Development of crop water stress index of wheat crop for scheduling irrigation using infrared thermometry

Gontia, Narendra Kumar; Tiwari, K. N.

doi:10.1016/j.agwat.2008.04.017

Cited by 128 publications

(54 citation statements)

References 11 publications

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“…CWSI has been used for assessing the water status of crops，such as grapevine [8,9] , wheat [10] , maize [11] and cotton. The CWSI [12] commonly varied between 0 and 1.…”

Section: Sitementioning

confidence: 99%

Irrigation Decision-making Methods Based on Multi-source Irrigation Information Fusion

Chen¹,

Wang²,

Sun³

et al. 2015

Proceedings of the 3rd International Conference on Advances in Energy and Environmental Science 2015

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“…CWSI has been used for assessing the water status of crops，such as grapevine [8,9] , wheat [10] , maize [11] and cotton. The CWSI [12] commonly varied between 0 and 1.…”

Section: Sitementioning

confidence: 99%

Irrigation Decision-making Methods Based on Multi-source Irrigation Information Fusion

Chen¹,

Wang²,

Sun³

et al. 2015

Proceedings of the 3rd International Conference on Advances in Energy and Environmental Science 2015

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“…A few studies have used an established CWSI value to trigger irrigations on soybean (Nielsen, 1990) and wheat (Garrot et al, 1994). Typically, the measurements were either instantaneous (Hattendorf et al, 1988;Nielsen, 1990;Farahani et al, 1993) or were taken as average values over a short interval usually near solar noon (Garrot et al, 1994;Olufayo et al, 1996;Ajayi and Olufayo, 2004;Gontia and Tiwari, 2008). Irrigation scheduling using the CWSI has not always been successful, and it has not become widely adopted.…”

Section: Introductionmentioning

confidence: 99%

“…This thermal stress index has been investigated to characterize plant water stress (Howell et al, 1986;Yuan et al, 2004;Möeller et al, 2007), estimate crop productivity and water stress relationships (Wanjura et al, 1990), and has been used as a tool for irrigation timing (Throssel et al, 1987;Nielsen, 1990;Garrot et al, 1994;Gontia and Tiwari, 2008), usually in its empirical form. The theoretical CWSI incorporates incoming solar radiation, relative humidity, air temperature, wind speed, canopy resistance at potential evapotranspiration, and crop height.…”

Section: Introductionmentioning

confidence: 99%

A crop water stress index and time threshold for automatic irrigation scheduling of grain sorghum

O’Shaughnessy

Evett

Colaizzi

et al. 2012

Agricultural Water Management

119

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a b s t r a c tVariations of the crop water stress index (CWSI) have been used to characterize plant water stress and schedule irrigations. Usually, this thermal-based stress index has been calculated from measurements taken once daily or over a short period of time, near solar noon or after and in cloud free conditions. A method of integrating the CWSI over a day was developed to avoid the noise that may occur if weather prevents a clear CWSI signal near solar noon. This CWSI and time threshold (CWSI-TT) was the accumulated time that the CWSI was greater than a threshold value (0.45); and it was compared with a time threshold (CWSI-TT) based on a well-watered crop. We investigated the effectiveness of the CWSI-TT to automatically control irrigation of short and long season grain sorghum hybrids (Sorghum bicolor (L.) Moench, NC+ 5C35 and Pioneer 84G62); and to examine crop response to deficit irrigation treatments (i.e. 80%, 55%, 30% and 0% of full replenishment of soil water depletion to 1.5-m depth). Results from automated irrigation scheduling were compared to those from manual irrigation based on weekly neutron probe readings. In 2009, results from the Automatic irrigation were mixed; biomass yields in the 55% and 0% treatments, dry grain yields in the 80% and 0% treatments, and WUE in the 80%, 55%, and 0% treatments were not significantly different from those in the corresponding Manual treatments. However, dry grain yields in the 55% and 30% treatments were significantly less than those in the Manual control plots. These differences were due mainly to soil water variability in the beginning of the growing season. This conclusion is reinforced by the fact that IWUE for dry grain yield was not significantly different for 30% and 55% treatments, and was significantly greater for Automatic control at 80%. In 2010, there were no significant differences in biomass, dry grain yield, WUE, or IWUE for irrigation control methods when compared across the same amount treatments. Similar results between irrigation methods for at least the highest irrigation rate (80% of soil water depletion) in 2009 and among all irrigation treatment amounts in 2010 indicate that the CWSI-TT method can be an effective trigger for automatically scheduling either full or deficit irrigations for grain sorghum in a semi-arid region.Published by Elsevier B.V.

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“…They are thus able to provide accurate enough information for both assessing plant water status in the field and implementing appropriate irrigation management strategies [4][5][6][7]. The crop water stress index (CWSI), a thermally-derived indicator of water deficit based on leaf/canopy temperature measurements [2] has been used to assess the water status of crops such as grapevines [8], French beans [9], wheat [10], rice [11], maize [12] and cotton [13].…”

Section: Introductionmentioning

confidence: 99%

Estimation of Water Stress in Grapevines Using Proximal and Remote Sensing Methods

et al. 2018

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Abstract:In light of climate change and its impacts on plant physiology, optimizing water usage and improving irrigation practices play a crucial role in crop management. In recent years, new optical remote sensing techniques have become widespread since they allow a non-invasive evaluation of plant water stress dynamics in a timely manner. Unmanned aerial vehicles (UAV) currently represent one of the most advanced platforms for remote sensing applications. In this study, remote and proximal sensing measurements were compared with plant physiological variables, with the aim of testing innovative services and support systems to farmers for optimizing irrigation practices and scheduling. The experiment, conducted in two vineyards located in Sardinia, Italy, consisted of two regulated deficit irrigation (RDI) treatments and two reference treatments maintained under stress and well-watered conditions. Indicators of crop water status (Crop Water Stress Index-CWSI-and linear thermal index) were calculated from UAV images and ground infrared thermal images and then related to physiological measurements. The CWSI values for moderate water deficit (RDI-1) were 0.72, 0.28 and 0.43 for 'Vermentino', 'Cabernet' and 'Cagnulari' respectively, while for severe (RDI-2) water deficit the values were 0.90, 0.34 and 0.51. The highest differences for net photosynthetic rate (Pn) and stomatal conductance (Gs) between RDI-1 and RDI-2 were observed in 'Vermentino'. The highest significant correlations were found between CWSI with Pn (R = −0.80), with Φ PSII (R = −0.49) and with Fv'/Fm' (R = −0.48) on 'Cagnulari', while a unique significant correlation between CWSI and non-photochemical quenching (NPQ) (R = 0.47) was found on 'Vermentino'. Pn, as well as the efficiency of light use by the photosystem II (PSII), declined under stress conditions and when CWSI values increased. Under the experimental water stress conditions, grapevines were able to recover their efficiency during the night, activating a photosynthetic protection mechanism such as thermal energy dissipation (NPQ) to prevent irreversible damage to the photosystem. The results presented here demonstrate that CWSI values derived from remote and proximal sensors could be valuable indicators for the assessment of the spatial variability of crop water status in Mediterranean vineyards.

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Development of crop water stress index of wheat crop for scheduling irrigation using infrared thermometry

Cited by 128 publications

References 11 publications

Irrigation Decision-making Methods Based on Multi-source Irrigation Information Fusion

Irrigation Decision-making Methods Based on Multi-source Irrigation Information Fusion

A crop water stress index and time threshold for automatic irrigation scheduling of grain sorghum

Estimation of Water Stress in Grapevines Using Proximal and Remote Sensing Methods

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