Soil suitability evaluation of selected Zaria soils for cassava production

The utilization of pedometrics to address a variety of soil challenges is increasingly capturing attention in recent times. This research was carried out to assess the capabilities of the newly developed Agricultural Land Use Evaluation System (ALUES) algorithm in predicting soil appropriateness for cultivating cassava in the Zaria region. Samples were taken from soils under different agricultural land management systems. Evaluations of land suitability considered terrain, soil composition, water availability, and temperature conditions. The outcomes yielded by the ALUES algorithm generated suitability scores and classes for the land parcels, employing a fuzzy logic approach. Consequently, the aggregate suitability scores led to the establishment of overall suitability classes of the soils as moderately suitable (S2), marginally suitable (S3), and unsuitable (N). This investigation reaffirms the efficacy of ALUES in gauging the appropriateness of agricultural land for cassava cultivation within tropical settings. Nevertheless, it's important to note that the presence of climate-related variables such as water and temperature, which are not easily adjustable, could impose limitations stemming from the climatic circumstances, potentially restricting the cultivation of cassava in the study areas.

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Publication Details

Journal
Agro-Science
Published
2025-02-19
DOI
https://doi.org/10.4314/as.v23i1.2
Primary Topic
Soil and Land Suitability Analysis
Type
article
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article

Soil suitability evaluation of selected Zaria soils for cassava production

A.B. Shobayo, G.M. Hussaini
Agro-Science
Soil and Land Suitability Analysis
article

Soil suitability evaluation of selected Zaria soils for cassava production

A.B. Shobayo, G.M. Hussaini
article en

Abstract

The utilization of pedometrics to address a variety of soil challenges is increasingly capturing attention in recent times. This research was carried out to assess the capabilities of the newly developed Agricultural Land Use Evaluation System (ALUES) algorithm in predicting soil appropriateness for cultivating cassava in the Zaria region. Samples were taken from soils under different agricultural land management systems. Evaluations of land suitability considered terrain, soil composition, water availability, and temperature conditions. The outcomes yielded by the ALUES algorithm generated suitability scores and classes for the land parcels, employing a fuzzy logic approach. Consequently, the aggregate suitability scores led to the establishment of overall suitability classes of the soils as moderately suitable (S2), marginally suitable (S3), and unsuitable (N). This investigation reaffirms the efficacy of ALUES in gauging the appropriateness of agricultural land for cassava cultivation within tropical settings. Nevertheless, it's important to note that the presence of climate-related variables such as water and temperature, which are not easily adjustable, could impose limitations stemming from the climatic circumstances, potentially restricting the cultivation of cassava in the study areas.

Agro-ScienceVol. 23(1)
Openalex Percentile: Top 95%
Soil and Land Suitability Analysis
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