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Scientific paper - Original scientific paper
The Relationship of Environmental Factors and the Cropland Suitability Levels for Soybean Cultivation Determined by Machine Learning
Poljoprivreda, 28 (2022), 1; 53-59. https://doi.org/10.18047/poljo.28.1.8
Radočaj, Dorijan; Vinković, Tomislav; Jurišić, Mladen; Gašparović, Mateo

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Radočaj, D., Vinković, T., Jurišić, M. & Gašparović, M. (2022). The Relationship of Environmental Factors and the Cropland Suitability Levels for Soybean Cultivation Determined by Machine Learning. Poljoprivreda, 28. (1), 53-59. doi: 10.18047/poljo.28.1.8

Radočaj, Dorijan, et al. "The Relationship of Environmental Factors and the Cropland Suitability Levels for Soybean Cultivation Determined by Machine Learning." Poljoprivreda, vol. 28, no. 1, 2022, pp. 53-59. https://doi.org/10.18047/poljo.28.1.8

Radočaj, Dorijan, Tomislav Vinković, Mladen Jurišić and Mateo Gašparović. "The Relationship of Environmental Factors and the Cropland Suitability Levels for Soybean Cultivation Determined by Machine Learning." Poljoprivreda 28, no. 1 (2022): 53-59. https://doi.org/10.18047/poljo.28.1.8

Radočaj, D., et al. (2022) 'The Relationship of Environmental Factors and the Cropland Suitability Levels for Soybean Cultivation Determined by Machine Learning', Poljoprivreda, 28(1), pp. 53-59. doi: 10.18047/poljo.28.1.8

Radočaj D, Vinković T, Jurišić M, Gašparović M. The Relationship of Environmental Factors and the Cropland Suitability Levels for Soybean Cultivation Determined by Machine Learning. Poljoprivreda [Internet]. 2022 June 30 [cited 2024 November 20];28(1):53-59. doi: 10.18047/poljo.28.1.8

D. Radočaj, T. Vinković, M. Jurišić and M. Gašparović, "The Relationship of Environmental Factors and the Cropland Suitability Levels for Soybean Cultivation Determined by Machine Learning", Poljoprivreda, vol. 28, no. 1, pp. 53-59, June 2022. [Online]. Available at: https://urn.nsk.hr/urn:nbn:hr:151:473165. [Accessed: 20 November 2024]

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Metadata
Title (english)The Relationship of Environmental Factors and the Cropland Suitability Levels for Soybean Cultivation Determined by Machine Learning
AuthorDorijan Radočaj
AuthorTomislav Vinković
AuthorMladen Jurišić
AuthorMateo Gašparović
Author's institutionJosip Juraj Strossmayer University of Osijek
Faculty of Agrobiotechnical Sciences Osijek
(Department of Agricultural Engineering and Renewable Energy Resources)
Scientific / art field,
discipline and subdiscipline		BIOTECHNICAL SCIENCES
Agronomy
Agricultural Engineering and Technology
Abstract (english)
The relationship between cropland suitability and the surrounding environmental factors has an important role in understanding and adjusting agricultural land management systems to natural cropland suitability. In this study, the relationship between soybean cropland suitability, determined by a novel machine learningbased approach, and three major environmental factors in continental Croatia was evaluated. These constituted of two major land cover classes (forests and urban areas), utilized soybean growth seasons per agricultural parcels during a 2017–2020 study period and soil types. The sensitivity analysis in geographic information system (GIS) using a raster overlay method, along with auxiliary spatial processing, was performed. The proximity of soybean agricultural parcels to forests showed a high correlation with suitability values, indicating a potential benefit of implementing agroforestry in land management plans. A notable amount of suitable agricultural parcels for soybean cultivation, which were previously not utilized for soybean cultivation was observed. A disregard of crop rotations was also noted, with the same soybean parcels within the study period in three and four years. This analysis showed considerable potential in understanding the effects of environmental factors on cropland suitability values, leading to more efficient land
Keywords (english)
Languageenglish
Publication typeScientific paper - Original scientific paper
Publication statusPublished
Peer reviewPeer review - domestic
Publication versionPublished version
Journal titlePoljoprivreda
Numberingvol. 28, no. 1, pp. 53-59
p-ISSN1330-7142
e-ISSN1848-8080
DOIhttps://doi.org/10.18047/poljo.28.1.8
URN:NBNurn:nbn:hr:151:473165
Publication2022-06-30
Document URLhttps://hrcak.srce.hr/file/405680
Type of resourceText
Access conditionsOpen access
Terms of useLicence In copyright icon
Created on2024-05-07 12:07:32