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Correlation of Spatial Variability of Soil Macronutrients with Crop Performance by Using Satellite and Remote Sensing Indices for Site Specific Agriculture: Chakwal Region | Abstract
ISSN: 2375-4338

Rice Research: Open Access
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Research Article

Correlation of Spatial Variability of Soil Macronutrients with Crop Performance by Using Satellite and Remote Sensing Indices for Site Specific Agriculture: Chakwal Region

Muhammad Zeeshan*, Muhammad Tariq Siddique, Nosheen Arab Ali and Muhammad Shakir Farooq

Department of soil science and SWC, PMAS-Arid Agriculture University Rawalpindi

*Corresponding Author:
Muhammad Zeeshan
Department of soil science and SWC
PMAS-Arid Agriculture University Rawalpindi, Pakistan
Tel: +923076907121
Email: [email protected]

Received date: 04 February, 2017; Accepted date: 20 April, 2017; Published date: 29 April, 2017

Citation: Zeeshan M, Siddique MT, Ali NA, Farooq MS (2017) Correlation of Spatial Variability of Soil Macronutrients with Crop Performance by Using Satellite and Remote Sensing Indices for Site Specific Agriculture: Chakwal Region. J Rice Res 5:182. doi: 10.4172/2375-4338.1000182

Copyright: © 2017 Zeeshan M, et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Abstract

Site-specific agriculture includes the application of soil on variable areas rather than the whole field and requires the knowledge of spatial variability of soil nutrients in the area. A survey was conducted to find out the spatial variation of soil macronutrient, to prepare the soil fertility maps and to correlate soil nutrients with NDVI values, at University Research Farm, Koont, Chakwal. Soil samples were collected and analyzed for soil macronutrient (NO3- N, P, K, SO4-S and CaCO3) concentration through standard procedures. Obtained data were analyzed by using GIS and ordinary statistics to predict the spatial variability and preparation of digital maps of the soil macronutrients. NDVI values were calculated by acquiring the cloud free landsat images of study area to correlate with soil macronutrients. The results showed that, NO3-N and Available P were deficient in study area and were having the mean value of 7.54 mg kg-1 and 6.64 mg kg-1 respectively. K and SO4-S were in satisfactory ranges and were having average values of 130.3 mg kg-1 and 8.69 mg kg-1 respectively. Study area was classified as moderately calcareous soil and lime content were having the mean value of 7.88%. Geostatistical analysis showed that NO3-N and available P were strongly spatial dependent while K, SO4-S and CaCO3 were moderately spatial dependent. Pearson correlation analysis among NDVI values and soil parameters showed that NO3-N, P, K and CaCO3 were significantly positively correlated with NDVI values whereas SO4-S showed non-significant positive correlation with NDVI values. Study recommended that spatial variability of soil properties should be taken in account in decision making processes regarding farm operations such as fertilizer application, more studies on different spatial scale should be conducted and use of such techniques in profitable and sustainable site-specific agriculture should be promoted.

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