Assessment of Soil Suitability for Sugarcane Cultivation using GIS and Multivariate Analysis in Binauli Block, Western Uttar Pradesh, India

This study assesses soil fertility in Binauli Block, Baghpat, India, using a nutrient index approach and GIS mapping. Soil samples from 54 sites were analysed for pH, organic carbon, electrical conductivity, macronutrients (nitrogen, phosphorus, potassium), and micronutrients (sulfur, zinc, boron, iron, copper, manganese). Soil samples were tested in the laboratory for various parameters. The obtained data was then analysed using SPSS and R software. The analysed values were interpolated using the Inverse Distance Weighting (IDW) method in Arc GIS. Results show low organic carbon (0.26), phosphorus (10.83), and electrical conductivity (0.75), while potassium (145.38) and nitrogen (149.01) are adequate. High pH (8.11) and optimal boron (0.94) and manganese (4.89) suggest fertility concerns impacting sugarcane productivity. Findings emphasize tailored fertilization to improve soil health and yields.

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-03-01
DOI
https://doi.org/10.5281/zenodo.15830006
Primary Topic
Soil Geostatistics and Mapping
Type
article
Field-Weighted Citation Impact
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article

Assessment of Soil Suitability for Sugarcane Cultivation using GIS and Multivariate Analysis in Binauli Block, Western Uttar Pradesh, India

Zenodo (CERN European Organization for Nuclear Research)
Soil Geostatistics and Mapping
article

Assessment of Soil Suitability for Sugarcane Cultivation using GIS and Multivariate Analysis in Binauli Block, Western Uttar Pradesh, India

article en

Abstract

This study assesses soil fertility in Binauli Block, Baghpat, India, using a nutrient index approach and GIS mapping. Soil samples from 54 sites were analysed for pH, organic carbon, electrical conductivity, macronutrients (nitrogen, phosphorus, potassium), and micronutrients (sulfur, zinc, boron, iron, copper, manganese). Soil samples were tested in the laboratory for various parameters. The obtained data was then analysed using SPSS and R software. The analysed values were interpolated using the Inverse Distance Weighting (IDW) method in Arc GIS. Results show low organic carbon (0.26), phosphorus (10.83), and electrical conductivity (0.75), while potassium (145.38) and nitrogen (149.01) are adequate. High pH (8.11) and optimal boron (0.94) and manganese (4.89) suggest fertility concerns impacting sugarcane productivity. Findings emphasize tailored fertilization to improve soil health and yields.

Zenodo (CERN European Organization for Nuclear Research)
Zero hunger
Openalex Percentile: Top 59%
Soil Geostatistics and Mapping
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