Land suitability analysis for taro (Colocasia esculenta) cultivation based on topo-edaphic variables in a smallholder farming system

Taro ( Colocasia esculenta ), one of the neglected and underutilized crop species (NUCS), is regarded as a climate-smart crop due to its ability to tolerate harsh environmental conditions associated with climate change. The crop plays a critical role in enhancing food and nutritional security while promoting resilience through crop diversification, particularly in smallholder farming systems in developing countries. Despite its recognized potential, a substantial knowledge gap exists regarding the identification of optimal areas for maximizing yield in local contexts. Hence, this study employed the Maximum Entropy (MaxEnt) machine learning algorithm to conduct a Land Suitability Analysis (LSA) for taro within rural landscapes dominated by smallholder farmers. To quantify the area suitable for cultivation, we evaluated topographic and edaphic influences at 0-20 and 20-50 cm using five models: (1) topographic- variables, (2) edaphic variables at 0-20 cm, (3) a combined model using topographic + edaphic variables at 0-20 cm, (4) edaphic variables at 20-50 cm, (5) a combined model using topographic + edaphic variables at 20-50 cm. Model 5 achieved the highest mean AUC (0.821 ± 0.083 SD) based on 10 replicated validations, although paired t-tests revealed that this improvement was statistically significant only when compared to the lowest-performing Model 1 (p = 0.005), while comparisons with Models 2, 3, and 4 were not significant (all p > 0.05). The results from Model 5 indicated that 7.92%, 11.04%, 16.80%, and 26.64% of the study area were classified as highly suitable, suitable, moderately suitable, and marginally suitable for taro cultivation, respectively. Based on the MaxEnt Jackknife test, slope, Topographic Wetness Index (TWI), and the soil’s calcium, iron, and phosphorus were the most important variables for taro growth. These findings provide practical information to support improved land-use planning, promote the integration of NUCS into local farming systems, and contribute to food and nutritional security, particularly within smallholder farming communities in rural areas.

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Journal
Scientific Reports
Published
2026-10-14
DOI
https://doi.org/10.1038/s41598-026-75106-x
Primary Topic
Soil and Land Suitability Analysis
Type
article
Field-Weighted Citation Impact
0.00

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article

Land suitability analysis for taro (Colocasia esculenta) cultivation based on topo-edaphic variables in a smallholder farming system

John Odindi, Onisimo Mutanga, Trylee Nyasha Matongera, Bheka Mlambo
Scientific Reports
Soil and Land Suitability Analysis
article

Land suitability analysis for taro (Colocasia esculenta) cultivation based on topo-edaphic variables in a smallholder farming system

John Odindi, Onisimo Mutanga, Trylee Nyasha Matongera, Bheka Mlambo
article en

Abstract

Taro ( Colocasia esculenta ), one of the neglected and underutilized crop species (NUCS), is regarded as a climate-smart crop due to its ability to tolerate harsh environmental conditions associated with climate change. The crop plays a critical role in enhancing food and nutritional security while promoting resilience through crop diversification, particularly in smallholder farming systems in developing countries. Despite its recognized potential, a substantial knowledge gap exists regarding the identification of optimal areas for maximizing yield in local contexts. Hence, this study employed the Maximum Entropy (MaxEnt) machine learning algorithm to conduct a Land Suitability Analysis (LSA) for taro within rural landscapes dominated by smallholder farmers. To quantify the area suitable for cultivation, we evaluated topographic and edaphic influences at 0-20 and 20-50 cm using five models: (1) topographic- variables, (2) edaphic variables at 0-20 cm, (3) a combined model using topographic + edaphic variables at 0-20 cm, (4) edaphic variables at 20-50 cm, (5) a combined model using topographic + edaphic variables at 20-50 cm. Model 5 achieved the highest mean AUC (0.821 ± 0.083 SD) based on 10 replicated validations, although paired t-tests revealed that this improvement was statistically significant only when compared to the lowest-performing Model 1 (p = 0.005), while comparisons with Models 2, 3, and 4 were not significant (all p > 0.05). The results from Model 5 indicated that 7.92%, 11.04%, 16.80%, and 26.64% of the study area were classified as highly suitable, suitable, moderately suitable, and marginally suitable for taro cultivation, respectively. Based on the MaxEnt Jackknife test, slope, Topographic Wetness Index (TWI), and the soil’s calcium, iron, and phosphorus were the most important variables for taro growth. These findings provide practical information to support improved land-use planning, promote the integration of NUCS into local farming systems, and contribute to food and nutritional security, particularly within smallholder farming communities in rural areas.

Scientific Reports
University of Nottingham Malaysia Campus (MY), University of KwaZulu-Natal (ZA)
National Research Foundation
Zero hunger
Openalex Percentile: Top 9%
Soil and Land Suitability Analysis
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