scholarly journals Towards Vine Water Status Monitoring on a Large Scale Using Sentinel-2 Images

2021 ◽  
Vol 13 (9) ◽  
pp. 1837
Author(s):  
Eve Laroche-Pinel ◽  
Sylvie Duthoit ◽  
Mohanad Albughdadi ◽  
Anne D. Costard ◽  
Jacques Rousseau ◽  
...  
Keyword(s):  
Climate Change ◽  
Water Potential ◽  
Large Scale ◽  
Water Status ◽  
Vegetation Indices ◽  
Machine Learning Algorithms ◽  
Severe Drought ◽  
Stem Water Potential ◽  
Stem Water ◽  
Sentinel 2

Wine growing needs to adapt to confront climate change. In fact, the lack of water becomes more and more important in many regions. Whereas vineyards have been located in dry areas for decades, so they need special resilient varieties and/or a sufficient water supply at key development stages in case of severe drought. With climate change and the decrease of water availability, some vineyard regions face difficulties because of unsuitable variety, wrong vine management or due to the limited water access. Decision support tools are therefore required to optimize water use or to adapt agronomic practices. This study aimed at monitoring vine water status at a large scale with Sentinel-2 images. The goal was to provide a solution that would give spatialized and temporal information throughout the season on the water status of the vines. For this purpose, thirty six plots were monitored in total over three years (2018, 2019 and 2020). Vine water status was measured with stem water potential in field measurements from pea size to ripening stage. Simultaneously Sentinel-2 images were downloaded and processed to extract band reflectance values and compute vegetation indices. In our study, we tested five supervised regression machine learning algorithms to find possible relationships between stem water potential and data acquired from Sentinel-2 images (bands reflectance values and vegetation indices). Regression model using Red, NIR, Red-Edge and SWIR bands gave promising result to predict stem water potential (R2=0.40, RMSE=0.26).

scholarly journals Continuous Monitoring of Cotton Stem Water Potential using Sentinel-2 Imagery

2020 ◽  
Vol 12 (7) ◽  
pp. 1176 ◽  
Author(s):  
Yukun Lin ◽  
Zhe Zhu ◽  
Wenxuan Guo ◽  
Yazhou Sun ◽  
Xiaoyuan Yang ◽  
...  
Keyword(s):  
Machine Learning ◽  
Linear Regression ◽  
Water Potential ◽  
Large Scale ◽  
Temporal Frequency ◽  
Vegetation Indices ◽  
Stem Water Potential ◽  
Spectral Bands ◽  
Red Edge ◽  
Sentinel 2

Monitoring cotton status during the growing season is critical in increasing production efficiency. The water status in cotton is a key factor for yield and cotton quality. Stem water potential (SWP) is a precise indicator for assessing cotton water status. Satellite remote sensing is an effective approach for monitoring cotton growth at a large scale. The aim of this study is to estimate cotton water stress at a high temporal frequency and at a large scale. In this study, we measured midday SWP samples according to the acquisition dates of Sentinel-2 images and used them to build linear-regression-based and machine-learning-based models to estimate cotton water stress during the growing season (June to August, 2018). For the linear-regression-based method, we estimated SWP based on different Sentinel-2 spectral bands and vegetation indices, where the normalized difference index 45 (NDI45) achieved the best performance (R2 = 0.6269; RMSE = 3.6802 (-1*swp (bars))). For the machine-learning-based method, we used random forest regression to estimate SWP and received even better results (R2 = 0.6709; RMSE = 3.3742 (-1*swp (bars))). To find the best selection of input variables for the machine-learning-based approach, we tried three different data input datasets, including (1) 9 original spectral bands (e.g., blue, green, red, red edge, near infrared (NIR), and shortwave infrared (SWIR)), (2) 21 vegetation indices, and (3) a combination of original Sentinel-2 spectral bands and vegetation indices. The highest accuracy was achieved when only the original spectral bands were used. We also found the SWIR and red edge band were the most important spectral bands, and the vegetation indices based on red edge and NIR bands were particularly helpful. Finally, we applied the best approach for the linear-regression-based and the machine-learning-based methods to generate cotton water potential maps at a large scale and high temporal frequency. Results suggests that the methods developed here has the potential for continuous monitoring of SWP at large scales and the machine-learning-based method is preferred.

Quantifying Almond Water Stress Using Unmanned Aerial Vehicles (UAVs): Correlation of Stem Water Potential and Higher Order Moments of Non-Normalized Canopy Distribution

2017 ◽  
Author(s):  
Tiebiao Zhao ◽  
YangQuan Chen ◽  
Andrew Ray ◽  
David Doll
Keyword(s):  
Water Potential ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Water Status ◽  
Vegetation Indices ◽  
Higher Order ◽  
Stem Water Potential ◽  
Higher Order Moments ◽  
Almond Trees ◽  
Stem Water

Optimization of water use relies on accurate measurement of water status of crops. Stem water potential (SWP) has become one of the most popular methods to monitor the water status of almond trees. However, it needs to take twice visit and at least thirty minutes to obtain one measurement, which makes it very difficult to understand the water status information in the orchard level. Unmanned aerial vehicle (UAV) based remote sensing promises to deliver reliable and precise field-scale information more efficiently by providing multispectral higher-resolution images with much lower cost and higher flexibility. This paper aims to extract almond water status from UAV-based multispectral images via building the correlation between SWP and vegetation indices. Different from the traditional method that focuses on normalized difference vegetation index (NDVI) means, higher-order moments of non-normalized canopy distribution descriptors were discussed to model SWP measurements. Results showed that the proposed methods performed better than traditional NDVI mean.

Estimation water status of the vineyard by calculating multispectral index from satellite images

2021 ◽  
Author(s):  
Marta Rodríguez-Fernández ◽  
María Fandiño ◽  
Xesús Pablo González ◽  
Javier J. Cancela
Keyword(s):  
Water Stress ◽  
Water Potential ◽  
Spectral Index ◽  
Satellite Images ◽  
Irrigation System ◽  
Water Status ◽  
Stress Index ◽  
Stem Water Potential ◽  
Stem Water ◽  
Water Potential Measurements

<p>The estimation of the water status in the vineyard, is a very important factor, in which every day the winegrowers show more interest since it directly affects the quality and production in the vineyards. The situation generated by COVID-19 in viticulture, adds importance to tools that provide information of the hydric status of vineyard plants in a telematic way.</p><p>In the present study, the stem water potential in the 2018 and 2019 seasons, is analysed in a vineyard belonging to the Rias Baixas wine-growing area (Vilagarcia de Arousa, Spain), with 32 sampling points distributed throughout the plot, which allows the contrast and validation with the remote sensing methodology to estimate the water status of the vineyard using satellite images.</p><p>The satellite images have been downloaded from the Sentinel-2 satellite, on the closets available dates regarding the stem water potential measurements, carried out in the months of June to September, because this dates are considered the months in which vine plants have higher water requirements.</p><p>With satellite images, two spectral index related to the detection of water stress have been calculated: NDWI (Normalized Difference Water Index) and MSI (Moisture Stress Index). Stem water potential measurements, have allowed a linear regression with both index, to validate the use of these multispectral index to determine water stress in the vineyard.</p><p>Determination coefficients of r<sup>2</sup>=0.62 and 0.67, have been obtained in July and August 2018 and 0.54 in June of 2019 for the NDWI index, as well as values of 0.53 and 0.63 in July 2018 and June 2019 respectively, when it has been analysed the MSI index.</p><p>Between both seasons, the difference observed, that implies slightly greater water stress in 2019, is reflected in the climate conditions during the summer months, with an average accumulated rainfall that doesn’t exceed 46 mm of water. Although, the NDWI index has allowed to establish better relationships in the 2018 season respect to the MSI index and the 2019 season, (r<sup>2</sup>=0.60 NDWI in 2018), as well as greater differences in terms of water stress presented in the vineyard.</p><p>With the spectral index calculated, it has been possible to validate the use of these index for the determination of the water stress of the vineyard plants, as an efficient, fast and less expensive method, which allows the application of an efficient irrigation system in the vineyard.</p>

scholarly journals Microtensiometers Accurately Measure Stem Water Potential in Woody Perennials

Plants ◽  
2021 ◽  
Vol 10 (12) ◽  
pp. 2780
Author(s):  
Victor Blanco ◽  
Lee Kalcsits
Keyword(s):  
Water Potential ◽  
Leaf Gas Exchange ◽  
Water Status ◽  
Full Range ◽  
Canopy Temperature ◽  
Plant Water ◽  
Stem Water Potential ◽  
Woody Tissue ◽  
Woody Perennials ◽  
Stem Water

Stem water potential (Ψstem) is considered to be the standard measure of plant water status. However, it is measured with the pressure chamber (PC), an equipment that can neither provide continuous information nor be automated, limiting its use. Recent developments of microtensiometers (MT; FloraPulse sensors), which can continuously measure water tension in woody tissue of the trunk of the tree, can potentially highlight the dynamic nature of plant water relations. Thus, this study aimed to validate and assess the usefulness of the MT by comparing the Ψstem provided by MT with those same measurements from the PC. Here, two irrigation treatments (a control and a deficit treatment) were applied in a pear (Pyrus communis L.) orchard in Washington State (USA) to capture the full range of water potentials in this environment. Discrete measurements of leaf gas exchange, canopy temperature and Ψstem measured with PC and MT were made every two hours for four days from dawn to sunset. There were strong linear relationships between the Ψstem-MT and Ψstem-PC (R2 > 0.8) and with vapor pressure deficit (R2 > 0.7). However, Ψstem-MT was more variable and lower than Ψstem-PC when Ψstem-MT was below −1.5 MPa, especially during the evening. Minimum Ψstem-MT occurred later in the afternoon compared to Ψstem-PC. Ψstem showed similar sensitivity and coefficients of variation for both PC and MT acquired data. Overall, the promising results achieved indicated the potential for MT to be used to continuously assess tree water status.

Partial rootzone drying improves almond tree leaf-level water use efficiency and afternoon water status compared with regulated deficit irrigation

2011 ◽  
Vol 38 (5) ◽  
pp. 372 ◽  
Author(s):  
Gregorio Egea ◽  
Ian C. Dodd ◽  
María M. González-Real ◽  
Rafael Domingo ◽  
Alain Baille
Keyword(s):  
Gas Exchange ◽  
Water Potential ◽  
Leaf Gas Exchange ◽  
Water Status ◽  
Stem Water Potential ◽  
Regulated Deficit Irrigation ◽  
Leaf Level ◽  
Use Efficiency ◽  
Stem Water ◽  
Partial Rootzone Drying

To determine whether partial rootzone drying (PRD) optimised leaf gas exchange and soil–plant water relations in almond (Prunus dulcis (Mill.) D.A. Webb) compared with regulated deficit irrigation (RDI), a 2 year trial was conducted on field-grown trees in a semiarid climate. Five irrigation treatments were established: full irrigation (FI) where the trees were irrigated at 100% of the standard crop evapotranspiration (ETc); three PRD treatments (PRD70, PRD50 and PRD30) that applied 70, 50 and 30% ETc, respectively; and a commercially practiced RDI treatment that applied 50% ETc during the kernel-filling stage and 100% ETc during the remainder of the growth season. Measurements of volumetric soil moisture content in the soil profile (0–100 cm), predawn leaf water potential (Ψpd), midday stem water potential (Ψms), midday leaf gas exchange and trunk diameter fluctuations (TDF) were made during two growing seasons. The diurnal patterns of leaf gas exchange and stem water potential (Ψs) were appraised during the kernel-filling stage in all irrigation regimes. When tree water relations were assessed at solar noon, PRD did not show differences in either leaf gas exchange or tree water status compared with RDI. At similar average soil moisture status (adjudged by similar Ψpd), PRD50 trees had higher water status than RDI trees in the afternoon, as confirmed by Ψs and TDF. Although irrigation placement showed no effects on diurnal stomatal regulation, diurnal leaf net photosynthesis (Al) was substantially less limited in PRD50 than in RDI trees, indicating that PRD improved leaf-level water use efficiency.

Multispectral reflectance vegetation indices are highly sensitive to water stress in grapefruit trees

2020 ◽  
Author(s):  
Pablo Berrios ◽  
Abdelmalek Temnani ◽  
David Pérez ◽  
Ismael Gil ◽  
Susana Zapata ◽  
...  
Keyword(s):  
Water Stress ◽  
Water Potential ◽  
Vegetation Index ◽  
Pearson Correlation ◽  
Vegetation Indices ◽  
Irrigation Scheduling ◽  
Plant Water ◽  
Citrus Paradisi ◽  
Stem Water Potential ◽  
Stem Water

<p>The sensitivity to water stress of different plant water indicators (PWI) at different plot scales (leaf and aerial) was evaluated during the second fruit growth stage of grapefruit (<em>Citrus paradisi</em> cv. Star Ruby) trees growing in a commercial orchard for a sustainable irrigation scheduling. Trees were drip-irrigated and submitted to two irrigation treatments: (i) a control (CTL), irrigated at 100% of crop evapotranspiration to avoid any soil water limitations, and (ii) a non-irrigated (NI) treatment, irrigated as the control until the 104 days after full bloom (DAFB) when the irrigation was suppressed, until to reach a severe water stress level in the plants (around -2.3 MPa of stem water potential at solar midday). The plant water indicators studied were: stem water potential (SWP); leaf conductance (Lc); net photosynthesis (Pn), and several vegetation indices (VI) in the visible spectral region derived from an unmanned aerial vehicle equipped with a multispectral sensor. The measurements were made at 9, 12 and 18h (solar time) on 50 and 134 DAFB, coinciding with a fruit diameter of 20 and 70 mm, respectively. The correlation analysis between the PWI at leaf scale (SWP, Lc and Pn) and at aerial scale showed relatively poor results, with Pearson correlation coefficients (r values) around 0.6. However, SWP presented the highest r value with the normalized difference vegetation index (NVDI), green index (GI), normalized difference greenness vegetation index (NDGI) and red green ratio index (RGRI) showing the higher coefficients 0.80, 0,80, 0.85 and 0.86, respectively. In addition, a quadratic regression curve fitting was made for the SWP and aforementioned indices, obtaining values ​​of R<sup>2</sup> around 0.7 in all cases; the best fit corresponded to SWP = - 4.869 + 15.765 NDGI - 14.283 NDGI<sup>2</sup> (R<sup>2 </sup>= 0.749) to predict SWP values between -0.5 and -2.3 MPa. Results obtained show the possibility of using certain vegetation indices to be used in the detection of water stress in adult grapefruits, and thus propose a sustainable and efficient irrigation scheduling.</p><p>Funding:</p><p>-WATER4EVER is funded by the European Commission under the framework of the ERA-NET COFUND WATERWORKS 2015 Programme</p><p>-RIS3MUR REUSAGUA is funded by the Consejería de Empresa, Industria y Portavocía of the Murcia Region under the Feder Operational Program 2014-2020</p>

Does predawn water potential discern between irrigation treatments in Galician white grapevine cultivars?

OENO One ◽  
2014 ◽  
Vol 48 (2) ◽  
pp. 123 ◽  
Author(s):  
José Manuel Mirás-Avalos ◽  
Emiliano Trigo-Córdoba ◽  
Yolanda Bouzas-Cid
Keyword(s):  
Water Potential ◽  
Leaf Water Potential ◽  
Water Status ◽  
Irrigation Management ◽  
Growing Season ◽  
Climatic Conditions ◽  
Leaf Water ◽  
Diurnal Changes ◽  
Stem Water Potential ◽  
Stem Water

<p style="text-align: justify;"><strong>Aims</strong>: To evaluate the usefulness of predawn water potential (<strong>Ψ</strong><sub>pd</sub>) to assess the water status of Galician grapevine cultivars for irrigation purposes.</p><p style="text-align: justify;"><strong>Methods and results</strong>: Three Galician white grapevine cultivars (Albariño, Godello and Treixadura) were subjected to rain-fed and irrigation conditions during the 2013 growing season. Diurnal changes in leaf water potential (<strong>Ψ</strong><sub>l</sub>) were measured using a pressure chamber on days with high evapotranspiration demand. Stem water potential (<strong>Ψ</strong><sub>s</sub>) was measured at midday. <strong>Ψ</strong><sub>pd</sub> was not able to discriminate between treatments, whereas <strong>Ψ</strong><sub>l</sub> and <strong>Ψ</strong><sub>s</sub> at midday were able to detect significant differences in water status among plants.</p><p style="text-align: justify;"><strong>Conclusion</strong>: <strong>Ψ</strong><sub>pd</sub> was not useful to evaluate vine water status under the Galician climatic conditions. In contrast, both <strong>Ψ</strong><sub>l</sub> and <strong>Ψ</strong><sub>s</sub> were effective for detecting differences between treatments and can thus be used for irrigation management purposes.</p><p style="text-align: justify;"><strong>Significance and impact of the study</strong>: This is the first study evaluating water status of Galician grapevine cultivars. It also provides useful information about the strategy for its control through measurements of midday <strong>Ψ</strong>l or <strong>Ψ</strong>s.</p>

scholarly journals Correlations among Predawn Leaf, Midday Leaf, and Midday Stem Water Potential and their Correlations with other Measures of Soil and Plant Water Status in Vitis vinifera

2002 ◽  
Vol 127 (3) ◽  
pp. 448-454 ◽  
Author(s):  
L.E. Williams ◽  
F.J. Araujo
Keyword(s):  
Vitis Vinifera ◽  
Water Potential ◽  
Leaf Water Potential ◽  
Leaf Gas Exchange ◽  
Water Status ◽  
Linear Regression Analysis ◽  
Leaf Water ◽  
Stem Water Potential ◽  
Stem Water ◽  
Water Potential Measurements

A study was conducted to compare three measurements of determining water status of grapevines (Vitis vinifera L.) in the field. Predawn leaf water potential (ΨPD), midday leaf water potential (Ψl), and midday stem water potential (Ψstem) were measured on `Chardonnay' and `Cabernet Sauvignon' grapevines grown in Napa Valley, California late in the 1999 growing season. Both cultivars had been irrigated weekly at various fractions (0, 0.5, and 1.0 for `Chardonnay' and 0, 0.5, 0.75, and 1.5 for `Cabernet') of estimated vineyard evapotranspiration (ETc) from approximately anthesis up to the dates of measurements. Predawn water potential measurements were taken beginning at 0330 hr and completed before sunrise. Midday Ψl and Ψstem measurements were taken only between 1230 and 1330 hr. In addition, net CO2 assimilation rates (A) and stomatal conductance to water vapor (gs) were also measured at midday. Soil water content (SWC) was measured in the `Chardonnay' vineyard using a neutron probe. Values obtained for ΨPD, Ψl, and Ψstem in this study ranged from about -0.05 to -0.8, -0.7 to -1.8, and -0.5 to -1.6 MPa, respectively. All three measurements of vine water status were highly correlated with one another. Linear regression analysis of Ψl and Ψstem versus ΨPD resulted in r2 values of 0.88 and 0.85, respectively. A similar analysis of Ψl as a function of Ψstem resulted in an r2 of 0.92. In the `Chardonnay' vineyard, all three methods of estimating vine water status were significantly (P < 0.01) correlated with SWC and applied amounts of water. Lastly, ΨPD, Ψl, and Ψstem were all linearly correlated with measurements of A and gs at midday. Under the conditions of this study, ΨPD, Ψl, and Ψstem represent equally viable methods of assessing the water status of these grapevines. They were all correlated similarly with the amount of water in the soil profile and leaf gas exchange as well as with one another.

Sign in / Sign up

Export Citation Format

Share Document