Dependence of CWSI-Based Plant Water Stress Estimation with Diurnal Acquisition Times in a Nectarine Orchard

Park, Suyoung; Ryu, Dongryeol; Fuentes, Sigfredo; Chung, Hoam; O’Connell, M.; Kim, Jun Chul

doi:10.3390/rs13142775

Cited by 24 publications

(10 citation statements)

References 32 publications

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“…Midday stem water potential and stomatal conductance have been traditionally used to assess tree water status due to their robust and fast response to soil water limitations ( Naor 2000 ; Van Beek et al., 2013 ; Conesa et al., 2019 ). Many studies have reported strong relationships between thermal-based indices, stem water potential and stomatal conductance ( García-Tejero et al., 2018 ; Ahumada-Orellana et al., 2019 ; Park et al., 2021 ). Our results are aligned with those studies and show high correlation coefficients between thermal-based indices and traditional water status indicators ( Figure 8B ).…”

Section: Discussionmentioning

confidence: 99%

Combining thermal imaging and soil water content sensors to assess tree water status in pear trees

et al. 2023

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Volumetric soil water content is commonly used for irrigation management in fruit trees. By integrating direct information on tree water status into measurements of soil water content, we can improve detection of water stress and irrigation scheduling. Thermal-based indicators can be an alternative to traditional measurements of midday stem water potential and stomatal conductance for irrigation management of pear trees (Pyrus communis L.). These indicators are easy, quick, and cost-effective. The soil and tree water status of two cultivars of pear trees ‘D’Anjou’ and ‘Bartlett’ submitted to regulated deficit irrigation was measured regularly in a pear orchard in Rock Island, WA (USA) for two seasons, 2021 and 2022. These assessments were compared to the canopy temperature (Tc), the difference between the canopy and air temperature (Tc-Ta) and the crop water stress index (CWSI). Trees under deficit irrigation had lower midday stem water potential and stomatal conductance but higher Tc, Tc-Ta, and CWSI. Tc was not a robust method to assess tree water status since it was strongly related to air temperature (R = 0.99). However, Tc-Ta and CWSI were greater than 0°C or 0.5, respectively, and were less dependent on the environmental conditions when trees were under water deficits (midday stem water potential values< -1.2 MPa). Moreover, values of Tc-Ta = 2°C and CWSI = 0.8 occurred when midday stem water potential was close to -1.5 MPa and stomatal conductance was lower than 200 mmol m-2s-1. Soil water content (SWC) was the first indicator in detecting the deficit irrigation applied, however, it was not as strongly related to the tree water status as the thermal-based indicators. Thus, the relation between the indicators studied with the stem water potential followed the order: CWSI > Tc-Ta > SWC = Tc. A multiple regression analysis is proposed that combines both soil water content and thermal-based indices to overcome limitations of individual use of each indicator.

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Section: Discussionmentioning

confidence: 99%

Combining thermal imaging and soil water content sensors to assess tree water status in pear trees

et al. 2023

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“…Due to the accuracy of the midday system in assessing CWSI values, as hypothesized by past researchers, additional research is required to determine the optimal time of day for this estimation (Santesteban et al, 2017). However, only a few efforts have been made to study CWSI diurnal variations (e.g., Park et al, 2021), particularly with TIR data collected in the morning utilizing UAS. Some studies showed that the TIR image processing failed due to surface temperatures' poor contrast, causing TIR image processing issues due to missing images from the thermal sensor (Martínez et al, 2017;Santesteban et al, 2017;Zhang et al, 2019).…”

Section: Ns Wetmentioning

confidence: 99%

Diurnal Soybean Water Stress Computed Using Statistical-Based Thermal Indices With High-Frequency Unmanned Aircraft Flights

Kashyap,

Heeren,

Maguire

et al. 2023

Journal of Natural Resources and Agricultural Ecosystems

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Highlights High-frequency UAS thermal data can identify the temporal nature of the spatial canopy stress patterns for soybean. Thermal indices were calculated using the statistical approach from the lower and upper bounds of confidence interval. The CWSI Histogram Approach (UAS) was compared to the CWSI Empirical Approach (IRT). The distribution of canopy temperature (using the inter-quartile range) may be useful for irrigation management. Abstract. The use of unmanned aerial systems (UAS) in the field of irrigation management has been increasing rapidly. Due to their ability to capture multi-temporal data over the field, new techniques for the calculation of the crop water stress index (CWSI) and degrees above non-stressed (DANS) using UAS have been evolving. In this study, a statistical CWSI approach (canopy temperature histogram method) was used to identify the diurnal crop water stress patterns in soybean crop at three different study sites in Nebraska. Two study sites were located in the Eastern Nebraska Research and Extension Center (ENREC) at Mead, Nebraska, having multiple irrigation treatments; the third site was located in the South Central Agricultural Laboratory (SCAL), Clay Center, Nebraska, having one uniform irrigation treatment. Based on the results obtained, the CWSI and DANS maps exhibited a clear diurnal pattern of crop water stress response from morning to afternoon, and recovery from late afternoon to evening, with variations between the treatments at ENREC and a similar trend on SCAL. ENREC had a stronger correlation between CWSI and DANS due to the wider range in canopy temperatures from having both irrigated and rainfed plots. When compared between deficit plots at ENREC and the irrigated treatment at SCAL, the study showed that the statistical approach was more reliable when there were differences in crop water stress among different treatments. The main advantage of using the statistical CWSI histogram approach compared to the conventional empirical CWSI approach is the reduced requirement of additional meteorological parameters and faster automation time. CWSI histogram distribution graphs were created for each flight to understand the temporal changes and reveal the mean CWSI values (approximately 0.49, 0.51, and 0.49, for ENREC1, ENREC2, and SCAL, respectively) and interquartile (IQR) range for the soybean crop. For a given field site, temporal changes in IQR were greater than temporal changes in mean CWSI. Besides the mean canopy temperature, the distribution of canopy temperature (using the IQR) may be useful for irrigation management. Keywords: Irrigation Management, Precision Agriculture, Python, Remote Sensing, Thermal Imagery, Unmanned Aircraft Systems.

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“…It was shown in previous studies that several crop-based indices such as canopy temperature [ 12 , 13 , 14 , 15 , 16 , 17 , 18 , 19 ], chlorophyll content [ 20 , 21 , 22 ], and vegetation indices [ 23 , 24 , 25 , 26 , 27 , 28 ], can be used to determine crop water content, and have been employed for managing water in irrigated agriculture [ 29 , 30 , 31 , 32 , 33 ]. Canopy temperature [ 34 ] thermal indices obtained with ground-based or aerial-based sensors, can indicate crop transpiration and water stress, allowing the development of indices that assess vine water status [ 13 , 35 ] in a non-destructive and non-invasive way [ 18 , 36 ].…”

Section: Introductionmentioning

confidence: 99%

“…The CWSI method has been widely used in irrigated crops, and is considered a standard method. Many studies have been carried out in different crops, including nectarines [ 17 , 19 ], soybean [ 48 ], cotton [ 49 ], tomato [ 50 ], olive trees [ 51 ] and vines [ 52 , 53 , 54 ].…”

Section: Introductionmentioning

confidence: 99%

Using Aerial Thermal Imagery to Evaluate Water Status in Vitis vinifera cv. Loureiro

Araújo-Paredes

Portela

Mendes

et al. 2022

Sensors

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The crop water stress index (CWSI) is a widely used analytical tool based on portable thermography. This method can be useful in replacing the traditional stem water potential method obtained with a Scholander chamber (PMS Model 600) because the latter is not feasible for large-scale studies due to the time involved and the fact that it is invasive and can cause damage to the plant. The present work had three objectives: (i) to understand if CWSI estimated using an aerial sensor can estimate the water status of the plant; (ii) to compare CWSI from aerial-thermographic and portable thermal cameras with stem water potential; (iii) to estimate the capacity of an unmanned aerial vehicle (UAV) to calculate and spatialize CWSI. Monitoring of CWSI (CWSIP) using a portable device was performed directly in the canopy, by measuring reference temperatures (Tdry, Twet, and canopy temperature (Tc)). Aerial CWSI calculation was performed using two models: (i) a simplified CWSI model (CWSIS), where the Tdry and Twet were estimated as the average of 1% of the extreme temperature, and (ii) an air temperature model (CWSITair) where air temperatures (Tair + 7 °C) were recorded as Tdry and in the Twet, considering the average of the lowest 33% of histogram values. In these two models, the Tc value corresponded to the temperature value in each pixel of the aerial thermal image. The results show that it was possible to estimate CWSI by calculating canopy temperatures and spatializing CWSI using aerial thermography. Of the two models, it was found that for CWSITair, CWSIS (R2 = 0.55) evaluated crop water stress better than stem water potential. The CWSIS had good correlation compared with the portable sensor (R2 = 0.58), and its application in field measurements is possible.

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Dependence of CWSI-Based Plant Water Stress Estimation with Diurnal Acquisition Times in a Nectarine Orchard

Cited by 24 publications

References 32 publications

Combining thermal imaging and soil water content sensors to assess tree water status in pear trees

Combining thermal imaging and soil water content sensors to assess tree water status in pear trees

Diurnal Soybean Water Stress Computed Using Statistical-Based Thermal Indices With High-Frequency Unmanned Aircraft Flights

Using Aerial Thermal Imagery to Evaluate Water Status in Vitis vinifera cv. Loureiro

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