Integrating deficit irrigation into surface and subsurface drip irrigation as a strategy to save water in arid regions

Agricultural Water Management 209 (2018) 55–61

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Integrating deficit irrigation into surface and subsurface drip irrigation as a strategy to save water in arid regions Hussein M. Al-Ghobari, Ahmed Z. Dewidar

T

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Agricultural Engineering Department, King Saud University, Riyadh 11451, Saudi Arabia

A R T I C LE I N FO

A B S T R A C T

Keywords: Subsurface drip irrigation Deficit irrigation Irrigation water use efficiency Tomato Water saving

Development of sustainable and efficient irrigation strategies is a priority for producers faced with water shortages. A promising management strategy for improving irrigation water use efficiency (IWUE) is deficit irrigation, which attempts to optimize yield and IWUE. Soil water use, crop yield and IWUE of tomato were evaluated for two consecutive years under two types of irrigation methods (subsurface and surface drip irrigation) and three irrigation strategies: 1.0 of full irrigation supply (T1), 0.8 of full irrigation supply (T2) and 0.6 of full irrigation supply (T3). The results showed that the highest yields were found in the plots irrigated by subsurface drip irrigation at T1 (94.1 ton/ha) and T2 (81.4 ton/ha). Conversely, the fully stressed treatment (T3) reduced the amount of irrigation water by 40%, but significantly decreased mean tomato yield by 25.6% and 26.1% under subsurface and surface drip irrigation, respectively, as compared to T1. The maximum IWUE tended to be higher for subsurface drip than for surface drip irrigation system. The greatest IWUEs were obtained from subsurface drip and surface drip at T3 (19.7 kg/m3 and 18.3 kg/m3), whereas the lowest IWUEs were those estimated in T1 (15.9 kg/m3 and 14.8 kg/m3, respectively). The primary conclusion is that deficit irrigation strategies present certain advantages to crop water management with minimal effects on production and quality, thus contributing to crop sustainability.

1. Introduction Saudi Arabia, one of the driest and hottest countries in the world, is roughly located between north latitudes 17 and 31 and east longitudes 37 and 56. Temperatures can reach more than 50 °C (122 °F) in some areas, producing overwhelmingly hot and dry conditions. Long-term average rainfall across the country is 114 mm per year (DeNicola et al., 2015). High temperatures and low precipitation together with high variability of both factors increase evapotranspiration, reduce soil moisture, and damage the soil by mechanical weathering (Alkolibi, 2002). These conditions have a negative impact on agriculture and water availability which made Saudi Arabia a very poor country in terms of agricultural potential and water resources. The country has scanty rains and no lakes, rivers, or streams. Total municipal water use in Saudi Arabia is about 9%. Agriculture accounts for 88% and industry consumes only 3% of the available water (AlZahrani and Baig, 2011). Mismanagement of water use in the agricultural sector and an increasingly Westernized and consumerism-based shift in lifestyle are mostly to blame for Saudi Arabia's water-starved status, as precious groundwater sources have been injudiciously used over many years to the point of depletion. Achieving greater irrigation

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water use efficiency (IWUE) is a primary challenge and it includes the employment of techniques and practices that deliver irrigation water to the crops more accurately. In this context, a combination of deficit irrigation (DI), surface drip irrigation (SDI) and subsurface drip irrigation (SSDI) may play an important role in increasing IWUE. DI is a water conservation technique that exposes crops to a particular level of water stress during a certain developmental phase or throughout the entire growing season without a significant reduction in yield (Pereira et al., 2012). The risk of DI is low because the response curve of crop yield to water supply often has a wide plateau, and a considerable amount of water can be saved without a significant yield reduction compared with full irrigation (Zhang, 2003). Kumar et al. (2007) studied the effect of DI on water saving and onion yield. They demonstrated that applying 80% and 60% of crop water requirements bring about yield reductions of 14% and 38%, and saved 18% and 33% of irrigation water compared to full irrigation within 2 years, respectively. Patanè et al. (2011) indicted that applying a 50% reduction in crop water for the entire or even partial growing season helps reduce fruit losses and maintain a high fruit quality. According to Nahar and Gretzmacher (2002), glucose, fructose, sucrose, malic acid, ascorbic acid and citric acid content

Corresponding author. E-mail address: [email protected] (A.Z. Dewidar).

https://doi.org/10.1016/j.agwat.2018.07.010 Received 25 January 2018; Received in revised form 26 June 2018; Accepted 12 July 2018 0378-3774/ Published by Elsevier B.V.

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recorded at every irrigation event through multi-jet dry dial water meters settled along the sub-main lines.

increased significantly with water stress. Besides, DI reduces production costs, conserves water and minimizes leaching of nutrients and pesticides in to ground water (Nuruddin et al., 2003). The use of pressurized irrigation system applying water through an emitter on soil surface (SDI) or below the soil surface (SSDI) at a small operational pressure and minimizing soil evaporation has been popular for saving water and improving IWUE (Camp, 1998; Lamm et al., 1995; Ayars et al., 2015). Cui et al. (2008) pointed out SDI and SSDI can improve IWUE by 26.7–46.4% and fruit quality of table grape without detrimental effect on the fruit yield in arid region. Hassanli et al. (2009) conducted a comparison between three irrigation methods: SDI, SSDI and furrow irrigation. The results demonstrated that the minimum amount of water along with highest use efficiency, is delivered through SSDI and SDI, respectively. del Amor and del Amor (2007) performed a comparison between SDI and SSDI systems. They found that higher tomato crop yields were achieved by SSDI as compared to SDI in sandy soil. Similarly, Al-Omran et al. (2010) concluded that SSDI increased the IWUE and yield of their tomato crop by producing a good moisture distribution in the root zone, leading to a conservation of irrigation water. Information on deficit irrigation scheduling is limited for many crops especially tomato, which is a vital horticultural crop within arid regions (Maas and Hoffman, 1977). Accordingly, in light of water limitations, there is a necessity to establish different irrigation strategies that may facilitate the conservation of water under both high evaporative demand and chronic shortages without incurring considerably influencing yields. For this reason, different deficit irrigation approaches have been applied to tomato plants under SDI and SSDI systems. Considering the issues analyzed above, the objectives of the present study are i) to evaluate the response of tomato yield and quality to various combinations of DI, SDI and SSDI, and ii) to determine the minimum irrigation treatment in tomatoes where the production and crop quality are least affected.

(900U )

ETo=

0.408Δ(Rn -G) +γ ⎡ T+2372 ⎤ (es−ea ) ⎣ ⎦ Δ + γ(1+0.34U2 )

(1)

where ETo is the daily reference crop evapotranspiration rate (mm/d), Rn is the net radiation at the canopy surface (MJ/m2/day), G is the soil heat flux at the soil surface (MJ/m2/day), T is the mean daily air temperature (°C), γ is the psychometric constant (kPa/°C), U2 is the mean daily wind speed at a 2.0 m height (m/s), es is the mean saturation vapor-pressure (kPa), ea is the mean actual vapor-pressure (kPa), (es-ea) is the saturated vapor pressure deficit (kPa) and Δ is the slope of the saturated vapor pressures temperature curve (kPa/°C). 2.3. Measurement of soil water content Once the experiment initiated, the volumetric soil water content was measured daily to a depth of 0.6 m at 0.2 m intervals in each of the irrigation treatments using multi-sensor capacitance probes (EnviroSCAN). The EnviroSCAN device (Sentek Pty Ltd, Stepney, Australia) is a multi-sensor capacitance probe measuring water content in different depths of a soil profile. A support rod was fitted with several sensors and inserted into a polyvinyl chloride access tube installed in the soil. Each sensor consists of two conductive rings acting as capacitor with the surrounding medium (solid soil, air and water) as dielectric. Sensor readings were normalized to a so-called scaled frequency SF = (Fa – Fs) / (Fa – Fw), where Fa is the sensor specific reading in air, Fw is the reading in water and Fs is the frequency reading in moist soil. Fa and Fw were determined for each sensor in the laboratory. Soil water content (θES) was calculated from SF by means of a standard default calibration relationship (Eq. 2), which generally delivers adequate results for common soil types (Paltineanu and Starr, 1997; Evett et al., 2002). Data were measured, processed and stored in a standard RT6logger from Sentek Company, from which the actual database was downloaded.

2. Materials and methods 2.1. Site description

0.4040 SF = 0.1957×θES +0.0285

Field experiments were conducted at the experimental site of King Saud University, Riyadh, Saudi Arabia. The geographical coordinates of the location are a latitude of 24.43 °N, longitude of 46.43°4 E, and altitude of 635 m. The climate in this region is definitely semi-arid with an average yearly precipitation of 100 mm. During the experimental period, the maximum and minimum mean monthly temperatures were 29.74 and 19.94 °C in May and February, respectively. The highest mean relative humidity was 30.29% during April, whereas the lowest one was 24% in February. Other climatic parameters are shown in Fig. 1. The soil has been classified as SC, clayey sand (Baylot et al., 2013) comprising of 72.6% sand, 12.75% silt and 14.65% clay. Soil bulk density was 1.64, 1.61 and 1.59 g cm−3 for soil depths at 0.2, 0.4 and 0.6 m, respectively. More information on the soil texture, field capacity (FC), wilting point (WP) and bulk density (ρd) (Table 1).

(2)

2.4. Crop data Tomato plants (Lycopersicon esculentum Mill, GS-12) were transplanted into the field on February 12, 2015 and February 12, 2016. The seedlings were cultivated in a single row with a line spacing of 0.8 m and an interplant spacing of 0.4 m. The tomato plants were grown for about 97 days, which as divided into four stages namely initial (20 days), development (30 days), middle (32 days) and late season (15 days). The crop coefficients during the crop season were 0.70, 1.15, 0.90 and 0.75 during the initial, developmental, middle, and late season stages, respectively (Allen et al., 1998). All plots received a basic application of 300 kg N/ha and 100 kg K2SO4/ha. Herbicides and insecticides were applied to each plot when necessary. The plant height, number of branches, fresh leaf weight, fresh stem weight and fresh plant weight were determined. Leaf samples were collected, washed in distilled water and dried at 70 °C in forced air-oven until the weight became constant (48–72 h) to calculate the dry matter contents. The early and total yields were recorded in each treatment for all replications, and the data were presented as tons per hectare. Five tomato samples were collected, juiced and filtered for measuring tomato content of total soluble solids (TSS, %), ascorbic acid (mg/100 g FW) and titratable acidity (TA, %) (Carrapiso and García, 2000).

2.2. Irrigation scheduling The experimental area was prepared, leveled and partitioned into two main fields isolated with buffer zones of 6 m. Each field was subdivided into nine plots with surface-area dimensions of 7 m in width x 10 m in length (Fig. 2). The plots in the first field were irrigated by SDI system, whereas SSDI was used to irrigate the plots in the second field. The plots in the both fields were irrigated daily with various amounts of water according to the daily reference crop evapotranspiration calculated by the FAO Penman-Monteith equation (Eq. 1) (Fig. 3). The irrigation treatments were composed of three approaches: T1 = 100% of crop evapotranspiration, T2 = 80% of crop evapotranspiration and T3 = 60% of crop evapotranspiration. The amounts of water were

2.5. Yield reductions and water saving Reductions in the total fruit yield and decrease in water use were 56

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Fig. 1. Daily values of climatic conditions at the experimental site throughout the growing cycles of tomatoes in 2015 and 2016.

with 3 replicates. All parameters were subjected to analysis of variance (ANOVA) to evaluate the statistical effect of irrigation treatments on tomato yields and components using SPSS version 20.0 software. The least significant differences method (LSD) was used to differentiate the means at a significance level of p < 0.05 (Snedecor and Cochran, 1989).

Table 1 Physical characterristics of different soil layers. Soil layer depth (cm)

Sand (%)

Silt (%)

Clay (%)

FC (%)

WP (%)

ρd (g cm-3)

0–20 20–40 40–60

74.81 72.64 70.35

11.77 11.65 14.82

13.42 15.71 14.83

14.74 17.27 15.90

5.32 6.54 6.58

1.64 1.61 1.59

3. Results and discussion

FC = field capacity, WP = wilting point and ρd = bulk density.

3.1. Soil water status

determined by using the following equations (Ismail, 2010):

Reduction in yield= ⎡ ⎢ ⎣

Water saving= ⎡ ⎢ ⎣

yield of T2 or T3 ×100⎤ ⎥ yield of T1 ⎦

water consumption of T2 or T3 ×100⎤ ⎥ water consumption of T1 ⎦

Fig. 4 shows the average volumetric water content (VWC) data in response to the different irrigation treatments under SDI and SSDI in 2015 and 2016. As shown in Fig. 4, the moisture distribution was directly associated with the amount of water added to whether full (T1) or deficit-irrigated (T2 and T3) treatments. The VWC values during the initial stage until 20 days after planting were high and similar to each other in SDI and SSDI. This was due to the large amount of water that had been applied during the transplanting stage. The VWC values at depths of 0.2, 0.4 and 0.6 m were either above or near the field capacity (not shown). After starting the irrigation treatments, the level of VWC was the highest in the T1 treatment followed by the T2 and T3 treatments in both SDI and SSDI systems. The relative increase of VWC for T1 in SDI and SSDI that was observed after 30 days after planting was the result of initiation in the tomato. Soil moisture measurements at 60 days after planting had significant variation in VWC when T1, T2 and T3 were compared. For example, the values of VWC in the plots irrigated with T1 under SDI and SSDI were on average 22% and 24.5% as compared to T2 (18% and 19%) and T3 (17% and 16%), respectively. At the beginning of the leaf yellowing stage (80 days after planting), VWC values in the irrigation treatments were reduced due to ripening of tomatoes. Overall, Greater moisture content below the soil surface with buried drip tape (SSDI) was captured for tomato to be

(3)

(4)

where T1 = 100% of crop evapotranspiration, T2 = 80% of crop evapotranspiration and T3 = 60% of crop evapotranspiration. 2.6. Irrigation water use efficiency IWUE is the ratio between the yield and total amount of water applied (Wang et al., 2010): n

IWUE=∑ [(y)/(wa)] i=1

(5)

where IWUE is irrigation water use efficiency (kg/m3), n is the number of plots with each irrigation strategy, y is the total yield (kg) and wa is the amount of seasonally applied irrigation water (m3). 2.7. Statistical analysis The experimental design was a completely randomized block design 57

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Fig. 2. Layout of the experimental field for three irrigation strategies: T1 (full irrigation supply), T2 (80% of full irrigation supply), and T3 (60% of full irrigation supply)under surface drip (SDI) and subsurface drip irrigation (SSDI).

Fig. 3. Daily values of reference crop evapotranspiration (ETo) at the experimental site throughout the growing cycles of tomatoes in 2015 and 2016.

advantageous by reducing evaporation. Camp (1998), reported similar conditions in the surface of a sandy loam when drip tape was buried at 0.1 m depth.

3.2. Water use by the crop Fig. 5 shows the average amount of water applied to the fully and deficit-irrigated plots under SSDI and SDI in 2015 and 2016. During the initial stage, the maximum irrigation depths added to the plots T1, T2 and T3 under SSDI and SDI were few as they were 5.5 and 5.8 mm, 4.4 and 4.6 mm and 3.3 and 3.4 mm per day, respectively. In the development stage, there was a slight increase in the depths of water applied due to the flowering of tomatoes. During the mid-season stage, there was a steady increase in the amount of water applied where the maximum irrigation depths reached 10 mm, 8 mm and 6 mm in the plots T1, T2 and T3, respectively, under SSDI. This is mainly because increasing the temperature and forming the tomatoes. Correspondingly, the increases in irrigation depths for the plots T1, T2 and T3 under SDI throughout the same period were 10.4 mm, 8.3 mm and 6.2 mm, respectively.

Fig. 4. Average values of volumetric water content using low (T3), medium (T2), and high (T1) irrigation treatments for SDI and SSDI systems during growth stages of the tomato crop in 2015 and 2016.

During the late-season stage, the depth of irrigation decreased due to the maturity of the tomatoes where it reached 7.4 mm, 6 mm and 4.5 mm in the plots T1, T2 and T3 irrigated by SSDI, respectively. Similarly, the irrigation depth decreases in the plots T1, T2 and T3 those irrigated by SDI were 7.8 mm, 6.2 mm and 4.6 mm, respectively.

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Fig. 5. Average amounts of water applied using low (T3), medium (T2), and high (T1) irrigation treatments for surface (SDI) and subsurface drip irrigation (SSDI) during the growing cycles of tomatoes in 2015 and 2016. Table 2 Average vegetative growth traits for tomato plants using different irrigation strategies during the growth cycles in 2015 and 2016. Irrigation system

Irrigation treatments

APH (cm)

NOB

LFW (g)

SFW (g)

PFW (g)

LDW (g)

SDW (g)

PDW (g)

Subsurface (SSDI)

T1 T2 T3 T1 T2 T3

75.5a 62.7b 57.3c 71.6a 58.5c 51.7e 3.63

8.7a 6.9c 5.2e 7.2b 5.7e 4.2f 0.94

705.4a 606.8c 512.9e 678.3b 579.1d 495.8f 9.38

196.7a 181.7c 165.9e 187.6b 168.7d 159.3f 5.78

818.3a 675.5c 603.9e 763.4b 598.5d 543.2f 10.57

86.7a 71.5c 63.1e 82.2b 68.0d 59.3f 2.46

50.4a 45.3c 37.4e 48.0b 42.6d 34.8f 2.35

125.7a 113.3c 94.6e 120.8b 109.6d 89.1f 2.59

Drip (SDI)

(100 % of ET) (80 % of ET) (60 % of ET) (100 % of ET) (80 % of ET) (60 % of ET)

LSD at 0.05%

Values with the same letters within a particular column are not significantly different based on an LSD test at a probability level of 0.05. LSD = least significant difference, ET = crop evapotranspiration, APH (cm) = average plant height, NOB = number of branches, LFW = leaf fresh weight, SFW = stem fresh weight, PFW = plant fresh weight, LDW = leaf dry weight, SDW = stem dry weight and PDW = plant dry weight. Table 3 Average fruit yield components for tomato plants using different irrigation strategies during the growth cycles in 2015 and 2016. Irrigation system

Irrigation treatments

Early yield (ton ha−1)

Total yield (ton ha−1)

Fruit weight (g)

Fruit number/ plant

Subsurface (SSDI)

T1 T2 T3 T1 T2 T3

53.46a 45.94c 38.56e 47.27b 36.93d 29.64f 1.03

94.12a 81.44c 69.97e 91.98b 78.89d 67.95f 1.58

149.23a 138.61c 91.57e 140.91b 129.50d 84.76f 2.01

31.46a 26.92c 23.61e 28.91b 25.05d 21.48f 0.72

Drip (SDI)

(100 % of ET) (80 % of ET) (60 % of ET) (100 % of ET) (80 % of ET) (60 % of ET)

LSD at 0.05%

Values with the same letters within a particular column are not significantly different based on an LSD test at a probability level of 0.05. LSD = least significant difference, and ET = crop evapotranspiration. Table 4 Average fruit quality traits for tomato plants using different irrigation strategies during the growth cycles in 2015 and 2016. Irrigation system

Irrigation treatments

FL (cm)

FD (cm)

DM (%)

TSS (%)

VC (mg/100 g FW)

TA (%)

Subsurface (SSDI)

T1 T2 T3 T1 T2 T3

5.96a 4.73c 3.53e 5.71b 4.49d 3.28f 0.22

5.86a 4.75c 3.55e 5.69b 4.45d 3.32f 0.11

5.71a 4.54c 3.81e 5.49b 4.42d 3.67f 0.1

6.78a 5.43c 3.99e 6.57b 5.21d 3.89f 0.1

29.56a 24.23c 18.12e 28.22b 22.37d 16.51f 0.96

0.69a 0.57c 0.44e 0.62b 0.48d 0.36f 0.02

Drip (SDI)

LSD at 0.05%

(100 % of ET) (80 % of ET) (60 % of ET) (100 % of ET) (80 % of ET) (60 % of ET)

Values with the same letters within a particular column are not significantly different based on an LSD test at a probability level of 0.05. LSD = least significant difference, ET = crop evapotranspiration, FL = fruit length, FD = fruit diameter, DM = dry matter, VC = vitamin C, TSS = total soluble solid and TA = total acidity.

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3.5. Fruit quality characteristics

Table 5 Yield reduction and decrease in water use for two types of irrigation methods and three irrigation strategies. Treatment

T1 (100 % of ET) T2 (80 % of ET) T3 (60 % of ET)

Yield reduction %

The tomato crop showed a significant difference in fruit quality characteristics (fruit length, fruit diameter, dry matter, total soluble solidity, vitamin C and total acidity) as a result of the various irrigation treatments (Table 4). Table 4 shows that the maximum values of fruit quality during 2015 and 2016 were obtained from T1-SSDI and T1-SDI. In a similar way, T2-SDI and T2-SSDI showed a comparable pattern, but were of lower quality than T1-SSDI and T1-SDI. This may be due to the fact that the fully irrigated plots received much more water than the deficit-irrigated plots. These results are in concurrence with the findings reported by Machado et al. (2003); del Amor and del Amor (2007); Wang et al. (2010) and Al-Omran et al. (2010).

Water saving %

SDI

SSDI

0.00 14.23 26.13

0.00 13.47 25.66

0 20 40

SDI = surface drip irrigation, SSDI = subsurface drip irrigation and ET = crop evapotranspiration.

3.6. Yield reductions and water saving Table 5 compares the yield reduction and decrease in water use for the two types of irrigation methods (SDI and SSDI) and three irrigation procedures (T1, T2 and T3). As can be seen from Table 5, the greatest reduction in fruit yield (26.13% and 25.6%) was obtained from the lowest irrigation treatment T3 for both irrigation systems, SDI and SSDI, respectively. At the same time, the irrigation treatment T3 saved about 40% of irrigation water. The moderate irrigation treatment T2 saved about 20% of irrigation water and obtained the lowest reduction in fruit yield (14.23% and 13.4%) for both SDI and SSDI systems, respectively, as compared to T1. These results are in conformity with those obtained by Ozbahce and Tari (2010) and Djurović et al. (2016).

Fig. 6. IWUE response to yield and seasonal water supply using low (T3), medium (T2), and high (T1) irrigation treatments for SDI and SSDI during the growing cycles of tomatoes in 2015 and 2016.

3.7. Irrigation water use efficiency 3.3. Comparison of vegetative growth Fig. 6 shows the IWUE for the fully and deficit-irrigated treatments. Clearly, the fully irrigated treatments showed a decrease in IWUE compared to the deficit-irrigated treatments, which greatly improved the IWUE in the tomato crop. As shown in Fig. 6, the greatest IWUE was obtained from T3-SSDI (19.7 kg/m3) and T3-SDI (18.3 kg/m3). Conversely, the lowest IWUE (15.9 and 14.8 kg/m3) was found in T1-SSDI and T1-SDI, respectively. These findings are in congruity with those obtained by Beuhler (2003) and Simonovic and Li (2003), who suggested that improving IWUE is a basic demand to guarantee the accessibility of water for both food production and competing human needs under future climate change.

The response of the tomato crop during the two years demonstrated that variations within the amount of water applied using different combinations of deficit irrigation significantly affected the vegetative growth traits (Table 2). The maximum values of the mean vegetative growth characteristics during the two years were found in T1-SSDI and T1-SDI systems. the analysis results showed that the average estimations of plant height, the number of branches, fresh leaf weight (g), fresh stem weight (g), fresh plant weight (g), dry leaf weight (g), dry stem weight (g) and dry plant weight (g) were considerably enhanced by 24%, 39%, 27%, 15%, 26%, 27%, 25% and 24% when T1-SSDI is used as compared to T3-SSDI, respectively. Similarly, the increases within the corresponding vegetative traits in T1-SDI were 27%, 41%, 26%, 15%, 28%, 27%, 27% and 26%, respectively, as compared to T3SDI. This is mainly due to (1) the amount of water applied at 100% crop evapotranspiration sufficiently met the crop water demand, and (2) the equal distribution of water and nutrients delivered through the SSDI system.

4. Conclusions Today, irrigation is the largest single consumer on the earth. Competition for water from other sectors will force irrigation to operate under water scarcity. In field crops, a well-designed deficit irrigation can optimize water productivity over an area when full irrigation is not possible. Our results have clearly shown that the adoption of modern irrigation systems combined with deficit irrigation strategies can improve both the irrigation water use efficiency and quality of tomato fruits. Deficit irrigation will gain more importance over time, but farmers must choose crops and irrigation strategies carefully to maximize the value of their crop while ensuring the sustainability of agriculture.

3.4. Comparison of fruit yield The average values of the yield traits during 2015 and 2016 were in order of T1-SSDI, T1-SDI, T2-SSDI, T2-SDI, T3-SSDI and T3-SDI, respectively (Table 3). This can be attributed to the higher amount of water used within the fully-irrigated plots, on the one hand, and the lower amount of evaporation losses from SSDI, on the other. The results obtained from Table 3 show that the average values of the total yields were significantly decreased by 13.47% and 25.66% for T2-SSDI and T3-SSDI, respectively, as compared to T1-SSDI. Similarly, the decreases in total yield from T2-SDI and T3-SDI were 14.23% and 26.13%, respectively, as compared to T1-SDI.

Acknowledgments With sincere respect and gratitude, we would like to express our deepest thanks to the Deanship of Scientific Research, King Saud University, and the Agriculture Research Center, College of Food and Agriculture Sciences for their financial support, sponsorship, and encouragement. 60

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