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Australian Journal of Agricultural Research, 2004, 55, 1149–1157

The effects of different drip irrigation regimes on watermelon [Citrullus lanatus (Thunb.)] yield and yield components under semi-arid climatic conditions Mehmet S¸ims¸ekA,C , Murat KaçıraB , and Tahsin TonkazA A Department

of Agricultural Structures and Irrigation, Faculty of Agriculture, Harran University, 63040 S¸anlıurfa, Turkey. B Department of Agricultural Machinery, Faculty of Agriculture, Harran University, 63040 S ¸ anlıurfa, Turkey. C Corresponding author. Email: [email protected]

Abstract. This study was conducted to investigate the effects of drip irrigation on yield and yield components of watermelon [Citrullus lanatus (Thunb.) Crimson Tide F1 ] under semiarid conditions in the Southeastern Anatolian Project Region, Harran Plain, S¸anlıurfa, Turkey, during 2002 and 2003. Using a 4-day irrigation period, 4 different irrigation regimes were applied as ratios of irrigation water/cumulative pan evaporation (IW/CPE): 1.25 (I125 ), 1.00 (I100 ), 0.75 (I75 ), and 0.50 (I50 ). Seasonal crop evapotranspiration (ETc ) rates were 720, 677, 554, and 449 mm in the first year and 677, 617, 519, and 417 mm in the second year for irrigation treatments I125 , I100 , I75 , and I50 , respectively. Amounts of irrigation water applied to the 4 respective treatments were 764, 642, 520, and 398 mm in 2002 and 709, 591, 473, and 355 mm in 2003. Maximum yield was obtained from I125 , with 84.1 t/ha in 2002 and 88.6 t/ha in 2003. Yield was reduced significantly as the irrigation water was reduced. The values of water use efficiency ranged from 9.6 to 11.7 kg/m3 in 2002 and 10.8 to 13.1 kg/m3 in 2003. The unstressed I125 treatment produced 10.1 kg marketable watermelons/m3 irrigation in 2002, and 11.3 kg/m3 in 2003. By comparison, the least irrigated (I50 ) treatment produced 12.4 kg/m3 in 2002, and 14.9 kg/m3 in 2003. A yield response factor (ky ) value of 1.15 was determined based on averages of 2 years, and watermelon was found to be sensitive to water stress. This result showed that yield loss (1 – Ya /Ym ) is more important than evapotranspiration deficit (1 – ETa /ETm ). The study demonstrates that 1.25 IW/CPE water applications by a drip system in a 4-day irrigation frequency might be optimal for watermelon grown in semi-arid regions similar to those in which the work was conducted. Additional keywords: deficit irrigation, water-yield relationship, watermelon, crop water stress index (CWSI).

Introduction The Southeastern Anatolia Project (GAP) of Turkey is a multisectoral human development project based on water resources. This project will enable irrigation of 1.7 million hectares of agricultural land when it is completed. Agriculture in the Harran Plain is mostly cotton production (90%). Other field crops include corn, vegetables, and horticultural crops, and the ecological richness of the region allows production of many different crops. Traditional irrigation methods such as furrow and basin irrigation are dominant practices; however, the use of microirrigation techniques is inevitable in the near future because of the salinity problem caused by traditional irrigation methods. Phene et al. (1979) and Papadopoulos (1991) indicated that soil salinity and degradation, and poor crop yields, could be prevented by applying water to the effective root level with low volume application of water under low pressures with micro-irrigation. © CSIRO 2004

Irrigation programs could be developed by applying deficit irrigation at different rates throughout the growing season, and seasonal crop evapotranspiration could be determined for different growing periods. Irrigation programs and applications based on the relationship between irrigation water (IW) and cumulative pan evaporation (CPE) are not complex. The standard United States Weather Bureau class A open pan evaporimeter is all that is needed in the application of water in irrigation management. Imtiyaz et al. (2000) and Saudan et al. (2000) obtained positive results in many crop plants by applying various IW/CPE ratios. This method of irrigation programming has been widely used because of its simplicity (Ferreira and Carr 2002). Lack of precipitation and limited water supply during the growing season are important considerations for crop production. Therefore, relationships between crop water consumption, crop water stress, and yield must be determined to achieve a better water saving. 10.1071/AR03264

0004-9409/04/111149

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Australian Journal of Agricultural Research

M. S¸ims¸ek et al.

Irrigation programming methods generally utilise soil water status or meteorological parameters for modelling or computing evapotranspiration. However, irrigation scheduling based on crop water status could be more advantageous. Canopy temperature has been investigated as an indicator of crop water status. Researchers have reported using an empirically determined crop water stress index (CWSI) for water stress assessment (Idso et al. 1977; Idso et al. 1981; Nielsen et al. 1984). An empirical CWSI approach has received much attention, since it is simple and requires only 3 variables for its calculation (canopy and air temperatures and relative humidity). The production of watermelon [Citrullus lanatus (Thunb.)] has great potential in the GAP region. Turkey annually produces 5% of the world’s supply and has one of the highest yields, at 64.2 t/ha (FAO 2003). The aim of this study was to determine the effect of different drip irrigation regimes, applied as different ratios of IW/CPE with 4-day irrigation intervals, on watermelon yield and yield components under semi-arid climatic conditions. Material and methods Experimental site and climatic data This study was conducted during 2002 and 2003 at the Experimental Research Field of the Faculty of Agriculture in Harran University, S¸anlıurfa, Turkey. The experimental field was located in the Harran

Plain (37◦ 08 N, 38◦ 46 E, semi-arid zone, 464 m above sea level). The soil series in the research field was ‘Ikizce’, developed on colluvial materials (Dinç et al. 1991). The texture of this soil series was clay throughout the profile (Table 1). The soils in the region were classified as Entisols and Fluvisols according to Soil Taxonomy (Soil Survey Staff 1999) and FAO-UNESCO (1974), respectively. Dominant clay minerals of the soils studied were smectite, fallowed by palygorskite, illite, and kaolinite (Kapur et al. 1991). The weather was hot and dry from May to September, with air temperatures up to 47◦ C and relative humidity averaging about 34%. The climatic variables for experimental years and long-term averages for May–July are given in Table 2 (Meteorology Station, S¸anlıurfa, 1929–2003). All other parameters except relative humidity were consistent since the start of irrigation. The reason for the considerable increment in relative humidity might be irrigation in the Plain (Tonkaz et al. 2003). In addition, total radiation databased on long-term averages, except for May 2003, showed an increasing trend as observed in relative humidity data. Crop management, experimental design, and irrigation treatments Watermelon (Crimson Tide F1 ) was sown in peat in the greenhouse on 13 April 2002 and 10 April 2003. The seedlings were then transplanted to the experimental field on 18 May (day after transplanting, DATP 1) in the first year and on 12 May (DATP 1) in the second year. On the transplanting dates, 58 and 34 mm of water was applied to the seedlings in 2002 and 2003, respectively. Prior to starting the different irrigation treatments at 3 weeks after transplanting, the watermelon crop was watered every 4 days. The total amount applied during this pre-treatment period was 154 mm in 2002 and 119 mm in 2003. After

Table 1. Selected properties of the soil used in the study FC, Field capacity; WP, permanent wilting point; AWC, available water holding capacity; BD, bulk density; OM, organic matter; EC, electrical conductivity Soil depth

FC (v/v%)

WP (v/v%)

AWC (mm)

BD (g/cm3 )

OM (%)

EC (dS/m)

0–15 15–30 30–45 45–60

41.6 41.7 41.3 41.5

30.5 30.8 30.6 29.9

16.7 16.4 16.1 17.5

1.41 1.38 1.41 1.37

2.3 2.1 2.0 1.9

0.06 0.05 0.07 0.08

Particle distribution (%) Sand Silt Clay 7 7 8 17

35 33 29 28

Table 2. Weather conditions during the experiments compared with the long-term mean Average air temp. (◦ C)

Av. relative humidity (%)

Total solar radiation (J/min.cm2 )

Av. wind speed (2 m height) (km/h)

Total class A pan evaporation (mm)

May June July

21.4 28.7 32.0

51 38 37

2002 2495 2730 2604

1.7 1.9 1.6

237 400 408

May June July

24.2 28.6 32.6

42 35 29

2003 1851 2830 2613

1.4 1.7 1.9

222 394 432

May June July

21.7 27.8 33.0

44 31 28

Long-term mean (1929–2003) 2106 2399 2328

1.6 1.8 1.7

201 410 419

58 60 63 55

Texture class Clay Clay Clay Clay

Drip irrigation effects on watermelon yield


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transplanting, the watermelon seedlings were treated with thiophanate methyl (60 g/100 L) applied to the rooting area in both the first and second years to control damping off and soil pathogens. In 2002, insecticide containing Dichlorvos (150 g/100 L) was applied twice to control Tetranychus spp. and Bemicia tabaci. No chemical application was done in 2003. The experiments were based on a complete randomised block design with 3 replications. Each plot consisted of 5 rows 7.5 m in length, with 2-m row spacing and 0.5-m in-row spacing. Three rows in the middle of each plot were used for harvesting and 2 side rows were considered as buffers. Based on this plan, each plot covered an area of 75 m2 and harvested area 39 m2 . Plant density was 10 000 plants/ha. Fruit was harvested manually on 25 July 2002 (DATP 68) and 18 July 2003 (DATP 68). Each harvested fruit was weighed and yield per hectare and mean fruit yield were determined based on marketable fruit yield per plant. Five fruits from each subplot were used to determine total soluble solids values (TSS) in units of ◦ Brix. Total vine length was measured 7 weeks after transplanting, corresponding to the peak period of plant biomass. Five plants were harvested from each plot when the plant biomass reached at its peak on DATP 51 in both years, and total vine length and vine dry weight were determined in the laboratory. A basal fertiliser application of 100 kg/ha of superphosphate was incorporated in the soil before transplanting. In addition, total amounts of 150 kg/ha of potassium nitrate and 120 kg/ha of ammonium nitrate were applied using fertigation in 3 portions: (i) before transplanting, (ii) 3 weeks after transplanting, and (iii) 6 weeks after transplanting. Phosphoric acid (H3 PO4 , 25 mg/L) was injected into the irrigation water every second irrigation. The electrical conductivity (ECw ) of the irrigation water was 0.31 dS/m. The irrigation treatments consisted of 4 different ratios of IW/CPE as 1.25 (I125 ), 1.00 (I100 ), 0.75 (I75 ), and 0.50 (I50 ). The CPE values were obtained on daily basis from a standard United States Weather Bureau Class A open pan evaporimeter located at the experimental site. Drip laterals were placed 10 cm away from the plants and were spaced with 2 m distance between each lateral. Water from the water tank was delivered to the field by a sub-main Ø32-mm PVC pipe, Ø16-mm laterals with in-line emitters located 0.5 m apart and surface drip laterals spaced at 2.0-m intervals. The operating pressure was constant at –152 kPa with a 2 L/h flow rate from each emitter. Irrigation treatments were started when the water content of the soil at the effective root depth (60 cm) decreased to 50% of the available soil water on 8 June (DATP 21) in the first year and 3 June (DATP 22) in the second year. This resulted in a total of 9 irrigations during the experiment.

where ETc is seasonal crop evapotranspiration, I is applied irrigation water, P is precipitation, D is drainage or deep percolation, R is surface runoff, and S is water storage change (mm).

The water balance

Results and discussion

Some physical and chemical properties of the study area are listed in Table 1. The soil had a field capacity of 41.3–41.7% and permanent wilting point 29.9–30.8% based on volumetric water content (v/v%) for the root-zone of 0–60 cm depth. The soils were clayey with bulk density of 1.37–1.41 g/cm3 , organic matter content 1.9–2.3%, and EC 0.05–0.08 dS/m. The gravimetric water content was measured from the soil samples taken at 8-day intervals after the start of experiment. The soil samples were taken from distances 25, 50, and 75 cm from the emitters at 0–15, 15–30, 30–45, and 45–60 cm depth. The volumetric water content (v/v%) of each soil layer was determined (Stone et al. 1987; Foroud et al. 1993) and the effective root depth was taken as 60 cm. In addition, the water content at depths 60–90 and 90–120 cm was also determined and the increase in total water content in these layers was considered to be deep percolation. Crop evapotranspiration under varying irrigation regimes was calculated using the water balance model:

Total water

ETc = I + P − D − R ± S

(1)

Water use efficiency and irrigation water use efficiency Water use efficiency (WUE) was defined as the ratio of marketable fruit yield (t/ha) and seasonal crop evapotranspiration (ETc ) (mm). Irrigation water use efficiency (IWUE) was calculated as the marketable fruit yield per unit irrigation water applied. Canopy temperature and crop water stress index The canopy temperature (Tc ) was measured using a hand-held IRT (Raytek MX2, Berlin, Germany) with a 1.4◦ field of view (Ø72 mm @ 3.0 m). The IRT was operated with an emissivity adjustment. The canopy temperature measurements were started after the irrigation treatments were initiated. The measurements were taken from 1000 to 1400 hours before each irrigation day. A total of 9 canopy temperature measurements were made from 6 June to 18 July at 4-day intervals in both 2002 and 2003. A mini data logger (Hobo H8, Onset Computer Corp., MA, USA) was used to measure air temperature and relative humidity in the experimental site. The sensor was adjusted to scan every 1 min and the data were averaged every 5 min and recorded. The CWSI values were calculated using the method of Idso et al. (1981). In this approach, the measured crop canopy temperatures were scaled relative to the lower limit of Tc – Ta (under no water stress) and upper limit of Tc – Ta under maximum water stress conditions. Using the lower and upper limit estimates, a CWSI value can be determined as: CWSI =

(Tc − Ta ) (Tc − Ta )LL (Tc − Ta )UL (Tc − Ta )LL

(2)

where Tc is canopy temperature (◦ C), Ta is air temperature (◦ C), (Tc – Ta )LL is lower limit of canopy-air temperature difference (◦ C) and (Tc – Ta )UL is upper limit of canopy-air temperature difference (◦ C). The lower limit (non-water stress baseline) of the Tc – Ta was determined using the measured data obtained from I125 treatment group. Statistical analysis Statistical data were analysed using commercial statistical software (SAS Inc. 1990). Analysis of variance (ANOVA) was conducted and significance of differences among treatments were tested using the least significant difference (l.s.d.) method. Differences were declared significant at P = 0.05 or P = 0.01.

Soil water content measurements started on 9 June 2002 and on 4 June 2003 and continued until the harvest. Soil moisture contents within 50 cm laterally and 30 cm vertically of the emitter were the same as next to the emitter, with no difference between irrigation treatments. Surface wetting extended to about 70, 60, 55, and 40 cm with I125 , I100 , I75 , and I50 treatments, respectively. The active root depth for watermelon was assumed to be 60 cm, and therefore deep percolation measurements were made at 60–90 and 90–120 cm soil depths. The results indicated that the only percolation occurred in I125 treatment, with 18%. Overall, the results indicated that under conditions of unlimited water, the I125 treatment seemed to be the

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best. However, the I75 treatment might be a better choice under limited water, because with this treatment, a 32.6% water saving was possible even though this application resulted in a 22.6 t/ha (26.2%) reduction in the crop yield. The IW and ETc values were similar between years. The IW and ETc values were 398–764 mm and 449–720 mm for 2002 and 355–709 mm and 417–677 mm for 2003 (Fig. 1a, b). The reason for the small difference between IW and ET might be the similarity of climatic conditions during the experimental years, similar dates for transplanting and harvesting, and similarity of the total growing periods (68 days) in both years. As a result, the interactions between IW and fruit yield (Fig. 2a) and ET consumption and fruit yield (Fig. 2b) were statistically significant. Fruit yield and yield components Fruit yield The 2-year average yields and yield components for the 4 IW/CPE treatments are shown in Table 3. No

significant difference (P > 0.05) was determined between yield and yield components for the experimental years. However, a significant difference was observed in irrigation regimes based on IW/CPE ratios (P < 0.01). Plant aboveground biomass increased as the amount of irrigation water increased, and consequently the yield increased significantly. The maximum yield was obtained at I125 (86.4 t/ha) and the minimum yield at I50 (51.0 t/ha). This indicated a 69.40% increase in yield with I125 compared with I50 . The amount of water applied at I125 was 95.60% higher than that at I50 . No significant difference was observed in yield between the I100 and I75 treatments. Plants experienced water stress as the ratio IW/CPE decreased with decreasing yield. The relationship between the decrease in the ratio and yield was significant (r2 = 0.91). As seen from the equation of the relationship, per unit increase in IW/CPE resulted in a 43.3 t/ha yield increase (Fig. 3a). Another reason for obtaining lower yields in stress treatment plants may be lesser fruit weight per plant, and smaller vine lengths and leaves in stressed groups. Srinivas et al. (1989) reported similar

800

(a)

700

I125

600

I100

I75

I50

500 400 300

Seasonal crop ETc (mm)

200 100 0 0

10

20

10

20

30

40

50

60

70

30

40

50

60

70

800

(b)

700 600 500 400 300 200 100 0 0

Days after transplanting

Fig. 1. Relationship between days after transplanting and seasonal crop evapotranspiration (ETc ) under different irrigation regimes in (a) 2002 (Day 0, 17 May), and (b) 2003 (Day 0, 11 May).



100

(a) y = 0.0001 IW2 – 0.06 IW + 58.51 r 2 = 0.91 (2003)

90 80 70 60

y = 0.0001 IW2 – 0.05 IW + 50.79 r 2 = 0.96 (2002)

Fruit yield (t/ha)

50 40 300

400

500

600

700

800

IW (mm) 100

(b) y = 0.0003 ETc2 – 0.25 ETc + 98.78 r 2 = 0.85 (2003)

90 80 70 60

y = 0.0003 ETc2 – 0.21 ETc + 89.70 r 2 = 0.86 (2002)

50 40 400

450

500

550

600

650

700

750

Seasonal crop ETc (mm)

Fig. 2. Relationship between (a) cumulative water applied (IW) and fruit yield, and (b) seasonal crop evapotranspiration (ETc ) and fruit yield.

results for watermelon. Erdem and Yüksel (2003) indicated that maximum yield (103.7 t/ha) in watermelon was obtained in non-stressed groups. Yield components An increase in IW/CPE ratio decreased total soluble solids (TSS), whereas it significantly increased mean fruit weight, total vine length, and total vine dry weight; the mean fruit weight was 6.6–8.3 kg and there was a strong correlation (r2 = 0.99) (Fig. 3b). The lowest TSS value (◦ Brix 8.1) was obtained in the I125 treatment, which resulted in the highest yield and mean fruit weight. In contrast, the highest TSS value was obtained from the I75 and I50 treatments (◦ Brix 9.1 and 9.3). A strong correlation was found between TSS and IW/CPE (r2 = 0.96) (Fig. 3c), in line with the findings

by Srinivas et al. (1989) and Erdem and Yüksel (2003), and supports the idea that increase in fruit water content causes a decrease in Brix values. The maximum values of total vine length were obtained from the I125 treatment (2456.5 cm) and the minimum vine length was obtained from the I50 treatment (835.3 cm) (Table 3). The correlation coefficient for vine length and IW/CPE was r2 = 0.88 (Fig. 3d). The maximum vine dry weight was 167.7 g for the I125 treatment, and the minimum was 73.1 g at I50 . As seen from the equation of the relationship for total vine dry weight and IW/CPE, a unit increase in IW/CPE resulted in an increase of 119.66 g in total vine dry weight (Fig. 3e). A positive linear relationship was also found between fruit yield and total vine dry weight, and a per unit increase in total vine dry weight caused a 0.36 kg/ha increase in fruit yield (Fig. 4). There were no significant differences in the yield and yield components between replications and years (P > 0.05); however, the differences in treatments were significant (P < 0.01). Water use efficiency The values of WUE and IWUE were similar in some treatment groups. Table 4 summarises the values of IW, ET, WUE, and IWUE. The WUE and IWUE values were similar. A possible reason for very close WUE values was the arid climate and low precipitation rates during the crop-growing season. Additionally, WUE values, in both years, were lower than IWUE except in the I125 treatment. This could be explained with higher crop water requirements than available water (given by irrigation) and an IW/CPE ratio that was less than the 0.25 increment. The TSS, WUE, and IWUE values were high in the I50 treatment group (Table 3 and 4). However, it is recommended that the use of the 0.5 IW/CPE ratio should be avoided if the conditions are not forcing the growers to apply it. Moreover, the IW/CPE ratios of the I100 and I75 treatment groups might be recommended if the water resources are limited, even though the yield is much less than in the I125 group. It is necessary to indicate that all these factors are related to the regulations and political issues on utilisation and cost of water.

Table 3. Yield and yield components data Within columns, means followed by the same letter are not significantly different at P = 0.05 Treatment (irrigation regimes) I125 I100 I75 I50

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Fruit yield (t/ha)

Mean fruit weight (kg)

Total soluble solids (◦ Brix)

Total vine length (cm)

Total vine dry weight (g)

86.4a 66.0b 63.8b 51.0c

8.3a 7.8ab 7.3b 6.6c

8.1c 8.5c 9.1b 9.3a

2456.5a 2095.5b 1897.3c 835.3d

167.7a 134.0b 118.5c 73.1d

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80

90

(a)

y = 43.32 (IW/CPE) + 28.88 r 2 = 0.91

Fruit yield (t/ha)

70 60 50

70 60 50

9

(b)

y = 2.28 (IW/CPE) + 5.50 r 2 = 0.99

8

40 50

100

150

200

Total vine dry weight (g) 7

Fig. 4. Relationship between fruit yield and total vine dry weight (average of 2 years).

6 10

Table 4. Water use and irrigation water use efficiency (IWUE) IW, Irrigation water; ET, evapotranspiration

(c) 9

8

Treatment

y = –1.68 (IW/CPE) + 10.22 r 2 = 0.96

Total vine length (cm)

7 3000

Total vine dry weight (g)

Total soluble solids (°Brix) Mean fruit weight (kg)

40

y = 0.3606x + 22.311 r 2 = 0.94

80

200

2500

(d )

y = 2024.70 (IW/CPE) + 59.58 r 2 = 0.88

IW (mm)

ETc (mm)

WUE (kg/m3 )

IWUE (kg/m3 )

I125 I100 I75 I50

764 642 520 398

2002 720 677 554 449

11.7 9.6 11.0 11.0

11.0 10.1 11.8 12.4

I125 I100 I75 I50

709 591 473 355

2003 677 617 519 417

13.1 10.8 12.8 12.7

12.5 11.3 14.1 14.9

2000 1500 1000 500

(e) 150

y = 119.66 (IW/CPE) + 18.62 r 2 = 0.97

[1 – (ETa /ETm)] 0.40

0.30

0.20

0.10

0.00 0.00

100

50 0.25

0.10 0.20 0.5

0.75

1

1.25

1.5

IW/CPE

Fig. 3. Relationship between irrigation regimes and (a) fruit yield, (b) mean fruit weight, (c) total soluble solids, (d ) total vine length, and (e) total vine dry weight (average of 2 years).

Yield response factor Doorenbos and Kassam (1979) studied the effect of water stress on crop production using the formula: Ya ETa 1− = ky 1 − (3) Ym ETm where Ya and ETa are the actual yield and actual evapotranspiration; Ym and ETm the maximum yield and maximum evapotranspiration; and ky is the yield response factor. The ky estimates the yield reduction that is incurred for each mm of evapotranspiration deficit that is in short supply

y = 1.15[1 – (ETa/ETm)] r 2 = 0.73

0.30 0.40

[1 – (Ya /Ym)]

Fruit yield (t/ha)

90

0.50

Fig. 5. Relationship between relative evapotranspiration deficit [1 – (ETa /ETm )] and relative yield reduction [1 – (Ya /Ym )] for watermelon (average of 2 years).

to meet the maximum seasonal evapotranspiration. The ky values are experimentally derived using field data, taking into account the linear relationship between yield loss (1 – Ya /Ym ) and deficit irrigation (1 – ETa /ETm ) during the whole growing season, or in one of the growth stages. However, variation in ky values can be observed due to a lack of experimental information in environmentally different conditions. Yield response factor (ky ) was determined for flowering (0.80), early vegetative (0.45), late vegetative (0.70), ripening (0.30), and total growing period (1.10).


2

4

6

8

(a) –1 –3 –5 Tc-Ta = –0.94 VPD + 0.38 r 2 = 0.78

–9 1

Crop water stress index and yield

(b)

Figure 6a and b illustrates the non-water stress baselines (lower limit of Tc – Ta v. VPD) for 2002 and 2003. The lower limit (non-water stress baseline) of Tc – Ta was determined using the measured data obtained from the I125 treatment group. The upper limits of Tc – Ta were found to be 0.14 and 0.61◦ C for 2002 and 2003 using the procedure given by Idso et al. (1981). The history of the CWSI values for the irrigation treatments for 2002 and 2003 is shown in Fig. 7a and b. The crops recovered from water stress after the irrigation and CWSI declined accordingly and increased prior to the following irrigation. Mean CWSI values for each treatment

–3 –5 –7 Tc-Ta = –1.10 VPD + 0.08 r 2 = 0.60

–11 –13

VPD (kPa)

Fig. 6. Non-water stressed baseline for Tc – Ta v. VPD air in (a) 2002 and (b) 2003. 1.2 I125

(a)

I100

I 75

I 50

0.8

0.4

0.0

189

194

179

174

169

164

CWSI

159

–0.4 189

1.2

(b) 0.8

0.4

0.0

Day of year

Fig. 7. History of crop water stress index (CWSI) for (a) 2002 and (b) 2003.

189

169

164

159

154

–0.4 184

–9

179

–1

184

Tc – Ta

–7

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Since there was no significant yield difference between years, the ky value was calculated using the average of both years’ crop yields (Fig. 5). The ky value of 1.15 obtained in this study agreed with the ky values reported by Doorenbos and Kassam (1979) and Erdem and Yüksel (2003) of 1.1 and 1.27, respectively. Fruit yield was higher in the I125 treatment than the other treatments, and I100 , I75 , and I50 were 23.6, 26.2, and 41.0% lower than I125 , indicating that in semiarid regions, if there is no water shortage, I125 is the best choice to irrigate watermelon. On the other hand, I75 could be recommended for irrigation if the water is limited.

10

1

174

0


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Fruit yield (t/ha)

100 90 y = –67.642 CWSI + 80.927 r 2 = 0.93

80 70 60 50 40 –1

0.0

0.1

0.2

0.3

0.4

0.5

0.6

CWSI

Fig. 8. Relationship between mean CWSI and mean fruit yield.

were calculated as averages of CWSI for the measurement periods of both years. The mean CWSI values were 0.00 (I125 ), 0.17 (I100 ), 0.31 (I75 ), and 0.50 (I50 ) in 2002, and 0.07 (I125 ), 0.11 (I100 ), 0.24 (I75 ), and 0.41 (I50 ) in 2003. Negative CWSI values result from canopy temperatures lower than the modelled non-water stress baseline. Figure 8 shows the relationship between the mean CWSI value and yield. An inversely linear relationship was obtained for these 2 parameters. When the irrigation level decreased, the transpiration rates of the crops decreased, resulting in increased crop canopy temperatures and CWSI values, and subsequent reductions in yield. This result agrees with other experimental studies carried out for watermelon (Orta et al. 2003) and confirms that the seasonal mean CWSI values of 0.14 or more would result in decreased fruit yields for watermelon grown in regions where similar conditions exist. Conclusions Increase in irrigation amounts resulted in increased mean fruit yield, total vine length, and total vine dry weight; however, TSS decreased substantially in both years. Water consumption was 449–720 mm and 417–677 mm in 2002 and 2003, respectively. Maximum fruit yield was obtained from the I125 treatment, with 720 and 677 mm irrigation water resulting in 84.4 and 88.6 t/ha. WUE and IWUE values in both years were close because of a 0.25 uniform decease in IW/CPE values. Yield response factor (ky ) was 1.15, indicating that the rate of decrease in yield was more important than water usage. In semiarid regions a yield response factor (ky ) of 1.15 could be suggested. Obtaining a yield response factor >1.0 could be attributed to the 0.25 uniform increments of IW/CPE values. These results suggest that the yield loss is more important than the evapotranspiration deficit when ky > 1. In the first year, crop production was lower than in the second year, even though insecticide application was made twice in that year. It was thought that heavy infestation of pests reduced the crop yield considerably. In the second year, there was no need for the chemical application.

An inverse linear relationship was determined between fruit yield and CWSI. The data obtained in this study with CWSI values >0 did not always mean reduced yields. The data suggested that yield would be reduced if the seasonal CWSI value were >0.14. However, the CWSI values fluctuated, even for the non-water stressed treatment, particularly in 2002. Thus, further studies and data may be needed to recommend a threshold CWSI value that could be used to determine instantaneous crop water stress. Overall, the results showed that the I125 treatment is the best application in semi-arid regions under no water shortage. On the other hand, under water shortage, the I75 treatment seemed to be a better choice because of a 32.6% water saving, even though there was a 26.2% yield loss. Considering water savings and the crop yield, I100 was not a good choice. Acknowledgments We would like to express our sincere thanks to the managing editor, Ms J. Fegent, for assistance, and the anonymous reviewer who helped us to improve our manuscript substantially. References Dinç U, S¸enol S, Sayın M, Kapur S, Yılmaz K, et al. (1991) The physical, chemical and biological properties and classification mapping of soils of the Harran Plain. TUBITAK Project number: TOAG-534. Doorenbos J, Kassam AH (1979) ‘Yield response to water.’ FAO Irrigation and Drainage Paper No. 33. (Food and Agriculture Organization of the United Nations: Rome) Erdem Y, Yüksel N (2003) Yield response of watermelon to irrigation shortage. Scientia Horticulturae 98, 365–383. doi: 10.1016/S03044238(03)00019-0 FAO (2003) http://www.fao.org FAO-UNESCO (1974) ‘Soil map of the world. 1 : 5 000 000 scale.’ (FAO: Rome) Ferreira TC, Carr MKV (2002) Responses of potatoes (Solunum tuberosum L.) to irrigation and nitrogen in a hot, dry climate. I. Water use. Field Crops Research 78, 51–64. doi: 10.1016/S03784290(02)00089-8 Foroud N, Mundel HH, Saidon G, Entz T (1993) Effect of level and timing of moisture stress on soybean plant development and yield components. Irrigation Science 13, 149–155. doi: 10.1007/ BF00190029 Idso SB, Jackson RD, Pinter PJ, Reginato RJ, Hatfield JL (1981) Normalizing the stress-degree-day parameter for environmental variability. Agricultural and Forest Meteorology 24, 45–55. Idso SB, Jackson RD, Reginato RJ (1977) Remote sensing of crop yields. Science 196, 19–25. Imtiyaz M, Mgadla NP, Manase SK, Chendo K, Mothobi EO (2000) Yield and economic return of vegetable crops under variable irrigation. Irrigation Science 19, 87–93. doi: 10.1007/ S002710050005 Kapur S, Sayın M, Gülüt K, Sahan S, C ¸ avusgil V, Yılmaz K, Karaman C (1991) Mineralogical and micromorphological properties of widely distributed soil series in the Harran Plain. TUBITAK Project Number 534. Nielsen DC, Clawson KL, Blad BL (1984) Effect of solar azimuth and infrared thermometer view direction on measured soybean canopy temperature. Agronomy Journal 76, 607–610.



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Manuscript received 23 December 2003, accepted 8 October 2004.

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