AI Summary & Key Takeaways
AI InsightTherefore, the Aqua-Crop model has proven to be a good Onion crop growth and yield predictor under different irrigation levels and mulch materials which can help improve Onion productivity in water-stressed areas like semi-arid Nigeria.
📌 3 Key Takeaways
Abstract
The Aqua-Crop simulation model has been playing a crucial role in assessing the performance of the existing strategies for the management of irrigation schemes for improving agricultural water use efficiency. This study evaluated the Aqua-Crop model using Onion crops under deficit irrigation and mulch practices in semi-arid Nigeria. Measurements were taken from the experimental plots which consisted of irrigation and mulch each at 4 levels were used to evaluate the Aqua-Crop model using canopy cover, biomass, yield, actual crop ET, and water productivity of Onion during the 2021 irrigation season. The simulated results from the Aqua-Crop model were evaluated and statistically compared with the experimental results. The model simulated canopy cover with the highest degree of correlation coefficient (0.74 ≤ r ≤ 0.94). The model perfectly predicted Onion yield and biomass under full irrigation irrespective of the mulching. However, the model underestimated Onion yield and biomass at deficit irrigation. The model has perfectly estimated the seasonal actual crop evapotranspiration at different irrigation levels and mulch materials while underestimating water productivity in most of the treatments except at 100% irrigation under white synthetic mulch. However, both model and experimental water productivity were better at white synthetic mulch plots. Therefore, the Aqua-Crop model has proven to be a good Onion crop growth and yield predictor under different irrigation levels and mulch materials which can help improve Onion productivity in water-stressed areas like semi-arid Nigeria.