3.1 Tomato fresh fruit yield (FY)
The Fresh fruit yield per hectare (FY) was calculated for each treatment as Mg ha− 1. FY for all different irrigation treatments through the three years of the experiment is shown in Table 4. In General, Table 4 shows that through the three years of the experiment, the highest yield was obtained under RW. As we can see from Table 4, the highest value was gained under the SDI treatment that received FI (SDI-FI), SDI treatment that received 70% FI (SDI-APRI), FUI treatment that received FI (FUI-FI), and FUI treatment that received 70% FI (FUI-APRI), respectively, whether under RW or CW. The results showed that under RW the values of FY under SDI-FI were increased compared to the values under SDI-APR through the years of the experiment, but this rise was not significant (P > 0.05) in the first and third years. Also, through the three years of the experiment, the FY with FUI-FI increased more than the values under FUI-APRI, but this increase is not significant (P > 0.05).
Table 4
Tomato fresh fruit yield (FY) Mg ha− 1 under all treatments throughout the three years.
|
Yield (Mg ha− 1)/SE
|
---|
Years
|
R-SDI-APRI
|
R-SDI-FI
|
R-FUI-APRI
|
R-FUI-FI
|
C-SDI-APRI
|
C-SDI-FI
|
C-FUI-APRI
|
C-FUI-FI
|
2017
|
137.82/83
|
145.94/1.09
|
114.39/2.65
|
116.48/2.41
|
109.39/0.87
|
118.27/1.27
|
103.29/1.52
|
108.46/0.63
|
2018
|
120.01/1.51
|
128.92/1.35
|
105.25/1.15
|
109.31/2.24
|
98.51/0.95
|
110.96/1.27
|
95.4/0.36
|
97.98/1.26
|
2019
|
116.68/2.54
|
121.96/1.38
|
103.28/1.25
|
107.16/0.46
|
91.66/1.04
|
98.72/0.77
|
79.61/0.16
|
88.65/1.06
|
Analysis of variance throughout the years of the experiment showed that there is a significant effect (P < 0.05) for the irrigation water qualities, irrigation techniques, and irrigation methods on the tomato yield. The interaction between the experimental factors also had a significant effect (P < 0.05) on the tomato yield except in the third year. According to Table 4, in each of the three years, the means of the tomato yield under RW were high compared to those under CW. Similarly, the means of the tomato yield under FI were high compared to those under APRI. The present study results that the tomatoes yield increased under RW, agrees with several researchers who reported that crop production increased under RW (Emongor et al., 2008; Gu et al., 2019; Xu et al., 2010). This increase in productivity may be attributable to the huge amount of nutrients that RW can supply (Guo et al., 2017; Teklehaimanot et al., 2015). Jamjoum and Khattari (1986) attributed the increase in the yield production of corn under RW to the improvement of soil physical characteristics and enhancement of nutrient uptake. The present study results are consistent with those of Najafi, (2006), who reported that the tomato maximum yield was obtained under drip irrigation compared with the other irrigation systems. This may be due to improved soil moisture and an increase in the amount of accessible nitrogen in the root zone. Furthermore, compared with surface irrigation, the SDI reduces the growth of grass and weeds and limits the plant nutrients’ leaching (Khawla et al., 2019; Singh et al., 2000).
The present study results were consistent with the findings of Zegbe et al., (2004), who observed that the regime treatments did not affect the FY of fruit. Also, the present results agree with Refs. Al-Hadidi and Sweity (2022), stated that compared with APRI and deficit irrigation, the treatments of FI gave the highest yield, and they attributed these results to that the soil water content was higher under full irrigation than it was under deficit irrigation.
Table 5 Analysis of variances on the effect of water qualities, irrigation methods, irrigation techniques, and their interaction on tomato yield IWUF, and NUE in the three years.
Factor
|
Yield ( Mg ha− 1)
|
IWUE (kg m− 3)
|
NUE (kg kg− 1)
|
---|
1st year
|
2nd year
|
3rd year
|
1st year
|
2nd year
|
3rd year
|
1st year
|
2nd year
|
3rd year
|
---|
Water Type
| | | | | | | | | |
RW (Reclaimed Wastewater)
|
128.66 a
|
115.87 a
|
112.27 a
|
21.21 a
|
23.20 a
|
18.51 a
|
221.68 a
|
199.64 a
|
213.28 a
|
CW (Clean water)
|
109.86 b
|
100.71 b
|
89.66 b
|
18.07 b
|
20.13 b
|
14.72 b
|
189.27 b
|
173.52 b
|
154.48 b
|
p-value
|
0.000
|
0.000
|
0.000
|
0.000
|
0.000
|
0.000
|
0.000
|
0.000
|
0.000
|
Irrigation Methods
| | | | | | | | | |
FI (Full irrigation)
|
122.29 a
|
111.79 a
|
104.12 a
|
16.66 b
|
18.56 b
|
14.19 b
|
210.70 a
|
192.61 a
|
189.52 a
|
APRI (Alternate partial root-zone irrigation)
|
116.23 b
|
104.79 b
|
97.81 b
|
22.63 a
|
24.77 a
|
19.04 a
|
200.25 b
|
180.55 b
|
178.24 b
|
p-value
|
0.000
|
0.000
|
0.000
|
0.000
|
0.000
|
0.000
|
0.000
|
0.000
|
0.000
|
Irrigation Techniques
| | | | | | | | | |
FUI (Furrow irrigation)
|
110.66 b
|
101.98 b
|
94.68 b
|
18.26 b
|
20.46 b
|
15.57 b
|
190.65 b
|
175.71 b
|
172.42 b
|
SDI (subsurface drip irrigation)
|
127.86 a
|
114.60 a
|
107.26 a
|
21.03 a
|
22.87 a
|
17.66 a
|
220.29 a
|
197.44 a
|
195.34 a
|
p-value
|
0.000
|
0.000
|
0.000
|
0.000
|
0.000
|
0.000
|
0.000
|
0.000
|
0.000
|
Water Type× Irrigation Methods× Irrigation Techniques.
| | | | | | |
p-value
|
0.000
|
0.000
|
0.166
|
0.464
|
0.037
|
0.557
|
0.661
|
0.208
|
0.380
|
Mean values followed by the same letter within each factor are not significantly different (P < 0.05).
| |
Irrigation Water use efficiency (IWUE)
The IWUE is an important indicator that reflects the effective use of water resources in crop production (Kuscu et al., 2014). The improvement in the IWUE is essential for maintaining crop yields while mitigating water shortages (Ma et al., 2015; Xu et al., 2018).
One of the goals of deficit irrigation is to raise IWUE by reducing the amount of water applied or by decreasing the number of irrigation events (Mohawesh and Karajeh, 2015; Serhat, 2017). So the amount of irrigation water applied (IWA) was recorded for the tomato crop under all treatments during the three years of the experiment as presented in Fig. 2.
During the three years of the experiment, the IWUE highest values were accompanied by the treatment of SDI-APRI, FUI-APRI, SDI-FI, and FUI-FI, respectively, both under RW and CW.
The values of IWUE for all irrigation treatments are shown in Fig. 3. Generally, the highest value of IWUE was obtained under APRI compared with FI throughout the three years, both under RW and CW. Also, the values of IWUE under SDI are high compared with the values under FUI. For all three years, the IWUE values of all treatments under RW are high compared with the corresponding values under CW.
The results illustrate that the IWUE values under SDI-APRI were greater under RW than the values under SDI-FI by 34.91%, 32.58%, and 36.68% in the first year, second year, and third year, respectively. The same trend was obtained under CW, where the values under SDI-APRI were greater than the SDI-FI values in the first year, second year, and third year by 32.12%, 26.45%, and 32.63%, respectively. When comparing the IWUE values of SDI-APRI under RW and CW, it was found that the values were raised by 25.99%, 21.82%, and 27.29% in the first year, second year, and the third year, respectively.
Statistical analyses through the three years showed a significant effect (P < 0.05) of water types, irrigation methods, and irrigation techniques on the IWUE. However, there was no significant effect (P > 0.05) for the interaction between the experimental factors on IWUE over the first and second years (Table 5). Table 5 shows that the mean values of IWUE were higher under the RW than under CW. It also shows that the mean values of IWUE were higher under the APRI than under FI, and were higher under the SDI than under FUI through the three years.
The current results were consistent with Cheng et al., (2021), Nardella et al., (2012) Tabatabaei et al., (2017), who indicated that the IWUE values obtained from APRI and deficit irrigation strategies were higher than those of FI. Also, the results are consistent with those of S Hashem et al., (2018), who reported that APRI has proven its efficiency in enhancing IWEU as compared to FI.
Increases in IWUE in tomatoes under water deficit treatments have been reported in the majority of the literature (Chen et al., 2013; Favati et al., 2009; Patanè et al., 2011; S Hashem et al., 2018). Kirda et al., (2004) indicated that in a greenhouse experiment using 70% of ETc to irrigate tomatoes, IWUE improved by 11.5% under APRI. According to Nangare et al., (2016), the use of deficit irrigation increased water productivity to its highest level. The findings of our study are consistent with those of Topçu et al., (2007) and Yang et al., (2012). They reported that the APRI practice and deficit irrigation increased the IWUE as compared to the FI. Yang et al., (2012) stated that compared to conventional irrigation, APRI improved IWUE.
The rise in IWUE values under the deficit irrigation practices could be attributed to the partial stomatal closure that occurs under PRD treatments and which results in a decrease in transpiration rate without detectable changes in plant water status and, consequently an increase in irrigation water use efficiency (Hashem et al., 2019). According to Cheng et al., (2021), the changes in yield under APRI were not dramatically different from FI for tomatoes and potatoes, whereas the corresponding IWUE was significantly higher. The APRI technique raises IWUE through a stress-related chemical produced by the drying roots (abscisic acid), which is delivered to the leaves and leads to physiological changes that will reduce water loss from leaves (El-Sadek, 2014).
Also, Pazzagli et al., (2016) indicate that the enhancement of IWUE was closely associated with the stomatal. According to Liu et al., (2013), the higher IWUE with lower irrigation depth may be a result of the root zone's efficient utilization of the available soil water. Under FI conditions, some of the irrigation water may not be used and left in the soil profile. Deep percolation beyond the root zone due to over-irrigation may also decrease the IWUE value.
Drip irrigation is the most effective irrigation method for vegetables because water drainage and evaporation are limited by the frequent supply of small amounts of water, which results in high IWUE (Zhang et al., 2017). Mehmood et al., (2019) revealed that IWUE under drip irrigation treatment was higher than that under surface irrigation treatment for the same nitrogen application rate. Hassanli et al., (2016) and Jha et al., (2016) also stated that IWUE was higher for drip irrigation than for FUI. Bai et al., (2020) reported that flood irrigation results in a low IWUE, which threatens the sustainable development of agriculture. Yuan et al., (2022) reported that drip irrigation significantly enhanced the average of IWUE by 8.8% compared with flood irrigation during the two winter wheat seasons. Jha et al., (2019), Stated that under deficit irrigation, the IWUE of the drip system is higher than that of surface irrigation systems. The main reasons for the increased IWUE in the SDI could be the lower evaporation, uniform distribution of water and nutrients, lower deep water percolation, and easy availability of nutrients and water within the root zone, thus enhancing the IWUE. Khawla et al., (2019) state that compared with surface irrigation, the largest amounts of nutrient elements were recorded under SDI.
Plants irrigated with the RW were more effective than those irrigated with CW for all water quantities (Alkhamisi et al., 2011). Also, Hassanli et al., (2009) reported that a higher IWUE was achieved with effluent irrigation than with fresh water. Similarly, Demir and Sahin (2017) mentioned that a higher IWUE was obtained under the treated wastewater treatment compared with freshwater treatment. According to Hassanli et al., (2010), as compared to freshwater irrigation, RW will have resulted in higher yield and higher IWUE because of its high nutrient content and organic matter. Al-Hadidi and Sweity, (2022), showed that 60% ETc under RW improved the IWUE by 20% and saved 40% water. Soltani-Gerdefaramarzi et al., (2021) stated that integrating the RW with deficit irrigation techniques can solve the problems of water scarcity and IWUE. Overall, APRI practices with RW in dry and semi-dry areas with limited water resources could be a practical and effective strategy to increase IWUE.
Nitrogen use efficiency (NUE)
This study consisted of eight treatments, with the same total nitrogen amount of 580.4 kg ha− 1 and the same nitrogen application schedules (53% base and 47% topdressing) as shown in Fig. 4.
Nitrogen is an extremely important nutrient element and it is the main index of the quality of agricultural soils (Chen et al., 2021). Split nitrogen application management during the crop growing period can contribute to satisfying the plant nitrogen demand, thereby improving NUE. Du et al., (2019) and Zhang et al., (2021) found that split nitrogen application under a reduced rate enhanced nitrogen uptake, nitrogen harvest index, NUE, and increased the yield of sweet potatoes. Split application of fertilizers can enable growers to avoid excessive fertilization in the early growth period of the crop and ensure sufficient nutrient supply at the later stages (Lu et al., 2021). Nitrogen use efficiency (NUE) values throughout the three years for all treatments are shown in Fig. 5. The highest value of NUE was achieved under RW during the three years.
NUE in the first year varied between 197.10 and 251.45 kg kg− 1 under RW, whereas it varied between 177.96 to 203.78 kg kg− 1 under CW. In the second year, the values ranged from 181.33 to 222.12 kg kg− 1 under RW, while it was 164.38 to 191.17 kg kg− 1 under CW. The values of NUE in the third year ranged from 196.21 to 231.68 kg kg− 1 under RW and from 137.16 to 170.10 kg kg− 1 under CW (Fig. 5). These data clearly show that under the same irrigation technique, higher water input led to greater NUE consistent with Wang and Xing, (2016). There was a significant effect (P < 0.05) for water types, irrigation methods, and irrigation techniques on the NUE throughout the three years. However, there was no significant effect (P > 0.05) for the interaction between the experimental factors on NUE over the three years (Table 5). Higher values of NUE were observed under the RW than CW. Similarly, the mean values of NUE were higher under the FI than under APRI and were higher under the SDI than under FUI through the three years.
The result illustrated that with the RW treatments, the NUE values under SDI-FI were 5.89%, 7.42%, and 4.52% higher than the values under SDI-APRI in the first, second, and third years, respectively (Fig. 5). However, this increase was not significant (P > 0.05). The same trend was seen under CW, where NUE values increased by 8.12%, 12.63%, and 7.70% under SDI-FI compared to SDI-APRI in the first, second, and third years, respectively. Also, the values under FUI-FI increased compared to the values under FUI-APRI throughout the three years, both under RW and CW, but this increase is not significant (P > 0.05).
These results agree with the findings of DU et al., (2017) who reported that for the same level of N application, the NUE increased with the amount of water applied. The NUE values under RW were higher compared to those under CW. This is because RW led to an increase in the yield since RW is a rich source of N, P, and K, which helps to enhance biomass production (Leonel and Tonetti, 2021; Nagi et al., 2020). In contrast to the soils that were irrigated with freshwater, many researchers reported that the total N, effective P, and total K content increased considerably in soil irrigated with RW (Guo et al., 2017; Li et al., 2014).
The NUE under SSD was higher compared with FUI due to the fruit yield improvement and timely scheduled fertigation that may have reduced N losses through several pathways. The current study results were consistent with those obtained by other researchers, such as Aujla et al., (2007) and Li et al., (2014), who demonstrated that, when compared to FUI, drip irrigation not only reduces water input and nitrate leaching but also increases NUE.
The use of irrigation techniques that limit the wetted volume in the root zone like SSD could enhance NUE (Singandhupe et al., 2003) because nitrate tends to accumulate toward the boundary of the wetted volume (Li et al., 2003)
EC, pH, and OM of Soil
The results illustrated that the EC, PH, and OM values at the beginning of the season in the first year were the same under all the treatments where the effect of the treatments did not start. In the following years, it was noticed that the EC and pH values at the beginning of the season were different under the different treatments, as this soil was under different treatments in the previous season compared with the beginning of the season of the first year.
Analysis of variance showed that there was no significant effect (P > 0.05) of water quality, irrigation technique, and irrigation methods on soil EC, PH, and OM over the three years. In addition, there was no significant effect (P > 0.05) on the interaction between the experimental factors over the three years.
Typically, soil electrical conductivity (EC) is used to indicate the concentration of soluble salts present in the soil. Crops only remove a small quantity of salt, hence salt distribution and its movement in soil are closely related to water movement (Heidarpour et al., 2007). Figures 6 and 7 present the EC values at different depths under all treatments throughout the three years.
It was noticed that the EC values under the APRI treatments were always higher than the corresponding values under the FI treatments, both under RW and CW treatments, throughout the three years. In the first year, after harvesting, the results revealed that water-saving treatment APRI under FUI and SDI increased the EC values by 21.61% and 19.87% under RW and CW, respectively, compared with the value at the beginning of the season (Figs. 6 and 7). At the end season of the first year, the average value of the EC of SDI-APRI under both RW and CW was increased by 8.36% and 8.49% compared with SDI-FI under RW and CW, respectively.
The same pattern emerged in the second and third years, with increases of 6.48% and 3.64% in the second year, and 4.17% and 5.63% in the third.
Also, when comparing the average of EC values under FUI-APRI and FUI-FI for both RW and CW, it was noticed to increase by 9.83% and 9.99%, respectively, in the first year, by 5.74% and 3.59% respectively, in the second year, and by 7.24% and 5.55% in the third year, respectively. This increase in EC under deficit irrigation is expected as the increase in irrigation water leads to the leaching of the soil salts compared to deficit irrigation.
When comparing the Soil EC values at the end of the season with the beginning of the season in all three years, it turns out that there is an increase in the EC values regardless of water quality. This increase ranged from 8.9–21.61%, 4.25–15.07%, and 1.84–6.91% in the first, second, and third years, respectively, across all treatments. This is an expected result, as irrigation water is one of the main sources of salts in the soil, and the salts also increase as a result of adding fertilizers during the growth stages.
Figures 6 and 7 show that throughout the three years, the EC values under all treatments were higher at 10 cm and then declined gradually until the values reached their lowest value at 50 cm. The high EC value in the upper layer under all treatments is due to water evaporation from the surface, whether under FUI treatments or SDI, where the irrigation pipes were placed at a depth of 15 cm. Hence, there was an upward movement of water by evaporation and capillary rise, resulting in salt accumulation at the soil surface. This result agrees with the results of others such as Assadian et al., (2005), Choi and Rey (2004), and Heidarpour et al., (2007). Many researchers, such as Du et al., (2022), Virga et al., (2020), and Wang et al., (2021) illustrated that the EC of the soil under RW treatments was not significantly different from the EC of the soil under CW, which is consistent with the findings of this study.
Although there were no significant differences between the treatments, we noted that throughout the three years, the EC values under the RW treatments were higher than the EC values under the corresponding treatments that were irrigated with CW.
For example, the EC under SDI-APRI irrigated with RW was higher than in the corresponding treatment that was irrigated with CW by 1.45%, 10.17%, and 7.94% at the end season of the first year, second year, and third year, respectively. The percentages of increase when comparing the FUI-APRI under RW with the FUI-APRI under CW were also close to these percentages, as they were 1.57%, 7.23%, and 9.46% at the end of the season of the first year, second year, and the third year, respectively. Irrigation water is considered the primary source of salts in the soil (Heidarpour et al., 2007). In this study, the EC value of RW was greater than that of CW. Therefore, the application of RW causes greater EC than CW in the soil layers (Table 1). These findings are in agreement with (Guo et al., 2017; Licata et al., 2022), who stated that irrigation with RW increased the EC of the soil compared to the CW. Similarly, (Liang et al., 2022) stated that the content of soil total salinity was higher after RW irrigation than after CW irrigation.
Numerous variables, such as the quality of irrigation water, irrigation techniques, soil properties, and plant absorption characteristics have an impact on the salt buildup in the soil. Additionally, the accumulation of salts increased as the number of irrigation cycles increased, which resulted in more ions being added to the soil (Guo et al., 2017).
Soil pH is a crucial parameter because it can affect the nutrient charge and affect how readily available nutrients are to crops (Urbano et al., 2017).
In the present study, over the three years, the values of soil pH in all treatments were between 8.06 and 9.05 with only a small variation among treatments (Figs. 8 and 9), and this may be due to high soil buffer capacity (Guo et al., 2017).
These results were in accordance with findings by (Licata et al., 2022) who stated that the soil pH varied very little throughout a three-year period. It was noticed that the soil pH at the upper layer is less than at the lower layers, and it begins to increase gradually until it reaches its highest value at a depth of 40–50 cm.
The average soil pH in the first year at the end of the season ranged from 8.78 to 9.01, while in the second year at the beginning of planting it ranged from 8.32 to 8.77, and then ranged from 8.46 to 8.63 at the end of the season. The pH value in the third year at the beginning of planting ranged from 8.63 to 8.46, while it ranged from 8.62 to 8.79 after harvesting. This same trend was also reported by Urbano et al., (2017) and (2015). There were no significant effects (P > 0.05) on soil pH due to the treatments. These results are similar to those of other researchers such as Du et al., (2022), Ebrahimizadeh (2009), Heidarpour et al., (2007), and Virga et al., (2020). They reported that there were no significant effects on the pH of soil due to water quality.
Bernstein et al., (2009) in a three years study, found that the pH of the soil was similar under both RW and CW treatments. Liang et al., (2022) reported that under RW irrigation, the soil pH (ranging from 7.76–8.73) after 5 years had no significant difference in different soils compared with the contrast treatment under CW. This is similar to the previous results, which also revealed no significant difference in soil pH after years of RW irrigation (Liu J, Chang Z, 2011). However, some researchers stated that irrigation with RW could increase the pH of soil due to the high concentration of HCO3 –, salt, and plant nutrients (Qian and Mecham, 2005).
Soil organic matter (OM) is a vital nutrient for the growth and development of plants and thus is assigned as one of the main indicators to determine soil fertility.
In the present study, the soil OM nearly did not change under the different treatments throughout the three years. The results showed that the influence of the experimental factors on soil OM was very slight between all treatments (Figs. 10 and 11). Organic Matter values in the first year ranged from 17.821 to 17.836 g kg− 1, while these values ranged from 17.833 to 17.927 g kg− 1 in the second year and from 17.837 to 18.050 in the third year. There was no significant difference (P > 0.05) in soil OM between all the experimental factors, and the same behavior was found in their interaction. The results showed that there was no notable tendency for the effect of irrigation techniques and irrigation methods on the values of soil OM.
The values of soil OM under RW treatments very slightly increased compared with the corresponding treatments under CW throughout the three years. Although this increase is very small, it increases every year compared to the year before, and this is consistent with the finding that OM is significantly increased by long-term reclaimed water irrigation (Urbano et al., 2017).
Compared to the soil OM under CW, the soil OM values under RW were increased by only 0.05–0.07%, 0.16–0.43%, and 0.36–0.96% in the first year, the second year, and the third year, respectively. This increase is negligible, although the RW has a higher content of OM than CW (Table 1). This result may be due to that RW containing an increased number of actinomycetes that help to accelerate the OM decomposition and reduce soil OM content, resulting in no changes in soil OM under the different treatments.
Our results are in accordance with the findings of (Virga et al., 2020). They reported that the level of organic constituents in the RW plots was not significantly higher than that of the CW plots. Also, (Liang et al., 2022) reported that the soil OM content did not change significantly after RW irrigation in most plants. However, (Du et al., 2022) reported that the soil OM significantly increased under unconventional water irrigation in the top layer. There is no consensus in the literature on the effects of RW on soil’s physical properties (Hashem and Qi, 2021). This discrepancy in OM may be related to the nature of the water sources, irrigation amount, and irrigation frequency.