Nutrient Variability Mapping and Demarcating Management Zones by Employing Fuzzy Clustering in Southern Coastal Region of Tamil Nadu, India

Precise nutrient management for enhancing crop yield is possible through delineating soil management zones. Generally, the fertilizer recommendations followed use a blanket application for a larger area without considering the soil spatial variability. This may lead to low fertilizer application in...

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Veröffentlicht in:Sustainability 2024-03, Vol.16 (5), p.2095
Hauptverfasser: Venugopal, Arunkumar, Kannan, Balaji, Ganapati, Patil Santosh, Krishnan, Ananthi, Manikandan, Kaniyaiah, Mathiyazhagan, Vijayakumar, Jayaraman, Somasundaram
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container_start_page 2095
container_title Sustainability
container_volume 16
creator Venugopal, Arunkumar
Kannan, Balaji
Ganapati, Patil Santosh
Krishnan, Ananthi
Manikandan, Kaniyaiah
Mathiyazhagan, Vijayakumar
Jayaraman, Somasundaram
description Precise nutrient management for enhancing crop yield is possible through delineating soil management zones. Generally, the fertilizer recommendations followed use a blanket application for a larger area without considering the soil spatial variability. This may lead to low fertilizer application in pockets of less nutrient content and vice versa. Therefore, this study aims to develop soil management zones (MZs) adopting geostatistical and fuzzy clustering techniques in the Alwarthirunagiri block of the Thoothukudi district in Southern India. One hundred and seventy-one surface samples were collected from a study area of 2760 ha. The collected soils were processed and characterized by available macronutrients and micronutrients. The coefficient of variation of the soils varied from low (9.72%) to high (74.60%). Ordinary kriging and semivariogram analysis showed wide variation in the soil characteristics within the study site, with a spatial dependence ranging from moderate to strong. Four management zones were demarcated based on fuzzy performance index and normalized classification entropy using PCA and fuzzy K-means clustering. The study results indicated that the soil properties differed significantly under different management zones and provided potential site-specific fertilizer management options. The management zone map could be useful to the farmers to adopt precise management of nutrients for different zones.
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source MDPI - Multidisciplinary Digital Publishing Institute; Elektronische Zeitschriftenbibliothek - Frei zugängliche E-Journals
subjects Agricultural production
Analysis
Clustering
Crop yields
Fertilizers
Geostatistics
Nutrients
Principal components analysis
Productivity
Software
Soil fertility
Soil management
title Nutrient Variability Mapping and Demarcating Management Zones by Employing Fuzzy Clustering in Southern Coastal Region of Tamil Nadu, India
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