Articles
Evaluating water deficit in banana crops using leaf area index and UAV-derived canopy cover under different irrigation regimes in the Canary Islands
Article number
1468_58
Pages
451 – 458
Language
English
Abstract
As a crop with high water demand, banana (Musa acuminata, Dwarf Cavendish subgroup, Brier® local selection) represents a significant challenge for irrigation management in water-scarce regions like the Canary Islands.
In this context, the use of physiological and canopy-related indicators is essential for detecting water deficit and improving irrigation management.
This study evaluated the response of banana plants to different irrigation regimes using leaf area index (LAI) and UAV-derived canopy cover (CC) as quantitative indicators of plant water status.
The experiment was conducted over 18 months under field conditions in northwestern Tenerife (Spain), applying four irrigation treatments corresponding to 1.0 × ETo, 0.75 × ETo, 0.55 × ETo and 0.35 × ETo (ET0: FAO-56 reference evapotranspiration), arranged in a randomized block design.
LAI was obtained monthly based on a non-destructive allometric equation using leaf length and width measurements, whereas CC was derived from multispectral UAV imagery using the triangular vegetation index (TVI) combined with Otsu’s thresholding algorithm for plant segmentation.
Results showed no significant differences (P>0.05) in LAI and CC except for 0.35 × ETo, indicating that moderate water restrictions did not compromise canopy development.
After 12 months of plantation, irrigation at 0.35 × ETo led to significant reductions (P<0.05) in both CC and LAI, together with noticeable phenological delays.
Both LAI and UAV-derived CC proved to be reliable indicators for detecting water deficit in banana crops.
Moreover, UAV-derived CC exhibited a strong correlation with LAI during early growth stages and the first postharvest months, highlighting its potential as a robust non-destructive tool for high-throughput monitoring of crop development and precision irrigation scheduling in commercial plantations.
In this context, the use of physiological and canopy-related indicators is essential for detecting water deficit and improving irrigation management.
This study evaluated the response of banana plants to different irrigation regimes using leaf area index (LAI) and UAV-derived canopy cover (CC) as quantitative indicators of plant water status.
The experiment was conducted over 18 months under field conditions in northwestern Tenerife (Spain), applying four irrigation treatments corresponding to 1.0 × ETo, 0.75 × ETo, 0.55 × ETo and 0.35 × ETo (ET0: FAO-56 reference evapotranspiration), arranged in a randomized block design.
LAI was obtained monthly based on a non-destructive allometric equation using leaf length and width measurements, whereas CC was derived from multispectral UAV imagery using the triangular vegetation index (TVI) combined with Otsu’s thresholding algorithm for plant segmentation.
Results showed no significant differences (P>0.05) in LAI and CC except for 0.35 × ETo, indicating that moderate water restrictions did not compromise canopy development.
After 12 months of plantation, irrigation at 0.35 × ETo led to significant reductions (P<0.05) in both CC and LAI, together with noticeable phenological delays.
Both LAI and UAV-derived CC proved to be reliable indicators for detecting water deficit in banana crops.
Moreover, UAV-derived CC exhibited a strong correlation with LAI during early growth stages and the first postharvest months, highlighting its potential as a robust non-destructive tool for high-throughput monitoring of crop development and precision irrigation scheduling in commercial plantations.
Authors
O. Renz, J.D. García-Garcés, C. Méndez Hernández, O. García-Tejera, D. Ríos Mesa, M. Arbelo Pérez
Keywords
banana, canopy cover, irrigation, leaf area index, UAV, water-stress
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