Soil quality indicator-based land productivity modelling for agricultural sustainability.
Rapid population expansion has made food security a global concern for humanity, necessitating a sustainable assessment of natural resources. Well evaluated and managed soil is one of the most significant resources that can assist close the gap between supply and demand for food to attain food secur...
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| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Public Library of Science (PLoS)
2025-01-01
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| Series: | PLoS ONE |
| Online Access: | https://doi.org/10.1371/journal.pone.0316840 |
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| Summary: | Rapid population expansion has made food security a global concern for humanity, necessitating a sustainable assessment of natural resources. Well evaluated and managed soil is one of the most significant resources that can assist close the gap between supply and demand for food to attain food security. A precise assessment of land productivity (LP) is essential for sustainable land use management. The primary aim of this research is to predict the land productivity index (LPI) for certain locations on Egypt's northwest coast under current conditions using soil quality indicators (SQIs). Additionally, the study proposed relevant management actions to boost land productivity in the future. To achieve this aim, a spatial model was created to assess LPI for some areas in the north western coast of Egypt. LP equation was used to estimate current land productivity index (CLPI) and potential land productivity index (PLPI). Results found that the study area mainly located under two classes of CLPI, e.g., average (class ⅡⅠ) represents an area of 13322.63 ha (67.55%) and good grade (class Ⅱ) covers an area of 4339.78 ha (22%). PLPI grades were good (II) and average (III) with an area of 16192.54 ha (82.10%) and 1903.23 ha (9.65%), respectively. The finding showed that more than 60% of the studied area was converted from poor and average class to good class after applying the proposed solutions of soil improvement. The methodology presented here can easily be replicated under similar circumstances in arid zones, allowing local governments and decision-makers to utilize the quantitative results obtained to ensure sustainable development. |
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| ISSN: | 1932-6203 |