Delineation of nutrient management zones in Chunian using soil attributes database developed by soil fertility research institute, Punjab, Pakistan

A significant increase in food production, approximately 70%, is needed to feed the estimated 9.1 billion world population by 2050. Site-specific nutrient management through adoption of Precision Agriculture (PA) technologies can potentially increase crop productivity while keeping the use of chem...

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Main Authors: Muhammad Salik Ali Khan, Shahzada Munawar Mehdi, Aftab Ahmed Sheikh, Abdul Ghaffar Khan, Muhammad Shakar, Alamgir Alvi, Hafiz Riaz Ahmad, Munir David
Format: Article
Language:English
Published: Soil Science Society of Pakistan (SSSP) 2018-12-01
Series:Soil & Environment
Online Access:http://se.org.pk/File-Download.aspx?archivedpaperid=833
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spelling doaj-2834d3611ec3492ca20004bda8ae406d2020-11-25T00:23:17ZengSoil Science Society of Pakistan (SSSP)Soil & Environment2074-95462075-11412018-12-0137211612210.25252/SE/18/61526Delineation of nutrient management zones in Chunian using soil attributes database developed by soil fertility research institute, Punjab, PakistanMuhammad Salik Ali Khan0Shahzada Munawar Mehdi1Aftab Ahmed Sheikh2Abdul Ghaffar Khan3Muhammad Shakar4Alamgir Alvi5Hafiz Riaz Ahmad6Munir David7Directorate of Rapid Soil Fertility Survey and Soil Testing Institute, Thokar Niaz Baig, Lahore, Punjab 54000 PakistanDirectorate of Rapid Soil Fertility Survey and Soil Testing Institute, Thokar Niaz Baig, Lahore, Punjab 54000 PakistanDirectorate of Rapid Soil Fertility Survey and Soil Testing Institute, Thokar Niaz Baig, Lahore, Punjab 54000 PakistanDirectorate of Rapid Soil Fertility Survey and Soil Testing Institute, Thokar Niaz Baig, Lahore, Punjab 54000 PakistanDirectorate of Rapid Soil Fertility Survey and Soil Testing Institute, Thokar Niaz Baig, Lahore, Punjab 54000 PakistanSoil and Water Testing Laboratory, JhelumSoil and Water Testing Laboratory, JhelumProvincial Reference Fertilizer Testing Laboratory, Raiwind.A significant increase in food production, approximately 70%, is needed to feed the estimated 9.1 billion world population by 2050. Site-specific nutrient management through adoption of Precision Agriculture (PA) technologies can potentially increase crop productivity while keeping the use of chemical fertilizers at its minimum required level. In this study, agricultural land of tehsil Chunian was delineated into management zones using georeferenced soil attributes database developed by Soil Fertility Research Institute (SFRI), Punjab. Appropriate number of zones was determined after conducting fuzzy c -means unsupervised clustering analysis by using Management Zone Analyst (MZA) software and finally Quantum Geographic Information System (QGIS) was used to differentiate study area into five zones. Analysis of variance was performed to verify whether these defined zones reflect soil attributes. We concluded that tehsil Chunian could be categorized into five statistically different management zones based on soil electrical conductivity (EC), pH, soil organic matter (SOM), available potassium and available phosphorus levels. The highest crop yield was predicted in southeastern parts of tehsil Chunian represented by management zone-2 (4.4 t ha-1) followed by zone-1 (4.3 t ha-1). Whereas, northern and northwest areas were predicted with decreasing trend of wheat yield (zone-5, 3.7 t ha-1; zone-4, 4.0 t ha-1), respectively. We found that MZA and QGIS software could be used as supportive tools for making informed-decisions and the database of soil attributes developed by SFRI would serve as primary source of information for adoption of PA technology in coming years.http://se.org.pk/File-Download.aspx?archivedpaperid=833
collection DOAJ
language English
format Article
sources DOAJ
author Muhammad Salik Ali Khan
Shahzada Munawar Mehdi
Aftab Ahmed Sheikh
Abdul Ghaffar Khan
Muhammad Shakar
Alamgir Alvi
Hafiz Riaz Ahmad
Munir David
spellingShingle Muhammad Salik Ali Khan
Shahzada Munawar Mehdi
Aftab Ahmed Sheikh
Abdul Ghaffar Khan
Muhammad Shakar
Alamgir Alvi
Hafiz Riaz Ahmad
Munir David
Delineation of nutrient management zones in Chunian using soil attributes database developed by soil fertility research institute, Punjab, Pakistan
Soil & Environment
author_facet Muhammad Salik Ali Khan
Shahzada Munawar Mehdi
Aftab Ahmed Sheikh
Abdul Ghaffar Khan
Muhammad Shakar
Alamgir Alvi
Hafiz Riaz Ahmad
Munir David
author_sort Muhammad Salik Ali Khan
title Delineation of nutrient management zones in Chunian using soil attributes database developed by soil fertility research institute, Punjab, Pakistan
title_short Delineation of nutrient management zones in Chunian using soil attributes database developed by soil fertility research institute, Punjab, Pakistan
title_full Delineation of nutrient management zones in Chunian using soil attributes database developed by soil fertility research institute, Punjab, Pakistan
title_fullStr Delineation of nutrient management zones in Chunian using soil attributes database developed by soil fertility research institute, Punjab, Pakistan
title_full_unstemmed Delineation of nutrient management zones in Chunian using soil attributes database developed by soil fertility research institute, Punjab, Pakistan
title_sort delineation of nutrient management zones in chunian using soil attributes database developed by soil fertility research institute, punjab, pakistan
publisher Soil Science Society of Pakistan (SSSP)
series Soil & Environment
issn 2074-9546
2075-1141
publishDate 2018-12-01
description A significant increase in food production, approximately 70%, is needed to feed the estimated 9.1 billion world population by 2050. Site-specific nutrient management through adoption of Precision Agriculture (PA) technologies can potentially increase crop productivity while keeping the use of chemical fertilizers at its minimum required level. In this study, agricultural land of tehsil Chunian was delineated into management zones using georeferenced soil attributes database developed by Soil Fertility Research Institute (SFRI), Punjab. Appropriate number of zones was determined after conducting fuzzy c -means unsupervised clustering analysis by using Management Zone Analyst (MZA) software and finally Quantum Geographic Information System (QGIS) was used to differentiate study area into five zones. Analysis of variance was performed to verify whether these defined zones reflect soil attributes. We concluded that tehsil Chunian could be categorized into five statistically different management zones based on soil electrical conductivity (EC), pH, soil organic matter (SOM), available potassium and available phosphorus levels. The highest crop yield was predicted in southeastern parts of tehsil Chunian represented by management zone-2 (4.4 t ha-1) followed by zone-1 (4.3 t ha-1). Whereas, northern and northwest areas were predicted with decreasing trend of wheat yield (zone-5, 3.7 t ha-1; zone-4, 4.0 t ha-1), respectively. We found that MZA and QGIS software could be used as supportive tools for making informed-decisions and the database of soil attributes developed by SFRI would serve as primary source of information for adoption of PA technology in coming years.
url http://se.org.pk/File-Download.aspx?archivedpaperid=833
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