing and fertilizer blending has been constructed, the knowledge map was used to organize and manage the knowledge related to soil testing and fertilizer blending, combined with the advantages of spatial location service and spatio-temporal annotation of GIS, to provide combined accurate service of soil testing data and soil testing formula knowledge to individualized guidance the farmers' scientific fertilization, and to improve the utilization rate of chemical fertilizer.

References

[1]
Deng M J, Deng J J, Liu J Y. On the space-time evolution of carbon emissions and reduction potential in Chinese grain crop fertilizer application[J]. Resources Science,2016,38 (3) :534-544.
[2]
LUCKMAN P G, JESSEN M R,GIBB R G. Use of expert systems and GIS in land evaluation[J].New Zealand Geographer,1990,46 (1) :15-20.
[3]
Abdelrahman M, Hegab R H, Yossif T . Soil fertility assessment for optimal agricultural use using remote sensing and GIS technologies[J]. Applied Geomatics, 2021:1-14.
[4]
Tunay T, Dedeoglu M, Dengiz O, Assessing soil fertility index based on remote sensing and gis techniques with field validation in a semiarid agricultural ecosystem[J]. Journal of Arid Environments, 2021.
[5]
Zhang Sh H, Ma Ch l, Wu C C, Yu Ch L. Application of GIS to Variable Rate Fertilization in Precision Agriculture[J]. Transactions of the Chinese Society of Agricultural Machinery,2003 (03) :92-95.
[6]
Liu G Ch. Study on Soil Fertility Geographic Information System in Jilin Province[J]. Industry and Technology Forum,2016,15 (14) :40-41.
[7]
Chen Ch, Li H, Lu Y Y, Zhang N, Pu X. Design and Development of Soil Fertility Comprehensive Evaluation System for Large Scale Farmland[A]. chinese society of environmental sciences. Papers of 2016 Annual Conference of Chinese Society of Environmental Sciences (Volume III)[C]. Chinese Society of Environmental Sciences: Chinese Society of Environmental Sciences,2016:8.
[8]
Zhong L Y, XU J B, Cai D N, Xiao Zh F. Research on spatial distribution of soil fertility and comprehensive assessment of cropland in mountain areas of north Guangdong[J]. Guangdong Agricultural Science,2015,42 (16) :37-43+2.
[9]
Liang B, Huang K, Shao X D, Li H G, Que J S, Lu Q H, Wang Ch, Hu Ch X. Suitability Evaluation of Soil Nutrients Content and Soil Fertility in Honghe Tobacco-planting Area[J]. Southwest China Journal of Agricultural Sciences,2017,30 (10) :2290-2296.
[10]
Xiong H X, Yang Z R, Jiang W X. Semantic Correlation of Multimodal Data in the Construction of Cross-media Knowledge Graph[J]. Information Atudies: Theory & Application,2019,42(02):13-18+24.
[11]
Hu Y, Yan H F, Chen Ch. Joint Entity and Relation Extraction for Constructing Financial Knowledge Graph[J]. Journal of Chongqing University of Technology ( Natural Science),2020,34(05):139-149.
[12]
Su F Z, Wu W Z, Zhang Y, From Geographic Information System to Intelligent Geographic System[J]. Journal of Geo-information Science, 2020,22(1):2-10.

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        cover image ACM Other conferences
        CSSE '22: Proceedings of the 5th International Conference on Computer Science and Software Engineering
        October 2022
        753 pages
        ISBN:9781450397780
        DOI:10.1145/3569966
        Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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        Association for Computing Machinery

        New York, NY, United States

        Publication History

        Published: 20 December 2022

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        Author Tags

        1. Geographic information system
        2. Knowledge atlas
        3. Knowledge services
        4. Location services
        5. Soil testing formula

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        • Research-article
        • Research
        • Refereed limited

        Funding Sources

        • National Key Research and Development Plan
        • Ministry of Finance of the People?s Republic of China and Ministry of Agriculture and Rural Affairs of the People?s Republic of China: supported by the National Modern Agricultural Industry Technology System
        • the Youth Scientific Research Fund Project of Beijing Academy of Agricultural and Forestry Sciences

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        CSSE 2022

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        Overall Acceptance Rate 33 of 74 submissions, 45%

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