Delineation of potential management zones for cowpea by factorial kriging and spatial Fuzzy C-Means of yield and soil chemical and texture properties
ABSTRACT In precision agriculture, accurate delineation of management zones and understanding spatial variability of soil properties and crop yields are critical for optimizing resource allocation and improving productivity. Spatial variability of different environmental factors (soil and plants) is...
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Sociedade Brasileira de Ciência do Solo
2025-02-01
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| Series: | Revista Brasileira de Ciência do Solo |
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| author | João Fernandes da Silva Júnior Thiago Thomé da Silva Devid Jackson da Silva Sousa Rose Luiza Moraes Tavares Benedito Dutra Luz de Souza Daniel Pereira Pinheiro |
| author_facet | João Fernandes da Silva Júnior Thiago Thomé da Silva Devid Jackson da Silva Sousa Rose Luiza Moraes Tavares Benedito Dutra Luz de Souza Daniel Pereira Pinheiro |
| author_sort | João Fernandes da Silva Júnior |
| collection | DOAJ |
| description | ABSTRACT In precision agriculture, accurate delineation of management zones and understanding spatial variability of soil properties and crop yields are critical for optimizing resource allocation and improving productivity. Spatial variability of different environmental factors (soil and plants) is evident in several studies. Associations between the texture and chemical properties of the soil and cowpea yield have been tested, but a large, unexplained variance of ranges between kriged maps is usually reported. This suggests that a deeper exploration into the soil properties of these spatial interactions may help develop our understanding on how to reduce the number of soil property maps to delineate management zones and simplify interpretation. The main objective of this study was to investigate whether factorial kriging analysis can be used as an auxiliar variable to cokriging of soil properties and cowpea yield, and what is the potential of Spatial Fuzzy c-Means associated with factorial kriging analysis to delineate management zones. This study employed factor maps and spatial clustering to classify the cowpea field in management zones based on a multivariate and geostatistical analysis using soil texture and chemical properties. From Farmer, 66 soil samples were collected at a layer of 0.00-0.20 m, at points with a regular spacing of 12 m, at Agropecuária Milênio in the municipality of Tracuateua, Pará State, to make the technology applicable to the most common data available to farmers. It also used Spatial Fuzzy c-Means to generate estimated maps. Only the kriged maps of soil properties were inefficient in delineating management zones. Factor maps and Spatial Fuzzy c-Means were efficient in delineating the two management zones. Factorial kriging analysis can be used in cokriging to estimate soil properties and the cowpea field. The proposed method is a practical tool to delineate management zones, performing better and more efficiently compared with soil multiple property maps. The optimal number of management zones for cowpea cultivation was determined to be two. This encompasses soil management, yield considerations, and site-specific choices, all aimed at mitigating the impacts of precision agriculture on high productivity. |
| format | Article |
| id | doaj-art-71634c0bb99f4021b697154ac8398c7b |
| institution | Kabale University |
| issn | 1806-9657 |
| language | English |
| publishDate | 2025-02-01 |
| publisher | Sociedade Brasileira de Ciência do Solo |
| record_format | Article |
| series | Revista Brasileira de Ciência do Solo |
| spelling | doaj-art-71634c0bb99f4021b697154ac8398c7b2025-02-04T07:41:11ZengSociedade Brasileira de Ciência do SoloRevista Brasileira de Ciência do Solo1806-96572025-02-014910.36783/18069657rbcs20230158Delineation of potential management zones for cowpea by factorial kriging and spatial Fuzzy C-Means of yield and soil chemical and texture propertiesJoão Fernandes da Silva Júniorhttps://orcid.org/0000-0002-1531-3486Thiago Thomé da Silvahttps://orcid.org/0009-0005-3008-1467Devid Jackson da Silva Sousahttps://orcid.org/0009-0008-4325-8833Rose Luiza Moraes Tavareshttps://orcid.org/0000-0003-4672-8470Benedito Dutra Luz de Souzahttps://orcid.org/0009-0004-4821-6094Daniel Pereira Pinheirohttps://orcid.org/0000-0002-5543-8187ABSTRACT In precision agriculture, accurate delineation of management zones and understanding spatial variability of soil properties and crop yields are critical for optimizing resource allocation and improving productivity. Spatial variability of different environmental factors (soil and plants) is evident in several studies. Associations between the texture and chemical properties of the soil and cowpea yield have been tested, but a large, unexplained variance of ranges between kriged maps is usually reported. This suggests that a deeper exploration into the soil properties of these spatial interactions may help develop our understanding on how to reduce the number of soil property maps to delineate management zones and simplify interpretation. The main objective of this study was to investigate whether factorial kriging analysis can be used as an auxiliar variable to cokriging of soil properties and cowpea yield, and what is the potential of Spatial Fuzzy c-Means associated with factorial kriging analysis to delineate management zones. This study employed factor maps and spatial clustering to classify the cowpea field in management zones based on a multivariate and geostatistical analysis using soil texture and chemical properties. From Farmer, 66 soil samples were collected at a layer of 0.00-0.20 m, at points with a regular spacing of 12 m, at Agropecuária Milênio in the municipality of Tracuateua, Pará State, to make the technology applicable to the most common data available to farmers. It also used Spatial Fuzzy c-Means to generate estimated maps. Only the kriged maps of soil properties were inefficient in delineating management zones. Factor maps and Spatial Fuzzy c-Means were efficient in delineating the two management zones. Factorial kriging analysis can be used in cokriging to estimate soil properties and the cowpea field. The proposed method is a practical tool to delineate management zones, performing better and more efficiently compared with soil multiple property maps. The optimal number of management zones for cowpea cultivation was determined to be two. This encompasses soil management, yield considerations, and site-specific choices, all aimed at mitigating the impacts of precision agriculture on high productivity.http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0100-06832025000100300&lng=en&tlng=enprecision agriculturegeostatisticssite-specific managementmultivariate analysisAmazon |
| spellingShingle | João Fernandes da Silva Júnior Thiago Thomé da Silva Devid Jackson da Silva Sousa Rose Luiza Moraes Tavares Benedito Dutra Luz de Souza Daniel Pereira Pinheiro Delineation of potential management zones for cowpea by factorial kriging and spatial Fuzzy C-Means of yield and soil chemical and texture properties Revista Brasileira de Ciência do Solo precision agriculture geostatistics site-specific management multivariate analysis Amazon |
| title | Delineation of potential management zones for cowpea by factorial kriging and spatial Fuzzy C-Means of yield and soil chemical and texture properties |
| title_full | Delineation of potential management zones for cowpea by factorial kriging and spatial Fuzzy C-Means of yield and soil chemical and texture properties |
| title_fullStr | Delineation of potential management zones for cowpea by factorial kriging and spatial Fuzzy C-Means of yield and soil chemical and texture properties |
| title_full_unstemmed | Delineation of potential management zones for cowpea by factorial kriging and spatial Fuzzy C-Means of yield and soil chemical and texture properties |
| title_short | Delineation of potential management zones for cowpea by factorial kriging and spatial Fuzzy C-Means of yield and soil chemical and texture properties |
| title_sort | delineation of potential management zones for cowpea by factorial kriging and spatial fuzzy c means of yield and soil chemical and texture properties |
| topic | precision agriculture geostatistics site-specific management multivariate analysis Amazon |
| url | http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0100-06832025000100300&lng=en&tlng=en |
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