# Remote Sensing for Irrigation of Horticultural Crops
## 4 Approaches to Precision Irrigation
### Leaf Temperature Variability
In more stressful conditions (37 \({}^{\circ}\mathrm{C}\) and very low air humidity), the authors measured a difference of 13 \({}^{\circ}\mathrm{C}\) in 'Syrah' and 17 \({}^{\circ}\mathrm{C}\) in 'Malbec' (\(\mathrm{T_{nws}}-\mathrm{T_{air}}\)). [PERSON] and [PERSON] [163] report that a difference between canopy and air temperature of vines of about 17 \({}^{\circ}\mathrm{C}\), which is much higher than with \(\mathrm{T_{dry}}\) values assumed in other studies and slightly less than the energy balance models developed by [PERSON] [111]. \(\mathrm{T_{dry}}\) for calculation of the CWSI was estimated as \(\mathrm{T_{air}}+15\)\({}^{\circ}\mathrm{C}\) for both grape cultivars, resulting in a CWSI value between 0 and 1 for irrigation scheduling purposes. The CWSI value obtained was a good representation of a measure of plant water stress. [PERSON] et al. (2018) studied the effect of different irrigation treatments on grapevines for achieving a higher fruit quality when the vineyard was subjected to mild-to-moderate levels of water stress. The authors found a higher accuracy for determining CWSI combining thermal and visible images, and adopting the following assumptions: (i) CWSI calculated with air temperature +5 \({}^{\circ}\)C and (ii) T\({}_{\text{wet}}\) assumed to be the average temperature of the wet artificial reference surface. Other surface temperatures were obtained by wetting the canopy surface before thermal image acquisition and from the energy balance according to [PERSON] (1996). There was a stable linear relationship when T\({}_{\text{wet}}\) was derived from the energy balance and from image analysis of a wetted part of the canopy. The authors suggested in-depth study was needed to develop this calculation as a tool for irrigation management on a field scale. [PERSON] et al. (2015) reported that in case of no transpiration, the difference between the T\({}_{\text{air}}\) and the T\({}_{\text{crop}}\) averaged 2.8 \({}^{\circ}\)C (n = 25). [PERSON] et al. (2010) determined an average value of 4.6 \({}^{\circ}\)C for corn. [PERSON] et al. (2017) determined in a study of trickle-irrigated watermelon upper baseline limits of 3.3 and 3.4 \({}^{\circ}\)C. [PERSON] et al. (2017) preferred the approach suggested by [PERSON] et al. (2016), whereby leaves of two sampled grapevines were coated on both sides with petroleum jelly to prevent leaf transpiration and interrupt the transpiration-cooling phenomenon, simulating the leaf physiological response to water stress conditions. The authors report a variation in vineyard temperature range of the (T\({}_{\text{dry}}\) and T\({}_{\text{wet}}\)) h of about 1.3 \({}^{\circ}\)C and 2.4 \({}^{\circ}\)C, respectively. [PERSON] and [PERSON] (1996) adopted a neural model to estimate daily mean CWSI starting from well-watered leaf temperatures and air temperature plus 15 \({}^{\circ}\)C for a non-transpiring leaf temperature (between 13:00 and 15:00 MDT). They were able to discriminate between deficit irrigation amounts, irrigation events, and rainfall. In contrast, [PERSON] et al. (2013) estimated the lower boundary temperature, representing the temperature of fully transpiring leaves, while the temperature of a non-transpiring leaf (T\({}_{\text{dry}}\)) was determined by air temperature at + 6 \({}^{\circ}\)C.  
[PERSON] et al. (2014) found T\({}_{\text{c}}-\)T\({}_{\text{air}}\) of well-irrigated grapes was effectively determined as T\({}_{\text{c}}-\)T\({}_{\text{air}}=0695-1.575\times\)VPD. [PERSON] et al. (2016) derived an instantaneous CWSI using air temperature, relative humidity, and solar radiance. T\({}_{\text{wet}}\) reference were empirically found using well-watered plants, while a standardized T\({}_{\text{dry}}\) reference of 5 \({}^{\circ}\)C above air temperature was utilized to represent the upper leaf temperature. The same results were obtained by [PERSON] et al. (2019) with an upper baseline of 5\({}^{\circ}\)C and a linear relation with VPD. [PERSON] et al.