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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Veröffentlicht in:Journal of soil science and plant nutrition 2024-12, Vol.24 (4), p.8331-8342
Hauptverfasser: Tripathi, Rahul, Tripathy, Bismay Ranjan, Gouda, Ashish Kumar, Swain, Chinmay Kumar, Mohanty, Sangita, Nayak, A. K.
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container_start_page 8331
container_title Journal of soil science and plant nutrition
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Tripathy, Bismay Ranjan
Gouda, Ashish Kumar
Swain, Chinmay Kumar
Mohanty, Sangita
Nayak, A. K.
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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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. 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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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