CORN. Determination of Crop Water Stress Index for Irrigation Timing and Yield Estimation of Corn. Suat Irmak,* Dorota Z. Haman, and Ruhi Bastug

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1 CORN Determination of Crop Water Stress Index for Irrigation Timing and Yield Estimation of Corn Suat Irmak,* Dorota Z. Haman, and Ruhi Bastug ABSTRACT the past decades, lightweight, hand-held, portable, and Corn (Zea mays L.) grown under a Mediterranean semiarid climate battery operated infrared thermometers (IRT) became requires supplemental irrigation to maximize the grain yield. Since available. Infrared thermometers can rapidly measure the cost of irrigation application has been increasing, elimination of canopy temperatures over large areas. The theory of unnecessary irrigation applications would improve economics of corn IRT operation (Fuchs and Tanner, 1966; Fuchs et al., production. There has been much interest in the crop water stress 1967; Hatfield, 1990; Gardner and Shock, 1989); and index (CWSI) as a potential tool for irrigation scheduling and yield (Gardner et al., 1992a) and temperature effects in infraestimation. An experiment was conducted to monitor and quantify red thermometry (Jackson and Idso, 1969) have been water stress, and to develop parameters for irrigation scheduling and discussed. In the 1980s, the use of IRT become more grain yield of summer-grown corn as a function of CWSI under Mediroutine in irrigation scheduling when Idso et al. (1981a) terranean semiarid cropping conditions. Three irrigation treatments were based on replenishing the 0.9-m deep root zone to field capacity developed and demonstrated an empirical method for when the soil water level dropped to 25, 50, and 75% of available using the crop water stress index (CWSI). water holding capacity (AWHC). A dryland treatment was also included. Idso et al. (1981a) observed a linear relationship bemeasured The lower (nonstressed) and upper (stressed) baselines were tween canopy minus air (T c T a ) temperature differ- to calculate CWSI. An equation that can be used to calculate ences and vapor pressure deficit (VPD) of the air for the yield potential of summer-grown corn under a Mediterranean well irrigated plants transpiring at potential rate during climate was developed using the relationship between the corn grain the daylight hours. As soil moisture was depleted, the yield and the seasonal mean CWSI. Permitting the seasonal average (T c T a ) vs. VPD relationship deviated from the linear CWSI value to exceed more than 0.22 resulted in decreased corn nonstressed baseline condition. The empirical CWSI grain yield. The CWSI behaved as expected, dropping to near zero following an irrigation and increasing gradually as corn plants depleted uses two baselines. The lower baseline represents the soil water reserves. We concluded that CWSI is a useful tool to monitor maximum rate of transpiration of a well watered crop and quantify the water stress of corn under a Mediterranean climate. and the upper baseline represents the T c T a of a canopy with no transpiration and for which the canopy temperature does not respond to VPD. The CWSI varies from Effective use of irrigation water is rapidly becoming 0 to 1 with 1 representing a plant having no transpiration an issue in Mediterranean regions and a method loss and 0 representing a plant transpiring at the maxi- for irrigation scheduling based on the CWSI has been mum rate. The CWSI has been correlated to yield suggested. Because of its climatic adaptation and high (Walker and Hatfield, 1983; Smith et al., 1985), leaf yields, irrigated corn has been grown for many years in water potential (Pinter and Reginato, 1981; O Toole southern Turkey. Since 1985 irrigated corn production et al., 1984; Jackson, 1991), and soil water availability in this region has expanded to ha (Irmak, 1996). (Hatfield, 1983; Reginato and Garrot, 1987). Although corn is one of the most widely grown feed Since the development of the CWSI method, many grains produced under irrigation in this region, not researchers have used it for irrigation management enough information is available to quantify water stress (Pinter and Reginato, 1982; Reginato, 1983; Howell et at the different soil water conditions to estimate grain al., 1984; O Toole et al., 1984; Reginato and Howe, yield and to schedule irrigations for corn based on 1985; Reginato and Garrett, 1987; Wanjura et al., 1990). the CWSI. However, it is often reported that early season CWSI A technique to measure plant water stress should values are particularly difficult to obtain because of provide nondestructive, rapid, and reliable estimates of partial canopy covers. In the early growing season, when plant water status. During the 1960s, infrared technolthe soil surface may be viewed by the IRT when T c plants are small, or for low plant populations, a part of ogy advanced rapidly, and instruments that could be used for agricultural purposes (to measure crop canopy measurements are made. Hatfield et al. (1985) detertemperature) became commercially available. During mined unstressed baselines of the CWSI for cotton un- der full and incomplete ground cover and reported that unstressed baselines for full ground cover had slopes S. Irmak and D.Z. Haman, Dep. of Agric. and Bio. Eng., Univ. of Florida, P.O. Box , Gainesville, FL 32611; R. Bastug, Faculty about twice those under partial canopy cover. They conof Agric., Univ. of Akdeniz, Antalya, Turkey, Florida Agric. Exp. Stn. Journal Ser. no. R Received 20 Nov *Correwater Abbreviations: AWHC, available water holding capacity; CWSI, crop sponding author (aysu@grove.ufl.edu). stress index; RMSE, root mean square error; SD, standard deviation; T a, air temperature; T c, canopy temperature; VPD, vapor Published in Agron. J. 92: (2000). pressure deficit. 1221

2 1222 AGRONOMY JOURNAL, VOL. 92, NOVEMBER DECEMBER 2000 cluded that partial canopy is a very complex system and MATERIALS AND METHODS the CWSI is overestimated when the crop is at less than The experiment was conducted during the summer of 1995 full cover which could lead to an overapplication of at the Mediterranean Agricultural Research Station located irrigation water. On the other hand, for some crops, a in Antalya, Turkey (36 55, 34 55, and altitude: 12 m). The single baseline has been used successfully for the entire region has a typical Mediterranean semiarid climate with an growing season. However, there are some serious diffi- average annual rainfall of 1068 mm. culties using only one baseline for the entire growing A single cross white corn (var. Antbey) was planted on 25 season (Gardner et al., 1992a). June 1995 following sorghum [Sorghum bicolor (L.) Moench]. It is reported that corn is relatively tolerant to water Time to 50% flowering is 50 to 67 d, average growing season stress in the vegetative stage, very sensitive during the is 120 to 130 d, maximum plant height is 2 to 2.3 m, cob height is 0.95 to 1.10 m, and the variety is not drought adapted. The period of tasseling, silking, and pollination, and moderexperiment was designed as a randomized complete block ately sensitive during the grain-filling stage (Shanahan with three replications for each treatment. There were 180 and Nielsen, 1987). Heermann and Duke (1978) used plants in each plot (7 by 4.90 m) and plant spacing was 0.75 m the average T c T a values between treatment plots and between the rows and 0.25 m within the rows. There were eight adjoining well-watered areas to study crop water stress rows in each plot; and two additional rows were maintained as under limited irrigation for corn plants irrigated by a guard rows at each side of the plot. The seeds were planted center-pivot irrigation system. They reported that the at the depth of 0.07 to 0.08 m. Plots were maintained in beds average temperature difference (T c T a ) elevation was and furrows to ensure uniform water distribution. Irrigation linearly related to irrigation and to relative dry-matter water was applied with furrow irrigation and total water to yield. They concluded that an average T each plot was measured with a TS-324 model flow meter c T a 1.5 C (Teksan, Inc., Istanbul, Turkey). 1 Gravimetric soil moisture was significantly correlated with grain yield reduction. samples were taken in each plot at 0 to 0.30 m depth. A neutron Geiser et al. (1982) compared the temperature differscattering moisture gauge (Model 4300, Troxler Electronic ence (T c T a ) method with resistance blocks and a water Laboratories, Inc., Raleigh, NC) was used to measure soil balance (checkbook) method of irrigation scheduling. moisture at depths of 0.60 and 0.90 m. Aluminum access tubes They concluded that water balance and resistance block were installed in the center of each plot. The neutron probe methods required additional water applications of 39 was calibrated at the beginning of the growing season for the and 18%, respectively, compared to the temperature experimental field by correlating probe readings with volumetdifference method. Gardner et al. (1981b) and Blad et ric water content of soil samples (100 cm 3 ) taken. The calibra- al. (1981) tested the deviation of midday canopy temper- tion equation for the neutron probe was WC (CR 0.065) / ature as an irrigation scheduling tool for corn plants (r , n 15, RMSE 0.022, WC volumetric water content by m 3 m 3, and CR count ratio). They found standard deviations of 0.3 C in well irrigated Field plot experiments were conducted on clay soil (47% and 4.2 C in nonirrigated corn plots. They concluded clay, 36% silt, and 17% sand) that received a 68 mm irrigation that plots that showed a standard deviation 0.3 C re- before planting. Four soil samples from each depth (0 120 cm quired irrigation. with 30 cm increments) at five different locations were taken Gardner et al. (1981a) correlated grain yields of corn from the experimental field in order to determine the soil plants with differences in canopy temperature (T c ) be- properties (Table 1). Soil particle size analysis and bulk density tween stressed and well-irrigated plants grown under (Black et al., 1965) were determined for each soil depth. Field different irrigation regimes. Midday differences in daily capacity (FC) and permanent wilting point (PWP) were also T c during the pollination and grain-filling stages were determined for each soil depth at 33 and 1500 kpa soil water effectively used to calculate grain yield with an accuracy tension using the pressure chamber method. Porosity, f, of each soil depth was calculated using the relationship f [1 of 10%. They also observed yield reduction when the ( b / s )] * 100 ( b bulk density, g cm 3, and s density of canopy temperature increased between the onset of tassolids, 2.65 g cm 3 ). Plots were fertilized with 400 kg ha 1 seling and the end of grain-filling stages. Clawson and of NH 4 NO 3 (ammonium nitrate) before planting. Irrigation Blad (1982) reported less water use (156 mm) in corn treatments were established to refill a 0.9 m depth rooting plots for which irrigations were scheduled based on the zone when soil water had depleted to given percentages of canopy temperature compared to a neutron probe the available water holding capacity (AWHC) in this rooting scheduled plot. They suggested that using canopy temsoil zone. Treatments designated S 1,S 2, and S 3 were irrigated when perature variability to initiate irrigation has the potential water dropped to 75, 50, and 25% of AWHC, respectively. for significant water savings due to improved effitreatments only (S 1,S 2, and S 3 ) on 20 July. A fourth treatment, In addition, 45 mm irrigation was applied to the irrigation ciency in the use of available soil water. S 4, was not irrigated after planting. Table 2 shows the irrigation Productivity response to water stress is different for dates and total amount of water applied (mm) to the experieach crop and this response is expected to vary with the mental plots. The total amount of applied water ranged from climate. Therefore, the critical values of CWSI should 68 to 441 mm. be determined for a particular crop in different climates Canopy temperatures ( C) were measured using a Model and soils to use it in yield prediction and irrigation 210 Ag Multimeter (Everest Interscience Inc., Fullerton, CA) scheduling. The objectives of this experiment were to portable hand-held infrared thermometer. The instrument has monitor and quantify water stress, and to develop parameters a field of view of 15 (can be adjusted to 4 ), a sensing window to estimate irrigation timing and grain yield of summer-grown corn as a function of CWSI under 1 The mention of trade names or commercial products is solely for Mediterranean semiarid cropping conditions using the the information of the reader and does not constitute an endorsement method developed by Idso et al. (1981a). or recommendation for use.

3 IRMAK ET AL.: DETERMINATION OF CROP WATER STRESS INDEX 1223 Table 1. Soil physical properties at Antalya, Turkey, including porosity, field capacity (FC), and permanent wilting point (PWP). Particle-size fractions Soil depth Bulk density Porosity Sand Silt Clay Soil texture FC PWP cm g cm 3 % Kg Kg 1 m 3 m C SiCL SiCL SiCL SiCL , Field capacity at 33 kpa, and permanent wilting point at 1500 kpa soil water tension, respectively. of 10.5 to 12.5 m, and a resolution of 0.1 C. The instrument The lower (nonstressed) and upper (stressed) basewas calibrated using a method described by Blad and Rosen- lines (Fig. 1) were measured for corn and the CWSI berg (1976). In each measurement the infrared thermometer values were calculated using this diagram as the relative was held above the plant canopy at an angle of 15 below the value between upper and lower baselines relating the horizontal so that plant parts, but no soil were viewed. Canopy difference between canopy (T c ) and air (T a ) temperatemperature (T c ) measurements were taken at each plot starttures ( C) to vapor pressure deficit (VPD, kpa) as outing from the early pollination stage when the ground cover was 100% and the corn plant height was approximately 1.2 m lined by Idso et al. (1981a). To develop the lower (non- (27 July) and continued until 11 September. In each measurevapor pressure deficits were selected as a subset of T c stressed) baseline in Fig.1, the leaf temperatures and ment, five canopy temperature measurements were taken from the east and five readings from the west, and then aver- data obtained on clear days when the treatments were aged. At each measurement time, dry and wet-bulb tempera- assumed to be nonstressed. The measurements were tures were taken above the canopy surface using an Assman taken from the treatment S 2 (although irrigated at 50% psychrometer (Qualimetrics Inc., Sacramento, CA) to deter- of available water holding capacity, treatment S 2 remine air temperature (T a ) and vapor pressure deficit (VPD). ceived the most water, had the highest yield, and was Grain yields, adjusted to 15.5% dry mass grain moisture, the least stressed), at 1200 h and 1300 h assuming that were determined from subplots hand harvested and hand shelled from each plot on 25 October. Four rows from the the VPD was at maximum for the day. This is the time middle of the each plot were selected for harvest to avoid of the day when water stress is likely to be the highest any edge effects. Harvest rows were 6.60 m in length. Yield and when the need for irrigation using CWSI should be response to treatments was analyzed by analysis of variance(anova). determined. Then, the differences between T c and T a When ANOVA identified treatment effects, were linearly correlated with VPD (Fig. 1). The resulting Duncans Multiple Range Test (DMRT) was used to identify baseline was described by the linear equation T c T a which treatments differed at the 5% significance level VPD (r , n 28, RMSE 0.415, P 0.01, SD 1.33), where T c T a is in C and VPD RESULTS AND DISCUSSION is in kpa. Idso (1982) reported the following relationship between T c T a and VPD for corn in Arizona:T c T a The weekly summary of the weather data measured VPD for sunlit and no tassels conditions. daily at the weather station located nearby the experi- The intercept was higher and the slope was lower than mental site is given in the Table 3. No rain occurred during the growing season. Table 3. Weekly summary of the 1995 weather data measured daily during the experiment at Antalya, Turkey. Table 2. Irrigation amount (mm) applied for different treatments Relative Wind during the 1995 growing season for Antbey corn grown at Month Week Temperature humidity Irradiance speed Antalya, Turkey. C % MJ m 2 d 1 ms 1 Treatments June Date S 1 S 2 S 3 S mm July 28 July August August August August August September September September 41 September September September Season total October This amount also includes 68 mm of water from preplant irrigation for all the treatments. On 20 July, irrigation treatments (S 1,S 2, and S 3 ) received additional 45 mm of irrigation water. No rain occurred during the growing season. Treatments S 1,S 2, and S 3 were irrigated when soil water dropped to 75, No rain occurred during the growing season. 50, and 25% of available water holding capacity, respectively. S 4 was Weekly average values were calculated from daily average values for not irrigated after the 68 mm preplant irrigation. each weather parameter.

4 1224 AGRONOMY JOURNAL, VOL. 92, NOVEMBER DECEMBER 2000 The upper baseline in Fig. 1 represents T c T a for plants that are severely stressed. The crop canopy temperature measurements obtained from nonirrigated plots, S 4, were used to create the upper baseline. For this purpose, temperature (T c and T a ) measurements were taken on selected days at 1200 and 1300 h from nonirrigated plots during 3 August through 12 September except for a few days when measurements were not possible due to the cloud cover. Then the average values of canopy temperature obtained from these plots were computed and subtracted from the average air temperature values and graphed against vapor pressure deficit. The T c T a values for upper baseline varied from 4 to 5.1 C. To create the upper baseline the average of T c T a values was computed ( 4.6 C, n 19, SD 0.33) and Fig. 1. Relationships between canopy temperature minus air temperathe baseline was drawn parallel to VPD from this point. ture (T c T a ) and vapor pressure deficit (VPD) of summer-grown corn at Atalya, Turkey. A is the point which was used as an example Accordingly, the upper baseline, which represents the of how CWSI value is calculated. B and C represent the upper T c T a of corn when transpiration has ceased, was asand lower limits for point A, respectively. BC is the vertical distance sumed to be relatively constant at about 4.6 C. between upper and lower baselines, AC is the vertical distance between point A and lower baseline, and the CWSI is the crop As an example of how CWSI was calculated for a water stress index. given day, consider point A in Fig. 1. The point A has a T c T a value of 2.3 C at a VPD value of 2.2 kpa. From in this study. However, the climate, soil type, and plant the definition of Idso et al. (1981b), the CWSI is the variety might have caused differences in the intercept ratio of the vertical distance between the measured and slope of the baseline of this study. The linear rela- T c T a and the lower baseline to the distance between tionship between T c T a and VPD was also found for the lower and upper baselines at the same VPD. The corn (T c T a VPD) by Steele et al. (1994). distance between the point A and the lower baseline is Development of the lower baseline at a single location 3.1 C, and the distance between the upper and lower is often limited by the VPD range that occurs, thereby baselines at 2.2 kpa is 5.5 C. Thus, the CWSI is 3.1/ limiting the baseline transportability to other locations (Gardner et al., 1992b). In our experiment, the lower When calculated CWSI values were graphed against baseline was developed for a relatively wide range of time for each irrigation treatment (S 1,S 2, and S 3 ), syn- VPD ( kpa). Gardner and Shock (1989) sug- chronous patterns with irrigation events were observed gested that a VPD range of 1 to 6 kpa is necessary to (Fig. 2). The CWSI values in irrigated plots generally define a baseline that could be used in other locations dropped very close to zero following each irrigation to determine CWSI. application, then increased steadily to a maximum value Fig. 2. The seasonal trend of the crop water stress index (CWSI). Treatments S 1,S 2, and S 3 were irrigated when soil water dropped to 75, 50, and 25% of available water holding capacity, respectively. On 20 July, irrigation treatments (S 1,S 2, and S 3 ) received additional 45 mm of irrigation water. Treatment S 4 was not irrigated after the 68 mm preplant irrigation. Arrows along the upper axis represent irrigation events.

5 IRMAK ET AL.: DETERMINATION OF CROP WATER STRESS INDEX 1225 Fig. 3. Water held (mm) in the 0.9 m crop root zone for four treat- Fig. 4. Grain yield (Y, kgm 2 ) as a linear function of irrigation water ments over the period of the experiment. Treatments S 1,S 2, and (IR, mm) for summer-grown corn at Antalya, Turkey. S 3 were irrigated when soil water dropped to 75, 50, and 25% of available water holding capacity, respectively. On 20 July, irrigation soil profile to the field capacity. There was a statistically treatments (S 1,S 2, and S 3 ) received additional 45 mm of irrigation water. Treatment S 4 was not irrigated after the 68 mm preplant irri- significant relationship between irrigation water applied gation. (IR, mm) and corn grain yield (Y, kgm 2 ) described by the linear equation Y IR (r 2 just prior to the next irrigation application as the soil 0.99; n 12, RMSE 0.029, P 0.01) (Fig. 4). In Fig. water in the crop root zone was depleted. The average 4, there is no yield vs. irrigation water data between the CWSI values were observed before irrigation times as range of 68 and 347 mm because there was no other 0.39, and 0.54 for S 1, and S 3 plots, respectively. The mean irrigation treatment between S 4 (nonirrigated) and S 3 CWSI value measured before irrigations for treatment (irrigated when soil water dropped to 25% of AWHC). S 2 was 0.27 and corresponds with the highest grain yield Yields were significantly different among treatments of corn in this experiment. Gardner et al. (1992b) reobtained (Table 4). The maximum grain yield (6058 kg ha 1 ) was ported that corn, wheat, and cotton plants are tolerant from treatment 2, S 2, (seasonal mean CWSI to a CWSI rise of 0.2 to 0.3 between irrigations without 0.22), which was irrigated when soil water dropped to significant economic yield reduction. However, it should 50% of AWHC remaining in the top 0.9 m of soil. be noted that due to some experimental difficulties, the Doorenbos and Kasam (1979) indicated that the maxi- CWSI values were determined a few days (2 3 d) before mum grain yield for corn was usually obtained when irrigation applications rather than at the irrigation times the corn plants were irrigated at 55% of available wa- for treatments S 1 and S 2. For the maximum stressed ter capacity. (nonirrigated) plot, S 4, the CWSI continuously increased Significant differences were found for seasonal mean as the soil water depleted by the plants and the CWSI CWSI among the treatments (Table 4). In Table 4, we reached a maximum value (1.0) approximately 52 d after compared the seasonal mean CWSI values obtained the planting (Fig. 2). from three replications for each treatment during the Figure 3 shows the soil water contents (mm) in the growing season. Since the canopy temperature measure- 0.9 m crop root zone for the four treatments across ments were taken at the different days in each treatment, the period of the experiment. Although the irrigation we cannot compare individual CWSI values among the applications for treatment S 1 were more frequent than treatments for the growing season. The seasonal mean for treatment S 2, it received less water in each irrigation CWSI values were related with the corn grain yield in and in total compared with treatment S 2 (Table 2). Since Fig. 5 by polynomial solution. Our results showed that treatment S 1 was irrigated when soil water dropped to corn yield decreases as the CWSI increases. This rela- 75% of available water holding capacity, less irrigation tionship can be described by the equation Y water was necessary in each irrigation to refill the 0.90 m 4.38CWSI CWSI 0.46 (r , n 12, Table 4. Seasonal mean crop water stress index (CWSI), mean CWSI before irrigations, and total yield (kg ha 1 ) for different irrigation treatments for Antbey corn grown at Antalya, Turkey. Total irrigation Seasonal mean Mean CWSI before Treatments water applied CWSI* irrigations Total yield* mm kg ha 1 S (0.031)b (99)c S (0.024)a (64)d S (0.010)c (185)b S (0.011)d 740 (158)a * Significant at the 0.05 probability level as indicated by Duncan s multiple range test. Treatments S 1,S 2, and S 3 were irrigated when soil water dropped to 75, 50, and 25% of available water holding capacity, respectively. On 20 July, treatments S 1,S 2, and S 3 received 45 mm of irrigation water. S 4 was not irrigated after the 68 mm preplant irrigation. The seasonal mean CWSI observed from mean of the three replications for each treatment from 27 July until 14 d following the last irrigation. Means of CWSI obtained from three replications for each treatment. Values in parentheses indicate standard deviations (SD).

6 1226 AGRONOMY JOURNAL, VOL. 92, NOVEMBER DECEMBER 2000 Fig. 5. Corn grain yield (Y, kgm 2 ) as a polynomial function of the seasonal mean crop water stress index, CWSI, (X). tool to reach such goals. This information can also be an important component of irrigation management models. Results showed that CWSI is an efficient technique to monitor and quantify the water stress for corn under a Mediterranean climate. The seasonal mean CWSI for treatment, S 2, (irrigated at 50% of AWHC) was Results indicated that permitting the seasonal mean CWSI value to exceed more than 0.22 would result in decreased corn grain yield. The mean CWSI value before the irrigation times for this treatment was This CWSI value was consistent with the highest yield for summer-grown corn in our study. However, we cannot conclude that this CWSI value should be used for timing of irrigations for corn since we did not test scheduling irrigations using CWSI. In addition, since the canopy temperatures were measured 2 to 3 d before the irrigation applications, it would not be appropriate to make this judgement. Further studies are needed to reach such a conclusion. Long term (2 3 yr) experiments with different irrigation treatments should be conducted to establish and to test a critical value of CWSI at which a farmer should irrigate corn in a Mediterranean climate. In addition, we suggest that monitoring the CWSI on a daily basis would be more appropriate to establish CWSI for timing irrigations. In this case, the CWSI can be used to quantify the extent of crop water stress encountered prior to an irrigation application. RMSE 0.027, P 0.01). Reginato (1983) and Howell et al. (1984) found linear relationships between yield and average CWSI for cotton. A linear relationship was also found by Idso et al. (1981c) and Abdul-Jabbar et al. (1985) for alfalfa (Medicago sativa L.), and by Tu- baileh et al. (1986) for spring barley (Hordeum vul- gare L.). SUMMARY AND CONCLUSIONS A field experiment was conducted to relate CWSI values to the amount of irrigation applied and to the REFERENCES yield of summer-grown corn. The CWSI technique of- Abdul-Jabbar, A.S., D.G. Lugg, T.W. Sammis, and L.W. Gay fers some important advantages for quantifying plant Relationship between crop water stress index and alfalfa yield and stress between irrigations. The method is neither de- evapotranspiration. Trans. ASAE 28: structive nor disruptive to the crop, and is sensitive to Black, C.A., D.D. Evans, J.L. White, L.E. Ensminger, and F.E. Clark. water stress. It has been shown (Pinter and Reginato, (ed.) Methods of soil analysis. Part I. Agron. Monogr. 9. ASA, Madison, WI. 1982; Pinter et al., 1983; Keener and Kircher, 1983; Niel- Blad, B.L., B.R. Gardner, D.G. Watts, and N.J. Rosenberg sen and Gardner, 1987; Calle et al., 1990) that the tech- Remote sensing of crop moisture status. Remote Sens. Q. 3:4 20. nique can be used for timing of irrigations and predicting Blad, B.L., and N.J. Rosenberg Measurement of crop temperature by leaf thermocouple, infrared thermometry and remotely yield. This is important in semiarid cropping regions where water application costs mean that maximum prof- sensed thermal imagery. Agron. J. 68: Calle, J.L., H.L. Manges, and P. Barnes Scheduling irrigation its are not usually related to the highest yields and elimi- of corn with infrared thermometry. ASAE Paper ASAE, nation of unnecessary irrigation makes crop production St. Joseph, MI. more economical. Clawson, K.L., and B.L. Blad Infrared thermometry for schedul- The upper (stressed) and lower (nonstressed) base- ing irrigation of corn. Agron. J. 74: Doorenbos, J., and A.H. Kassam Yield response to water. FAO lines were calculated to quantify and monitor crop water Irrig. and Drain. Paper No. 33. stress for summer-grown corn in a Mediterranean cli- Fuchs, M., E.T. Kanemasu., J.P. Kerr, and C.B. Tanner Effect of mate. The lower baseline was described by the linear viewing angle on canopy temperature measurements with infrared equation T c T a VPD (r , n 28, thermometers. Agron. J. 59: RMSE 0.415, P 0.01, SD 1.33), where T Fuchs, M., and C.B. Tanner Infrared thermometry of vegetation. c T a is Agron. J. 58: in C and VPD is in kpa. The seasonal mean CWSI was Gardner, B.R., B.L. Blad, R.E. Maurer, and D.G. Watts. 1981a. Relarelated to grain yield (Y, kgm 2 ) of corn, with yield tionship between crop temperature and the physiological and phedecreasing as CWSI increased. The second order poly- nological development of differentially irrigated corn. Agron. J. nomial equation Y 4.38CWSI CWSI : (r , n 12, RMSE 0.027, P 0.01) can be Gardner, B.R., B.L. Blad, and D.G. Watts. 1981b. Plant and air temperatures in differentially irrigated corn. Agric. Meteorol. 25: used to predict the yield potential of summer-grown corn under a Mediterranean climate. Predicting yield Gardner, B.R., D.C. Nielsen, and C.C. Shock. 1992a. Infrared therresponse to crop water stress is important in developing mometry and the crop water stress index. I. History, theory, and strategies and decision-making for use by farmers and baselines. J. Prod. Agric. 5: their advisors, and researchers for irrigation managemometry and the crop water stress index. II. Sampling procedures Gardner, B.R., D.C. Nielsen, and C.C. Shock. 1992b. Infrared ther- ment under limited water conditions. The equation and interpretation. J. Prod. Agric. 5: which was developed in this experiment to predict the Gardner, B.R., and C.C. Shock Interpreting the crop water corn grain yield as a function of CWSI can be a useful stress index. ASAE Paper ASAE, St. Joseph, MI.

7 IRMAK ET AL.: DETERMINATION OF CROP WATER STRESS INDEX 1227 Geiser, K.M., D.C. Slack, E.R. Allred, and K.W. Stange Irriga- with the crop water stress index (CWSI). Appl. Agric. Res. 2: tion scheduling using crop canopy-air temperature difference Trans. ASAE 25: O Toole, J.C., N.C. Turner, O.P. Namuco, M. Dingkukn, and K.A. Hatfield, J.L The utilization of thermal infrared radiation measurements Gomez Comparison of some crop water stress measurement from grain sorghum as a method of assessing their irriga- methods. Crop Sci. 24: tion requirements. Irrig. Sci. 3: Pinter, P.J., Jr., K.E. Fry, G. Guinn, and J.R. Mauney Infrared Hatfield, J.L., D.F. Wanjura, and G.L. Barker Canopy tempera- thermometry: A remote sensing technique for predicting yield in ture response to water stress under partial canopy. Trans. ASAE water-stressed cotton. Agric. Water Manage. 6: : Pinter, P.J., Jr., and R.J. Reginato Thermal infrared techniques Hatfield, J.L Measuring plant stress with an infrared thermometer. for assessing plant water stress. p In Irrigation Scheduling for Hort Science 25: Water and Energy Conservation in the 80s. Proc. Am. Soc. Agric. Heermann, D.F., and H.R. Duke Evaluation of crop water Eng. Irrig. Scheduling Conf., Chicago, IL Dec ASAE, stress under limited irrigation. ASAE Paper ASAE, St. St. Joseph, MI. Joseph, MI. Pinter, P.J., Jr., and R.J. Reginato A thermal infrared technique Howell, T.A., J.L. Hatfield, H. Yamada, and K.R. Davis Evalua- for monitoring cotton water stress and scheduling irrigation. Trans. tion of cotton canopy temperature to detect crop water stress. ASAE 25: Trans. ASAE 27: Reginato, R.J Field quantification of crop water stress. Trans. Idso, S.B Non-water-stressed baselines: A key to measuring ASAE 26: and interpreting plant water stress. Agric. Meteorol. 27: Reginato, R.J., and D.J. Garrot, Jr Irrigation scheduling with Idso, S.B., R.D. Jackson, P.J. Pinter, Jr., R.J. Reginato, and J.L. Hatfield. the crop water stress index. p In Western Cotton Production 1981a. Normalizing the stress-degree-day parameter for envi- Conf. Summary Proc., Phoenix, AZ August, Cotton ronmental variability. Agric. Meteorol. 24: Growers Assoc., Memphis, TN. Idso, S.B., R.J. Reginato, R.D. Jackson, and P.J. Pinter, Jr. 1981b. Reginato, R.J., and J. Howe Irrigation scheduling using crop Measuring yield-reducing plant water potential depressions in indicators. J. Irrig. Drain. Eng. 3: wheat by infrared thermometry. Irrig. Sci. 2: Shanahan, J.F., and D.C. Nielsen Influence of growth retardants Idso, S.B., R.J. Reginato, D.C. Reicosky, and J.L. Hatfield. 1981c. (Anti-Gibberellins) on corn vegetative growth, water use, and grain Determining soil-induced plant water potential depressions in al- yield under different levels of water stress. Agron. J. 79: falfa by means of infrared thermometry. Agron. J. 73: Smith, R.G.C., H.D. Barrs, J.L. Stainer, and M. Stapper Rela- Irmak, S The possibility of using soil water potential and crop tionship between wheat yield and foliage temperature: Theory and water stress index values to monitor water stress and to determine its application to infrared measurements. Agric. For. Meteorol. the irrigation time of maize (Zea mays L.). M.E. thesis. Univ. of 36: Akdeniz, Faculty of Agric. Eng., Antalya, Turkey. Steele, D.D., E.C. Stegman, and B.L. Gregor Field comparison Jackson, R.D., and S.B. Idso Ambient temperature effect in of irrigation scheduling methods for corn. Trans. ASAE 37: infrared thermometry. Agron. J. 61: Jackson, S.H Relationship between normalized leaf water po- Tubaileh, A.S., J.W. Sammis, and D.G. Lugg Utilization of tential and crop water stress index values for acala cotton. Agric. thermal infrared thermometry for detection of water stress in spring Water Manage. 20: barley. Agric. Water Manage. 12: Keener, M.E., and P.L. Kircher The use of canopy temperature Walker, G.K., and J.L. Hatfield Stress measurement using foas an indicator of drought stress in humid regions. Agric. Mete- liage temperature. Agron. J. 75: orol. 28: Wanjura, D.F., J.L. Hatfield, and D.R. Upchurch Crop water Nielsen, D.C., and B.R. Gardner Scheduling irrigations for corn stress index relationship with crop productivity. Irrig. Sci. 11:93 99.