Agronomy Journal Journal of Natural Resources and Life Sciences Education
HOME HELP FEEDBACK SUBSCRIPTIONS ARCHIVE SEARCH TABLE OF CONTENTS
QUICK SEARCH:   [advanced]


     

This Article
Right arrow Abstract Freely available
Right arrow Figures Only
Right arrow Full Text (PDF) Free
Right arrow Alert me when this article is cited
Right arrow Alert me if a correction is posted
Services
Right arrow Similar articles in this journal
Right arrow Similar articles in ISI Web of Science
Right arrow Alert me to new issues of the journal
Right arrow Download to citation manager
Right arrow reprints & permissions
Citing Articles
Right arrow Citing Articles via HighWire
Right arrow Citing Articles via ISI Web of Science (19)
Right arrow Citing Articles via Google Scholar
Google Scholar
Right arrow Articles by Irmak, S.
Right arrow Articles by Bastug, R.
Right arrow Search for Related Content
PubMed
Right arrow Articles by Irmak, S.
Right arrow Articles by Bastug, R.
Agricola
Right arrow Articles by Irmak, S.
Right arrow Articles by Bastug, R.
Related Collections
Right arrow Water Stress
Right arrow Maize
Right arrow Irrigation
Agronomy Journal 92:1221-1227 (2000)
© 2000 American Society of Agronomy

CORN

Determination of Crop Water Stress Index for Irrigation Timing and Yield Estimation of Corn

Suat Irmaka, Dorota Z. Hamana and Ruhi Bastugb

a Dep. of Agric. and Bio. Eng., Univ. of Florida, P.O. Box 110570, Gainesville, FL 32611 USA
b Faculty of Agric., Univ. of Akdeniz, Antalya, Turkey, 07070

aysu{at}grove.ufl.edu


   ABSTRACT
TOP
 NOTES
 ABSTRACT
INTRODUCTION
 Materials and methods
 Results and discussion
 Summary and conclusions
 REFERENCES
 
Corn (Zea mays L.) grown under a Mediterranean semiarid climate requires supplemental irrigation to maximize the grain yield. Since the cost of irrigation application has been increasing, elimination of unnecessary irrigation applications would improve economics of corn production. There has been much interest in the crop water stress index (CWSI) as a potential tool for irrigation scheduling and yield estimation. An experiment was conducted to monitor and quantify water stress, and to develop parameters for irrigation scheduling and grain yield of summer-grown corn as a function of CWSI under Mediterranean semiarid cropping conditions. Three irrigation treatments were based on replenishing the 0.9-m deep root zone to field capacity when the soil water level dropped to 25, 50, and 75% of available water holding capacity (AWHC). A dryland treatment was also included. The lower (nonstressed) and upper (stressed) baselines were measured to calculate CWSI. An equation that can be used to calculate the yield potential of summer-grown corn under a Mediterranean climate was developed using the relationship between the corn grain yield and the seasonal mean CWSI. Permitting the seasonal average CWSI value to exceed more than 0.22 resulted in decreased corn grain yield. The CWSI behaved as expected, dropping to near zero following an irrigation and increasing gradually as corn plants depleted soil water reserves. We concluded that CWSI is a useful tool to monitor and quantify the water stress of corn under a Mediterranean climate.

Abbreviations: AWHC, available water holding capacity • CWSI, crop water stress index • RMSE, root mean square error • SD, standard deviation • Ta, air temperature • Tc, canopy temperature • VPD, vapor pressure deficit


   INTRODUCTION
TOP
 NOTES
 ABSTRACT
 INTRODUCTION
Materials and methods
 Results and discussion
 Summary and conclusions
 REFERENCES
 
EFFECTIVE USE of irrigation water is rapidly becoming an issue in Mediterranean regions and a method for irrigation scheduling based on the CWSI has been suggested. Because of its climatic adaptation and high yields, irrigated corn has been grown for many years in southern Turkey. Since 1985 irrigated corn production in this region has expanded to 610 000 ha (Irmak, 1996). Although corn is one of the most widely grown feed grains produced under irrigation in this region, not enough information is available to quantify water stress at the different soil water conditions to estimate grain yield and to schedule irrigations for corn based on the CWSI.

A technique to measure plant water stress should provide nondestructive, rapid, and reliable estimates of plant water status. During the 1960s, infrared technology advanced rapidly, and instruments that could be used for agricultural purposes (to measure crop canopy temperature) became commercially available. During the past decades, lightweight, hand-held, portable, and battery operated infrared thermometers (IRT) became available. Infrared thermometers can rapidly measure canopy temperatures over large areas. The theory of IRT operation (Fuchs and Tanner, 1966; Fuchs et al., 1967; Hatfield, 1990; Gardner and Shock, 1989); and (Gardner et al., 1992a) and temperature effects in infrared thermometry (Jackson and Idso, 1969) have been discussed. In the 1980s, the use of IRT become more routine in irrigation scheduling when Idso et al. (1981a) developed and demonstrated an empirical method for using the crop water stress index (CWSI).

Idso et al. (1981a) observed a linear relationship between canopy minus air (Tc -Ta) temperature differences and vapor pressure deficit (VPD) of the air for well irrigated plants transpiring at potential rate during the daylight hours. As soil moisture was depleted, the (Tc -Ta) vs. VPD relationship deviated from the linear nonstressed baseline condition. The empirical CWSI uses two baselines. The lower baseline represents the maximum rate of transpiration of a well watered crop and the upper baseline represents the Tc -Ta of a canopy with no transpiration and for which the canopy temperature does not respond to VPD. The CWSI varies from 0 to 1 with 1 representing a plant having no transpiration loss and 0 representing a plant transpiring at the maximum rate. The CWSI has been correlated to yield (Walker and Hatfield, 1983; Smith et al., 1985), leaf water potential (Pinter and Reginato, 1981; O'Toole et al., 1984; Jackson, 1991), and soil water availability (Hatfield, 1983; Reginato and Garrot, 1987).

Since the development of the CWSI method, many researchers have used it for irrigation management (Pinter and Reginato, 1982; Reginato, 1983; Howell et al., 1984; O'Toole et al., 1984; Reginato and Howe, 1985; Reginato and Garrot, 1987; Wanjura et al., 1990). However, it is often reported that early season CWSI values are particularly difficult to obtain because of partial canopy covers. In the early growing season, when plants are small, or for low plant populations, a part of the soil surface may be viewed by the IRT when Tc measurements are made. Hatfield et al. (1985) determined unstressed baselines of the CWSI for cotton under full and incomplete ground cover and reported that unstressed baselines for full ground cover had slopes about twice those under partial canopy cover. They concluded that partial canopy is a very complex system and the CWSI is overestimated when the crop is at less than full cover which could lead to an overapplication of irrigation water. On the other hand, for some crops, a single baseline has been used successfully for the entire growing season. However, there are some serious difficulties using only one baseline for the entire growing season (Gardner et al., 1992a).

It is reported that corn is relatively tolerant to water stress in the vegetative stage, very sensitive during the period of tasseling, silking, and pollination, and moderately sensitive during the grain-filling stage (Shanahan and Nielsen, 1987). Heermann and Duke (1978) used the average Tc -Ta values between treatment plots and adjoining well-watered areas to study crop water stress under limited irrigation for corn plants irrigated by a center-pivot irrigation system. They reported that the average temperature difference (Tc -Ta) elevation was linearly related to irrigation and to relative dry-matter yield. They concluded that an average Tc -Ta > 1.5°C was significantly correlated with grain yield reduction. Geiser et al. (1982) compared the temperature difference (Tc -Ta) method with resistance blocks and a water balance (checkbook) method of irrigation scheduling. They concluded that water balance and resistance block methods required additional water applications of 39 and 18%, respectively, compared to the temperature difference method. Gardner et al. (1981b) and Blad et al. (1981) tested the deviation of midday canopy temperature as an irrigation scheduling tool for corn plants. They found standard deviations of 0.3°C in well irrigated and 4.2°C in nonirrigated corn plots. They concluded that plots that showed a standard deviation >0.3°C required irrigation.

Gardner et al. (1981a) correlated grain yields of corn plants with differences in canopy temperature (Tc) between stressed and well-irrigated plants grown under different irrigation regimes. Midday differences in daily Tc during the pollination and grain-filling stages were effectively used to calculate grain yield with an accuracy of ±10%. They also observed yield reduction when the canopy temperature increased between the onset of tasseling and the end of grain-filling stages. Clawson and Blad (1982) reported less water use (156 mm) in corn plots for which irrigations were scheduled based on the canopy temperature compared to a neutron probe scheduled plot. They suggested that using canopy temperature variability to initiate irrigation has the potential for significant water savings due to improved efficiency in the use of available soil water.

Productivity response to water stress is different for each crop and this response is expected to vary with the climate. Therefore, the critical values of CWSI should be determined for a particular crop in different climates and soils to use it in yield prediction and irrigation scheduling. The objectives of this experiment were to monitor and quantify water stress, and to develop parameters to estimate irrigation timing and grain yield of summer-grown corn as a function of CWSI under Mediterranean semiarid cropping conditions using the method developed by Idso et al. (1981a).


   Materials and methods
TOP
 NOTES
 ABSTRACT
 INTRODUCTION
 Materials and methods
Results and discussion
 Summary and conclusions
 REFERENCES
 
The experiment was conducted during the summer of 1995 at the Mediterranean Agricultural Research Station located in Antalya, Turkey (36° 55', 34° 55', and altitude: 12 m). The region has a typical Mediterranean semiarid climate with an average annual rainfall of 1068 mm.

A single cross white corn (var. Antbey) was planted on 25 June 1995 following sorghum [Sorghum bicolor (L.) Moench]. Time to 50% flowering is 50 to 67 d, average growing season 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 experiment was designed as a randomized complete block with three replications for each treatment. There were 180 plants in each plot (7 by 4.90 m) and plant spacing was 0.75 m between the rows and 0.25 m within the rows. There were eight rows in each plot; and two additional rows were maintained as guard rows at each side of the plot. The seeds were planted at the depth of 0.07 to 0.08 m. Plots were maintained in beds and furrows to ensure uniform water distribution. Irrigation water was applied with furrow irrigation and total water to each plot was measured with a TS-324 model flow meter (Teksan, Inc., Istanbul, Turkey).1 Gravimetric soil moisture samples were taken in each plot at 0 to 0.30 m depth. A neutron scattering moisture gauge (Model 4300, Troxler Electronic Laboratories, Inc., Raleigh, NC) was used to measure soil moisture at depths of 0.60 and 0.90 m. Aluminum access tubes were installed in the center of each plot. The neutron probe was calibrated at the beginning of the growing season for the experimental field by correlating probe readings with volumetric water content of soil samples (100 cm3) taken. The calibration equation for the neutron probe was WC = (CR - 0.065)/2.42 (r2 = 0.91, n = 15, RMSE = 0.022, WC = volumetric water content by m3 m-3, and CR = count ratio).

Field plot experiments were conducted on clay soil (47% clay, 36% silt, and 17% sand) that received a 68 mm irrigation before planting. Four soil samples from each depth (0–120 cm with 30 cm increments) at five different locations were taken from the experimental field in order to determine the soil properties (Table 1) . Soil particle size analysis and bulk density (Black et al., 1965) were determined for each soil depth. Field capacity (FC) and permanent wilting point (PWP) were also determined for each soil depth at 33 and 1500 kPa soil water tension using the pressure chamber method. Porosity, f, of each soil depth was calculated using the relationship f = [1 - ({rho}b / {rho}s)] * 100 ({rho}b = bulk density, g cm-3, and {rho}s = density of solids, 2.65 g cm-3). Plots were fertilized with 400 kg ha-1 of NH4NO3 (ammonium nitrate) before planting. Irrigation treatments were established to refill a 0.9 m depth rooting zone when soil water had depleted to given percentages of the available water holding capacity (AWHC) in this rooting zone. Treatments designated S1, S2, and S3 were irrigated when soil water dropped to 75, 50, and 25% of AWHC, respectively. In addition, 45 mm irrigation was applied to the irrigation treatments only (S1, S2, and S3) on 20 July. A fourth treatment, S4, was not irrigated after planting. Table 2 shows the irrigation dates and total amount of water applied (mm) to the experimental plots. The total amount of applied water ranged from 68 to 441 mm.


View this table:
[in this window]
[in a new window]
  		Table 1 Soil physical properties at Antalya, Turkey, including porosity, field capacity (FC), and permanent wilting point (PWP)

 

View this table:
[in this window]
[in a new window]
  		Table 2 Irrigation amount (mm) applied for different treatments during the 1995 growing season for `Antbey' corn grown at Antalya, Turkey

 
Canopy temperatures (°C) were measured using a Model 210 Ag Multimeter (Everest Interscience Inc., Fullerton, CA) portable hand-held infrared thermometer. The instrument has a field of view of 15° (can be adjusted to 4°), a sensing window of 10.5 to 12.5 µm, and a resolution of 0.1°C. The instrument was calibrated using a method described by Blad and Rosenberg (1976). In each measurement the infrared thermometer was held above the plant canopy at an angle of 15° below the horizontal so that plant parts, but no soil were viewed. Canopy temperature (Tc) measurements were taken at each plot starting from the early pollination stage when the ground cover was 100% and the corn plant height was approximately 1.2 m (27 July) and continued until 11 September. In each measurement, five canopy temperature measurements were taken from the east and five readings from the west, and then averaged. At each measurement time, dry and wet-bulb temperatures were taken above the canopy surface using an Assman psychrometer (Qualimetrics Inc., Sacramento, CA) to determine air temperature (Ta) and vapor pressure deficit (VPD).

Grain yields, adjusted to 15.5% dry mass grain moisture, were determined from subplots hand harvested and hand shelled from each plot on 25 October. Four rows from the middle of the each plot were selected for harvest to avoid any edge effects. Harvest rows were 6.60 m in length. Yield response to treatments was analyzed by analysis of variance(ANOVA). When ANOVA identified treatment effects, Duncans Multiple Range Test (DMRT) was used to identify which treatments differed at the 5% significance level.


   Results and discussion
TOP
 NOTES
 ABSTRACT
 INTRODUCTION
 Materials and methods
 Results and discussion
Summary and conclusions
 REFERENCES
 
The weekly summary of the weather data measured daily at the weather station located nearby the experimental site is given in the Table 3 . No rain occurred during the growing season.


View this table:
[in this window]
[in a new window]
  		Table 3 Weekly summary of the 1995 weather data measured daily during the experiment at Antalya, Turkey{dagger}{ddagger}

 
The lower (nonstressed) and upper (stressed) baselines (Fig. 1) were measured for corn and the CWSI values were calculated using this diagram as the relative value between upper and lower baselines relating the difference between canopy (Tc) and air (Ta) temperatures (°C) to vapor pressure deficit (VPD, kPa) as outlined by Idso et al. (1981a). To develop the lower (nonstressed) baseline in Fig.1, the leaf temperatures and vapor pressure deficits were selected as a subset of Tc data obtained on clear days when the treatments were assumed to be nonstressed. The measurements were taken from the treatment S2 (although irrigated at 50% of available water holding capacity, treatment S2 received the most water, had the highest yield, and was the least stressed), at 1200 h and 1300 h assuming that the VPD was at maximum for the day. This is the time of the day when water stress is likely to be the highest and when the need for irrigation using CWSI should be determined. Then, the differences between Tc and Ta were linearly correlated with VPD (Fig. 1). The resulting baseline was described by the linear equation , where Tc -Ta is in °C and VPD is in kPa. Idso (1982) reported the following relationship between Tc -Ta and VPD for corn in Arizona: for sunlit and no tassels conditions. The intercept was higher and the slope was lower than in this study. However, the climate, soil type, and plant variety might have caused differences in the intercept and slope of the baseline of this study. The linear relationship between Tc -Ta and VPD was also found for corn by Steele et al. (1994).



View larger version (19K):
[in this window]
[in a new window]
  		Fig. 1 Relationships between canopy temperature minus air temperature (Tc-Ta) and vapor pressure deficit (VPD) of summer-grown corn at Atalya, Turkey. A is the point which was used as an example of how CWSI value is calculated. B and C represent the upper and lower limits for point A, respectively. BC is the vertical distance between upper and lower baselines, AC is the vertical distance between point A and lower baseline, and the CWSI is the crop water stress index

 
Development of the lower baseline at a single location is often limited by the VPD range that occurs, thereby limiting the baseline transportability to other locations (Gardner et al., 1992b). In our experiment, the lower baseline was developed for a relatively wide range of VPD (1.1–5.7 kPa). Gardner and Shock (1989) suggested that a VPD range of 1 to 6 kPa is necessary to define a baseline that could be used in other locations to determine CWSI.

The upper baseline in Fig. 1 represents Tc -Ta for plants that are severely stressed. The crop canopy temperature measurements obtained from nonirrigated plots, S4, were used to create the upper baseline. For this purpose, temperature (Tc and Ta) 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 Tc -Ta values for upper baseline varied from 4 to 5.1°C. To create the upper baseline the average of Tc -Ta values was computed and the baseline was drawn parallel to VPD from this point. Accordingly, the upper baseline, which represents the Tc -Ta of corn when transpiration has ceased, was assumed to be relatively constant at about +4.6°C.

As an example of how CWSI was calculated for a given day, consider point A in Fig. 1. The point A has a Tc -Ta value of 2.3°C at a VPD value of 2.2 kPa. From the definition of Idso et al. (1981b), the CWSI is the ratio of the vertical distance between the measured Tc -Ta and the lower baseline to the distance between the lower and upper baselines at the same VPD. The distance between the point A and the lower baseline is 3.1°C, and the distance between the upper and lower baselines at 2.2 kPa is 5.5°C. Thus, the CWSI is .

When calculated CWSI values were graphed against time for each irrigation treatment (S1, S2, and S3), synchronous patterns with irrigation events were observed (Fig. 2) . The CWSI values in irrigated plots generally dropped very close to zero following each irrigation application, then increased steadily to a maximum value just prior to the next irrigation application as the soil water in the crop root zone was depleted. The average CWSI values were observed before irrigation times as 0.39, and 0.54 for S1, and S3 plots, respectively. The mean CWSI value measured before irrigations for treatment S2 was 0.27 and corresponds with the highest grain yield of corn in this experiment. Gardner et al. (1992b) reported that corn, wheat, and cotton plants are tolerant to a CWSI rise of 0.2 to 0.3 between irrigations without significant economic yield reduction. However, it should be noted that due to some experimental difficulties, the CWSI values were determined a few days (2–3 d) before irrigation applications rather than at the irrigation times for treatments S1 and S2. For the maximum stressed (nonirrigated) plot, S4, the CWSI continuously increased as the soil water depleted by the plants and the CWSI reached a maximum value (1.0) approximately 52 d after the planting (Fig. 2).



View larger version (22K):
[in this window]
[in a new window]
  		Fig. 2 The seasonal trend of the crop water stress index (CWSI). Treatments S1, S2, and S3 were irrigated when soil water dropped to 75, 50, and 25% of available water holding capacity, respectively. On 20 July, irrigation treatments (S1, S2, and S3) received additional 45 mm of irrigation water. Treatment S4 was not irrigated after the 68 mm preplant irrigation. Arrows along the upper axis represent irrigation events

 
Figure 3 shows the soil water contents (mm) in the 0.9 m crop root zone for the four treatments across the period of the experiment. Although the irrigation applications for treatment S1 were more frequent than for treatment S2, it received less water in each irrigation and in total compared with treatment S2 (Table 2). Since treatment S1 was irrigated when soil water dropped to 75% of available water holding capacity, less irrigation water was necessary in each irrigation to refill the 0.90 m soil profile to the field capacity. There was a statistically significant relationship between irrigation water applied (IR, mm) and corn grain yield (Y, kg m-2) described by the linear equation (Fig. 4) . In Fig. 4, there is no yield vs. irrigation water data between the range of 68 and 347 mm because there was no other irrigation treatment between S4 (nonirrigated) and S3 (irrigated when soil water dropped to 25% of AWHC). Yields were significantly different among treatments (Table 4) . The maximum grain yield (6058 kg ha-1) was obtained from treatment 2, S2, (seasonal mean CWSI = 0.22), which was irrigated when soil water dropped to 50% of AWHC remaining in the top 0.9 m of soil. Doorenbos and Kasam (1979) indicated that the maximum grain yield for corn was usually obtained when the corn plants were irrigated at 55% of available water capacity.



View larger version (22K):
[in this window]
[in a new window]
  		Fig. 3 Water held (mm) in the 0.9 m crop root zone for four treatments over the period of the experiment. Treatments S1, S2, and S3 were irrigated when soil water dropped to 75, 50, and 25% of available water holding capacity, respectively. On 20 July, irrigation treatments (S1, S2, and S3) received additional 45 mm of irrigation water. Treatment S4 was not irrigated after the 68 mm preplant irrigation

 


View larger version (14K):
[in this window]
[in a new window]
  		Fig. 4 Grain yield (Y, kg m-2) as a linear function of irrigation water (IR, mm) for summer-grown corn at Antalya, Turkey

 

View this table:
[in this window]
[in a new window]
  		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

 
Significant differences were found for seasonal mean CWSI among the treatments (Table 4). In Table 4, we compared the seasonal mean CWSI values obtained from three replications for each treatment during the growing season. Since the canopy temperature measurements were taken at the different days in each treatment, we cannot compare individual CWSI values among the treatments for the growing season. The seasonal mean CWSI values were related with the corn grain yield in Fig. 5 by polynomial solution. Our results showed that corn yield decreases as the CWSI increases. This relationship can be described by the equation . 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 Tubaileh et al. (1986) for spring barley (Hordeum vulgare L.).



View larger version (13K):
[in this window]
[in a new window]
  		Fig. 5 Corn grain yield (Y, kg m-2) as a polynomial function of the seasonal mean crop water stress index, CWSI, (X)

 

   Summary and conclusions
TOP
 NOTES
 ABSTRACT
 INTRODUCTION
 Materials and methods
 Results and discussion
 Summary and conclusions
REFERENCES
 
A field experiment was conducted to relate CWSI values to the amount of irrigation applied and to the yield of summer-grown corn. The CWSI technique offers some important advantages for quantifying plant stress between irrigations. The method is neither destructive nor disruptive to the crop, and is sensitive to water stress. It has been shown (Pinter and Reginato, 1982; Pinter et al., 1983; Keener and Kircher, 1983; Nielsen and Gardner, 1987; Calle et al., 1990) that the technique can be used for timing of irrigations and predicting yield. This is important in semiarid cropping regions where water application costs mean that maximum profits are not usually related to the highest yields and elimination of unnecessary irrigation makes crop production more economical.

The upper (stressed) and lower (nonstressed) baselines were calculated to quantify and monitor crop water stress for summer-grown corn in a Mediterranean climate. The lower baseline was described by the linear equation , where Tc -Ta is in °C and VPD is in kPa. The seasonal mean CWSI was related to grain yield (Y, kg m-2) of corn, with yield decreasing as CWSI increased. The second order polynomial equation can be used to predict the yield potential of summer-grown corn under a Mediterranean climate. Predicting yield response to crop water stress is important in developing strategies and decision-making for use by farmers and their advisors, and researchers for irrigation management under limited water conditions. The equation which was developed in this experiment to predict the corn grain yield as a function of CWSI can be a useful 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, S2, (irrigated at 50% of AWHC) was 0.22. 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 0.27. 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.


   NOTES
TOP
 NOTES
ABSTRACT
 INTRODUCTION
 Materials and methods
 Results and discussion
 Summary and conclusions
 REFERENCES
 
Florida Agric. Exp. Stn. Journal Ser. no. R-06412.

1 The mention of trade names or commercial products is solely for the information of the reader and does not constitute an endorsement or recommendation for use. Back

Received for publication November 20, 1998.
   REFERENCES
TOP
 NOTES
 ABSTRACT
 INTRODUCTION
 Materials and methods
 Results and discussion
 Summary and conclusions
 REFERENCES
 




This article has been cited by other articles:


Home page
 Agron. J.Home page
J. T. Baker, D. C. Gitz, P. Payton, D. F. Wanjura, and D. R. Upchurch
Using Leaf Gas Exchange to Quantify Drought in Cotton Irrigated Based on Canopy Temperature Measurements
Agron. J., April 4, 2007; 99(3): 637 - 644.
[Abstract] [Full Text] [PDF]

Home page
 J Exp BotHome page
M Moller, V Alchanatis, Y Cohen, M Meron, J Tsipris, A Naor, V Ostrovsky, M Sprintsin, and S Cohen
Use of thermal and visible imagery for estimating crop water status of irrigated grapevine
J. Exp. Bot., March 1, 2007; 58(4): 827 - 838.
[Abstract] [Full Text] [PDF]

Home page
 J Exp BotHome page
Y. Cohen, V. Alchanatis, M. Meron, Y. Saranga, and J. Tsipris
Estimation of leaf water potential by thermal imagery and spatial analysis
J. Exp. Bot., July 1, 2005; 56(417): 1843 - 1852.
[Abstract] [Full Text] [PDF]

Home page
 Agron. J.Home page
A. E. Ajayi and A. A. Olufayo
Evaluation of Two Temperature Stress Indices to Estimate Grain Sorghum Yield and Evapotranspiration
Agron. J., September 1, 2004; 96(5): 1282 - 1287.
[Abstract] [Full Text] [PDF]

This Article
Right arrow Abstract Freely available
Right arrow Figures Only
Right arrow Full Text (PDF) Free
Right arrow Alert me when this article is cited
Right arrow Alert me if a correction is posted
Services
Right arrow Similar articles in this journal
Right arrow Similar articles in ISI Web of Science
Right arrow Alert me to new issues of the journal
Right arrow Download to citation manager
Right arrow reprints & permissions
Citing Articles
Right arrow Citing Articles via HighWire
Right arrow Citing Articles via ISI Web of Science (19)
Right arrow Citing Articles via Google Scholar
Google Scholar
Right arrow Articles by Irmak, S.
Right arrow Articles by Bastug, R.
Right arrow Search for Related Content
PubMed
Right arrow Articles by Irmak, S.
Right arrow Articles by Bastug, R.
Agricola
Right arrow Articles by Irmak, S.
Right arrow Articles by Bastug, R.
Related Collections
Right arrow Water Stress
Right arrow Maize
Right arrow Irrigation

HOME HELP FEEDBACK SUBSCRIPTIONS ARCHIVE SEARCH TABLE OF CONTENTS
The SCI Journals Crop Science Vadose Zone Journal
Journal of Natural Resources
and Life Sciences Education		 Soil Science Society of America Journal
Journal of Plant Registrations Journal of
Environmental Quality		 The Plant Genome