Potential of Precise Fertilization through Adoption of Management Zones Strategy to Enhance Wheat Production
Zainab Haroon,
Muhammad Jehanzeb Masud Cheema (),
Shoaib Saleem,
Muhammad Amin,
Muhammad Naveed Anjum,
Muhammad Naveed Tahir (),
Saddam Hussain,
Usama Zahid and
Faiza Khan
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Zainab Haroon: Data-Driven Smart Decision Platform, PMAS-Arid Agriculture University, Rawalpindi 46000, Pakistan
Muhammad Jehanzeb Masud Cheema: Data-Driven Smart Decision Platform, PMAS-Arid Agriculture University, Rawalpindi 46000, Pakistan
Shoaib Saleem: Data-Driven Smart Decision Platform, PMAS-Arid Agriculture University, Rawalpindi 46000, Pakistan
Muhammad Amin: Data-Driven Smart Decision Platform, PMAS-Arid Agriculture University, Rawalpindi 46000, Pakistan
Muhammad Naveed Anjum: Data-Driven Smart Decision Platform, PMAS-Arid Agriculture University, Rawalpindi 46000, Pakistan
Muhammad Naveed Tahir: Data-Driven Smart Decision Platform, PMAS-Arid Agriculture University, Rawalpindi 46000, Pakistan
Saddam Hussain: Department of Irrigation and Drainage, University of Agriculture Faisalabad, Faisalabad 38000, Pakistan
Usama Zahid: Data-Driven Smart Decision Platform, PMAS-Arid Agriculture University, Rawalpindi 46000, Pakistan
Faiza Khan: Data-Driven Smart Decision Platform, PMAS-Arid Agriculture University, Rawalpindi 46000, Pakistan
Land, 2023, vol. 12, issue 3, 1-20
Abstract:
The variability in soil properties and crop yield can be overcome by adoption of smart farming practices through interpolation and mapping of spatial variability patterns. Geospatial technologies can be utilized to determine the cause of spatial variability in fields for site-specific application of fertilizer. This study was designed to quantify and identify the spatial variation in soil properties and wheat ( Triticum aestivum L.) yield and to delineate prescription maps for precise application of fertilizer in a semi-arid subtropical region of Pakistan. To examine the variability in soil properties on the production of the considered crop, this study comprised two different fields and each field was divided into (20 × 20 m) grids. The samples of soil were collected at 15 cm and 30 cm soil depths before the fertilization to analyze the different soil characteristics i.e., nitrogen (N), electrical conductivity (EC), potassium (K), soil organic matter (SOM), phosphorus (P), and pH. The boundaries of selected fields and grid points were established with a real-time kinematics-global positioning system (RTK-GPS). The soil data were acquired with a soil proximal sensor at a depth of 7 cm after fertilization. The statistical analysis coefficient of variation (CV), geostatistical-analysis-nugget-to-sill ratio (N:S), and the interpolated maps (ArcGIS pro 2.3) were used to characterize the least to moderate variability of soil parameters and yield, demanding site-specific management of fertilizer application. Cluster analysis was conducted using Minitab 21, which classified soil and yield characteristics into five categories: “very good”, “very low”, “good”, “poor”, and “medium”, with an external heterogeneity and internal homogeneity both more than 60%. Significant relationships ( p < 0.05) between soil and crop properties were used to develop the management zones (MZs) for the precise application of fertilizer in wheat fields. Significant differences ( p < 0.05) in soil nutrients were found in the very high and very low productivity zones at both sampling times, which suggest delineating the MZs for precise application of fertilizer according to the need of crop and soil properties. The results revealed that the optimum number of MZs for the wheat fields was five and there was heterogeneity in the soil nutrients in five MZs. The findings of this study also highlight the necessity of predicting the crop and soil factors by using precision technologies to develop the prescription maps, because sampling and analysis of soil are expensive and time-consuming. Based on the demand of the soil and crops, site-specific fertilization can increase economic and environmental efficiency.
Keywords: crop production; geospatial techniques; soil variability; variable rate fertilization; precise application of nutrients; NPK (search for similar items in EconPapers)
JEL-codes: Q15 Q2 Q24 Q28 Q5 R14 R52 (search for similar items in EconPapers)
Date: 2023
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