Impact of Water pH and Cultivar on Lettuce Growth, Water Use Efficiency, and Nutrient Use Efficiency in Deep Water Culture Systems

Abstract

Maintaining optimal pH in hydroponic systems typically requires continuous pH adjustment, increasing both labor and production costs. In regions with alkaline water sources, this challenge is especially critical. Identifying lettuce cultivars tolerant to high pH conditions offers a cost-effective and sustainable alternative to frequent pH buffering. This study evaluated the impact of water pH on growth, water use efficiency (WUE), and nutrient use efficiency (NUE) of lettuce (Lactuca sativa L.) in deep water culture (DWC) hydroponics. A greenhouse experiment was conducted from June to July 2024 using a completely randomized design with four pH treatments: T1 (unbuffered control), T2 (pH 6.3), T3 (pH 7.0), and T4 (pH 8.3). Three lettuce cultivars—Tacitus (L1), Rex (L2), and Rutilai (L3)—were tested, with three replicates per treatment. Results showed that fresh yield was significantly affected by cultivar but not by pH treatment. Rex produced the highest yield, reaching 132 g/plant at pH 7.0, compared to 127 g/plant for Tacitus and 98 g/plant for Rutilai. WUE differed strongly among cultivars, with Rex achieving 68.7 g/L at pH 7.0, which is nearly double that of Rutilai (37.2 g/L). Nitrogen uptake was unaffected by treatment; however, nitrogen NUE differed significantly, with Rutilai recording 12.8 mg N/g fresh weight at pH 8.3, compared to 8.3 mg N/g fresh weight for Rex and 6.7 mg N/g fresh weight for Tacitus. Calcium uptake and NUE were significantly influenced by both pH and cultivar, ranging from 3.2 to 10.7 mg Ca/g fresh weight. These findings suggest that selecting pH-tolerant cultivars plays a more critical role than pH adjustment in determining yield and efficiency in hydroponic lettuce. Choosing pH-tolerant cultivars such as Rex can reduce dependence on chemical buffering, offering a cost-effective strategy for sustainable hydroponic lettuce production in regions with alkaline water sources.

1. Introduction

With the growing global need to address food security, resource efficiency, and environmental sustainability, Controlled Environment Agriculture (CEA) has emerged as a promising solution for producing high-quality crops year-round in optimized environments. Among the various crops cultivated within CEA systems, hydroponic lettuce production stands out due to its rapid growth cycle, resource efficiency, and consistent market demand. CEA technologies—including greenhouses, vertical farms, and indoor growing systems—offer precise control over light, temperature, humidity, and nutrient delivery. This level of control enables consistent crop production independent of seasonal or climatic variability [1]. As climate change continues to introduce greater variability in temperature, precipitation, and extreme weather events, traditional open-field agriculture faces increasing challenges. CEA offers a climate-resilient alternative, especially in regions with harsh conditions or limited arable land [2]. Urban vertical farming within CEA systems further brings food production closer to population centers, reducing transportation emissions and costs, and supporting the farm-to-table movement [3]. Additionally, CEA enables continuous production cycles and multiple harvests per year, especially for fast-growing crops like lettuce. Optimized lighting and carbon dioxide enrichment further enhance photosynthetic efficiency and yield per unit area [4].

CEA systems also promote efficient resource use. Compared to traditional agriculture, water use can be reduced by up to 90% [5], and nutrient losses are minimized through recirculating systems. Nutrient solutions are applied directly to plant roots, improving nutrient use efficiency (NUE) and minimizing environmental impacts. Hydroponics, a soilless cultivation method particularly suited to leafy greens like lettuce, allows plants to grow in nutrient-rich solutions without soil. Lettuce (Lactuca sativa L.) is a widely consumed vegetable with a short growth cycle, making it an ideal candidate for hydroponic cultivation within CEA. Jensen and Malter (1995) [6] reported that lettuce can mature in as little as 30 days, enabling frequent harvests and consistent production. Hydroponic lettuce systems offer high water use efficiency (WUE) and are particularly beneficial in water-limited regions. Resh (2013) [7] found that hydroponic lettuce can use up to 90% less water than soil-based systems due to closed-loop nutrient recycling. This efficiency, along with direct nutrient delivery, supports optimal growth and improved crop quality—including better leaf color, flavor, and texture [8]. Stacked and vertical hydroponic systems further enhance productivity per unit area, especially in urban environments where space is limited [9]. Additionally, hydroponic systems reduce exposure to soilborne diseases and pests, which lowers the need for chemical pesticides and improves food safety [10].

In CEA systems, particularly in hydroponics, pH and nutrient solution composition play critical roles in plant health, nutrient availability, and resource use efficiency. The optimal pH range for lettuce in hydroponic systems is 5.5 to 6.5, where nutrient solubility and uptake are maximized [11]. However, some water sources—such as municipal water in regions like Fargo, ND—can have high pH levels (e.g., pH 9.2), presenting challenges for maintaining ideal root-zone conditions. Elevated pH reduces the solubility of essential micronutrients such as iron, manganese, and zinc, thereby limiting nutrient uptake and lowering NUE [7,12]. As nutrient availability is restricted, plants often compensate by increasing water consumption, which in turn decreases WUE [13,14]. Maintaining WUE and NUE under high-pH conditions often requires buffering the water or adjusting nutrient formulations—such as using chelated micronutrients or slightly increasing electrical conductivity (EC) to stabilize the solution [15]. While these strategies can be effective, they also add to operational costs and system complexity. Environmental control further plays a central role in supporting nutrient uptake and productivity. Goto and Both (2015) [16] emphasized that greenhouse and plant factory environments must be optimized not only for light and temperature but also for CO₂ and humidity, as these variables influence nutrient mobility and leaf development. In high-tech CEA systems, adjusting environmental parameters alongside nutrient solution chemistry enhances resource use efficiency and crop quality.

Previous studies highlight the importance of nutrient management in hydroponic lettuce systems. Jensen (1997) [17] underscored variability in crop pH tolerance and the need for continuous monitoring to maintain balance. He et al. (2018) [18] demonstrated that pH shifts influence ionic availability of nutrients, indirectly affecting crop quality and leaf morphology. Johnson and Shaw (2019) [19] reported notable cultivar differences in tolerance to high pH and nutrient deficiencies, suggesting that appropriate cultivar selection can help mitigate adverse effects. Similarly, Mitchell et al. (2015) [20] emphasized the role of LED lighting in optimizing growth, while Sakamoto and Suzuki (2005) [21] and Yan et al. (2012) [22] showed that root-zone temperature and nutrient concentration interactively affect nutrient uptake, yield, and crop quality. Samarakoon et al. (2006) [13] and Thakulla et al. (2021) [23] confirmed that deviations from optimal pH reduce nutrient availability and lettuce quality, while Thompson et al. (1998) [24] and Wurr et al. (1992) [25] highlighted synergistic roles of pH and temperature in maximizing growth. The increasing adoption of CEA, as evidenced by USDA’s reported doubling of producers from 2009 to 2019 [26], further underscores the need to optimize crop selection and management strategies.

Despite recognition that root-zone pH strongly influences nutrient availability and lettuce performance [11,13,17], most studies focus on buffering pH to maintain optimal ranges, which increases cost and complexity [15]. Although some cultivar differences in pH tolerance have been documented [19], few studies have systematically compared lettuce varieties under alkaline hydroponic conditions. This study aims to address this gap by evaluating lettuce growth, water use efficiency, and nutrient use efficiency under four pH levels (including high-pH conditions) and by identifying cultivars tolerant to alkaline water sources.

2. Materials and Methods

2.1. Experimental Setup

A completely randomized design was implemented in a greenhouse from June to July 2024 to evaluate the effects of water pH on lettuce (Lactuca sativa L.) growth and WUE under deep water culture (DWC) hydroponics. The study included four pH treatments, T1-unbuffered control, T2-buffered to pH 6.3, T3-buffered to pH 7.0, and T4-buffered to pH 8.3, which represent the recommended hydroponic optimum, a moderate deviation, and a high-alkaline condition typical of municipal water sources in the region. Three lettuce cultivars, L1-Tacitus, L2-Rex, and L3-Rutilai, were chosen because they are widely used in commercial hydroponics, represent different leaf types, and have shown contracting responses to abiotic stresses in prior studies, making them suitable for testing cultivar and pH interactions. Each treatment combination was replicated three times, and all experimental units were randomly distributed across four rows on two wooden benches, following the layout shown in Figure 1 [27].

Lettuce seeds were sown in Rockwool cubes (2.54 × 2.54 × 3.81 cm) on 13 May 2024 and irrigated with tap water for the first two weeks. From 27 May onward, a nutrient solution containing 200 mg/L N, 87.2 mg/L P and 166 mg/L K (prepared using a proportioner and a 20-20-20 general purpose water soluble commercial fertilizer) was applied for two additional weeks. Once seedlings reached the 6–7 leaf stage and attained a height of 8–10 cm, they were transplanted into the DWC system on 11 June 2024.

The DWC system is a tub with dimensions of 34.3 × 29.2 × 15.2 cm. A 1.9 cm thick Styrofoam board, custom-cut to fit the DWC surface, was placed on each container. Each board was drilled with four 2.9 cm diameter holes, spaced at least 15.2 cm apart, allowing one plant per hole and ensuring adequate spacing for growth.

After the DWC system setup, the entire system was aerated using a central air diffuser, with a main pipe running between two sets of DWCs on each bench top, and air stone was inserted into each DWC (Figure 1b).

2.2. Environmental Monitoring

The greenhouse environment was equipped with four high-pressure sodium (HPS) lights, each rated at 1000 W, suspended approximately 1.9 m above the bench surface. Initial measurements of photosynthetic photon flux density (PPFD) using a LI-180 Spectrometer (LI-COR, Lincoln, NE, USA) revealed that the combined lighting system produced an average PPFD of approximately 1000 µmol m⁻² s⁻¹. This exceeded the optimal range for indoor lettuce cultivation, typically 250–300 µmol m⁻² s⁻¹ [18]. As a result, the HPS artificial lighting system was generally turned off, and only natural sunlight was used throughout the study. However, the supplemental lights were turned on once, on 18 June 2024, due to overcast conditions.

Due to the greenhouse structure and the angle of the Exo-lite (double-layer plexiglass) glazing material, uniform light distribution at the plant canopy was not guaranteed. Manual PPFD measurements were taken weekly at the center of each DWC system. To assess light distribution uniformity, intensity measurements were conducted at five points per DWC unit at 8:00 a.m., 1:00 p.m., and 6:00 p.m. on 6 July 2024, two days before harvest, following the methodology of [28].

Environmental conditions within the greenhouse were continuously monitored using a mini-weather station placed near the west end of the two growing benches (Figure 1a). Air temperature and RH were recorded by a combination sensor (Temperature/RH Smart Sensor S-THB-M002, S-THB-M008; Onset Computer, Bourne, MA, USA), shielded from direct solar radiation and mounted approximately 30 cm above the lettuce canopy. Photosynthetically active radiation (PAR) was measured using a Photosynthetic Light Sensor (S-LIA-M003, Onset Computer), positioned at canopy height and adjusted as plant height increased. All environmental data were recorded at 15 min intervals by a HOBO H21-001 weather station datalogger (Onset Computer, Bourne, MA, USA).

2.3. pH Treatments

The primary treatment in this experiment was the pH level of the nutrient solution. Tap water obtained from the Fargo municipal supply, with an average pH of 9.2, served as the base water source for all treatments. After nutrient addition, pH adjustments were made using pH Up (base) and pH Down (acid) solutions (General Hydroponics, Santa Rosa, CA, USA) to achieve the desired levels for the buffered treatments (T2–T4). The control treatment (T1) remained unbuffered, undergoing no further adjustment following nutrient addition.

Interestingly, nutrient addition caused a natural reduction in pH in the unbuffered control solution. Based on daily in situ measurements using a portable pH meter (HQ440d multi-sensor, Hach, Loveland, CO, USA), the average pH of the control solution stabilized at 6.89 ± 0.39 (mean ± standard deviation). Using the same instrument, the electrical conductivity (EC) and temperature in the water solution were also measured.

After initial setup and pH adjustment at the beginning of the experiment, pH, EC, and temperature were monitored twice weekly in each DWC unit. No further adjustments were made during regular monitoring to simulate natural fluctuations in pH due to nutrient uptake by the plants.

2.4. Growth Parameters

Lettuce was harvested on 8 July 2024, a total of 26 days after transplantation. Evaluation of fresh shoot and root weight, plant size, and plant quality were conducted on three out of the four plants in each DWC system immediately after harvest. The plant and root samples were then sealed in paper bags and transferred to a drying chamber, where they were dried at 55 °C for seven days. After cooling to room temperature, the dry shoot and root weights were measured. The shoot-to-root ratios were calculated based on dry weights to accurately assess whether the lettuce had been grown under optimal conditions.

2.5. Water Use Efficiency

A total of 10 L of water was added to each DWC unit at the beginning of the experiment. This volume was determined based on the container dimensions and was selected to leave approximately 3 cm of headspace below the top edge after placing a 1.9 cm thick foam on the solution to support the plants. The amount of water consumed by the four plants in each DWC was calculated by subtracting the volume collected for nutrient analysis and the final volume remaining. Additional water was added when the water level dropped below quarter of the initial volume. Water levels were measured weekly using a ruler to provide a rough estimate of weekly water usage. Based on these measurements, a refill using nutrient solution at the same concentration was performed during the third week of the experiment. After the refill, the pH in each DWC was adjusted to the target level using standard pH up and pH down solutions [27].

The water usage per lettuce plant (WU, L/plant) was estimated using Equation (1):

$$WU={\displaystyle \frac{\mathrm{W}\mathrm{D}-\mathrm{W}\mathrm{R}-\mathrm{W}\mathrm{A}+\mathrm{W}\mathrm{S}}{4}}$$

(1)

where WD is the total volume of water added to each DWC (L), WR is the water remaining in each DWC at the end of the experiment (L), WA is the total volume collected for nutrient analysis (L), WS is the supplemental water added during the experiment (L), and 4 represents the number of plants grown in each DWC system.

After estimating water usage per plant, the WUE (g/L) was determined using Equation (2):

$$WUE={\displaystyle \frac{\mathrm{Y}\mathrm{D}}{\mathrm{W}\mathrm{U}}}$$

(2)

where YD is the fresh yield of lettuce per plant (g) to reflect the marketable value.

2.6. Nutrient Use Efficiency

The nutrient solution used contained 100 mg/L of N, 29.1 mg/L of P, 166 mg/L of K, 66.7 mg/L of Ca, 16.7 mg/L of Mg, and 0.7–1.7 mg/L of micronutrients essential for plant growth, including B, Cu, Fe, Mn, and Zn. A mixed fertilizer (FoxFarm Grow Big Hydroponic, FoxFarm Soil & Fertilizer Company, Arcata, CA, USA) was used to prepare the solution. City tap water was stored in covered containers for 24 h to allow it to reach room temperature before mixing with the fertilizer solution. In the tap water, there are 1.25 mg/L of N, 0.4 mg/L of P, 6 mg/L of K, 36 mg/L of Ca, 7.5 mg/L of Mg, and 0.2 mg/L of micronutrients essential for plant growth, including B, Cu, Fe, Mn, and Zn (A&L Great Lakes, Fort Wayne, IN, USA). The total hardness is estimated as 120.75 mg/L as CaCO₃.

Water samples were collected at the beginning of the experiment and weekly thereafter from each DWC system. Each 10 mL nutrient solution sample was extracted using a syringe and transferred into plastic containers with threaded caps. The samples were then transported from the greenhouse to the laboratory in a cooler to prevent temperature fluctuations during transit. Upon arrival, samples were immediately analyzed for N, P, Ca, and water hardness using a DRB200 instrument (Hach, Loveland, CO, USA). Over the four-week experiment, samples were collected five times, resulting in a total of 180 samples.

Nutrient usage was estimated by calculating the difference between the nutrient concentrations in the initial and added solutions and subtracting the nutrients remaining at the end of the experiment as well as those removed for sampling. The nutrient usage per lettuce plant (NU, mg/plant) was estimated using Equation (3).

Nutrient usage per plant (NU, mg/plant) was estimated using Equation (3):

$$NU={\displaystyle \frac{WD\times C_{WD}-WR\times C_{WR}-WA\times C_{WA}+WS\times C_{WS}}{4}}$$

(3)

where C_WD is nutrient concentration in the added water WD (mg/L), C_WR is nutrient concentration in the remaining water W_R (mg/L), C_WS is nutrient concentration in the water samples WA (mg/L), CWS is nutrient concentration in the supplemental water WS (mg/L), and 4: number of lettuce plants grown in each DWC system.

Similarly, the NUE (g of lettuce per g of nutrient consumed) was estimated using Equation (4):

$$NUE={\displaystyle \frac{\mathrm{Y}\mathrm{D}}{\mathrm{N}\mathrm{U}}}$$

(4)

2.7. Statistical Analysis

Water usage, water use efficiency, nutrient usage, nutrient use efficiency, and plant yield data were statistically analyzed to evaluate treatment effects. A one-way analysis of variance (ANOVA) was performed to detect significant differences among treatments. When significant differences were found, Tukey’s Honestly Significant Difference (HSD) test was used for multiple comparisons. All statistical analyses were conducted using Microsoft Excel and SigmaPlot version 11.0. A significance level of p < 0.05 was used for all tests.

3. Results

3.1. Environmental Conditions

The environmental conditions within the greenhouse were carefully monitored throughout the experimental period to characterize the growing environment and assess the influence of external weather fluctuations on internal microclimate stability.

Air temperature (°C), RH (%) and PAR were collected during the study period. The average hourly values are represented in Figure 2.

The three environmental parameters were strongly interrelated. The highest temperature, 28.93 °C, was recorded at 16:00, coinciding with the lowest relative humidity (RH) of 56.36%. The highest PAR reading, 667.08 µmol/m²/s, occurred at 14:00, two hours earlier than the peak temperature. In contrast, the lowest temperature (17.4 °C) and the highest RH (86.01%) were both recorded at 6:00 a.m. The average daytime temperature was 26.12 °C and the average nighttime temperature was 19.03 °C, which are slightly higher than the optimal range of 19 °C to 24 °C [29]. However, previous studies have indicated that some lettuce varieties, such as Skyphos and Muir, can achieve higher fresh yields at elevated temperatures around 28 °C [30].

The average RH was 72.02%, which is below the recommended threshold of 85% for optimal lettuce production [31]. High humidity reduces transpiration and disrupt calcium transport, leading to reduced yield [32], and also encourages the development of diseases, such as botrytis and mildew [29]. Therefore, the lower RH observed in this study may be beneficial for lettuce production.

The PAR level exceeded 100 µmol/m²/s for approximately 13 h, from 8:00 a.m. to 8:00 p.m. During the daytime, the PAR level remained above 400 µmol/m²/s for seven hours, exceeding the typical requirement for lettuce growth and potentially creating suboptimal growing conditions. A light measurement taken across the entire study area on 6 July 2024, just before harvest, showed that the PPFD levels averaged 245.81 ± 92.29, 349.62 ± 170.75, and 125.71 ± 18.16 µmol/m²/s at 8:00 a.m., 1:00 p.m., and 6:00 p.m., respectively [27]. At the exact location where the PAR readings were measured, the PAR and PPFD values were nearly identical at the same time, with an average PAR of 229.95 µmol/m²/s and an average PPFD of 220.80 µmol/m²/s—a difference of 9.15 µmol/m²/s. These PPFD levels are within the acceptable light intensity ranges [33]. The light uniformity index of the growing area was 0.38, slightly higher than the commonly accepted threshold of 0.3 or below [27,34], indicating that the light distribution is acceptable and should not significantly affect overall plant performance. Based on the 15 min PAR measurements over the experimental period, the Daily Light Integral (DLI) averaged 18.03 mol/m² with a standard deviation of 5.39 mol/m², which falls within the optimal range for maximum lettuce growth [28].

3.2. Yield Comparison

Lettuce yield was measured in terms of fresh and dry weights of both shoot and root tissues following harvest. A representative image of the harvested fresh lettuce is presented in Figure 3.

Although it is challenging to observe clear visual differences among the varieties and treatments, Figure 3 shows noticeable size and shape differences among the varieties, but not among the treatments. Detailed variations in fresh shoot weight provide a more accurate assessment of treatment effects, as market sales are based on fresh weight.

Table 1. Fresh and dry shoot and root weights, shoot-to-root ratio (based on dry weights), head size, and root length of lettuce grown in deep-water culture (DWC) under four pH treatments: no pH control (T1), pH 6.3 (T2), pH 7.0 (T3), and pH 8.3 (T4), across three lettuce cultivars—Tacitus (L1), Rex (L2), and Rutilai (L3). The values in parentheses represent standard deviations. Values highlighted in red indicate the highest, and those in blue the lowest, within each category.

pH Treatment	Lettuce Variety	Fresh Shoot Weight (g)	Dry Shoot Weight (g)	Fresh Root Weight (g)	Dry Root Weight (g)	Shoot-to-Root Ratio	Plant Width (cm)	Plant Height (cm)	Root Length (cm)
T1	L1	119.33 (±21.47)	8.61 (±1.52)	11.20 (±4.76)	1.04 (±0.32)	8.28	25.16 (±2.33)	22.27 (±3.56)	42.62 (±11.96)
	L2	135.08 (±37.89)	5.82 (±1.40)	11.15 (±3.14)	0.60 (±0.16)	9.70	16.11 (±3.10)	20.61 (±1.91)	53.44 (±18.30)
	L3	127.11 (±45.02)	6.10 (±3.07)	9.87 (±6.44)	0.50 (±0.21)	12.20	19.11 (±3.47)	23.38 (±4.21)	38.27 (±11.71)
T2	L1	129.44 (±37.44)	9.36 (±2.53)	12.91 (±5.39)	1.02 (±0.28)	9.18	23.91 (±1.91)	23.11 (±2.69)	50.22 (±9.25)
	L2	122.36 (±25.74)	6.01 (±0.85)	12.66 (±6.11)	0.67 (±0.13)	8.97	16.44 (±0.68)	21.50 (±2.10)	54.55 (±10.75)
	L3	127.56 (±16.39)	6.38 (±1.34)	7.80 (±4.19)	0.52 (±0.12)	12.27	20.77 (±1.45)	26.55 (±2.06)	36.22 (±13.79)
T3	L1	127.11 (±38.20)	8.60 (±2.61)	16.51 (±6.65)	0.91 (±0.29)	9.45	25.00 (±2.05)	23.66 (±4.52)	47.11 (±9.20)
	L2	132.44 (±29.59)	6.14 (±1.02)	11.32 (±2.63)	0.62 (±0.21)	9.90	17.27 (±2.09)	21.88 (±1.85)	57.44 (±7.04)
	L3	98.07 (±21.14)	6.90 (±1.15)	9.09 (±2.61)	0.67 (±0.21)	10.30	20.77 (±1.33)	25.66 (±3.55)	39.55 (±8.20)
T4	L1	94.93 (±18.63)	7.20 (±9.31)	18.38 (±8.30)	1.19 (±0.51)	6.05	24.83 (±1.79)	24.05 (±2.75)	46.44 (±8.05)
	L2	100.88 (±13.81)	6.70 (±6.23)	22.00 (±18.59)	0.85 (±0.15)	7.88	17.27 (±1.31)	22.38 (±1.82)	60.33 (±5.57)
	L3	103.21 (±18.63)	7.32 (±1.45)	11.03 (±3.20)	0.79 (±0.09)	9.27	21.61 (±1.48)	26.77 (±2.78)	42.22 (±9.53)
Average		118.60 (±32.55)	6.80 (±2.17)	13.10 (±8.31)	0.80 (±0.33)	8.50	20.20 (±3.90)	23.30 (±3.51)	48.40 (±13.16)

presents the fresh and dry shoot biomass of lettuce across different varieties and pH treatments [27].

One-way ANOVA results by pH treatment showed a significant difference in fresh shoot weight among the treatments (p = 0.04), while all other measured parameters showed no significant differences (p > 0.05). A Tukey HSD test for fresh shoot weight further revealed a significant difference between T1 (no pH control) and T4 (pH 8.3), with p = 0.048, indicating that lettuce grown without pH adjustment produced significantly higher fresh shoot weight than those grown at high pH under alkaline conditions. No other pairwise comparisons were statistically significant (p > 0.05). These findings suggest that alkaline water conditions at pH 8.3 may reduce lettuce yield compared to unbuffered or more neutral pH levels.

In contrast, ANOVA results by lettuce variety showed significant differences in dry shoot weight, dry root weight, shoot-to-root ratio, plant width, plant height, and root length (p < 0.05), while fresh shoot weight and fresh root weight did not differ significantly among varieties (p > 0.05). Further analysis using Tukey’s HSD test revealed a significant difference in dry shoot weight between varieties L1 and L3 (p < 0.05), with L3 producing higher dry shoot biomass than L1. No other pairwise comparisons were statistically significant for the remaining parameters.

Fresh root weight exhibited considerable variation across the pH treatments; however, ANOVA analysis indicated no statistically significant differences among the different pH treatments. In contrast, fresh root weight varied significantly among the lettuce cultivars, with ANOVA results showing a statistically significant effect of cultivar (p = 0.0019). This suggests that genetic differences among the cultivars played a more prominent role in influencing root biomass than the external pH conditions did.

Dry root weight followed a similar trend, with lower absolute values due to the absence of water content. As with fresh root weight, no significant differences were detected among pH treatments, according to ANOVA results. However, dry root weight differed significantly among the lettuce cultivars, with ANOVA revealing a statistically significant effect of cultivar (p = 0.0019). This indicates that cultivar-specific characteristics substantially influenced root biomass development, even more so than pH treatment.

For root length, no significant differences were observed among the pH treatments; however, a statistically significant difference was found among the lettuce cultivars, indicating that root elongation was more strongly influenced by genetic factors than by pH conditions.

The shoot-to-root ratios (SRR) ranged from 6.05 to 12.27, which falls within the typical range for hydroponic lettuce (6–12), suggesting that the plants maintained a healthy biomass allocation. Among the three cultivars, L3 generally exhibited higher SRR values, implying vigorous shoot growth and potentially increased nutrient uptake. In contrast, the T4 treatment yielded the lowest SRR, indicating a more balanced growth pattern with well-developed roots that may enhance long-term nutrient and water uptake.

However, ANOVA analysis showed no statistically significant differences in SRR across pH treatments (p = 0.2706), suggesting that pH had limited influence on shoot-to-root allocation within the tested range. Additionally, no significant differences in SRR were detected among cultivars, likely due to small sample sizes or variability within groups. Therefore, while trends in SRR were observed, statistical evidence did not confirm treatment or cultivar effects on biomass allocation ratios in this study.

Other lettuce size parameters, such as plant width and plant height, showed inverse relationships with the fresh shoot weight. For example, L2 had the highest weight but relatively small width and height, especially under T1 treatment. Overall, there was no strong linear correlation between fresh shoot weight and plant weight or height across all cultivars. Some plants with smaller widths had higher short weights, suggesting that biomass density or leaf thickness may play a role to yield differences. Plant height showed more consistency within each cultivar but did not explain variation in fresh shoot weight.

3.3. Water Use Analysis

The WUE was estimated from a simple water balance for each DWC based on its pH treatment and varieties. The results for water consumption and WUE as well as the standard deviation is shown in

Table 2. Water consumption (WC, L/Plant) and water use efficiency (WUE, g/L) for four pH treatments—no pH control (T1), pH 6.3 (T2), pH 7.0 (T3), and pH 8.3 (T4)—across three lettuce cultivars: Tacitus (L1), Rex (L2), and Rutilai (L3).

pH Treatment	Lettuce Variety	WC (L/Plant)		WUE (g/L)
		Average	Standard Deviation	Average	Standard Deviation
T1	L1	3.14	0.28	39.54	3.91
	L2	2.09	0.25	62.73	10.02
	L3	2.59	0.29	39.46	4.04
T2	L1	3.12	0.39	43.72	5.40
	L2	2.16	0.34	58.63	8.80
	L3	2.50	0.06	38.95	1.78
T3	L1	2.54	0.33	50.78	5.54
	L2	1.89	0.07	68.72	3.44
	L3	2.79	0.08	37.24	1.64
T4	L1 *	2.58	0.85	48.65	2.35
	L2	2.09	0.22	63.36	7.51
	L3	2.87	0.30	34.64	5.86
Average		2.53	0.29	48.87	5.02

* L1 only used two replicates.

.

The results showed that lettuce variety has a strong effect on water consumption, regardless of pH treatments, as indicated by the two-way ANOVA. The interaction between pH and variety was significant (p < 0.05), suggesting that different varieties respond differently to pH levels. However, pH treatment alone did not significantly affect water consumption. A Tukey HSD pairwise comparison among all combinations of treatment and variety revealed five significant differences. These occurred between the following pairs: T1-L1 and T1-L2, T3-L2, T4-L2, T4-L1, and T2-L1 and T3-L2. The T1 treatment for the L1 variety showed the most significant differences compared to other treatment-variety combinations, which means that Rutilai under the Control treatment had one of the highest water consumption levels. Rutilai is a fast-growing, large-leaf variety that uses more water due to higher evapotranspiration. Under the Control condition, Rutilai likely experienced the best alignment between water pH and its physiological requirements, along with high growth potential, greater leaf area, optimal nutrient uptake, and no stress from acidic or alkaline pH conditions, which collectively contributed to its higher biomass and water use.

The WUE results, based on two-way ANOVA, showed that lettuce variety had a highly significant effect on water use efficiency (p < 0.05). This indicates that different lettuce varieties use water with significantly different efficiencies. Treatment (pH level) alone did not have a significant effect on WUE, and no significant interaction was observed between pH level and variety.

Across all four pH treatments, L2 (Rex) consistently outperformed the other two varieties, suggesting its strong potential for production under conditions with poor water quality. A Tukey HSD pairwise comparison among all treatment-variety combinations identified two significant differences: between T3-L2 and T4-L3, and between T4-L1 and T4-L3.

From Table 2, it was observed that WUE across all treatments ranged from 34.64 to 68.72 g/L, which falls within the optimal range for hydroponically grown lettuce in DWC systems [7]. The average WUE across all treatments was approximately 48 g/L, and an upward trend between WUE and yield was observed up to this value. Beyond 48 g/L, lettuce yield began to plateau, indicating a point of diminishing returns where increased WUE did not result in significantly higher yield.

Across treatments, the highest yield was observed in T1-L2; however, its WUE was 62.73 g/L, which was not the highest. T1L2 also exhibited the largest WUE dispersion (standard deviation 10.02 g/L), driven by one plant with substantially higher fresh yield than its container mates while water use was averaged at the container level (four plants per DWC). The mismatch between per-plant yield (numerator) and pooled water consumption (denominator) inflated the variance, yielding an outlying WUE and increasing the standard deviation. The maximum WUE was recorded in T3-L2, at 68.72 g/L, while the lowest WUE, 34.64 g/L, was associated with one of the lower-yielding combinations.

When comparing pH treatments, T1 and T2 performed similarly, with average WUE values of 47.25 g/L and 47.10 g/L, respectively. The best average WUE was found in T3, suggesting that water pH may have some influence on WUE. However, the two-way ANOVA did not show a statistically significant effect of pH treatment alone on WUE.

The most significant differences in WUE were attributed to lettuce variety. L2 had the highest average WUE (63.36 g/L), as well as the highest yield and the lowest water consumption at 2.06 L/plant, clearly outperforming L1 (45.67 g/L) and L3 (37.57 g/L). These results indicate that variety selection has a much greater impact on WUE and overall water productivity than pH adjustments in the hydroponic system according to our study.

3.4. Nutrient Uptake

Nutrient uptake in hydroponic systems is influenced by several key factors, including pH, electrical conductivity (EC), and solution temperature. In this study, pH adjustment was performed only at the start of the experiment and during nutrient solution refills, but not continuously or periodically as would be performed in commercial systems equipped with automated monitoring and control. Throughout the experimental period, pH, EC, and temperature of the nutrient solution were measured 2–3 times per week for monitoring purposes only. Figure 4 showed the pH, EC and solution temperature changes over time.

The EC, pH, and temperature values in the hydroponic solutions varied over the study period, reflecting plant-driven changes in solution chemistry. A weak positive correlation was observed between pH and EC; however, this association was not statistically significant. Temperature remained relatively constant and showed no significant relationship with either EC or pH. Overall, these results indicate that pH had minimal effect on EC and temperature has minimal influence on either variable during the study. The most notable changes were temporal, occurring regardless of cultivar or pH treatment (Figure 4).

As indicated in Section 2.3, nutrient use was estimated based on measured nutrient concentrations and water consumption. Nutrient concentrations were measured weekly from water samples and a decrease in concentration over time was expected due to plant nutrient uptake. Because additional nutrients were added to the DWC system on 2–3 July, Figure 5 presents the resulting changes in nutrient concentrations over time at different pH treatments and for different cultivars. The mean deviations are plotted as error bars for each treatment.

Average N, P, and Ca concentrations showed clear temporal and treatment-dependent patterns across lettuce cultivars (Figure 5). Nitrogen concentrations began at similar levels across treatments but declined steadily through 28 June, reflecting plant uptake. Following nutrient supplementation on 2–3 July, N levels partially recovered or stabilized by 8 July in several treatments, particularly under T2. Phosphorus concentrations also declined by 28 June, indicating rapid uptake, but a noticeable increase was observed on July 8 in selected treatments (e.g., T2L1 and T4L3), corresponding to nutrient additions. Calcium concentrations were substantially higher than N and P, ranging from 150 to over 300 mg/L, and generally increased over time, particularly after supplementation. Greater variability in Ca concentrations was observed under higher pH conditions (T3 and T4), consistent with pH-dependent solubility and cultivar-specific uptake. Across all nutrients, error bars indicated moderate to large variability, suggesting that nutrient uptake efficiency differed among lettuce cultivars and pH treatments.

The NU and WUE for N, P, and Ca based fresh shoot weight were calculated using Equations (1)–(4) and are shown in

Table 3. Nitrogen (N), phosphorus (P), and calcium (Ca) usage (NU) and use efficiency (NUE) for four pH treatments: no pH control (T1), pH 6.3 (T2), pH 7.0 (T3), and pH 8.3 (T4), across three lettuce cultivars—Tacitus (L1), Rex (L2), and Rutilai (L3). The values in parentheses represent standard deviations. Values highlighted in red indicate the highest, and those in blue the lowest, within each category.

pH Treatment	Lettuce Variety	N NU (mg/Plant)	N NUE (mg of N/g of Fresh Shoot)	P NU (mg/Plant)	P NUE (mg of N/g of Fresh Shoot	Ca NU (mg/Plant)	Ca NUE (mg of Ca/g of Fresh Shoot)
T1	L1	1108 (±120)	9.0 (±1.54)	227 (±53)	2.2 (±0.39)	1312 (±283)	10.7 (±2.72)
	L2	995 (±51)	7.7 (±0.55)	261 (±35)	2.0 (±0.35)	851 (±173)	6.6 (±1.17)
	L3	1056 (±61)	10.4 (±0.56)	278 (±5)	2.7 (±0.04)	871 (±196)	8.6 (±1.74)
T2	L1	1086 (±86)	8.0 (±0.42)	228 (±67)	1.7 (±0.52)	1175 (±211)	8.7 (±1.55)
	L2	1026 (±82)	8.2 (±0.47)	180 (±33)	1.4 (±0.23)	979 (±74)	7.9 (±0.43)
	L3	1060 (±84)	10.9 (±0.90)	179 (±26)	1.8 (±0.31)	972 (±165)	10.0 (±1.57)
T3	L1	1076 (±160)	8.4 (±1.02)	247 (±41)	1.9 (±0.27)	505 (±86)	4.0 (±0.74)
	L2	914 (±438)	7.1 (±3.44)	269 (±57)	2.1 (±0.40)	416 (±209)	3.2 (±1.62)
	L3	1135 (±240)	11.0 (±2.54)	215 (±116)	2.1 (±1.16)	841 (±248)	8.1 (±2.38)
T4	L1	833 (±151)	6.7 (±0.96)	306 (±29)	2.5 (±0.25)	922 (±27)	4.9 (±4.26)
	L2	1090 (±198)	8.3 (±1.55)	271 (±38)	2.1 (±0.26)	794 (±69)	6.0 (±0.50)
	L3	1251 (±159)	12.8 (±2.61)	172 (±123)	1.8 (±1.33)	1014 (±415)	10.5 (±4.57)
Average		1052 (±153)	9.0 (±1.38)	240 (±52)	2.0 (±0.46)	887 (±180)	7.4 (±1.94)

.

Nitrogen uptake appeared to be unaffected by pH level, lettuce variety, or their interaction. In contrast, NUE showed clear varietal differences. Cultivar L3 consistently demonstrated higher NUE, particularly under pH treatments T3 and T4, suggesting greater efficiency under more extreme pH conditions. In comparison, L1 exhibited the lowest NUE under T4, indicating that it is the least efficient in nitrogen utilization under alkaline conditions. ANOVA analysis confirmed that lettuce type had a significant effect on NUE (p < 0.05), supporting the conclusion that NUE varies among different lettuce cultivars, whereas pH level and the interaction between pH and cultivar did not significantly affect NUE.

Unlike N, both phosphorus NU and NUE appeared to be unaffected by pH level, lettuce cultivar, or their interactions, with no significant influences. This finding contrasts with a previous study that reported high pH (>7.5) significantly reduced P uptake [35].

For calcium, pH level had a highly significant effect on NU, indicating that different pH treatments strongly influenced the amount of calcium absorbed. Lettuce cultivar also showed a significant effect, suggesting that different cultivars absorb calcium at different rates. However, the interaction between pH level and lettuce type was not statistically significant. ANOVA results also showed that pH level significantly affected Ca NUE, meaning that Ca NUE varied across pH treatments. Lettuce type had a similarly significant effect, indicating that different lettuce varieties utilized calcium with different efficiencies. The interaction between pH level and lettuce type did not significantly influence Ca NUE. In summary, both pH level and lettuce variety independently and significantly affect calcium uptake and use efficiency, while their interaction does not. This emphasizes that optimizing either the pH level or crop variety can improve calcium utilization in hydroponic systems.

4. Discussion

This study demonstrates that lettuce variety plays a more pivotal role than water pH in determining yield, WUE, and NUE in DWC hydroponic systems. These findings align with previous research showing that WUE and NUE responses can be strongly species- or cultivar-specific, even under standardized hydroponic conditions. Kudirka et al. (2023) [36] reported that lettuce grown at pH 6.0–6.5 exhibited a 44% higher WUE compared with plants grown at lower pH levels (5.0–5.5). Among the three cultivars tested in the present study, Rex consistently showed superior performance, producing the highest yield and WUE across pH treatments. Notably, its performance remained stable even at pH 8.3, suggesting strong tolerance to alkaline conditions. Similarly, Anderson et al. (2017) [37] found that a Butterhead lettuce cultivar had 26% lower fresh weight and 18% lower dry weight when grown at pH 7.0 compared with pH 5.8. Furthermore, Regmi et al. (2024) [38] concluded that crop type and cultivar identity are among the most influential factors affecting WUE and NUE in hydroponic systems, across multiple system types, and often outweigh individual environmental variables such as pH. Collectively, these results emphasize the importance of cultivar selection and the integration of environmental conditions for optimizing yield, WUE, and NUE in controlled hydroponic systems.

While pH alone did not significantly affect total yield, it had a statistically significant influence on calcium uptake and calcium NUE. The effect of pH on calcium uptake can be attributed to its influence on calcium solubility and ionic availability in nutrient solutions. At high pH levels, Ca²⁺ is more prone to precipitation—particularly as calcium phosphate or calcium carbonate—thereby reducing its availability for uptake [39,40]. In contrast, slightly acidic to neutral pH maintains calcium in soluble and bioavailable forms. Moreover, optimal nutrient uptake—including that of calcium—typically occurs within a pH range of approximately 5.5–6.5 in hydroponic systems. Deviations from this optimal range can result in the lockout of not only calcium but also other secondary macronutrients and micronutrients due to reduced solubility or altered root-zone chemistry [41]. This is particularly important given calcium’s critical role in maintaining cell wall strength and preventing physiological disorders such as tip burn in leafy greens [29,32]. The interaction between pH and cultivar was not statistically significant for most variables, indicating that inherent genetic traits of the cultivar exert a stronger influence on performance than nutrient solution pH within the tested range.

Interestingly, nitrogen uptake (NU) remained largely unchanged across pH levels and varieties. However, nitrogen NUE varied significantly among cultivars, with Rutilai (L3) demonstrating high NUE, especially under higher pH conditions. This suggests that while Rex excels in yield and WUE, Rutilai may have physiological mechanisms for more efficient nitrogen assimilation under alkaline stress [7]. In contrast, phosphorus uptake and NUE were not significantly affected by either pH or cultivar, indicating stability of phosphorus availability and utilization under these experimental conditions [35].

These findings carry important implications for resource-limited or small-scale growers. In many rural or urban agricultural settings, growers rely on untreated water with naturally high pH. Since frequent pH monitoring and buffering can be expensive, identifying pH-resilient cultivars such as Rex allows these growers to maintain productivity while reducing input costs. The continued development of low-cost pH sensors and automation technologies may further support this transition [42].

5. Conclusions

The greatest yield overall in this experiment was obtained from the Rex lettuce variety grown under the pH 7.0 treatment. Rex also achieved the highest yield under the control condition, indicating its robustness across pH levels. Statistical analysis found no significant differences in yield across pH levels, but significant differences among varieties. This suggests that Rex can outperform Tacitus and Rutilai regardless of pH treatment. This is particularly valuable for smaller growers who may lack the resources to adjust or maintain pH levels in DWC systems due to the cost of buffering agents, sensors, and calibration solutions. This study suggests that by selecting appropriate hydroponic methods and pH-tolerant varieties such as Rex, growers can produce marketable lettuce even without ideal pH control—offering a sustainable and practical solution for low-input CEA operations.

Our conclusions are based on one greenhouse season with four pH treatments, three cultivars, and three replicates under controlled conditions. While this design minimized confounding factors, single-season studies may overstate effects or miss year–treatment interactions. Replication across additional seasons and facilities is needed to confirm cultivar and pH responses, and such trials are planned to strengthen producer recommendations.