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ORIGINAL RESEARCH article

Front. Sustain. Food Syst.

Sec. Climate-Smart Food Systems

Volume 9 - 2025 | doi: 10.3389/fsufs.2025.1698211

This article is part of the Research TopicConservation Agriculture For Food Security And Climate ResilienceView all 13 articles

Enhancing AquaCrop model precision for accurate simulation of sweet potato and taro landraces

Provisionally accepted
  • 1University of KwaZulu-Natal, South Africa, Durban (PMB campus), KwaZulu-Natal, South Africa
  • 2London School of Hygiene and Tropical Medicine, University of London, London, United Kingdom

The final, formatted version of the article will be published soon.

Neglected and underutilised crop species (NUS) such as orange-fleshed sweet potato (OFSP) and taro are nutrient-dense, climate-resilient crops with high potential to diversify food systems. While the AquaCrop model has been calibrated to simulate canopy cover (CC), biomass, and yield for both crops, independent testing across diverse agro-ecological zones is required to critically assess model robustness. We, therefore, evaluated AquaCrop's ability to simulate the growth and yield of OFSP and taro at three locations in the KwaZulu-Natal province, South Africa. Critical recalibration adjustments included reducing taro's maximum rooting depth, modifying soil water depletion thresholds to better reflect water stress, and parameterising phenology based on tuber mass stabilisation. Recalibration improved model performance for CC (R2, coefficient of determination, up to 0.954 for OFSP; 0.632 for taro), biomass (NSE, Nash-Sutcliffe efficiency, up to 0.975), and final yield (absolute deviations ≤ 6% under optimal irrigation). Validation across three locations confirmed that AquaCrop reliably simulates growth and yield under non-stressed conditions, although performance declined under water-limited environments. The model was run in growing degree-day mode to account for climate variability, which is recommended for future validations. These results demonstrate that, with high-quality calibration datasets representing multiple landraces, AquaCrop can provide reliable yield predictions for NUS. This enables more accurate water management, operational yield predictions, and climate risk assessments for both smallholder and commercial farmers. By bridging the modelling gap for NUS, this work supports their integration into climate adaptation strategies, strengthens food and nutrition security, and promotes resilient agricultural diversification under variable climatic conditions.

Keywords: Calibration, crop modelling, Underutilised crops, Validation, Water stress, Yield prediction

Received: 03 Sep 2025; Accepted: 16 Oct 2025.

Copyright: © 2025 Mthembu, Kunz, Mabhaudhi and Gokool. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

* Correspondence:
Thando Lwandile Mthembu, thandomthembu007@gmail.com
Tafadzwanashe Mabhaudhi, tafadzwanashe.mabhaudhi@lshtm.ac.uk

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