The effects of different irrigation regimes on cucumber ( L.) yield and yield characteristics under...

The effects of different irrigation regimes on

cucumber (Cucumbis sativus L.) yield and yield

characteristics under open field conditions

Mehmet Simseka,*, Tahsin Tonkaza, Murat Kacırab,Nuray Comlekciogluc, Zeki Dogand

aDepartment of Agricultural Structures and Irrigation, Faculty of Agriculture,

Harran University, 63040 Sanlıurfa, TurkeybDepartment of Agricultural Machinery, Faculty of Agriculture, Harran University, 63040 Sanlıurfa, Turkey

cDepartment of Horticulture, Faculty of Agriculture, Harran University, 63040 Sanlıurfa, TurkeydDepartment of Biometry Science, Faculty of Agriculture, Harran University, 63040 Sanlıurfa, Turkey

Accepted 26 October 2004

Abstract

A study was conducted to determine the effects of different drip irrigation regimes on yield and

yield components of cucumber (Cucumbis sativus L.) and to determine a threshold value for crop

water stress index (CWSI) based on irrigation programming. Four different irrigation treatments as

50 (T-50), 75 (T-75), 100 (T-100) and 125% (T-125) of irrigation water applied/cumulative pan

evaporation (IW/CPE) ratio with 3-day-period were studied.

Seasonal crop evapotranspiration (ETc) values were 633, 740, 815 and 903 mm in the 1st year and

were 679, 777, 875 and 990 mm in the 2nd year for T-50, T-75, T-100 and T-125, respectively.

Seasonal irrigation water amounts were 542, 677, 813 and 949 mm in 2002 and 576, 725, 875 and

1025 mm in 2003, respectively. Maximum marketable fruit yield was from T-100 treatment with

76.65 t ha�1 in 2002 and 68.13 t ha�1 in 2003. Fruit yield was reduced significantly, as irrigation rate

was decreased. The water use efficiency (WUE) ranged from 7.37 to 9.40 kg m�3 and 6.32 to

7.79 kg m�3 in 2002 and 2003, respectively, while irrigation water use efficiencies (IWUE) were

between 7.02 and 9.93 kg m�3 in 2002 and between 6.11 and 8.82 kg m�3 in 2003.

When the irrigation rate was decreased, crop transpiration rate decreased as well resulting in

increased crop canopy temperatures and CWSI values and resulted in reduced yield. The results

www.elsevier.com/locate/agwat

Agricultural Water Management 73 (2005) 173–191

* Corresponding author. Tel.: +90 414 2472487; fax: +90 414 2474480.

E-mail address: [email protected] (M. Simsek).

0378-3774/$ – see front matter # 2004 Elsevier B.V. All rights reserved.

doi:10.1016/j.agwat.2004.10.013

indicated that a seasonal mean CWSI value of 0.20 would result in decreased yield. Therefore, a

CWSI = 0.20 could be taken as a threshold value to start irrigation for cucumber grown in open field

under semi-arid conditions.

Results of this study demonstrate that 1.00 IW/CPE water applications by a drip system in a 3-day

irrigation frequency would be optimal for growth in semiarid regions.

# 2004 Elsevier B.V. All rights reserved.

Keywords: Drip irrigation regimes; Cucumber (Cucumbis sativus L.); Yield and yield characteristics; CWSI

1. Introduction

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. Agricultural production in 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. It is well

documented that degradation of soils, including salinity, will be a major problem in GAP

region unless modern agricultural and irrigation techniques are applied, due to highly clay

content of the soil and the high evaporation rates (Yazar et al., 2002).

Effective use of water is critical in arid and semi-arid regions. Excessive watering and

improper irrigation techniques lead to non-uniform distribution of water in crop field, with

reduces yield (Phene and Sanders, 1976). Phene et al. (1979) and Papadopoulos (1991)

indicated that negative developments in soil and crops could be prevented by applying

water to the effective root zone with low volume application of water under low pressures

by microirrigation. Locascio and Smajstrala (1995) reported that a drip irrigation system

applied to tomato used 37% less water when compared to furrow irrigation. More effective

utilisation of water for vegetable production in India by drip irrigation as opposed to furrow

irrigation is reported (Pandey and Mahajan, 1999). Yield in tomato and water use efficiency

(WUE) is increased with drip irrigation systems in USA compared to basin irrigation (Pruit

et al., 1989). In a different study, WUE obtained by drip irrigation was found 68.0–76.8%

more than application of furrow irrigation (Singandhupe et al., 2003).

Irrigation programs could be developed by application of deficit irrigation at different

rates throughout the growing season and seasonal crop evapotranspiration could be

determined for different growing periods (Jansen, 1968). Various researches have been

conducted on determining of water production functions and these functions have been

developed by using evapotranspiration, transpiration and applied irrigation (Jansen, 1968;

Hiler and Clark, 1971). Irrigation programs and applications based on the relationship

between irrigation water (IW) and cumulative pan evaporation (CPE) are not complex.

Only a standard United States Weather Bureau class A pan evaporimeter is needed for this

application of irrigation water management. Indian government advised this method to the

M. Simsek et al. / Agricultural Water Management 73 (2005) 173–191174

farmers (Panigrahi et al., 2001). Imtiyaz et al. (2000) and Saudan et al. (2000) have

obtained positive results in many crop plants by applying various IW/CPE ratios. This

method of irrigation programming has been widely used due to its simplicity (Ferreia and

Carr, 2002).

Lack of precipitation and limited water supply during crop growing season are

important considerations that need which need careful attention for crop production.

Therefore, the relationships between crop water consumption, crop water stress and yield

have to be determined for a better water saving.

Drip irrigation method is hardly used to irrigate several crops in GAP region and Turkey.

Therefore, researches on application of this system for irrigation of field crops is still

conducted in GAP region where semi-arid climatic conditions prevalent. Most of the

research is conducted to investigate the effects of different irrigation intervals and

irrigation amounts on crop yield.

Irrigation programming methods are generally based on soil water status or

meteorological parameters for modelling or computing evapotranspiration. However,

scheduling based on crop water status could be more advantageous since crops respond to

both soil and their environment. Canopy temperature has been investigated as an indicator

of its water status. As crops are heated by radiation, plants transpire to cool themselves to

prevent overheating. Crop canopy temperature rises, if there is not enough water supply

or heating load exceeds transpirative cooling load. Researchers have reported using

empirically determined crop water stress index (CWSI) for water stress assessment (Idso

et al., 1977, 1981a; Nielsen et al., 1984). Because it is simple and requires only three

variables to be measured (canopy and air temperatures and relative humidity), the

empirical approach has received much attention. An empirical linear relationship for

canopy-air temperature difference (Tc � Ta) versus vapor pressure deficit (VPD) of air

exist for a crop transpiring at its potential rate. The lower limit of Tc � Ta versus VPD

represents the measured temperature difference when the crops are well watered. The

upper limit of Tc � Ta is obtained from crops with transpiration approaching zero

(maximum stress).

Cucumber, with 36.4 million tonnes production in the world and 1.75 million tonnes in

Turkey, is one of the most important vegetable (www.fao.org, 2002). Cucumber is grown as

first crop during spring and can also be grown as a second crop after the harvest of first crop

during summer–fall in the open field in Harran Plain. However, the production of cucumber

as a second crop depends on the ecological factors such as soil type, availability of water,

air temperature and humidity and these are the main factors affecting the yield and quality

in the production. Economical yield in cucumber is determined by total yield (total fruit

weight) and fruit quality. The most important quality characteristics are weight, diameter

and dry matter of the crop.

The production of dry matter in a crop depends on its capability to utilize existing

resources. The most significant inputs in single crop production are solar energy and the

effective use of irrigation water. When more than one crop is grown in intensive

agriculture in the same location, the yield is increased due to extra utilization of resources

and this is essential (Caviglia et al., 2004). The effectiveness of resources is measured by

the ratio of production to annual consumption of photosynthetic active radiation or

consumed water.

M. Simsek et al. / Agricultural Water Management 73 (2005) 173–191 175

The goal of this study was to determine the effect of different drip irrigation regimes,

applied as different ratios of IW/CPE with 3-day irrigation intervals, on yield and yield

characteristics of cucumber grown in field under semi-arid climate conditions.

2. Materials and methods

2.1. Experimental site and climatic data

A field experiment in 2002 and 2003 was conducted at the University of Harran

Agricultural Experimental Research Field, Sanlıurfa, Turkey (378080N and 388460E, 464 m

above sea level).

The soil series in the research field is ‘Ikizce’ formed from the colluvials and bajadas

physiographic units (Dinc et al., 1991). The texture of Ikizce soils is clay throughout the

profiles. The soil studied is classified as Entisol and Fluvisol, according to soil taxonomy

(Soil Survey Staff, 1999) and FAO-UNES (1974). The majority of the studied soils were

determined to have dominant smectite fallowed by palygorskite, illite and kaolinite (Kapur

et al., 1991).

The weather is hot and dry from July to October when temperatures can reach up to

47 8C, and an average of 410 mm of precipitation occurs in a year and the relative humidity

averages about 49%. Table 1 shows the climatic variables for experimental years and

averages of long years especially for the months of July to October during which the

experiments were conducted. (Anon., 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 due to irrigation in the plain (Tonkaz et al., 2003).

2.2. Crop management, experimental design and irrigation treatments

Cucumbis sativus L. Beit alpha cv. Amelia F1 cucumber seed was used in the

experiments. The seeds were sown in the field on July 22nd and July 16th in 2002 and 2003,

respectively. Thiophanate methyl (0.75 g L�1) was added to the first irrigation water

against fungicides. In 2002 and 2003, an insecticide, containing Dichlorvos, (1.6 g L�1)

was applied twice to control Tetranychus spp. and Bemicia tabaci. The field experiment

was setup employing a randomized complete block design with three replications. As

shown in Fig. 1, each replication contains four different irrigation regimes, randomly

distributed in the plots. Each plot consists of three double rows. Inter double row spacing is

2.0 m and inter single row spacing is one-half meter. Intra row spacing is 0.4 m. Each plot

size is 39 m2 and consists of 78 cucumber plants and it means that plant density is 2 plants

per m2.

A total of 21 harvests in 2002 and 23 harvests in 2003 were performed. Each cucumber

fruit was weighted in each harvest to determine mean fruit weight (MFW). Yield per ha was

obtained from marketable fruit yield (MTFY). Fruit diameter (FD), fruit length (FL) and

fruit dry matter (FDM) was measured in the 2nd year.

Just before sowing, phosphate (P2O5) was applied at a rate of 100 kg ha�1 and

potassium (K2O) was applied at a rate of 200 kg ha�1. In addition, nitrogen was applied


at a rate of 130 kg ha�1. One-third of potassium and ammonium nitrate was applied

before sowing and 2/3 was applied at equal dosages to the root region with the

automatic fertigation system between 4th- and 9th-week after sowing. Two hundred

liters fertilizer tank and venture injector were used for fertigation and phosphoric-acid

(H3PO4) application. H3PO4, at a rate of 0.035 g L�1, was applied once in three

irrigations.

The four different irrigation treatments were 50 (T-50), 75 (T-75), 100 (T-100) and

125% (T-125) of IW/CPE. The CPE values were obtained from a standard United States

Weather Bureau. Class A pan evaporimeter was located in the experimental site. Three-day

CPE values were used for irrigation. The use of IW/CPE ratios makes irrigation

programming easier. There have been many research conducted related to irrigation

programming using IW/CPE ratios such as Ferreia and Carr (2002).

The irrigation water was delivered to the plants by 8 m3 h�1 capacity centrifuge water

pump (KSB1 Germany). The water from water tank was delivered to the field by a sub-

main 32-mm diameter polyethylene (PE), 16-mm diameter laterals with in-line emitters

located 0.4-m apart, surface drip laterals spaced at 2.5 m intervals, one drip lateral each row

and operating at constant pressure of 152 kPa with 2.0 L h�1 (model Typhoon 25-0.63-20

Netafim Irrigation Inc., Israel). Irrigation water was checked by flow water meter in valves

and drip irrigation system was setup 3 days before seedlings.

Lateral lines were plugged at the ends with figure-eight loops. Irrigation treatments were

started when soil water content at the effective root depth (60 cm) decreased to 50% of the

available soil water on August 12th (21 days after sowing; 21 DAS) in the 1st year and on

August 6th (21 DAS) in the 2nd year. This resulted in total of 18 and 20 irrigation events in

2002 and 2003, respectively.


Table 1

Weather conditions during the experiments compared to the long term mean

Years Average air

temperature

(8C)

Average

relative

humidity

Total

precipitation

(mm)

Total solar

radiation

(cal min�1 cm�2)

Average

wind speeda

(km h�1)

Class A-pan

evaporation

(mm)

2002

July 32.0 37.0 4.6 622.30 1.6 408

August 30.5 43.7 0.0 573.30 3.0 378

September 26.9 47.8 0.7 474.60 2.6 286

October 21.8 48.6 6.6 338.90 1.7 189

2003

July 32.6 29.0 0.0 636.75 1.9 432

August 32.7 32.2 0.0 545.49 2.3 339

September 26.4 42.4 0.1 470.25 2.5 281

October 20.7 47.9 15.9 329.71 2.0 176

Long run average (1929–2003)

July 33.0 28.3 0.7 555.60 1.7 419

August 31.1 31.0 1.5 507.34 2.1 375

September 26.7 34.0 1.4 422.69 1.8 294

October 20.0 44.0 20.6 306.42 1.3 191

a Average wind speed (at 2 m height).

2.3. The water balance

The soil water content percentage (w/w) at field capacity was between 28.50 and

30.10% (w/w) and permanent wilting point between 21.90 and 23.10% (w/w). Some

physical and chemical properties of the study area are listed in Table 2. The bulk density

was between 1.37 and 1.44 Mg m�3, organic matter was between 1.91 and 2.29% and

electrical conductivity (EC) was between 0.05 and 0.08 dS m�1. Parameters between soil

layers did not show significant differences (Table 2). The parameters in the soil, except EC,

decreased as moved from upper the lower layers. The small changes in the EC in lower

layer could be attributed to the possibility of salinization in that layer.

The gravimetric water content was measured from the soil samples taken at 9-day

intervals after the start of experiment. The variation of soil water content at 0–15, 15–30,


Fig. 1. The setup of the irrigation system in to first replication.

30–45 and 45–60 cm soil depths in each treatment plot was continuously determined

using gravimetrically and volumetric water content% (v/v) was calculated using

gravimetric water content% (w/w) and bulk density (rb) using % (v/v) = % (w/w) � rb

(Stone et al., 1987). The bulk density of the soil was determined before planting when the

soil water content was at 30–34% (v/v). Volumetric soil water was then converted into

millimeter and accounted for each incremental soil depth (d) by [% (v/v) � d)/10]

(Foroud et al., 1993).

Crop evapotranspiration under varying irrigation regimes was calculated using the water

balance model (Eq. (1)),

ETc ¼ IW þ P � D � R � DS

ðIW ¼ kp � E; kp : 0:50; 0:75; 1:00 and 1:25Þ(1)

where ETc (and also ETa) is the seasonal crop evapotranspiration, IW the applied irriga-

tion water, kp is crop pan coefficient (irrigation treatment; 0.50:T-0.50, 0.75:T-0.75,

1.00:T-1.00 and 1.25:T-1.25, respectively), E the evaporation, P the precipitation, D

the drainage, R the run-off and �DS is variation in water content of the soil profile. All

terms are expressed in mm of water in the cucumber root zone. The effective root depth

was taken as 60 cm. In addition, the water content at the depths of 60–120 cm were also

determined and the total water content in these layers was considered to be deep

percolation. Run-off was taken to be zero since it did not occur with the use of drip

irrigation system.

2.4. Water use efficiency (WUE) and irrigation water use efficiency (IWUE)

WUE is the ratio of MTFY (t ha�1) and seasonal crop ET (ETc) (mm) (Eq. (2)),

WUE ¼ Ya

ETc(2)

If the crop yield; Ya is expressed in kg and the water use ETc is expressed in m3 m�2, then

WUE has units of kg m�3 on a unit water volume basis or g kg�1 when expressed on a unit

water mass basis. (Vites, 1962; Stanhill, 1986). IWUE is obtained fruit weight from per unit

IW (Eq. (3)),

IWUE ¼ Ya

IW(3)


Table 2

Selected properties of the soila

Soil depth FC% (w/w) WP% (w/w) AWC (mm) BD (Mg m�3) OM (%) EC (dS m�1)

0–15 30.10 22.40 16.63 1.44 2.29 0.05

15–30 29.60 23.10 14.04 1.41 2.15 0.05

30–45 28.70 22.30 13.82 1.39 2.10 0.06

45–60 28.50 21.90 14.26 1.37 1.91 0.08

a FC: field capacity; WP: permanent wilting point; AWC: available water holding capacity; BD: bulk density;

OM: organic matter; EC: electrical conductivity.

2.5. Canopy temperature and crop water stress index (CWSI)

The canopy temperature (Tc) was measured using a hand-held IRT (Raytek1MX2,

Berlin Germany) with a 1.48 field of view (1 72 mm at 3.0 m). The IRT was operated with

the emissivity adjustment. The canopy temperature measurements were done 1 day before

irrigation event. The measurements were made between 10:00 a.m. and 14 p.m.

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 sensors were scanned

every 1 min and the data was averaged every 5 min and recorded. Canopy temperature

measurements were taken after the treatment irrigation was started. Total of nine canopy

temperature measurements were taken with 3-day interval both from August 20th to

September 21st in 2002 and from August 18th to September 19th in 2003.

The CWSI values were calculated using the method outlined Idso et al. (1981a). In the

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. The lower limits of the Tc � Ta versus VPD relationship were determined using

the data collected only in well-watered treatment group (T-125). The upper limit of Tc � Ta

was computed using the method provided by Idso et al. (1981b). Using the lower and upper

limit estimates, a CWSI value can be determined as (Eq. (4));

CWSI ¼ ðTc � TaÞ � ðTc � TaÞLL

ðTc � TaÞUL � ðTc � TaÞLL

(4)

where, Tc (8C) is canopy temperature, Ta (8C) is air temperature, (Tc � Ta)LL is lower limit

of canopy–air temperature difference and (Tc � Ta)UL is upper limit of canopy–air

temperature difference.

2.6. Statistical analysis

Data were analyzed using SAS statistical program (SAS Inst., 1991). Analysis of

variance (ANOVA) was conducted and significance of differences among treatment was

tested using the least significant difference using the Duncan method. Differences were

declared very significant at P < 0.01 and significant P < 0.05.

3. Results

3.1. Total water and water use

Vertical and horizontal soil moisture measurements at all treatments indicated that the

soil moisture values at the emitter point with irrigation treatments of T-125, T-100, T-75

and T-50 were similar to 50, 40, 30 and 25 cm distances in both side of the emitters at 15–

30 cm depth, respectively. In addition horizontal movement of the irrigation water stops at

75, 60, 55 and 40 cm with the treatments T-125, T-100, T-75 and T-50, respectively. Active

root depth for cucumber assumed to be 60 cm, and therefore, deep percolation

measurements were made 60–90 cm and 90–120 cm soil depths. Result indicated that


percolation occurred only with T-125 treatment of about 21% calculated from 2 years

average. Maximum yield was obtained from T-100 treatment with non-detected deep

percolation, indicating a more effective use of irrigation water.

Crops were pre irrigated before irrigation treatments started. The irrigation treatments

started on 21 days after sowing (DAS) in both years and were ended on 75 and 81 DAS in

2002 and 2003, respectively.

The total water applied (IW) to the treatment groups T-50, T-75, T-100 and T-125 were

542, 677, 813 and 949 mm for the 1st year and were 576, 725, 875 and 1025 mm for the 2nd

year (Fig. 2a, b). The crop evapotranspiration (ETc) were determined to be 633, 740, 815

and 903 mm in the 1st year and 679, 777, 875 and 990 mm in the 2nd year for T-50, T-75,

T-100 and T-125, respectively. The values of IW for the T-125 treatment group were found

to be higher than ETc values in both years. The reason for ETc < IW in T-125 treatment was

due to the fact that the irrigation water applied to the plants in this group was more than the

crop’s need and occurrence of deep percolation. The values of ETc and IW were similar in

T-100 treatment group. However, the IW values were found to be much smaller than ETc

values. Thus, it could be said that the water extracted by the crops from the soil in these

treatment groups was higher than the water applied.


Fig. 2. Cumulative irrigation water (IW) applied for cucumber under different irrigation regimes.

A strong and polynomial relationship was determined between MTFY and IW for both

years (Eq. (5)–(8)). The maximum yield was obtained from T-100 treatment group

(Fig. 3(a) and (b)). More irrigation water resulted in vigorous leave development on the

plants. Through non-linear regression analysis, a mathematical function was obtained.

3.1.1. Relationship between IW and MTFY

Year 2002:

MTFY ¼ �0:0002 IW2 þ 0:4109 IW � 97:167 ðr2 ¼ 0:82Þ (5)

Year 2003:

MTFY ¼ �0:0001 IW2 þ 0:2680 IW � 55:086 ðr2 ¼ 0:91Þ (6)

3.1.2. Relationship between ETc and MTFY

Year 2002:

MTFY ¼ �0:0005 ET2c þ 0:8038 ETc � 261:93 ðr2 ¼ 0:76Þ (7)


Fig. 3. The relationship between (a) marketable total fruit yield (MTFY) and irrigation water (IW) and (b) MTFY

and crop evapotranspiration (ETc) for 2002 and 2003, respectively.

Year 2003:

MTFY ¼ �0:0003 ET2c þ 0:5952 ETc � 201:55 ðr2 ¼ 0:93Þ (8)

3.2. Fruit yield and yield characteristics

Harvest was started on 39 and 42 DAS in 2002 and 2003, respectively. The total growing

periods were 79 and 86 DAS for 2002 and 2003, respectively. The maximum yield was

obtained on the 8th harvest in the 1st year, while it was achieved between 4th and 6th

harvest days in the 2nd year (Fig. 4). The reason for the difference was attributed to

variation in climate. The fruits were classified as marketable and non-marketable fruits in

each harvest and the yields were determined. The reason for obtaining low marketable fruit

yield was due to sudden air temperature decreased 8–10 8C during 4th to 9th September

and 4–5 8C during 18th to 20th September in 2003.

Analysis of variance results and yield and yield characteristics are presented in

Tables 3–5 for 2002 and 2003, respectively.

A linear relationship between IW/CPE and fruit yield was obtained in all treatment

groups except T-125. Cucumber MTFY was 76.65–53.81 t ha�1 in 2002 and 68.13–


Fig. 4. The history of marketable total fruit yield MTFY during harvest for (a) 2002 and (b) 2003.

M.

Sim

seket

al./A

gricu

ltura

lW

ater

Ma

na

gem

ent

73

(20

05

)1

73

–1

91

18

4

Table 3

Summary of ANOVA for growing parameters (significance of the sources of variation, 2002–2003)

Source DF 2002 2003

MTFY (t ha�1) MTFYPP (g) FNPP MFW (g) MTFY (t ha�1) MTFYPP (g) FNPP FMW (g)

Mean

square

F-value Mean

square

F-value Mean

square

F-value Mean

square

F-value Mean

square

F-value Mean

square

F-value Mean

square

F-value Mean

square

F-value

Treatment 3 272.0 895.3* 680029.3 895.0* 48.6 21.8* 59.7 2.8ns 159.1 44.7* 397756.0 44.6* 32.1 30.0* 11.9 4.2ns

Block 2 41.2 13.7* 10440.9 13.7* 2.2 1.0ns 6.0 0.3ns 0.4 0.1ns 1009.1 0.1ns 0.7 0.7ns 2.6 0.9ns

Error 6 0.3 759.8 2.2 21.5 3.6 8917.5 1.1 2.8

Statistical significance level; ns: not significant (P > 0.05).* Significant at the P < 0.01 probability level.

50.82 t ha�1 in 2003. Non-marketable fruit yield (N-MTFY) for T-50, T-75, T-100 and T-

125 groups were determined to be 4.88, 7.35, 10.86 and 10.63 t ha�1 for the 1st year and

they were 6.47, 7.91, 10.60 and 10.77 t ha�1 for the 2nd year (not shown in Table).

Significant differences in MTFY, MTFYPP and FNPP among the treatments were

determined (Table 4) (P < 0.01). Based on the results, MTFY increase was obtained in T-

100 treatment with maximum N-MTFY.

A linear relationship between MTFY or MTFYPP and IW was obtained in both years,

except for T-125 treatment group. It was observed that 25% in irrigation water did not

result in an increase in MTFY in T-125 group. On the contrary, a 13.13 in and 8.14% of

decrease in yield in 2002 and 2003 was found in T-125 group compared to T-100 group. It

was concluded that the water was not used effectively in T-125 treatment group and this

suggested that more irrigation water did not resulted in more MTFY. The reason for this

was that the cucumber showed a negative response to excessive watering and this response

was clearly observed on MTFY and MTFYPP values. These results suggested that the

cucumber is sensitive to excessive watering indicating a significant amount of loss could

occur both in the irrigation water and the yield. Therefore, IW/CPE ratio of 1.0 could be

recommended for water balance in semi-arid regions. Either a decrease or increase in IW

was insignificant on FD and FL values (P > 0.05). The decrease in IW in T-50 and T-75

groups resulted in significant increase in FDM (P < 0.05). A high fruit yield is more

desirable in cucumber since it is a vegetable and it is consumed as fresh. Thus, a higher

FDM obtained in T-50 and T-75 treatment groups does not suggest that the irrigation


Table 4

Summary of ANOVA for yield characteristic significance of the sources of variation, 2003

Source FD (cm) FL (cm) FDM (% of fruit weight)

DF Mean square F-value Mean square F-value Mean square F-value

Treatment 3 0.004 0.7ns 0.6 0.6ns 0.76 4.1ns

Block. 2 0.012 2.3ns 0.6 0.6ns 0.02 0.1ns

Error 6 0.005 1.1 0.18

Total 12

Probability level; ns: not significant (P > 0.05).

Table 5

Cucumber marketable fruit yield and yield characteristic in response to irrigation

Year Treatment MTFY (t ha�1) MTFYPP (g) FNPP FMW (g) FD (cm) FL (cm) FDM (%)

2002 T-50 53.81 a 2691 a 27.39 a 98.38 ab

T-75 62.02 b 3101 b 33.32 b 93.30 a

T-100 76.65 d 3832 d 36.88 c 104.00 b

T-125 66.58 c 3329 c 34.39 bc 96.80 ab

2003 T-50 50.82 a 2541 a 28.38 a 89.58 a 2.33 a 22.73 a 4.43 b

T-75 58.54 b 2927 b 32.00 b 91.48 ab 2.32 a 22.30 a 3.80 ab

T-100 68.13 d 3406 d 36.16 c 94.23 b 2.26 a 23.37 a 3.50 a

T-125 62.58 c 3129 c 33.68 b 92.90 ab 2.33 a 22.60 a 3.27 a

Note: Numbers followed by different letters are statistically different (P < 0.05).

regime in these treatment groups is more appropriate. Because, MTFY, MTFYPP and

FNPP values were found to be significantly low in these treatment groups. It could be

pointed out that some of the yield components such as FD, FL and FDM were not

investigated in the 1st year and this does not affect the fundamental basis of the current

study (Table 5).

3.3. Water use efficiency (WUE and irrigation water use efficiency (IWUE)

It is a very crucial to maximize water use due to energy requirement by the drip

irrigation system and limited water supplies. The only way to accomplish this is to use

water effectively.

The WUE and IWUE values were similar in both years ranged from 7.37 to 9.40 and

7.02 to 9.93 kg m�3 for the 1st year and they were within the ranges between 6.32–7.79 and

6.11–8.82 kg m�3 for the 2nd year, respectively (Table 6).

The WUE and IWUE values were similar in both years (Table 6). Maximum value of

IWUE, 9.93 and 8.82 kg m�3, was determined in T-50 group in both years whereas

minimum values were obtained from T-125 treatment group with 7.02 and 6.11 kg m�3.


Table 6

Water use and irrigation water use efficiency for different treatments

Year Treatment MTFY (t ha�1) IW (mm) ETc (mm) IWUE (kg m�3) WUE (kg m�3)

2002 T-50 53.81 542 633 9.93 8.50

T-75 62.02 677 740 9.16 8.38

T-100 76.65 813 815 9.43 9.40

T-125 66.58 949 903 7.02 7.37

2003 T-50 50.82 576 679 8.82 7.48

T-75 58.54 725 777 8.07 7.53

T-100 68.13 875 875 7.79 7.79

T-125 62.58 1025 990 6.11 6.32

Fig. 5. The lower baselines for Tc � Ta vs. VPD for 2002.

Maximum values of WUE were found in T-100 with 9.40 and 7.79 kg m�3. This result

indicated that the water was used most effectively in T-100 group. As the irrigation water

increased, a linear increase was determined in T-50, T-75 and T-100 treatment groups while

the values of MTFY decreased and a significant decline was also observed in T-125 group

as well. The decrease of yield in T-50 compared to T-100 treatment group was found to be

23.27 and 25.41% for 2002 and 2003, respectively. The yield was also decreased in T-125

group compared to T-100 by 21.2 and 18.7% in 2002 and 2003, respectively, as the

irrigation water was increased by 25%. The overall results indicated that deficit and excess

irrigation did not show significant effect on the yield and yield components of cucumber

crop. Mao et al. (2003) reported that maximum IWUE and WUE were obtained in

treatment groups with minimal irrigation in greenhouse conditions with border irrigation.

The reason for obtaining higher yield in their study compared to this study might be

attributed to the fact that their experiments were conducted in greenhouse conditions. The

current study showed that the irrigation performance of the cucumber, especially those in

T-100 treatment group in which highest yield was obtained, as a second crop in semi-arid

region was good.


Fig. 6. The lower baselines for Tc � Ta vs. VPD for 2003.

Fig. 7. The history of CWSI for the experiment period in 2002.

3.4. Crop water stress index and yield

Figs. 5 and 6 illustrate the non-water stress baselines (lower limit of Tc � Ta versus

VPD) for 2002 and 2003, respectively. The upper limits of Tc � Ta were found to be 4.03

and 3.17 8C for 2002 and 2003 using the procedure out lined by Idso et al. (1981a).

As seen from the figure, crop recovered from water stress after the irrigation and CWSI

declined accordingly and increased prior to the next irrigation. The results also showed that

CWSI values were ranked accordingly to the available water in the soil based on the

irrigation treatments. A mean CWSI values for each treatment was calculated as the

averages of CWSI values for all measurement period for 2 years (Figs. 7 and 8). The mean

CWSI values of 0.07 (T-125), 0.21 (T-100), 0.30 (T-75) and 0.52 (T-50) were determined in

2002 and the CWSI values of 0.03 (T-125), 0.19 (T-100), 0.35 (T-75) and 0.51 (T-50) were

found in 2003 (Figs. 7 and 8). In general, as the crop water stress increases, the yield is

expected to decrease. Fig. 9 shows the relationship between the mean CWSI value and the

yield excluding the data from T-125 treatment group. Fruit yield was increased by the

irrigation level. An inverse linear relationship was obtained for these two parameters.

When the irrigation level is decreased, the transpiration rates of the crops were decreased


Fig. 8. The history of CWSI for the experiment period in 2003.

Fig. 9. The relationship between mean CWSI and mean fruit yield for average of the 2 years.

resulting in increased crop canopy temperatures and CWSI values resulting in reduced

yield. This result agrees with many other studies (Orta et al., 2003) and for other crops

(Reginato, 1983; Howell et al., 1986; Wanjura et al., 1995; Yazar et al., 1999). The results

of this study indicated that permitting the seasonal mean CWSI values of 0.20 would result

in decreased fruit yields.

4. Conclusions

The results of MTFYPP were found to be similar to MTFY in all treatment groups. A

21% deep percolation was observed in T-125 treatment and 21.2 (2002) and 18.7% (2003)

of decrease in MTFY IW/CPE was determined in the same treatment compared to values of

T-100 treatment. This suggests that more irrigation water does not result in more yields in

cucumber.

Irrigation treatments did not significantly affect FD and FL. Excessive irrigation caused

decrease in fruit dry matter. As observed in T-50 treatment, 50% reduction in irrigation

water resulted in 4.43% increase in FDM values in compared to those determined in T-75,

T-100 and T-125 groups in both years.

The maximum WUE was found in T-100 treatment group. Application of 1 mm

irrigation water in 1000 m2 area resulted in 9.40 and 7.79 kg MTFY in 2002 and 2003,

respectively. Application of water in T-125 group resulted in minimum WUE values as

7.37 and 6.32 kg for the experimental years.

The period of June 15th to September 15th is important for growing cucumber as a

second crop. If the ecological conditions are favorable (temperature, radiation, relative

humidity, etc.) as in this region where the current study was conducted and the water is

available, alternative second crops could be grown and substantial profit could be made

from such production. The results of this study, therefore, recommend production of

cucumber as a second crop in regions similar to that in this study.

A plant response based irrigation program using CWSI could be used for irrigation

automation. In this case, it is necessary to determine threshold values to activate irrigation

event. The results of this study indicated that permitting the seasonal mean CWSI values of

0.20 would result in decreased fruit yields. Therefore, a value of CWSI = 0.20 or smaller

values could be taken as a threshold value to start irrigation for cucumber grown in open

field under the growing conditions described in this paper.

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