Articles
Remote sensing in precision fruit farming: estimation of spectral response in olives irrigated with saline reclaimed water
Article number
1433_29
Pages
227 – 234
Language
English
Abstract
Remote sensing in fruit farming is an innovative technology for sustainable fruit production.
This study evaluated the effectiveness of unmanned aerial vehicles (UAVs) equipped with multispectral cameras for identifying water and salt stress.
The experiment was conducted in potted olive trees (Olea europaea ‘Arbosana’) planted under Mediterranean conditions and subjected to two irrigation strategies (full irrigation and regulated deficit irrigation) combined with two water resources: low-cost water DEsalination and SEnsoR Technology (DESERT, ECw ~1 dS m‑1) and reclaimed water (RW, ECw ~3 dS m‑1). Flights and leaf measurements were conducted twice a day (early morning and midday) throughout the irrigation season.
The data set included UAV’s single bands, different vegetation indices (VIs) and physiological parameters, i.e., stem water potential (SWP), and leaf water potential (LWP). After image processing and data analysis, the results showed that remote sensing method can identify water stress within the different treatments, which consequently can lead to several benefits, such as safe and sustainable wastewater reuse in agriculture.
Positive results have been obtained with VIs, including near-infrared (NIR) and red-edge bands.
Different VIs were significantly correlated with water status, and the highest Pearson correlation coefficients were obtained with normalized difference red-edge (r=0.85 for SWP and r=0.81 for LWP) and normalized ratio vegetation index (r=0.85 for SWP and r=0.81 for LWP) for the olive trees under regulated deficit irrigation.
However, the r values obtained were lower for olive trees under full irrigation; the best results were achieved with the NIR band for SWP (r=0.45) and the optimized soil adjusted vegetation index for LWP (r=0.58). These results demonstrated that applying multispectral bands and VIs can provide a faster, cheaper, and simpler alternative to traditional field measurement methods.
This study evaluated the effectiveness of unmanned aerial vehicles (UAVs) equipped with multispectral cameras for identifying water and salt stress.
The experiment was conducted in potted olive trees (Olea europaea ‘Arbosana’) planted under Mediterranean conditions and subjected to two irrigation strategies (full irrigation and regulated deficit irrigation) combined with two water resources: low-cost water DEsalination and SEnsoR Technology (DESERT, ECw ~1 dS m‑1) and reclaimed water (RW, ECw ~3 dS m‑1). Flights and leaf measurements were conducted twice a day (early morning and midday) throughout the irrigation season.
The data set included UAV’s single bands, different vegetation indices (VIs) and physiological parameters, i.e., stem water potential (SWP), and leaf water potential (LWP). After image processing and data analysis, the results showed that remote sensing method can identify water stress within the different treatments, which consequently can lead to several benefits, such as safe and sustainable wastewater reuse in agriculture.
Positive results have been obtained with VIs, including near-infrared (NIR) and red-edge bands.
Different VIs were significantly correlated with water status, and the highest Pearson correlation coefficients were obtained with normalized difference red-edge (r=0.85 for SWP and r=0.81 for LWP) and normalized ratio vegetation index (r=0.85 for SWP and r=0.81 for LWP) for the olive trees under regulated deficit irrigation.
However, the r values obtained were lower for olive trees under full irrigation; the best results were achieved with the NIR band for SWP (r=0.45) and the optimized soil adjusted vegetation index for LWP (r=0.58). These results demonstrated that applying multispectral bands and VIs can provide a faster, cheaper, and simpler alternative to traditional field measurement methods.
Authors
F. Abbatantuono, A. Tallou, J. Ikken, V. Cianciola, S. Álvarez, S. Camposeo, G.A. Vivaldi
Keywords
deficit irrigation, ‘Arbosana’, precision agriculture, olive, water management
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