The crop water stress index (CWSI) for drip irrigated cotton in a semi-arid region of Turkey

Self-organizing map estimator for the crop water stress index

ABSTRACTThe Crop Water Stress Index (CWSI) is a widely used method for quantifying crop water status and predicting yield. However, its evaluation across different irrigation methods and its stage‐specific response to crop yield is rarely evaluated. In this study, controlled field experiments were conducted on winter wheat using drip irrigation (DI) and flood irrigation (FI) during the 2021–2022 and 2022–2023 seasons in western Uttar Pradesh, India. The irrigation treatments included 50% MAD (maximum allowable depletion) (DI), 55% MAD (DI), 60% MAD (DI), 50% MAD (FI), local farmer's field replication (FI), rain‐fed, and well‐watered treatment (DI). The derived mean CWSI values for the irrigation treatments ranged from 0.03 to 0.66 in season 1 and 0.06 to 0.57 in season 2 across treatments. The seasonal mean CWSI for 50% MAD (DI) was 0.12 (season 1) and 0.11 (season 2), while 50% MAD (FI) yielded higher mean CWSI values of 0.29 (season 1) and 0.22 (season 2). The 50% MAD (DI) treatment produced the highest grain yield and water use efficiency in both seasons. A comprehensive analysis of stage‐specific CWSI values and grain yields revealed that grain yield was more sensitive to post‐heading CWSI as compared to pre‐heading CWSI values. Among the growth stages, CWSI values during the flowering stage were the most critical for predicting wheat yield. The study recommends that the CWSI values in the flowering and post‐heading stages are more relevant in predicting wheat yield accurately as compared to the pre‐heading and seasonal mean CWSI.

This study was designed to evaluate the crop water stress index (CWSI) for low-energy precision application (LEPA) irrigated corn (Zea mays L.) grown on slowly-permeable Pullman clay loam soil (fine, mixed, Torrertic Paleustoll) during the 1992 growing season at Bushland, Tex. The effects of six different irrigation levels (100%, 80%, 60%, 40%, 20%, and 0% replenishment of soil water depleted from the 1.5-m soil profile depth) on corn yields and the resulting CWSI were investigated. Irrigations were applied in 25 mm increments to maintain the soil water in the 100% treatment within 60–80% of the “plant extractable soil water” using LEPA technology, which wets alternate furrows only. The 1992 growing season was slightly wetter than normal. Thus, irrigation water use was less than normal, but the corn dry matter and grain yield were still significantly increased by irrigation. The yield, water use, and water use efficiency of fully irrigated corn were 1.246 kg/m2, 786 mm, and 1.34 kg/m3, respectively. CWSI was calculated from measurements of infrared canopy temperatures, ambient air temperatures, and vapor pressure deficit values for the six irrigation levels. A “non-water-stressed baseline” equation for corn was developed using the diurnal infrared canopy temperature measurements as Tc–Ta = 1.06–2.56 VPD, where Tc was the canopy temperature (°C), Ta was the air temperature (°C) and VPD was the vapor pressure deficit (kPa). Trends in CWSI values were consistent with the soil water contents induced by the deficit irrigations. Both the dry matter and grain yields decreased with increased soil water deficit. Minimal yield reductions were observed at a threshold CWSI value of 0.33 or less for corn. The CWSI was useful for evaluating crop water stress in corn and should be a valuable tool to assist irrigation decision making together with soil water measurements and/or evapotranspiration models.

Crop water stress index for watermelon

Field experiments were conducted in 2019 and 2021 growing seasons to evaluate the chlorophyll readings and crop water stress index (CWSI) response to full and deficit irrigation for drip-irrigated sugar beet (Beta vulgaris L.) under sub-humid climate of Bursa, Turkey. In addition, the changes of soil water content under different irrigation treatments and statistical relationships between chlorophyll and CWSI values and ETc, root yield and sugar yield were investigated. Experiments were carried out in a completely randomized blocks design with three replications. Irrigations were scheduled based on the replenishment of 100 (S1), 66 (S2), 33 (S3), and 0% (S4) of soil water depletion within the soil profile of 0–90 cm using 7 day irrigation intervals. Lower and upper baselines obtained by measurements based on the canopy temperature from the treatments full irrigated and non-irrigated were used to calculate CWSI. The variations in CWSI values were consistent with the variations of seasonal soil water contents induced by the different irrigation practices. CWSI values generally varied between 0 and 1 throughout the experimental periods. In 2019, seasonal mean chlorophyll readings varied between 203.3 and 249.1, and mean CWSI values varied between 0.12 and 0.85. In 2021, seasonal mean chlorophyll readings varied between 232.7 and 259.3 and mean CWSI values between 0.19 and 0.89. Unlike chlorophyll values, CWSI decreased with increased irrigation water amount. In both years, statistically significant relationships were determined between chlorophyll readings and CWSI and ETc, root yield and sugar yield. The greatest root yield was achieved with a seasonal mean CWSI value of 0.12. An exponential equation determined as “Root Yield = 10.804e−1,55CWSI” between seasonal average CWSI values and root yield can be used for estimation of root yield in sugar beet farming. The mean CWSI values determined by infrared thermometer technique can be used in determination of crop water stress and irrigation scheduling of sugar beet cultivation under sub-humid climatic conditions.

As the drought conditions persist in California and water continues to become less available, the development of methods to reduce water inputs is extremely important. Therefore, improving irrigation water use efficiency and developing water conservation strategies is crucial for maintaining urban green infrastructure. This two-year field irrigation project (2018–2019) focused on the application of optical and thermal remote sensing for turfgrass irrigation management in central California. We monitored the response of hybrid bermudagrass and tall fescue to varying irrigation treatments, including irrigation levels (percentages of reference evapotranspiration, ETo) and irrigation frequency. The ground-based remote sensing data included NDVI and canopy temperature, which was subsequently used to calculate the crop water stress index (CWSI). The measurements were done within two hours of solar noon under cloud-free conditions. The NDVI and canopy temperature data were collected 21 times in 2018 and 10 times in 2019. For the tall fescue, a strong relationship was observed between NDVI and visual rating (VR) values in both 2018 (r = 0.92) and 2019 (r = 0.83). For the hybrid bermudagrass, there was no correlation in 2018 and a moderate correlation (r = 0.72) in 2019. There was a moderate correlation of 0.64 and 0.88 in 2018 and 2019 between tall fescue canopy minus air temperature difference (dt) and vapor pressure deficit (VPD) for the lower CWSI baseline. The correlation between hybrid bermudagrass dt and VPD for the lower baseline was 0.69 in 2018 and 0.64 in 2019. Irrigation levels significantly impacted tall fescue canopy temperature but showed no significant effect on hybrid bermudagrass canopy temperature. For the same irrigation levels, increasing irrigation frequency slightly but consistently decreased canopy temperature without compromising the turfgrass quality. The empirical CWSI values violated the minimum expected value (of 0) 38% of the time. Our results suggest NDVI thresholds of 0.6–0.65 for tall fescue and 0.5 for hybrid bermudagrass to maintain acceptable quality in the central California region. Further investigation is needed to verify the thresholds obtained in this study, particularly for hybrid bermudagrass, as the recommendation is only based on 2019 data. No CWSI threshold was determined to maintain turf quality in the acceptable range because of the high variability of CWSI values over time and their low correlation with VR values.

Impact of soil water stress on Nigellone oil content of black cumin seeds grown in calcareous-gypsifereous soils

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.

Leaf temperature has long been recognized as an indicator of water availability. The stress level in a plant can be quantified from leaf temperature by using the crop water stress index (CWSI). In this study, it was investigated whether infrared thermometer measurements and accordingly CWSI could be used to create irrigation schedules for olive trees (cultivated variety Memecik). The research was conducted at the olive tree plantation of the Olive Research Station between 2009 and 2010. In the study, the effects of different irrigation treatments on the yield, canopy temperature, and CWSI of olive trees were investigated, and the optimum irrigation schedule was determined according to the findings. Seven different water application treatments were created using the drip irrigation method. Five treatments consisted of irrigating at a rate equivalent to 25% (S-0.25), 50% (S-0.50), 75% (S-0.75), 100% (S-1.00), and 125% (S-1.25) of the cumulative evaporation in 5 days from a Class A evaporation pan. The other two treatments consisted of a treatment in which the humidity lost at a soil depth of 0–90 cm was replenished each time to the field capacity (Control, S-C) and a treatment in which no irrigation was performed and cultivation was carried out under completely rain-based conditions (Stress, S-0). In the study, the amounts of irrigation water applied to the treatments ranged from 0 to 809 mm, and the crop water consumption values varied from 127 to 853 mm according to the average of both years. The highest water-use efficiency was obtained in the S-0 treatment, whereas the highest irrigation water–use efficiency was obtained from the S-0.50 treatment. One of the important findings of this study was that handheld infrared thermometer can be used for stress detection and irrigation scheduling of olive trees. When the mean CWSI values in the experimental years were examined in terms of the irrigation treatments, the CWSI values ranged from 0 to 0.68 in 2009 and from 0.02 to 0.71 in 2010. In both years, the highest values were recorded in the S-0 treatment, and the lowest values in the S-1.25 treatment. When water-use efficiency is evaluated along with CWSI values, irrigation can be recommended at half of the evaporation from a Class A evaporation pan (S-0.50, when CWSI values reach 0.39). In conditions in which water sources are insufficient, it can be recommended that irrigation be started when evaporation is a quarter (S-0.25), that is, when CWSI values reach 0.49.

This study was carried out to evaluate the use of the crop water stress index (CWSI) for irrigation scheduling of sugar beet for two years under the semi arid climate of Iran. Statistical relationships between CWSI and yield, quality parameters and irrigation water use efficiency (IWUE) were investigated. Irrigations were scheduled based on 100 (I100), 85 (I85), 70 (I50) and 0% (I0) of plant water requirement. CWSI values were calculated from the measurements of canopy temperatures by infrared thermometer, air temperatures and vapor pressure deficit values for all the irrigated treatments. The highest IWUE was found in I70 with 9.16 and 1.66 kg m−3 for the root and sugar yield, respectively, in 2013. A non-water stressed baseline (lower line) equation for sugar beet was measured from full irrigated plots as (Tc − Ta)ll = −0.832VPD + 2.1811; R2 = 0.6508. There was a high determination coefficient between CWSI with the root and sugar yield and IWUE. The CWSI could be used to determine the irrigation time of sugar beet, and 0.3 could be offered as a threshold value. Results indicated that the CWSI can be used to evaluate crop water stress and improve irrigation scheduling for sugar beet under semiarid conditions.

An experiment was conducted to determine the effect of water stress on yield and various physiological parameters, including the crop water stress index for tomatoes in the Central Anatolian region of Turkey. For this purpose, the irrigation schedule used in this study includes 120%, 100%, 80%, and 60% (I120, I100, I80, I60) of evaporation from the gravimetrically. Water deficit was found to cause a stress effect in tomato plants, which was reflected in changes in plants’ morphological and pomological function (such as stem diameter, fruit weight, pH, titratable acidity, and total soluble solids). Irrigation levels had a significant effect on the total yield of tomatoes. The lowest water use efficiency (WUE) was obtained from the I60, while the highest WUE was found in the I100 irrigation level. The CWSI was calculated using an empirical approach from measurements of infrared canopy temperatures, ambient air temperatures, and vapor pressure deficit values for four irrigation levels. The crop water stress index (CWSI) values ranged from −0.63 to a maximum value of 0.53 in I120, from −0.27 to 0.63 in I100, from 0.06 to 0.80 in I80, and from 0.37 to 0.97 in I60. There was a significant relation between yield and CWSI. The yield was correlated with mean CWSI values, and the linear equation Total yield = −2398.9CWSI + 1240.4 can be used for yield prediction. The results revealed that the CWSI value was useful for evaluating crop water stress in tomatoes and predicting yield.

This study was conducted to develop baseline equations, which can be used to quantify crop water stress index (CWSI) for evaluating crop water stress in three winter wheat genotypes (Triticum aestivum L.) and to schedule irrigation and predict yield. Plants were grown under basin irrigation and subjected to five water treatments ranging from 100 to 0 % (100, 75, 50, 25, 0 %) replacement of evapotranspirational losses within 0.90 m soil profile. The highest yield and water use was obtained under fully irrigated conditions (100 % replenishment of soil water depleted). The lower (non-stressed) and upper (stressed) baselines were determined empirically from measurements of canopy and ambient air temperatures and vapour pressure deficit (VPD) on fully watered plants (100%) and under maximum water stress (0 %), respectively. The CWSI was determined by using the empirical approach for the five irrigation levels. The yield was directly correlated with the mean CWSI values and the linear equation for three genotypes (Saraybosna, Kate-A-1 and F-85), “Y = 1463.3 - 1062.3 CWSI”, “Y = 1483.8 - 1052.8 CWSI” and “Y = 1701.8 - 1367.7 CWSI” can be used for the yield prediction. CWSI values may also provide a valuable tool for monitoring water status and planning irrigation scheduling for wheat.

The canopy temperatures of rice were observed by the infrared temperature measuring equipment under different irrigation conditions in this experiment, and also it applied the CWSI empirical model and theoretical model to measure whether the crop were suffered from water stress or not. Meanwhile, in this paper, it gave a compare of these two models on the effect of monitoring rice water stress. The result showed that under non-ideal condition, the CWSI value of the empirical model was very volatile and often overflowed the range of 0-1, however, the theoretical model was relatively stable. So it concluded that the CWSI theoretical model was much suitable for the application on monitoring the rice water stress. The results showed that the theoretical model has a good relation with the above indexes, and it can reflect the characteristics of the crop water stress. In addition, some practical experience and viewpoints were given in this paper.

This study was designed to evaluate different threshold values of crop water stress index (CWSI) to schedule irrigation for watermelon (Citrullus vulgaris) grown with drip irrigation Irrigations were started when CWSI values reached to 0.2, 0.4, 0.6, 0.8 and 1.0 (non-irrigation). The CWSI values were computed from measurements of canopy temperature, air temperature and vapor pressure defi cit. The total irrigations amount of 342, 280, 248 and 193 mm were applied to the 0.2, 0.4, 0.6 and 0.8 CWSI treatments, respectively. The maximum seasonal evapotranspiration (ET) as 412 mm was measured from 0.2 CWSI treatment. Irrigation levels signifi cantly affected fruit yield. Although the highest fruit yield (76.3 t ha-1) was obtained from the 0.2 CWSI treatment, the 0.4 and 0.6 of CWSI treatments were statistically in the same letter group with this treatment. Also, maximum water use effi ciency (WUE) and irrigation water use efficiency (IWUE) were obtained from 0.6 of CWSI treatment as 22.1 and 13.3 kg m-3, respectively. Therefore, based on these results, 0.6 of CWSI value should be used for irrigation time of watermelon under Tekirdag, Turkey conditions.

Highlights Empirical CWSI was developed for 'Westcoaster' tall fescue and ‘Tifgreen’ hybrid bermudagrass. The canopy temperature of both species was monitored under multiple irrigation scenarios. Deficit irrigation might reduce the cooling benefits of irrigated urban lawns. Abstract. Canopy temperature provides valuable information for efficient irrigation management and for detecting drought injury in a fast and non-destructive way. It also helps quantify the trade-offs between water conservation and the cooling benefit of the irrigated urban landscape, a critical issue in semiarid inland southern California with limited available water resources. Two adjacent hybrid bermudagrass and tall fescue irrigation trials were conducted to determine canopy temperature changes under a wide range of irrigation treatments from 2017 to 2019 in Riverside, California, USA. The canopy temperature data were also used to develop an empirical crop water stress index (CWSI) for each species. The CWSI values ranged from -0.15 to 0.71 for tall fescue and from -0.28 to 0.54 for hybrid bermudagrass. We observed a moderate correlation between visual rating scores (VR) and CWSI values for tall fescue (r = -0.68) and hybrid bermudagrass (r = -0.61). The fitted linear regression between VR and CWSI data suggested CWSI thresholds close to zero for both species to maintain their acceptable visual quality. The irrigation level consistently showed a significant effect on canopy temperature for both species. On average, a 10% decrease in irrigation application increased the canopy temperature of tall fescue and hybrid bermudagrass by 1.3°C and 0.9°C, respectively. Therefore, deficit irrigation might reduce the cooling benefits of irrigated urban lawns in the semiarid climate of inland southern California. Keywords: Canopy temperature, Evapotranspiration, Smart irrigation controller, Urban heat island, Urban irrigation, Water conservation.