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

Arunkumar Venugopal (), Balaji Kannan, Patil Santosh Ganapati, Ananthi Krishnan, Kaniyaiah Manikandan, Vijayakumar Mathiyazhagan and Somasundaram Jayaraman
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Arunkumar Venugopal: Department of Soil Science and Agricultural Chemistry, Agricultural College and Research Institute, Tiruvannamalai 606753, India
Balaji Kannan: Agricultural Engineering College and Research Institute, Tamil Nadu Agricultural University, Coimbatore 641003, India
Patil Santosh Ganapati: Agricultural Engineering College and Research Institute, Tamil Nadu Agricultural University, Coimbatore 641003, India
Ananthi Krishnan: Department of Soil Science and Agricultural Chemistry, Agricultural College and Research Institute, Tiruvannamalai 606753, India
Kaniyaiah Manikandan: Tamil Nadu Rice Research Institute, Aduthurai 612101, India
Vijayakumar Mathiyazhagan: Agricultural College and Research Institute, Kudumiyanmalai 622104, India
Somasundaram Jayaraman: ICAR-Indian Institute of Soil and Water Conservation, Research Centre, Fernhill, Udhagamandalam 643004, India

Sustainability, 2024, vol. 16, issue 5, 1-16

Abstract: 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.

Keywords: site-specific nutrient management zones; soil fertility; variability mapping; fuzzy clustering; geostatistics (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2024
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