Stem Water Potential Monitoring in Pear Orchards through WorldView-2 Multispectral Imagery

Beek, Jonathan Van; Tits, Laurent; Somers, Ben; Coppin, Pol

doi:10.3390/rs5126647

Cited by 32 publications

(28 citation statements)

References 46 publications

(66 reference statements)

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“…The Red-edge Normalized Difference Vegetation Index (ReNDVI; Equation (2)) [24], a normalized difference ratio between the NIR (Near-Infrared; 770-895 nm) and Red-edge (705-745 nm), was applied as it was previously related to water status (i.e., stem water potential) and plant health in irrigated and rainfed pear orchards [24]. This association could provide significant correlations with fruit yield and quality [1,22].…”

Section: Discussionmentioning

confidence: 99%

“…This association could provide significant correlations with fruit yield and quality [1,22]. The spectral bands used for ReNDVI were calculated based on the WorldView-2 spectral response function [30,31], similar to [24].…”

Section: Discussionmentioning

confidence: 99%

“…The correlation between ReNDVI values and production variables was highly variable between both orchards (Figure 4e and Figure 5f). This might be caused by the underlying relationship with stem water potential [24]. As a result of the deficit irrigation treatment in the irrigated orchard, large stem water potential differences were maintained during the end of fruit fall without significant fruit yield and fruit quality differences because of the ability to irrigate in later stages of fruit development.…”

Section: Production Versus Spectral Measurementsmentioning

confidence: 99%

“…Trees with more vegetative growth produced less flower buds (i.e., decreased number of fruits and total yields), as a result of the considerable consumption of water from excessive vegetative growth [47]. The spectral vegetation indices provided an overall indication of plant health-plant vigor [24], water content [24,29,32], photosynthetic efficiency [32]-which in turn was related to production variables. Because of the indirect nature of this relationship, several periods within the growing season showed insignificant correlation between vegetation indices and production variables (Figures 4a and 5a).…”

Section: Potential and Limitationsmentioning

confidence: 99%

“…During this period, two irrigation treatments were applied. More information on the irrigation treatment can be found in Van Beek et al [24]. Four plots of four trees each were selected on fixed intervals (±30 m) within four rows and monitored throughout the 2011, 2012 and 2013 growing seasons (48 plots).…”

Section: Study Areamentioning

confidence: 99%

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Temporal Dependency of Yield and Quality Estimation through Spectral Vegetation Indices in Pear Orchards

et al. 2015

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Yield and quality estimations provide vital information to fruit growers, yet require accurate monitoring throughout the growing season. To this end, the temporal dependency of fruit yield and quality estimations through spectral vegetation indices was investigated in irrigated and rainfed pear orchards. Both orchards were monitored throughout three consecutive growing seasons, including spectral measurements (i.e., hyperspectral canopy reflectance measurements) as well as yield determination (i.e., total yield and number of fruits per tree) and quality assessment (i.e., fruit firmness, total soluble solids and fruit color). The results illustrated a clear association between spectral vegetation indices and both fruit yield and fruit quality (|r| > 0.75; p < 0.001). However, the correlations between vegetation indices and production variables varied throughout the growing season, depending on the phenological stage of fruit development. In the irrigated orchard, index values showed a strong association with production variables near time of OPEN ACCESSRemote Sens. 2015, 7 9887 harvest (|r| > 0.6; p < 0.001), while in the rainfed orchard, index values acquired during vegetative growth periods presented stronger correlations with fruit parameters (|r| > 0.6; p < 0.001). The improved planning of remote sensing missions during (rainfed orchards) and after (irrigated orchards) vegetative growth periods could enable growers to more accurately predict production outcomes and improve the production process.

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Section: Discussionmentioning

confidence: 99%