Thermal imaging at plant level to assess the crop-water status in almond trees (cv. Guara) under deficit irrigation strategies

García-Tejero, Iván Francisco; Rubio, A.E.; Viñuela, I.; Hernández, A.; Gutiérrez-Gordillo, Saray; Rodríguez-Pleguezuelo, Carmen Rocío; Durán-Zuazo, Víctor Hugo

doi:10.1016/j.agwat.2018.06.002

Cited by 79 publications

(71 citation statements)

References 45 publications

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“…Several studies have shown that there is a high correlation between stomatal conductance and CWSI calculated from thermal images [9,29,41]. The stomatal conductance was measured to further validate the accuracy of the different CWSI types in this paper.…”

Section: Relationships Between Cwsi and Cotton Physiological Indicatorsmentioning

confidence: 79%

Simplified Evaluation of Cotton Water Stress Using High Resolution Unmanned Aerial Vehicle Thermal Imagery

et al. 2019

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Irrigation water management and real-time monitoring of crop water stress status can enhance agricultural water use efficiency, crop yield, and crop quality. The aim of this study was to simplify the calculation of the crop water stress index (CWSI) and improve its diagnostic accuracy. Simplified CWSI (CWSIsi) was used to diagnose water stress for cotton that has received four different irrigation treatments (no stress, mild stress, moderate stress, and severe stress) at the flowering and boll stage. High resolution thermal infrared and multispectral images were taken using an Unmanned Aerial Vehicle remote sensing platform at midday (local time 13:00), and stomatal conductance (gs), transpiration rate (tr), and cotton root zone soil volumetric water content (θ) were concurrently measured. The soil background pixels of thermal images were eliminated using the Canny edge detection to obtain a unimodal histogram of pure canopy temperatures. Then the wet reference temperature (Twet), dry reference temperature (Tdry), and mean canopy temperature (Tl) were obtained from the canopy temperature histogram to calculate CWSIsi. The other two methods of CWSI evaluation were empirical CWSI (CWSIe), in which the temperature parameters were determined by measuring natural reference cotton leaves, and statistical CWSI (CWSIs), in which Twet was the mean of the lowest 5% of canopy temperatures and Tdry was the air temperature (Tair) + 5 °C. Compared with CWSIe, CWSIs and spectral indices (NDVI, TCARI, OSAVI, TCARI/OSAVI), CWSIsi has higher correlation with gs (R2 = 0.660) and tr (R2 = 0.592). The correlation coefficient (R) for θ (0–45 cm) and CWSIsi is also high (0.812). The plotted high-resolution map of CWSIsi shows the different distribution of cotton water stress in different irrigation treatments. These findings demonstrate that CWSIsi, which only requires parameters from a canopy temperature histogram, may potentially be applied to precision irrigation management.

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Section: Relationships Between Cwsi and Cotton Physiological Indicatorsmentioning

confidence: 79%

Simplified Evaluation of Cotton Water Stress Using High Resolution Unmanned Aerial Vehicle Thermal Imagery

et al. 2019

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“…In the context of precision agriculture, the application of UAS, their future prospects, and knowledge gaps are discussed in [53,[78][79][80][81]. While many horticultural crops have been studied using UAS technology, the most studied horticultural crops are vineyards [31,[82][83][84], citrus [85,86], peach [32,33], olive [18,87,88], pistachio [89,90], and almond [91][92][93][94], among others [95][96][97][98][99]. Some of the UAS types used for water status studies of horticultural crops are shown in Figure 2.…”

Section: Unmanned Aircraft Systemsmentioning

confidence: 99%

“…The CWSI is normalised within zero and one, whereas I g and I3 represent stress using numbers between zero and infinity. CWSI has been adopted most widely in horticultural applications to assess the water status of crops, such as the grapevines [100,213], almond [91,198], citrus [85,110], and others [18,87,99,214]. By normalising between the lower and upper limits of (T c − T a ), the CWSI of the canopy presents quantifiable relative water stress.…”

Section: Normalised Thermal Indicesmentioning

confidence: 99%

A Review of Current and Potential Applications of Remote Sensing to Study the Water Status of Horticultural Crops

Gautam

Pagay

2020

Agronomy

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With increasingly advanced remote sensing systems, more accurate retrievals of crop water status are being made at the individual crop level to aid in precision irrigation. This paper summarises the use of remote sensing for the estimation of water status in horticultural crops. The remote measurements of the water potential, soil moisture, evapotranspiration, canopy 3D structure, and vigour for water status estimation are presented in this comprehensive review. These parameters directly or indirectly provide estimates of crop water status, which is critically important for irrigation management in farms. The review is organised into four main sections: (i) remote sensing platforms; (ii) the remote sensor suite; (iii) techniques adopted for horticultural applications and indicators of water status; and, (iv) case studies of the use of remote sensing in horticultural crops. Finally, the authors' view is presented with regard to future prospects and research gaps in the estimation of the crop water status for precision irrigation.

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“…The CWSI found wide application possibilities [34], among others, in determining the needs of the irrigation of agricultural and horticultural crops [35,36]. The wide range of CWSI applications in addition to agricultural crops includes its use in assessing the water status of trees: Fruit orchards [37,38], olive [39], and almond trees [40]. The advantage of CWSI application is it requires only basic meteorological parameters (air temperature and relative humidity), canopy temperature, and limiting cases derived empirically [41] or theoretically [42].…”

Section: Introductionmentioning

confidence: 99%

Remotely Sensed Land Surface Temperature-Based Water Stress Index for Wetland Habitats

et al. 2020

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Despite covering only 2–6% of land, wetland ecosystems play an important role at the local and global scale. They provide various ecosystem services (carbon dioxide sequestration, pollution removal, water retention, climate regulation, etc.) as long as they are in good condition. By definition, wetlands are rich in water ecosystems. However, ongoing climate change with an ambiguous balance of rain in a temperate climate zone leads to drought conditions. Such periods interfere with the natural processes occurring on wetlands and restrain the normal functioning of wetland ecosystems. Persisting unfavorable water conditions lead to irreversible changes in wetland habitats. Hence, the monitoring of habitat changes caused by an insufficient amount of water (plant water stress) is necessary. Unfortunately, due to the specific conditions of wetlands, monitoring them by both traditional and remote sensing techniques is challenging, and research on wetland water stress has been insufficient. This paper describes the adaptation of the thermal water stress index, also known as the crop water stress index (CWSI), for wetlands. This index is calculated based on land surface temperature and meteorological parameters (temperature and vapor pressure deficit—VPD). In this study, an unmanned aerial system (UAS) was used to measure land surface temperature. Performance of the CWSI was confirmed by the high correlation with field measurements of a fraction of absorbed photosynthetically active radiation (R = −0.70) and soil moisture (R = −0.62). Comparison of the crop water stress index with meteorological drought indices showed that the first phase of drought (meteorological drought) cannot be detected with this index. This study confirms the potential of using the CWSI as a water stress indicator in wetland ecosystems.

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Thermal imaging at plant level to assess the crop-water status in almond trees (cv. Guara) under deficit irrigation strategies

Cited by 79 publications

References 45 publications

Simplified Evaluation of Cotton Water Stress Using High Resolution Unmanned Aerial Vehicle Thermal Imagery

Simplified Evaluation of Cotton Water Stress Using High Resolution Unmanned Aerial Vehicle Thermal Imagery

A Review of Current and Potential Applications of Remote Sensing to Study the Water Status of Horticultural Crops

Remotely Sensed Land Surface Temperature-Based Water Stress Index for Wetland Habitats

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