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Location of the almond field in Les Borges Blanques (Lleida, Spain) and experimental design of the field, showing in different colours the three production systems and the three irrigation treatments (color figure online)
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A growing number of intensive irrigated production systems of the almond crop have been established in recent years. However, there is little information regarding the crop water requirements. Remote sensing-based models such as the two-source energy balance (TSEB) have proven to be reliable ways to accurately estimate actual crop evapotranspiratio...
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Citations
... To our knowledge, no study has directly assessed the WP of different almond production systems by monitoring canopy transpiration. Only a recent study by Quintanilla-Albornoz et al. (2023) demonstrated that transpiration estimates of almonds through the combined use of a TSEB contextual approach and an adapted version of the Campbell and Norman radiation transmittance model for rectangular hedgerow crops had an overall coefficient of determination (R 2 ) of 0.77 and root mean square error (RMSE) of 0.13 mm h − 1 . This study aims to go a step further and determine the WP of 12-year-old almond trees with different training systems and planting distances subjected to diverse irrigation regimes during two consecutive growing seasons. ...
... In addition, the normalized difference vegetation index (NDVI) (Jackson and Huete, 1991), the normalized difference water index (NDWI) (McFeeters, 1996) and the modified triangular vegetation index (MTVI2) (Xing et al., 2020) were also calculated. These parameters were used as additional inputs of a machine learning approach to estimate the leaf area index (LAI) using a random forest algorithm (scikit-learn Python library) and following the methodology described by Quintanilla-Albornoz et al. (2023) in a study which demonstrated that this approach was able to estimate the LAI with an RMSE of 0.30 m 2 m − 2 . The extraction of biophysical traits from high resolution images was conducted using the Python programming language (Python Software Foundation. ...
... To estimate canopy transmittance, a basic clumping index was assumed for the open vase system. Meanwhile, a rectangular hedgerow clumping index was applied to the open vase (MP), central axis and hedgerow systems, following the procedure outlined by Quintanilla-Albornoz et al. (2023). The contextual TSEB approach was applied with direct measurement of T c and T s from high-resolution thermal images. ...
In recent years, more intensive production systems have been developed, coinciding with a growing scarcity of water resources. This context underscores the imperative of prioritizing water productivity (WP) as a critical factor in choosing the optimal production system to minimize agricultural water use. This study aims to contribute by evaluating WP in almond orchards under four production systems: open vase with severe pruning (open vase), open vase with minimal pruning (open vase (MP)), central axis and hedgerow. Three irrigation treatments were applied over two consecutive growing seasons: fully irrigated, mild stress and severe stress. Crop transpiration was monitored over the two years using both sap flow sensors and the two-source energy balance (TSEB) model with remote sensing. The severe stress treatment exhibited a notable reduction in kernel yield and nut load of 31.6 % and 34.5 %, respectively, in the second year of water deficit. The hedgerow system tended to have similar kernel yield to the open vase (MP) and central axis systems, and higher compared to the open vase system. Additionally, both transpiration measurement methods revealed that hedgerow exhibited lower transpiration rates across all irrigation treatments. Therefore, the highest WP was observed in the hedgerow system throughout both studied years. Similar findings were derived from the analysis of long-term data. Our findings indicate that the hedgerow production system had the highest WP, averaging 0.43 kg m−3 historically, compared to 0.33 kg m−3 for the open vase, 0.34 kg m−3 for the open vase (MP), and 0.36 kg m−3 for the central axis systems.
... The absence of significant differences in LAI among production systems could affect the accuracy of ETp. Quintanilla-Albornoz et al. (2023) already showed a discrepancy between measured LAI and the fraction of intercepted photosynthetically active radiation (fIPAR) at the study site, where the hedgerow presented higher LAI values but low fIPAR levels. Considering that 630 fIPAR represents 45% of the absorbed light spectrum (Campbell and Norman 1998), these results reinforce the idea of https://doi.org/10.5194/hess-2024-5 ...
The daily transpiration (Td) is crucial for both irrigation water management and increasing crop water productivity. The use of the remote sensing-based two-source energy balance model (TSEB) has proven to be robust in estimating plant transpiration and evaporation separately for various crops. However, remote sensing models provide instantaneous estimations, so daily upscaling approaches are needed to estimate daily fluxes. Daily upscaling methodologies have not yet been examined to upscale solely transpiration in woody crops. In this regard, this study aims to evaluate the proper image acquisition time throughout the day and four methodologies to retrieve Td in almond trees with different production systems and water status. Hourly transpiration (Th) was estimated using the TSEB contextual approach (Th-TSEB) with high-resolution imagery five times during two diurnal courses. The tested methodologies were the following: the simulated evaporative fraction variable (EFsim), irradiance (Rs), reference evapotranspiration (ETo) and potential evapotranspiration (ETp). These approaches were firstly evaluated with in situ sap flow (T-SF) data and then applied to the Th-TSEB. Daily T-SF showed significant differences among production systems and levels of water stress. The EFsim and ETp methods correlated better with measured T-SF, and reduced the underestimation observed using the Rs and ETo methods, especially at noon in the severely water stressed trees. However, the daily upscaling approaches applied in the TSEB (Td-TSEB) failed to detect differences between production systems. The lack of sensibility of Td-TSEB among production systems poses a challenge when estimating Td in canopies with discontinuous architectural structures. The improvement of ETp estimations or more sophisticated ETp models could solve this issue.
... Another UAV study focused on a different topic, where Quintanilla-Albornoz et al. [101] assessed irrigation effects on almond tree transpiration, revealing variations in transpiration rates among different irrigation treatments. Figure 12a shows that satellites were the most frequently used platform in 63% of the studies, followed by UAVs in 20% and MAVs in 17%. ...
Almond cultivation is of great socio-economic importance worldwide. With the demand for almonds steadily increasing due to their nutritional value and versatility, optimizing the management of almond orchards becomes crucial to promote sustainable agriculture and ensure food security. The present systematic literature review, conducted according to the PRISMA protocol, is devoted to the applications of remote sensing technologies in almond orchards, a relatively new field of research. The study includes 82 articles published between 2010 and 2023 and provides insights into the predominant remote sensing applications, geographical distribution, and platforms and sensors used. The analysis shows that water management has a pivotal focus regarding the remote sensing application of almond crops, with 34 studies dedicated to this subject. This is followed by image classification, which was covered in 14 studies. Other applications studied include tree segmentation and parameter extraction, health monitoring and disease detection, and other types of applications. Geographically, the United States of America (USA), Australia and Spain, the top 3 world almond producers, are also the countries with the most contributions, spanning all the applications covered in the review. Other studies come from Portugal, Iran, Ecuador, Israel, Turkey, Romania, Greece, and Egypt. The USA and Spain lead water management studies, accounting for 23% and 13% of the total, respectively. As far as remote sensing platforms are concerned, satellites are the most widespread, accounting for 46% of the studies analyzed. Unmanned aerial vehicles follow as the second most used platform with 32% of studies, while manned aerial vehicle platforms are the least common with 22%. This up-to-date snapshot of remote sensing applications in almond orchards provides valuable insights for researchers and practitioners, identifying knowledge gaps that may guide future studies and contribute to the sustainability and optimization of almond crop management.
