Relationships between leaf water potential, CWSI, yield and fruit quality of sweet lime under drip irrigation

Agricultural water management ELSEVIER

AgriculturalWater Management25 (1994) 13-22

Relationships between leaf water potential, CWSI, yield and fruit quality of sweet lime under drip irrigation A.R. Sepaskhah*, S.M. Kashefipour Department of Irrigation, Shiraz University, Shiraz, lran (Accepted 9 June 1993)

Abstract This study was initiated to correlate the leaf water potential and crop water stress index (CWSI) with the yield and yield quality of sweet lime ( Citrus limetta, Swing) under drip irrigation with water application based on different fractions of pan evaporation (0.4 Epanto 1.0 Epa°). The lower baseline for CWSI of Idso et al. (1981) was (Tc-Ta) =3.61-1.74 (VPD), and the upper limit for CWSI calculations was 5.0°C. The average CWSI during the growing season varied from zero to 0.435 at different irrigation treatments ( 1.0 Ep,n to 0.4 Epan). The maximum fruit yield was produced at a pan evaporation fraction of 0.75, corresponding to the CWSI of 0.103 and leaf water potential of - 2.03 MPa with maximum water-use efficiency of 26.8 kg/mm. However, the maximum weight of fruit, pulp and juice resulted at higher water application while the total dissolved solid, ascorbic acid and vitamin C were lower. The relationship between the leaf water potential and CWSI was dependent on the air vapor pressure deficit (VPD). Furthermore, a relationship between (Tc-Ta) and VPD was proposed for irrigation scheduling of sweet lime with an infrared thermometer method. Key words." Leaf water potential;Crop water stress index;Sweet lime;Drip irrigation

I. Introduction Sweet lime (Citrus limetta, Swing) is one of the most important fruits in the arid region of the Fars province of Iran. The fruit production is dependent on irrigation water. Irrigation water is usually applied by drip irrigation, and irrigation scheduling is necessary. Irrigation scheduling can be based on pan evaporation fraction (Shalhevet et al., 1976) which is an *Correspondingauthor. 0378-3774/94/$07,00 © 1994 ElsevierScienceB.V. All rights reserved SSDIO378-3774(93)EO031-F

14

A.R. Sepaskhah, S.M. Kashefipour / Agricultural Water Management 25 (1994) 13-22

indirect estimate of crop water status. Irrigation scheduling can also be based directly on plant water status which may be a better method. Plant temperature has long been recognized as an indicator of plant water stress (Tanner, 1963). The concept of stress-degree day which is based on temperature differential between the canopy (Tc) and air (Ta) when Ta is at its maximum ( 1-1.5 h after solar noon), was introduced as an indication of when to irrigate (Idso et aI., 1977; Jackson et al., 1977). The term crop water stress index (CWSI) has recently been introduced (Idso et al., 1981; Jackson et al., 1981 ). By introduction of the hand-held infrared thermometer, the CWSI method has been used to measure crop water status for irrigation scheduling purposes (Pinter and Reginato, 1982; Reginato, 1983; Reginato and Howe, 1985; Sepaskhah et al., 1987; Jackson, 1991 ). Leaf water potential measurement by pressure chamber has been used for irrigation scheduling (Grimes et al., 1987). Although this method has been extensively correlated to crop yield (Johnson et al., 1989), it is laborious and uses few measurements to characterize a large population of plants. Leaf water potential, CWSI and fraction of pan evaporation may be used for irrigation scheduling of sweet lime, but there is little information correlating the mentioned parameters with yield and yield quality of this fruit. Therefore, this study was initiated to correlate the fraction of pan evaporation, leaf water potential and CWSI with the yield and yield quality of sweet lime under drip irrigation.

2. Materials and methods

The experiments were conducted at the Jahrom Soil and Water Research Station located 175 km SE of Shiraz (latitude of 28,30 N, longitude of 53,33 E, and 985 m above mean sea level). The trials were conducted on a gravelly loam soil with a field capacity and permanent wilting point of 0.32 and 0.1 cm3/cm 3, respectively. The experimental period was two growing seasons which started in April 1987. It was conducted in a typical 14year-old sweet lime (Citrus limetta, Swing) orchard. The sweet lime was grafted on lime with spacing of 6 * 6 m and irrigated with the drip irrigation method. In March, phosphorous and potassium were directly applied to soil as 137.5 kg/ha superphosphate and 97.3 kg/ha potassium sulphate, respectively. One hundred kg/ha N as ammonium sulphate and 13.9 kg/ha iron chelate were applied to soil through the irrigation system. The climate is arid with an average annual rainfall of 317 ram, which falls during the winter months (November-March). The average monthly minimum and maximum temperatures are 0.2°C and 40.9°C, respectively and the mean monthly minimum and maximum relative humidity are 18.6 and 86.3%, respectively. The experiment consisted of four irrigation treatments: 100, 90, 75 and 60% of class A pan evaporation ( 1.0 Epan, 0.9 Epan, 0.75 Epa n, 0.6 Evan) during 1987, and 90, 75, 60 and 40% of class A pan evaporation (0.9 Ep,n, 0.75 Epan, 0.6 Epan, 0.4 Epan) during 1988. Irrigation water was applied every other day through 4 1/h emitters with 12 to 14 emitters per tree. The chemical analysis of the irrigation water indicated that it is suitable for drip irrigation (data were not shown). The amounts of applied water were measured by a water

A.R. Sepaskhah, S.M. Kashefipour / Agricultural Water Management 25 (1994) 13-22

15

meter. Each irrigation treatment was applied to triplicate plots of four trees inside the citrus groove. The treatment plots were separated at least by one row of trees. The CWSI was measured on trees which received this treatment. Canopy temperature (Tc) was measured with an infrared thermometer with 7.5 to 14.0 /zm band filter 2 ° field of view that was calibrated for use in a high ambient temperature. The instrument was hand held at 2 m so that the tree was viewed from all cardinal directions, N, E, S and W at about 15 ° above the horizontal, and two readings were taken from each direction. The instrument was pointed on parts of trees with about 90% of green cover. Vapor pressure deficit (VPD) was calculated from wet and dry bulb temperatures measured at a weather station at margins of the experimental site in the orchard. The canopy and air temperatures and VPD measurements for baseline determination were made at three different days from 6 : 0 0 to 14:00 h at 30-60-min intervals. For CWSI measurements, canopy and air temperatures and VPD were measured weekly on the day between irrigations at 1 2 : 0 0 - 1 4 : 0 0 h. The water potential of leaf xylem of new growth was measured every week by a pressure bomb (Scholander et al., 1965). The measurements were made between 11 : 30 and 14 : 00 h. At the same time, the average soil water content in root zone beneath the emitters was measured by the neutron scattering method. Then, they were converted to the soil matric potentials by the moisture-retention curve of the field soil (Kashefipour, 1988). VPD was also measured along with leaf xylem potential. The CWSI was determined using the empirical method of Idso (Idso et al., 1981 ). This method required determination of the relationship between VPD and canopy and air temperature differential ( T c - T a ) , under well watered conditions ( 1.0 Epan) when the plants are transpiring at a potential rate. By increasing the amount of applied water ( 1.0Epan VS. 0.9 E p a . ) , a n increase of about 3% in ET was reported by Kashefipour (1988) which is negligible. A linear equation was fitted to the relationship by regression. Two trees were also used by withdrawing irrigation water such that a wilting sign was observed. The upper baseline is the relationship between VPD and ( T c - T a ) under maximum stress conditions when transpiration has essentially ceased. Fruit yield was harvested at about mid December of 1987 and 1988. Total weight and number of fruits and the average weight of one fruit for trees in all treatments were determined. Fruit samples from each replicate of the treatments ( 1.0 Epa, to 0.6 Epan) in the ! 987 experiment and dry treatment (0.4 Epa,) in the 1988 experiment were taken for quality determination. The quality measurements were percent of peel, pulp,juice, acid, total soluble solid (sugar), pH, and vitamin C content. Percent of total soluble solid was determined by a refractometer. Vitamin C content of fruit was measured by a procedure proposed by Wardowski et al. (1979). Acid content was determined by titration procedure.

3. Results and discussion The relationship between canopy and air temperature differential ( T c - T a ) and air ( VPD ) of well watered treatment in the 1987 experiment is shown in Fig. 1. The lower baseline was described by the following equation:

16

A.R. Sepaskhah, S.M. Kashefipour/ Agricultural WaterManagement25 (1994) 13-22 ( T c - T a ) = 3.61-1.74 (VPD), r 2 = 0.955, n = 150

(1)

where ( T c - T a ) is in °C and VPD is in kPa. Data of ( T c - T a ) and VPD at 1 2 : 0 0 - 1 4 : 0 0 h of treatment 1.0/?pan obtained during the growing period plus the data obtained through 3 days have been used to establish the lower baseline. Therefore, the generality of Eq. ( 1 ) may not be restricted. Figure 1 indicates that canopy temperatures are from I°C to 8°C cooler than the air temperature over the range of observed air VPD. Abdul-Jabbar et al. (1985) reported that alfalfa canopy temperatures ranging from 1 to 9°C cooler than the air temperature over the range of observed air VPD. The values of slope and intercept of Eq. (1) were reported to be 1.77°C/kPa and 4.22°C, respectively for fig tree (Idso, 1982), which is almost similar to those of sweet lime [Eq. ( 1 ) ]. The average value of ( T c - T a ) for well stressed trees or upper baseline was 5.0°C (Fig. 1).

CWSI by the ldso method Knowing the lower and upper baseline, the CWSI can be calculated using the method of Idso et al. (1981) for different irrigation treatments in 1987 and 1988. CWSI is defined as the ratio of the deviation of the measured ( T c - T a ) from the lower baseline to the range between the lower and upper baseline at a given VPD (Idso et al., 1981 ). The results of 2year averages of CWSI computation are shown in Table 1. CWSI increased at drier irrigation treatments. However, due to the variation of data points around the baseline, the CWSI of treatment 1.0 Epan has been obtained as - 0 . 0 0 5 (very close to zero) instead of zero. The relationship between CWSI and leaf water potential The relationship between leaf water potential (q~l) at midday (MPa) and CWSI is as follows: ~bI = - 1.45-1.65 CWSI, r = - 0 . 4 6 , n = 55.

(2)

Although the correlation coefficient of Eq. (2) is very low, its regression coefficients are similar to those obtained for early season of Acala S J-2 cotton reported by Jackson ( 1991 ) and dissimilar to that for sugarbeet (Sepaskhah et al., 1987). Inclusion of the VPD in kPa in Eq. (2) by multiple-regression analysis resulted as follows: ~0~= - 1.38 CWSI - 0 . 1 4 (VPD) - 0 . 8 8 , r = 0 . 8 0 1 , n = 5 5 .

(3)

Inclusion of VPD nearly doubled the correlation coefficient and decreased the standard error of estimate (2.64 vs. 1.77). Use of leaf water potential for irrigation scheduling is laborious and uses few measurements to characterize large population of plants. Therefore, use of CWSI as a quick and accurate method is desirable (Sepaskhah et al., 1987; Jackson, 1991 ). However, for sweet lime in the study area, the relationship between ~01 and CWSI is dependent on the VPD.

Irrigation scheduling by canopy and air temperature differential The relationship between ~01 (MPa), VPD (kPa) and soil water potential, qJ~ (MPa) was analyzed by multiple regression. The result is as follows: ~ = - 0 . 2 7 VPD - 0 . 0 7 6 ( T c - T a ) + 35.6 tp~-0.37, r = 0.837 n = 41.

(4)

A.R. Sepaskhah, S.M. Kashefipour / Agricultural Water Management 25 (1994) 13-22 i

o~ ._1

i

u

i

_<

i

•

•

°

Z~T=5

4

I-. Z

ego o

" "-~

Upper baseline

17

lib

W

¢r" u.I

u.

2

I.J_

O iii

0 I--

< n," nun

O_

-2

U.J

I..¢1-

~<

-4

~/~be -~ z

o°

•

o < C.~ <~

-8 0

1

2

3

VAPOR PRESSURE DEFICIT

4

5

6

VPD (kPa)

Fig. I. Relationship between canopy and air temperature differential and air vapor pressure deficit (VPD) for sweet lime. Table 1 CWSI according to Idso, yield, weight of one fruit, amount of irrigation water and water-use efficiency of sweet lime at different irrigation treatments (1987-1988) Irrigation treatments, fraction of Eva,' 1.00b

0.90 0.75 0.60 0.40 b

CWSI

Fruit yield kg/tree

Weight of one fruit (g)

Mean

SEa

Mean

SE

Mean

SE

--0.005 0.075 0.116 0.175 0.435

2.88× 10 -3 7.20× 10 -3 0.015 8.31 × 10 -3 0.057

125.7 100.0 177.6 104.4 49.0

6.13 29.76 52.79 32.97 19.49

168.8 122.1 115.0 104.8 81.2

8.24 6.80 3.83 2.82 2.72

Irrigation Water-use efficiency water use (kg/mm) (cm) 247.1 221.5 184.2 148.2 90.6

14.1 12.6 26.8 19.6 15.0

~Standard error. bOnly one-year data. If the o p t i m u m soil and l e a f water potentials at m i d d a y for sweet lime were known, Eq. (4) w o u l d be simplified for irrigation scheduling purposes as follows: (Tc-Ta)c = a(VPD)

+ b

(5)

Therefore, by temperature and relative h u m i d i t y of air at 1-1.5 h after solar noon, the V P D will be obtained, and f r o m Eq. (5) the critical ( T c - T a ) c for start o f irrigation will be calculated. T h e n the m e a s u r e d ( T c - T a ) is c o m p a r e d with ( T c - T a ) c and w h e n its value is equal or greater than ( T c - T a ) c the orchard should be irrigated. A l t h o u g h Eq. (4) has resulted f r o m drip irrigation it should be considered further in field irrigation practice.

18

A.R. Sepaskhah, S.M. Kashefipour /Agricultural Water Management 25 (1994) 13-22

Yield The 2-year averages of fruit yield and weight of one fruit at different irrigation treatments are depicted in Table 1. The results indicated that the highest fruit yield was produced at irrigation treatment of 0.75 Epan. At the higher water application ( 1.0 Ep,, and 0.9 Epa,0, lower yield may be attributed to nutrient wash-out from the root depth in the light texture soil of the orchard. However, at lower water application (0.6 Epan and 0.4 Eras), water deficit resulted in lower fruit yield (Shalhevet et al., 1976). The size of fruit was the greatest at 1.0 Epan irrigation treatment and the smallest at 0.4 Epa, irrigation treatment. The higher plant water potential at greater water application was speculated to result in larger fruit size (Levy et al., 1979). The highest fruit size did not coincide with the highest fruit yield. Therefore, the highest fruit yield was produced at 0.75 Ep~, with smaller fruit size. Furthermore, higher water applications might have resulted in greater flower senescence and consequently lower fruit yield per tree, but larger fruit size. Water-use efficiencies (WUE) at different irrigation treatments are shown in Table 1. The highest WUE resulted in a 0.75 Epan irrigation treatment.

Fruit quality Different quality parameters of fruit are shown in Table 2. Higher amounts of water application increased the pulp and juice percentages and decreased the peel, total soluble solid, acid percentages and vitamin C. Increase in juice percent and decrease in peel thickness at higher irrigation for Novel orange were also reported by Mougheith et al. (1977). Irrigation treatment of 1.0 Epan produced the highest percentages of pulp and juice and 0.4 Epan irrigation treatment resulted in the highest percentage of peel, total soluble solid (sugar), acid and vitamin C. Cruse et al. (1982), and Levy et al. (1978a,b) also reported an increase in concentration of total soluble solid (TSS) and acid in juice at shortages of irrigation water. The ratio of TSS to acid content was lower at the highest and the lowest water applications (Table 2). This ratio was invariant at water application treatments of 0.9 Epa n to 0 . 6 Epa n.

Yield analysis The relationship between fruit yield (Y, kg/tree), irrigation water (I, m3/tree), and CWSI, and the relative fruit yield and ~bj (MPa) obtained by multiple-regression analysis are as follows: Y = - 0 . 0 7 1 ( 1 ) 2 + 9 . 8 1 ( 1 ) - 1 9 7 . 9 , r e = 0.52, n = 15

(6)

Y = - 7 5 4 . 4 ( C W S I ) 2 + 154.6(CWSI) + 123.2, r 2 = 0.59, n = 5

(7)

(Y)% = - 7 5 6 . 8 ( ~ 1 ) 2 - 3 0 7 0 . 6 ~ - 3 0 1 8 . 5 , r = 0.876.

(8)

The maximum fruit yield ( 141 kg/tree) occurred at 69.1 m3/tree of irrigation water. The maximum fruit yield occurred at CWSI of 0,103 with corresponding fruit yield of 131 kg/ tree which is in accordance with 141 kg/tree resulted from Eq. (6). The relative fruit yield was correlated with the leaf water potential quadratically [ Eq. (8) ]. The maximum relative yield resulted at ~O~of - 2 . 0 3 MPa which is close to that reported by Kashefipour (1988) ( - 2.1 MPa). Similar leaf water potential for irrigation initiation for different citrus trees was reported by Shalhevet and Levy (1990) from other researchers.

14.3+1.15 13.5_+0.94 17.3-+0.31 15.7_+0.86 17.7_+0.53

1.00 0.90 0.75 0.60 0.40 h

~Total soluble solid (sugar). bData from 1988.

Peel (% )

Irrigation treatment; fraction of Ep.n

85.7_+1.15 86.5+0.94 82.7+0.31 84.3-+0.86 82.3_+0.53

Pulp (%)

77.2+1.27 77.2+0.56 74.6_+1.13 73.3+0.67 72.2+0.22

Juice (%)

Table 2 Fruit quality of sweet lime at different irrigation treatments (1987)

5.57+0.02 5.63+_0.03 5.63+0.03 5.64+0.04 5.32_+0.06

pH

8.2+_0.22 8.9+0.24 9.2_+0.36 10.0_+0.69 11.5_+0.73

TSS ~ (%)

0.057+0.001 0.058+0.001 0.059-+0.001 0.062_+0.001 0.091-+0.008

Acid (%)

40.1_+0.97 43.5+0.67 43.4_+2.04 46.8_+1.40 62.7_+4.02

Vitamin C (mg/100 cc)

143.9_+4.28 153.4+3.10 155.9_+4.12 161.3_+8.13 126.1+6.69

TSS/acid

2.

20

A.R. Sepaskhah, S.M Kashefipour / Agricultural Water Management 25 (1994) 13-22

Fruit size analysis The relationship between fruit size (S, g) and irrigation water (I, m3/tree) obtained by linear-regression analysis is as follows: S = 2 9 . 8 + 1.42(1), r 2 = 0.862, n = 14.

(9)

Again, it is indicated that fruit size has been increased by higher water application. The relationship between fruit size (S, g) and CWSI analyzed by regression is as follows: S = 144.6 -

16.30 CWSI, r 2 = 0.71, n = 15.

(10)

The maximum fruit size at zero CWSI is 144.6 g. The fruit size further decreased as CWSI increased. The fruit size at optimum CWSI for optimum fruit yield (0.103) is about 128.1 g. Regression analysis resulted in a relationship between fruit size (S, g) and daily lowest leaf water potential (~bt, MPa) at 1987 as follows: S = 331.6+104.8 ~ r 2 = 0.615, n = 12.

(11)

Comparison of Eq. ( 11 ) with Eq. (10) indicated that fruit size correlation with CWSI was better than with tp~.

4. Conclusions Similar lower baseline to that of fig tree was resulted (slope = - 1.74°C kPa ~, intercept = 3.61°C). The upper limit of canopy to air temperature difference was 5.0°C. It was concluded that the relationship between minimum daily leaf water potential ( ~b~) and CWSI was dependent on the VPD. The results showed that the higher water application treatment (1.0 Epa n and 0.9 Epan) decreased the fruit yield due to nutrient wash-out from the light texture soil of the orchard. But the fruit size was the largest at the highest water application treatment. However, at the lower water application treatments (0.6 Epa n and 0.4 Epan) , w a t e r deficit caused reduced fruit yield and size. The highest fruit size did not coincide with the highest fruit yield and fruit-juice content. Therefore, the highest fruit yield was produced at 0.75 Epa, with smaller fruit size and fruit-juice content. However, higher fruit yield did coincide with higher total soluble solid and vitamin C. The maximum fruit yield was obtained at 69.1 m3/tree irrigation water application, CWSI of 0.103 and daily lowest leaf water potential of - 2 . 0 3 MPa. Fruit size was correlated better with CWSI than the daily lowest leaf water potential.

5. Acknowledgements This research was supported in part by project no. 65-AG-387-181 of the Shiraz University Research Council. The authors also wish to thank the staff of the Jahrom Soil and Water Research Station of the Ministry of Agriculture for their valuable assistance in conducting the experiment.

A.R. Sepaskhah, S.M. Kashefipour /Agricultural Water Management 25 (1994) 13-22

21

6. References Abdul-Jabbar, A.S., Lugg, D.G., Sammis, T.W. and Gay, L.W., 1985. Relationships between crop water stress index and alfalfa yield and evapotranspiration. Trans. ASAE., 28:454-461. Cruse, R.R., Wiegand, C.L. and Swanson, W.A., 1982. The effect of rainfall and irrigation management on citrus juice quality in Texas. J. Am. Soc. Hortic. Sci., 107: 767-770. Grimes, D.W., Yamada, H. and Hughes, S.W., 1987. Climate-normalized cotton leaf water potentials for irrigation scheduling. Agric. Water Manage., 12: 293-304. Idso, S.B., 1982. Non-water stressed base line: A key to measuring and interpreting plant water stress. Agric. Meteorol., 27: 59-70. Idso, S.B., Jackson, R.D. and Reginato, R.J., 1977. Remote sensing of crop yields. Science, 196: 19-25. Idso, S.B., Jackson, R.D., Pinter, P.J., Jr., Reginato, R.J. and Hatfield, J.L., 1981. Normalizing the stress-degree day parameter for environmental variability. Agric. Meteorol., 24: 45-55. Jackson, R.D., Reginato, R.J. and Idso, S.B., 1977. Wheat canopy temperature: A practical tool for evaluating water requirements. Water Resour. Res., 13:651-656. Jackson, R.D., Idso, S.B., Reginato, R.J. and Pinter, Jr., P.J., 1981. Canopy temperature as a crop water stress indicator. Water Resour. Res., 17:1133-1138. Jackson, S.H., 1991. Relationships between normalized leaf water potential and crop water stress index values for acala cotton. Agric. Water Manage., 20:109-118. Johnson, S., Kerby, T. and Grimes, D.W., 1989. To stress or not to stress-irrigation cotton for maximum yield. In: J.M. Brown (Editor), Proc. Beltwide Cot. Res. Conf., Nashville, TN, 2-7 Jan. Natl. Cotton Conf., Memphis, TN, pp. 525-527. Kashefipour, S.M., 1988. Determination of evapotranspiration rate and its effects on quantity and quality of sweet lime (Citrus limetta, Swing) under trickle irrigation in Jahrom (in Persian). M.S. Thesis, Irrigation Department, Shiraz University, 259 pp. Levy, Y., Shalhevet, J. and Bielorai, H., 1979. Effect of irrigation regime and water salinity on grapefruit quality. J. Am. Soc. Hortic. Sci., 104: 356-359. Levy, Y., Bar-Akiva, A. and Vaadia, Y., 1978a. Influence of irrigation and environmental factors on grapefruit acidity. J. Am. Hortic. Sci., 103: 73-76. Levy, Y., Bielorai, H. and Shalhevet, J., 1978b. Long-term effects of irrigation regimes on grapefruit tree development and yield. J. Am. Soc. Hortic. Sci., 103: 680-683. Mougheith, M.G., El-Ashram, M., Amerhom, G.W. and Modbouly, M., 1977. Effect of different rates of irrigation on navel orange tree. II. Yield and fruit quality. Ann. Agric. Sci. Moshtohor, 8:119-127. Pinter, Jr., P.J. and Reginato, R.J., 1982. A thermal infrared technique for monitoring cotton water stress and scheduling irrigations. Trans. ASAE, 25: 1651-1655. Reginato, R.J., 1983. Field quantification of crop water stress index. Trans. ASAE, 26: 772-775. Reginato, R.J. and Howe, J., 1985. Irrigation scheduling using crop indicators. J. Irrig. Eng., 3: 125-133. Shalhevet, J. and Levy, Y., 1990. Citrus trees. In: B.A. Stewart and D.R. Nielsen (Eds), Irrigation of Agricultural Crops, Agronomy Series no. 30, ASA, Madison WI, pp. 951-986. Shalhevet, J., Mantell, A., Bielorai, H. and Shimshi, D., 1976. Irrigation of field and orchard crops under semiarid conditions. Inter. Irrig. Info. Center Publication no. 1. Scholander, P.F., Hammel, H.T., Bradstreet, E.D. and Hemmingsen, E.A., 1965. Sap pressure in vascular plants. Science, 148: 339-346. Sepakhah, A.R., Nazemossadat, S.M.J. and Kamgar-Haghighi, A.A., 1987. Water stress of sugarbeet as related to leaf and canopy temperature to leaf water content. Iran Agric. Res., 6: 29-43. Stegman, E.C. and Soderlund, M.G., 1989. Irrigation scheduling of spring wheat using infrared thermometry. Inter. Winter Meeting of the ASAE, New Orleans. Paper no. 89-2688. Tanner, C.B., 1963. Plant temperatures. Agron. J., 55:210-211. Wardowski, W., Soule, J., Grierson, W. and Westbrook, G., 1979. Florida citrus quality test. Bulletin 188. Florida Cooperation Extension Service, Institute of Food and Agricultural Science, University of Florida.