Delineating Homogeneous Management Zones for Nutrient Management in Rice Cultivated Area of Eastern India
Delineating soil homogeneous management zones (HMZs) is crucial for optimizing nutrient management in rice cultivation. The objectives of this study were to delineate HMZs using fuzzy clustering. This study was conducted in Badakusunpur village, Cuttack district, Odisha, India. Soil parameters and s...
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description | Delineating soil homogeneous management zones (HMZs) is crucial for optimizing nutrient management in rice cultivation. The objectives of this study were to delineate HMZs using fuzzy clustering. This study was conducted in Badakusunpur village, Cuttack district, Odisha, India. Soil parameters and satellite-derived vegetation indices were used for delineating HMZs. Soil sampling was done from 102 points and analyzed for major nutrients i.e. available nitrogen (AN), available phosphorus (AP), available potassium (AK) and available iron (Fe), available zinc (Zn), available copper (Cu) and available manganese (Mn). Geostatistical analysis was performed for mapping the interpolated soil parameters. Principal component analysis was used to find out the most explained components, which were Management Zone Analyst (MZA) to delineate the homogeneous cluster based on Fuzzy performance index (FPI) and Normalized classification entropy (NCE). Geostatistical analysis revealed that exponential and gaussian models were best fit models for soil parameters. The spatial dependence for AN and AK was weak, while Cu and Fe demonstrating strong spatial dependence. Four Principal Components, explaining 71.1% of total variance were used in MZA and three management zones were delineated. Zone 3 (48.98%) had the highest area coverage followed by Zone 2 (39.75%) and Zone 1 (11.26%). AN, AK and Fe were found to be highest in Zone 1, while lowest in Zone 3. All the soil nutrient parameters within the three zones were significantly different. Creating HMZs allow farmers to customize nutrients management in their farmland, which may help them in enhancing rice yields by making fertilizer use more efficient. |
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K.</creator><creatorcontrib>Tripathi, Rahul ; Tripathy, Bismay Ranjan ; Gouda, Ashish Kumar ; Swain, Chinmay Kumar ; Mohanty, Sangita ; Nayak, A. K.</creatorcontrib><description>Delineating soil homogeneous management zones (HMZs) is crucial for optimizing nutrient management in rice cultivation. The objectives of this study were to delineate HMZs using fuzzy clustering. This study was conducted in Badakusunpur village, Cuttack district, Odisha, India. Soil parameters and satellite-derived vegetation indices were used for delineating HMZs. Soil sampling was done from 102 points and analyzed for major nutrients i.e. available nitrogen (AN), available phosphorus (AP), available potassium (AK) and available iron (Fe), available zinc (Zn), available copper (Cu) and available manganese (Mn). Geostatistical analysis was performed for mapping the interpolated soil parameters. Principal component analysis was used to find out the most explained components, which were Management Zone Analyst (MZA) to delineate the homogeneous cluster based on Fuzzy performance index (FPI) and Normalized classification entropy (NCE). Geostatistical analysis revealed that exponential and gaussian models were best fit models for soil parameters. The spatial dependence for AN and AK was weak, while Cu and Fe demonstrating strong spatial dependence. Four Principal Components, explaining 71.1% of total variance were used in MZA and three management zones were delineated. Zone 3 (48.98%) had the highest area coverage followed by Zone 2 (39.75%) and Zone 1 (11.26%). AN, AK and Fe were found to be highest in Zone 1, while lowest in Zone 3. All the soil nutrient parameters within the three zones were significantly different. Creating HMZs allow farmers to customize nutrients management in their farmland, which may help them in enhancing rice yields by making fertilizer use more efficient.</description><identifier>ISSN: 0718-9508</identifier><identifier>EISSN: 0718-9516</identifier><identifier>DOI: 10.1007/s42729-024-02118-9</identifier><language>eng</language><publisher>Cham: Springer International Publishing</publisher><subject>Agricultural land ; Agriculture ; Biomedical and Life Sciences ; Cluster analysis ; Clustering ; Copper ; Crop yield ; Cultivation ; Ecology ; Environment ; Environmental impact ; Farmers ; Fertilizers ; Geostatistics ; Grain cultivation ; Iron ; Life Sciences ; Management ; Manganese ; Mathematical models ; Nutrient availability ; Nutrients ; Original Paper ; Parameters ; Performance indices ; Plant Sciences ; Principal components analysis ; Ratios ; Rice ; Software ; Soil analysis ; Soil classification ; Soil fertility ; Soil nutrients ; Soil sampling ; Soil Science & Conservation ; Soils ; Spatial dependencies ; Statistical analysis ; Vegetation ; Vegetation index</subject><ispartof>Journal of soil science and plant nutrition, 2024-12, Vol.24 (4), p.8331-8342</ispartof><rights>The Author(s) under exclusive licence to Sociedad Chilena de la Ciencia del Suelo 2024 Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.</rights><rights>Copyright Springer Nature B.V. 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K.</creatorcontrib><title>Delineating Homogeneous Management Zones for Nutrient Management in Rice Cultivated Area of Eastern India</title><title>Journal of soil science and plant nutrition</title><addtitle>J Soil Sci Plant Nutr</addtitle><description>Delineating soil homogeneous management zones (HMZs) is crucial for optimizing nutrient management in rice cultivation. The objectives of this study were to delineate HMZs using fuzzy clustering. This study was conducted in Badakusunpur village, Cuttack district, Odisha, India. Soil parameters and satellite-derived vegetation indices were used for delineating HMZs. Soil sampling was done from 102 points and analyzed for major nutrients i.e. available nitrogen (AN), available phosphorus (AP), available potassium (AK) and available iron (Fe), available zinc (Zn), available copper (Cu) and available manganese (Mn). Geostatistical analysis was performed for mapping the interpolated soil parameters. Principal component analysis was used to find out the most explained components, which were Management Zone Analyst (MZA) to delineate the homogeneous cluster based on Fuzzy performance index (FPI) and Normalized classification entropy (NCE). Geostatistical analysis revealed that exponential and gaussian models were best fit models for soil parameters. The spatial dependence for AN and AK was weak, while Cu and Fe demonstrating strong spatial dependence. Four Principal Components, explaining 71.1% of total variance were used in MZA and three management zones were delineated. Zone 3 (48.98%) had the highest area coverage followed by Zone 2 (39.75%) and Zone 1 (11.26%). AN, AK and Fe were found to be highest in Zone 1, while lowest in Zone 3. All the soil nutrient parameters within the three zones were significantly different. Creating HMZs allow farmers to customize nutrients management in their farmland, which may help them in enhancing rice yields by making fertilizer use more efficient.</description><subject>Agricultural land</subject><subject>Agriculture</subject><subject>Biomedical and Life Sciences</subject><subject>Cluster analysis</subject><subject>Clustering</subject><subject>Copper</subject><subject>Crop yield</subject><subject>Cultivation</subject><subject>Ecology</subject><subject>Environment</subject><subject>Environmental impact</subject><subject>Farmers</subject><subject>Fertilizers</subject><subject>Geostatistics</subject><subject>Grain cultivation</subject><subject>Iron</subject><subject>Life Sciences</subject><subject>Management</subject><subject>Manganese</subject><subject>Mathematical models</subject><subject>Nutrient availability</subject><subject>Nutrients</subject><subject>Original Paper</subject><subject>Parameters</subject><subject>Performance indices</subject><subject>Plant Sciences</subject><subject>Principal components analysis</subject><subject>Ratios</subject><subject>Rice</subject><subject>Software</subject><subject>Soil analysis</subject><subject>Soil classification</subject><subject>Soil fertility</subject><subject>Soil nutrients</subject><subject>Soil sampling</subject><subject>Soil Science & Conservation</subject><subject>Soils</subject><subject>Spatial dependencies</subject><subject>Statistical analysis</subject><subject>Vegetation</subject><subject>Vegetation index</subject><issn>0718-9508</issn><issn>0718-9516</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2024</creationdate><recordtype>article</recordtype><recordid>eNp9UE1LAzEQDaJg0f4BTwHPq_nYj-RYarWFqiB68RKyu7NLSpvUJCv4701dUU8OzAcz772Bh9AFJVeUkOo65KxiMiMsT0mpyOQRmpDqMBS0PP6ZiThF0xA2JIUgpCDVBJkb2BoLOhrb46XbuR4suCHge211DzuwEb86CwF3zuOHIXpzWP25GoufTAN4PmyjedcRWjzzoLHr8EKHCN7ilW2NPkcnnd4GmH73M_Ryu3ieL7P1491qPltnDSMkZoxz1oiOdRSgaGpRQi45azlthCxrRnmRC1Z0soaOSckko9DWgrISiGbQaH6GLkfdvXdvA4SoNm7wNr1UnOaionkqCcVGVONdCB46tfdmp_2HokQdXFWjqyq5qr5cVTKR-EgKCWx78L_S_7A-AR2EejM</recordid><startdate>20241201</startdate><enddate>20241201</enddate><creator>Tripathi, Rahul</creator><creator>Tripathy, Bismay Ranjan</creator><creator>Gouda, Ashish Kumar</creator><creator>Swain, Chinmay Kumar</creator><creator>Mohanty, Sangita</creator><creator>Nayak, A. K.</creator><general>Springer International Publishing</general><general>Springer Nature B.V</general><scope>AAYXX</scope><scope>CITATION</scope><orcidid>https://orcid.org/0000-0001-8826-9132</orcidid></search><sort><creationdate>20241201</creationdate><title>Delineating Homogeneous Management Zones for Nutrient Management in Rice Cultivated Area of Eastern India</title><author>Tripathi, Rahul ; Tripathy, Bismay Ranjan ; Gouda, Ashish Kumar ; Swain, Chinmay Kumar ; Mohanty, Sangita ; Nayak, A. 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The objectives of this study were to delineate HMZs using fuzzy clustering. This study was conducted in Badakusunpur village, Cuttack district, Odisha, India. Soil parameters and satellite-derived vegetation indices were used for delineating HMZs. Soil sampling was done from 102 points and analyzed for major nutrients i.e. available nitrogen (AN), available phosphorus (AP), available potassium (AK) and available iron (Fe), available zinc (Zn), available copper (Cu) and available manganese (Mn). Geostatistical analysis was performed for mapping the interpolated soil parameters. Principal component analysis was used to find out the most explained components, which were Management Zone Analyst (MZA) to delineate the homogeneous cluster based on Fuzzy performance index (FPI) and Normalized classification entropy (NCE). Geostatistical analysis revealed that exponential and gaussian models were best fit models for soil parameters. The spatial dependence for AN and AK was weak, while Cu and Fe demonstrating strong spatial dependence. Four Principal Components, explaining 71.1% of total variance were used in MZA and three management zones were delineated. Zone 3 (48.98%) had the highest area coverage followed by Zone 2 (39.75%) and Zone 1 (11.26%). AN, AK and Fe were found to be highest in Zone 1, while lowest in Zone 3. All the soil nutrient parameters within the three zones were significantly different. Creating HMZs allow farmers to customize nutrients management in their farmland, which may help them in enhancing rice yields by making fertilizer use more efficient.</abstract><cop>Cham</cop><pub>Springer International Publishing</pub><doi>10.1007/s42729-024-02118-9</doi><tpages>12</tpages><orcidid>https://orcid.org/0000-0001-8826-9132</orcidid></addata></record> |
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subjects | Agricultural land Agriculture Biomedical and Life Sciences Cluster analysis Clustering Copper Crop yield Cultivation Ecology Environment Environmental impact Farmers Fertilizers Geostatistics Grain cultivation Iron Life Sciences Management Manganese Mathematical models Nutrient availability Nutrients Original Paper Parameters Performance indices Plant Sciences Principal components analysis Ratios Rice Software Soil analysis Soil classification Soil fertility Soil nutrients Soil sampling Soil Science & Conservation Soils Spatial dependencies Statistical analysis Vegetation Vegetation index |
title | Delineating Homogeneous Management Zones for Nutrient Management in Rice Cultivated Area of Eastern India |
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