The feasibility of producing maize under gated pipes technique was investigated comparing with traditional surface irrigation. The field experiment included twenty treatments which were all possible combinations between four irrigation treatments (traditional surface “flooding” and gated pipes with three discharge rates, i.e. 3.6 m³∙h⁻¹ “GP1”, 4.8 m³∙h⁻¹ “GP2” and 6 m³∙h⁻¹ “GP3”) and five maize hybrids (S.C 10, S.C 130, S.C 131, S.C 2031 and T.W.C 321). The outside diameter of gated pipe is 6" and 6 m length. Pipe is made of UPVC with gates spacing 0.70 m. The flow rate out of each gate system is controlled by the percent of opening the main valve according to the discharge rates. Maize hybrids used for study were white color varieties produced by Agricultural Research Center, Egypt except S.C 2031 which produced by Hi-Tech Co.

A layout of the experimental plots is shown in Figure 1. Each of surface irrigation system (traditional or gated pipes) was divided into five sectors to evaluate the five hybrids which randomly assigned. Sub-plot area was 60 m length × 3.5 m width, occupying an area of 210 m². Each plot was included 5 furrows, 0.7 m width for each (furrow area = 42 m²). A distance of 2.1 m was left between each irrigation treatments as a border. In the gated pipes technique, the pipes were located at the head of the irrigated field across the furrows and connected directly with main valve and water pump (60 m³∙h⁻¹). Each furrow had one gate to water control and measure the irrigation efficiency. The irrigation treatments were distributed in the main plots, whereas maize hybrids were assigned at random in the sub-plots.

Using field stalks and surveying tape, the furrows were divided into number of six stations having equal distances between them (10 m). Irrigation water advanced into the furrow (arrival times) were recorded at the end of each station. When water uncovers the field surface completely as a wave moving at the same direction of flow, recession times were observed and recorded at each station. This mark is the initiation of the water drying or recession front.

The water infiltration opportunity time along furrow length is the difference between the last time when water disappeared and the first time when water started at the same point along furrow. It can be determined according to [19] as formulated in Equation (9).

where:

t_o = infiltration opportunity time (min)

t_l = advance time (min)

t_r = recession time (min)

Cutoff time of water flow (min∙furrow⁻¹) is cumulative time since the initiation of irrigation until the inflow is terminated. It was recorded when the water has been totally arrived in the end of each furrow. Irrigation water applied (m³∙ha⁻¹) was calculated according to the cutoff time and discharge rate depends on the maize growth stage and environmental conditions.

Water infiltration in soil depth (Z) was measured in the upper 30 cm of soil surface using double ring infiltrometer in beginning of experiment at site location. The two rings were driven into the soil to 15 cm depth. The two rings were set to measure infiltration rate in the next 15 cm soil layer. Filling water rate into inner cylinder was also recorded. The disappeared irrigation depth was recorded with interval time. Water infiltration was determined according to Equation (10).

System coefficient of variation (CV%) was estimated from Equation (11).

where:

S = Standard deviation

= Depth average of water distribution along furrow stations

The schedule parameter (α) specifies the deviation of any schedule irrigation depth (d) to average of water distribution depth in terms of CV and can be calculated according to [10] as formulated in Equation (12).

where:

d = Water depth expressing the plant water requirement calculated from ET.

The uniformity coefficient (UC) can be expressed in power distribution for water infiltrated depth which determined from Equation (13) as stated by [20] .

The distribution uniformity (DU) is a measure of how uniformly water is applied to the area being watered, expressed as a percentage. It determined from Equation (14).

Application and storage efficiencies were used to evaluate the design of the irrigation system synchronizing with the irrigation scheduling.

Storage efficiency (E_s) defined as the ratio of amount of water stored to the water needed into root zone. It was calculated as from Equation (15).

The deficit percentage (P_D) is defined as the ratio of water deficit to the required water into the root zone, can be formulated using linear distribution for water applied by the irrigation system (Figure 2) according to [21] in Equation (16).

When the linear distribution is used to express the water profile of irrigation system, α will range from −1.725 to 1.725 under optimum irrigation, α ≥ 1.725 in deficit irrigation, and α ≥ −1.725 in excess irrigation according to [21] . In deficit irrigation condition, when α ≥ 1.725 and d ≥ Z_max, no deep seepage has occurred. The deficit percentage can be determined using of Equation (17).

Application efficiency (E_a) is defined as the ratio of water stored in the root zone to the total water applied. E_a was calculated from Equation (18).

where:

P_s = deep seepage percent.

The deep seepage percent can be described using a linear distribution as derivative from the basic analyses by [21] . In under irrigation when α ranged from −1.725 to 1.725, deep seepage percentage P_s could be determined from Equation (19).

When a ≤ −1.725, deep seepage percentage could be calculated from Equation (20).

Water saving is referring to the consumption differences among surface irrigation systems.

During the growth phase, total chlorophyll (Chl) was measured at 50 days after sowing (DAS) with a hand-held chlorophyll meter (SPAD-502, Konica Minolta Company, Tokyo, Japan). At the period of 60 - 75 DAS crop growth rate (CGR) g plant⁻¹ day⁻¹ was determined as the following formula:

where: W₁ and W₂ = plant dry weight (g.) at T₁ and T₂ (date of sampling), respectively. After 75 DAS, ear leaf area (ELA) was determined as formula, ELA = ear blade length × maximum blade width × 0.75 (cm²).

At maturity, grain and stover yields (based on 15.5% moisture content) were determined by hand harvesting the area of two inner furrows and converted to kg∙ha⁻¹. Yield samples of eighteen plants were collected along the furrow from each plot to determine yield components.

Irrigation water use efficiency (WUE) in kg∙m⁻³ was calculated according to formula, WUE = Grain yield kg∙ha⁻¹/amount of irrigation water applied m³∙ha⁻¹.

Plant chemical composition was determined by plant partitioned into stover (stalk and leaves) and grains. Samples were dried in air-oven at 70˚C to constant weight before grinding with a mill to pass through a 0.5 mm sieve. The samples were chemically analyzed to determine their contents of nitrogen. The total nitrogen percentage was determined by the Kjeldahl method as described by [22] . Nitrogen accumulation (kg∙ha⁻¹) = sample N concentration × dry matter yield.

The experimental field was ploughed twice, harrowed and leveled with slope 0.1% after wheat harvesting. Maize planting was done on 8^th and 10^th May 2013 and 2014, respectively using two grains per hill at a spacing of 25 cm and thinned to one plant at 21 DAS, to give a population of 57,140 plants ha⁻¹. The experiment was irrigated seven times, where the first irrigation was applied at 21 DAS and the following irrigations were applied every 13 days until physiological maturity. All experimental plots were fertilized with NPK. Calcium superphosphate (15.5% P₂O₅) was added during soil preparation at the rate of 74 kg P₂O₅ ha⁻¹. Nitrogen fertilizer at a rate of 286 kg N ha⁻¹ in the form of urea (46.5% N) was added in two equal doses, the first dose was added after thinning (before the first irrigation), while the second dose was applied before the second irrigation. Potassium fertilizer was added in the form of potassium sulfate (48% K₂O) at the rate of 57 kg K₂O ha⁻¹ before the first irrigation. Weed control was done chemically before seedling emergence and mechanically after emergence in a timely manner.

Data were analyzed using an analysis of variance split plot design with three replicates described by [23] . Statistical analysis was done using CoStat Version 6.311 (CoHort software, USA). Treatments means were compared using Duncan’s multiple test [24] . Means followed by the same letter are not significantly different from one another at P > 0.05. Capital letters in rows and columns indicate significant differences among irrigation systems and maize hybrids, respectively. Small letters indicate significant differences of the interaction between irrigation and hybrids treatments.

Laboratory calibration of modified gate along pipe line was illustrated in Figure 3. Results of hydraulic parameters (Table 2) showed that the average of determined discharges for GP1, GP2 and GP3 were 3.6, 4.8 and 6

m³∙h⁻¹ respectively. The actual discharges (q) from the gates along line were nearly equal to theoretical discharges values. The coefficient of variation (CV%) of discharges gates along the pipes line was 2.28%, 2.27% and 1.80% for GP1, GP2 and GP3 systems, respectively. The values of head pressure pump were 13, 23 and 36.5 cm for GP1, GP2 and GP3, respectively. This means that gates discharges were approximately constant. Accordingly, uniformity of water flow from the first gate to last gate along gated pipe lines according to different GP systems.

Physiological traits were significantly affected by irrigation systems and maize hybrids (Table 5). In both seasons, GP1 (3.6 m³∙h⁻¹) exhibited the highest values of Chl, CGR and ELA. The increases in Chl, CGR and ELA resulting from GP1 amounted to 14.34%, 13.44% and 5.46%, respectively more than the traditional irrigation. Flooding irrigation treatment was over-irrigated and resulted in considerable water losses by runoff and deep percolation below the root zone (Figure 4). Relative greenness of maize leaves was also affected due to flooding treatment as there was fading of leaf color as reflected by their corresponding SPAD values [27] . In this concern, [28] [29] mentioned that increasing or decreasing soil moisture may be resulted in unbalanced soil water-air re-

lations that lead to reducing the photosynthesis activity and unbalanced relations between plant hormones and biological processes in the whole plant organs. These adverse conditions in the treated soils are undoubtedly of great importance throughout the vegetative growth and dry matter accumulation. The findings obtained in this study were in good agreement to those reported by [30] -[33] .

There were significant differences among maize hybrids in their physiological characters (Table 5). S.C 2031 variety significantly surpassed the other hybrids. S.C 2031 had Chl, CGR and ELA values that were 21.69%, 44.34% and 14.62% greater than those of S.C 10, respectively. Such results could be attributed to the differences in the genetic constitution of the tested varieties. Increase in Chl and consequently increase in rate of dry matter accumulation leads to an increase in ear leaf area because proportion of dry matter allocated to leaves are increased constantly. Genetic variability of maize genotypes was also reported by [2] [4] [27] .

The interaction between irrigation systems and varieties had a significant effect on physiological traits in both seasons. S.C 2031 plants irrigated with GP1 (3.6 m³∙h⁻¹) surpassed other combinations and gave the highest values of Chl (54.48 and 51.83), CGR (12.27 and 12.74) and ELA (710.88 and 687.45) in both seasons. Meanwhile, S.C 10 irrigated with GP3 (6 m³∙h⁻¹) achieved the lowest values. Some of the differences among genotypes in growth and photosynthesis can be traced to different capacities for water acquisition and transport at a given water status [6] . This superiority might be due to well utilization of soil nutrients in meristematic tissues and metabolism activity which improved these traits. These results are consistent with the findings of [27] and [32] .

The data in Table 6 and Table 7 show that the differences among the surface irrigation treatments were significant for yield and its components. The irrigation systems significantly affected plant height. Using of GP1 system (3.6 m³∙h⁻¹) achieved the longest stems, while the shortest one was recorded with GP3 system (6 m³∙h⁻¹). With regard to maize ear traits, GP1 system surpassed other systems in number of rows per ear, number of grains per row and 100-grain weight followed by traditional irrigation in both seasons. From these results, it can be concluded that the superiority of GP1 in yield than traditional irrigation may be generally due to the tendency of this technique to produce more leaf chlorophyll, ear leaf area and CGR as shown in Table 5. The maize productivity was highly significantly affected by irrigation systems. Gated pipes system (GP1) produced the highest significant grain and stover yields, followed by traditional system. In contrast, GP3 system produced the lowest yields in both seasons. These results showed a positive relation between the yield and water quantity applied (Table 3). However, applying several inches of excess water (flooding) will lower the net return for the irrigated field potentially due to depressed grain yield resulting from more infiltration in traditional irrigation than GP (Figure 4) lead to leaching nutrients below the active root zone and inhibiting soil aeration. On the contrary, water deficit reduce carbon availability and dry matter partitioning to the ear during the critical period that de- termines grain number [34] and size of the sinks [1] . Corn yield is closely related to crop evapotranspiration (ET_c) and usually yield would be lowered if ET is lowered [12] . Drought and flooding are abiotic stresses which caused crop yield decrease [21] [35] . In this concern, other investigators indicated that the furrow irrigation by gated pipes achieved the highest yields of maize [9] [36] and sugarcane [26] .

Results in Table 6 and Table 7 indicated that maize varieties exhibited significant differences in their yield and its components. Results revealed that, S.C 2031 variety significantly surpassed other varieties in plant height followed by T.W.C 321 variety, while S.C 130 had the shortest plants. S.C 2031 variety recorded the highest values of number of rows per ear, number of grains per row and plant grain yield without significant different with S.C 130 and S.C 131 for number of rows in the first season. However, the highest grain index was recorded by T.W.C 321 followed by S.C 2031 variety without significant. On the contrary, the lowest values were obtained by S.C 10 (for number of rows per ear), S.C 130 (for 100-grain weight) and S.C 131 (for number of grains per row) in both seasons. These results can be attributable to changes in light interception and utilization due to increases in chlorophyll content and ear leaf area (Table 5). An increase in CGR during the vegetative growth is indicative of response of the photosynthetic apparatus to an increase in demand for assimilates to afford growth of the grain fraction. Varieties significantly affected dry matter production and partitioning into the different plant components (grain and stover). S.C 2031 exhibited the highest grain and stover yields ha⁻¹ in both seasons. It is clear from the obtained results that, S.C 2031 variety sowing led to an increase amounted to 32.06%, 21.71%, 12.29% and 18.99% for grain yield ha⁻¹ and 39.44%, 21.75%, 11.09% and 20.71% for stover yield ha⁻¹ than other S.C 10, S.C 130, S.C 131 and T.W.C 321, respectively. Genotypic superiority for grain and stover yields is particularly related to differences in any of yield components and dependent on the inherent genetic potential of the varieties themselves. In our study, varieties with higher values of physiological traits were higher yielding than those with lower values. These results are in harmony with those obtained by [4] [37] and [38] who indicated that single crosses of maize significantly surpassed the other crosses in growth and yield attributes.

The interaction effect between irrigation systems and varieties had a significant effect on the most yield and its components traits. No interaction effects were detected on number of rows per ear and 100-grain weight in both seasons. The highest values of yield attributes being obtained for S.C 2031 variety irrigated with GP1. By contrast, the shortest plants were recorded by S.C 130 and S.C 10 varieties irrigated with GP3. The lowest grains number was detected by irrigated S.C 10 and S.C 130 in the first season and S.C 10, S.C 130 and S.C 131 in the second one with GP3 system. Concerning maize yields, S.C 2031 variety irrigated with GP1 exhibited the first significant rank in plant grain yield and grain and stover yields ha⁻¹. Therefore this combination is recommended as the treatment that maximizes grain and stover yields. This combination may be exhibited better water and light utilization due to maintenance of green leaf area and leaf photosynthesis rather than other treatments. There is evidence that the variations in the grain yield response were due to variations in physiological traits that co-

determine tolerance to water stress. The interaction significance may be due to the different responses of each maize genotype to the different irrigation regimes as reported by [27] [29] [39] .

The combined effects of irrigation systems and varieties on irrigation water use efficiency were significant in both seasons (Table 7). GP1 had WUE values that were 5.34%, 11.29% and 23.26% greater than those of GP2, GP3 and traditional methods, respectively. The use of GP1 technique increased WUE from 1.44 kg∙m⁻³ for the farmer’s usual water management practice to 1.78 kg∙m⁻³ as average of both seasons. Increasing irrigation water led to decrease water use efficiency. Low WUE can occur when soil evaporation is high relative to crop evapotranspiration, early growth rates are low, water application does not correspond to crop demand, or shallow roots are unable to utilize deep water in the soil profile [12] . In this concern, [40] found that using gated pipes to irrigate long furrow (100 m long) resulted in saving water by 20% and 38% as well as increasing the water use efficiency by 58% and 26% for beans and corn, respectively compared with conventional surface irrigation method used short furrows (6 - 10 m long) in sandy soil. Meanwhile, [26] stated that use gated pipe system in sugarcane fields can reduce the irrigation quota by 48 - 156 m³∙ha⁻¹ for each irrigation cycle in comparing with open field head ditch.

The differences among the five maize varieties in their WUE were significant in both seasons. It is clear that S.C 2031 variety recorded the highest values followed by S.C 131. On the contrary, the lowest one was obtained by S.C 10. This means that S.C 2031 variety is more able to extract water from soil zones, and convert it into plant biomass than other varieties. [41] reported that maize plants are especially sensitive to water stress because their root system is relatively sparse.WUE of maize cultivars has been studied by several workers including [42] and [43] . These studies are important for identifying maize cultivars that are efficient in the use of limited soil water for biomass and grain yield production.

The response of maize plants to irrigation systems has been shown to change with hybrids (Table 7). It is interesting to note that the irrigated S.C 2031 variety with GP1 and GP2 system had highest WUE values similar to those obtained by the same variety under GP3 in the first season. The lower WUE was recorded with traditional irrigation especially under planting S.C 10 variety. Better management of the water balance with gated pipes technique can make significant improvements in water use efficiency under maize genotypes. [31] stated that maize genotypes with early adventitious rooting, increase root NAD⁺-alcohol dehydrogenase activity and high starch accumulation in stem tissues showed good tolerance to excess soil moisture stress.

Plant tissue analysis has been used to reveal the status of nitrogen element in a soil-plant system. The grains and stover nitrogen percentage and accumulations were significantly different with various irrigation regimes and varieties (Table 8). Nitrogen % and accumulation were significantly increased by 1.30% and 7.05% in grains and 2.92% and 6.33% in stover, respectively when GP1 was applied in comparing to traditional irrigation. Nitrogen uptake was more dependent on water supply. N uptake decrease with greater water applied [30] . Since the oxygen is limited, microorganisms may turn to pathways of metabolism that can affect the availability and uptake of certain plant nutrients [29] . Adequate moisture improve uptake of nutrients by diffusion and root interaction, and will increase organic matter decomposition, which releases N, P and S. Low moisture can result in the formation of insoluble nutrient-containing. However, flooded or very wet soils increase the solubility of minerals and promote nitrogen leaching and the contamination of ground water by nitrates. [13] stated that maize leaf nutrients concentrations were reduced with increasing applied water quantity, indicating that leaf N concentration with the 0.80 ET_c treatment were generally equal to or higher than the concentrations with 1.00 ET_c.

By comparing the average values of varieties, the highest nitrogen percent and accumulations were attained by S.C 2031 more than other varieties. Meanwhile, S.C 130, T.W.C 321 and S.C 10 had the lowest values of grain N, stover N and accumulations, respectively. The canopy nutritional state can be evaluated through pigment concentration, as chlorophyll concentration in leaves is usually correlated to its nitrogen content. Indices that are good indicators of Chl are usually also good indicators of N-content [33] . Selection of genotypes with a more efficient mechanism of N uptake and metabolism is strategy aimed to increasing maize crop. From these results, it can be concluded that S.C 2031 had the ability to transport enough absorbed nitrogen to grains and stover more than that of other varieties.

Maize varieties differently responded to irrigation systems for grain N and accumulations (Table 8). It attributed to the differences of root distribution of genotypes under irrigation regimes. The hybrids response, especially S.C 2031, was increased with using GP1. Under this combination, N accumulations represent the capacity of plants to absorb more N from soil and fertilization applied. These findings are in line with the results of [1] .