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Article

Optimizing Planting Density for Increased Resource Use Efficiency in Baby-Leaf Production of Lettuce (Lactuca sativa L.) and Basil (Ocimum basilicum L.) in Vertical Farms

by
Vivek Jadhav
1,
Tiziano Grondona
1,
Alessandro Pistillo
1,
Giuseppina Pennisi
1,*,
Marco Ghio
2,
Giorgio Gianquinto
1 and
Francesco Orsini
1
1
DISTAL–Department of Agricultural and Food Sciences, Alma Mater Studiorum–University of Bologna, Viale Giuseppe Fanin 44, 40127 Bologna, Italy
2
Germina S.r.l., Via di Brera 2, 16121 Genova, Italy
*
Author to whom correspondence should be addressed.
Horticulturae 2025, 11(4), 343; https://doi.org/10.3390/horticulturae11040343
Submission received: 14 January 2025 / Revised: 13 March 2025 / Accepted: 18 March 2025 / Published: 21 March 2025
(This article belongs to the Section Protected Culture)
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Abstract

:
Vertical farming is gaining popularity as a sustainable solution to global food demand, particularly in urban areas where space is limited. However, optimizing key factors such as planting density remains a critical issue, as it directly affects light interception, energy efficiency, and crop yield. Lettuce and basil, the most commonly grown crops in vertical farms, were chosen for this study, with the aim of addressing the impact of planting density on light interception and overall productivity for improving the performance and sustainability of vertical farming systems. Plants were grown in an ebb-and-flow system of a fully controlled experimental vertical farm, where light was provided by light-emitting diode fixtures delivering a photoperiod of 16 h d−1 and 200 µmol m−2 s−1 of photosynthetic photon flux density. Experimental treatments included three planting densities, namely 123 (low density, LD), 237 (medium density, MD), and 680 (high density, HD) plant m−2. At the final harvest (29 days after sowing), the adoption of the highest planting density (680 plant m−2) resulted in greater fresh yield (kg FW m−2), leaf area index (LAI, m2 m−2), light use efficiency (LUE, g DW mol−1) and light energy use efficiency (L-EUE, g FW kWh−1) for both lettuce (+207%, +227%, +142%, +206%, respectively), and basil (+312%, +316%, +291, +309%, respectively), as compared to the lowest density (123 plant m−2). However, the fresh and dry weights of the individual plants were lowered, probably as a result of the reduced light availability due to the highly dense plants’ canopy. Overall, these findings underscore the potential of increasing planting density in vertical farms to enhance yield and resource efficiency.

1. Introduction

Resilient food production systems, located closer to consumers and less vulnerable to supply chain disruptions, are becoming increasingly important. This is due to unpredictable climate change, environmental pollution, fossil fuel shortages, drought [1], and food supply chain failures, such as those caused by the COVID-19 pandemic [2]. At the same time, the growth of the global population is driving an increasing demand for food, mainly in urban areas, where two-thirds of the global population will reside by 2050 [3]. This necessity has driven the development and expansion of novel agricultural production systems, such as vertical farms (VFs).
Vertical farms (VFs) are emerging globally as a promising solution to address challenges such as unpredictable climate, water scarcity, and the indiscriminate use of fertilizer and pesticides in intensive production systems [4]. Highly efficient in terms of land use, VFs are claimed to offer a viable strategy to enhance food security in densely populated urban areas by reducing food miles while significantly contributing to sustainable food production systems [5]. VFs are designed as controlled environments with multi-level structures and artificial lighting fixtures equipped with light-emitting diodes (LEDs) tailored to optimize plant growth. These systems enable year-round production [6], less risk of pests’ attack (and consequently reduced use of pesticides) while also allowing for precisely regulating water and nutrient supply (with benefits both in terms of resource-saving and overall crop performances) [4]. Additionally, VFs reduce the cost, time, and quality loss associated with transporting fresh vegetables, which are highly perishable due to their high water content [1]. By integrating advanced technologies and precise environmental controls, VFs represent a sustainable and efficient alternative to traditional agriculture, offering a resilient solution to meet the growing demand for fresh, high-quality produce in urban settings.
The energy consumption associated with VFs remains, however, a significant challenge due to the fact that all photosynthetic requirements must be met through artificial lighting [7]. Indeed, the current adoption of VF technology is hindered by the substantial energy demand associated with lighting (about half of the total energy costs), as well as for climate control (in the range of 30–35% for cooling, heating, and dehumidification), topping out at 10–15% for other production operations [8]. Accordingly, electricity is one of the largest cost components in VFs, and recent research efforts have addressed strategies for improving energy use efficiency, for example, by manipulating light spectral quality [9], light intensity [10], and photoperiod [11]. Moreover, increasing the fraction of light captured by the crop can be achieved through variable planting densities (also referred to as dynamic planting [12]) or the inclusion of reflectors [7].
Planting density is a critical parameter in VFs, where higher densities are typically used as compared to other cultivation systems (e.g., greenhouses or open fields) [8]. Optimal planting density, defined as the population that maximizes yield and optimizes plant arrangement per unit area, enables crops to efficiently use resources and produce the highest yields [13]. Indeed, while high planting densities can reduce individual plant growth due to resource competition, they also have the potential to enhance water use efficiency in lettuce, particularly when densities exceed 270 plants m−2 [4]. Even if no information is available on testing different planting densities for basil cultivation in VFs, recent research has demonstrated that yield in leafy greens such as lettuce may be increased by up to 25% by optimizing planting density [14]. Although it is generally acknowledged that ensuring optimal conditions, including temperature, CO2 concentration, nutrient delivery, humidity, and other relevant factors, is crucial for plant growth and development [15], the role of appropriate planting density in enhancing resource use without compromising produce quality remains an underrated and under-researched topic in VFs.
VFs are becoming a valuable choice for farmers addressing the production of baby leaf greens, thanks to their short growth cycle (and elevated yield), as well as their rewarding price (thanks to the growing demand by consumers, as well as the added value provided by high-quality, ready-to-eat options) [16]. In this context, lettuce (Lactuca sativa L.) and basil (Ocimum basilicum L.) are particularly well-suited for vertical farming due to their compact growth habits, short production cycles (especially when harvested at the baby-leaf stage), and high nutritional value, making them ideal crops for optimizing space utilization and economic returns in VF systems [17,18,19].
Knowledge of their response to changes in planting density enables precise control over growth and morphology, facilitating efficient system design and management [17,20]. In this context, the present study aims to determine the effects of different planting densities on lettuce and basil biomass production, morphological and physiological adaptations, as well as light and energy use efficiency. By optimizing planting density, this research seeks to enhance productivity and resource efficiency, contributing to the sustainability and economic viability of vertical farming.

2. Materials and Methods

2.1. Experimental Site and Growing Condition

The trial was conducted within AlmaVFarm, the experimental vertical farm located in the Department of Agricultural and Food Science at the University of Bologna (Italy), formerly described in Carotti et al. [4]. Throughout the trial, air temperature and humidity were maintained at 24/21 °C and 70/75 ± 10% day/night, respectively, and additional CO2 was supplied to maintain a constant concentration of 850 ppm. For the research, five ebb-and-flow cultivation sectors were used, each composed of a 3-level tray stacked cultivation, with a surface area of 0.53 m2 on each floor.

2.2. Plant Material

Sweet basil (Ocimum basilicum L. var. Italiano Classico) and lettuce (Lactuca sativa L. var. Canasta) plants were tested in this study. Both species’ seeds were sourced from Florsilva Ansaloni (San Lazzaro Di Savena, BO, Italy).

2.3. Light Management

Lighting was supplied by red (R, peak at 645 nm) and blue (B, peak at 466 nm) LED lamps (Flytech srl, Belluno, Italy), where diodes maintained a specific ratio between the two spectral regions of 3:1 (R:B). The spectral distribution was measured using an illuminance spectrophotometer (CL-500A, Konica Minolta, Chiyoda, Tokyo, Japan). The photosynthetic photon flux density (PPFD) was set at 200 μmol m−2 s−1, with a photoperiod of 16 h d−1, resulting in a Daily Light Integral (DLI) of 11.52 mol m−2 d−1. The PPFD values were monitored using an MQ-610 ePAR meter (Apogee Instruments, Logan, UT, USA) [4].

2.4. Nutrient Solution Management

Two stock solutions, A and B, were used to prepare the nutrient solution, which was replaced every 15 days. The nutrient solution used in the experiment had an electrical conductivity (EC) of 2.3 ± 0.2 dS m−1 and a pH of 5.8 ± 0.2, and the following composition: N-NO3: 14 mM (196 mg L−1); N-NH4: 4.4 mM (61.6 mg L−1); P: 1.0 mM (31 mg L−1); K: 5.0 mM (195.5 mg L−1); S: 2.0 mM (64.2 mg L−1); Ca: 5.2 mM (208.5 mg L−1); Mg: 1.2 mM (29.2 mg L−1); Fe: 17.9 μM (1.0 mg L−1); Cu: 2.0 μM (0.13 mg L−1); Zn: 3.8 μM (0.25 mg L−1); B: 11.6 μM (0.13 mg L−1); Mn: 18.2 μM (1.0 mg L−1); Mo: 0.5 μM (0.048 mg L−1). A closed-loop water cycle was used, with the drained nutrient solution returning to a water tank, where a fully automated fertigator (NidoPro®, LogicSun, Cattolica, RN, Italy) checked (96-time d−1) and, if necessary, corrects pH and EC parameters before the nutrient solution returned into the system. The nutrient solution was circulated once a day for 10 min for the first two weeks (specific requirements of the crops and their growth stages) of the growing period (1 to 14 days after sowing, DAS) and twice a day for 10 min each for the last two weeks (from 15 DAS to the end of the cycle). Both species received the same nutrient solution throughout the experiment [4].

2.5. Growth Analysis and Resource Use Efficiency

Destructive measurements were performed at 15, 22, and 29 days after sowing (DAS). At harvesting, shoot fresh weight (g FW plant−1) was measured, and shoot dry weight (g DW plant−1) was quantified after drying samples at 65 °C for 72 h. Dry matter content (%) was calculated as the ratio between dry and fresh shoot weights. Fresh yield (kg FW m−2) was obtained by multiplying shoot fresh weight by planting density. Plant height (cm) was measured using a ruler and considering the distance from the collar to the apex. In addition, excluding the cotyledon leaves, plant leaf area (cm2 plant−1) was measured using digital images assessed through a mobile phone application (Easy Leaf Area) [21]. Leaf area index (LAI, m2 m−2) was obtained by multiplying the plant leaf area by the planting density. Relative growth rate (RGR) was calculated for two intervals of time: the first from 15 to 22 DAS, and the second from 22 to 29 DAS. RGR was determined using the formula: RGR = ln (DW2/DW1)/time, where DW2 and DW1 represent the dry weights at the respective time points. Light energy use efficiency (L-EUE, g FW kWh−1) was determined as the ratio between the yield and the lamps’ cumulated electricity absorption (kWh m−2) at 15, 22, and 29 DAS. Similarly, light use efficiency (LUE, g DW mol−1) was calculated as the ratio of dry weight and the incident moles of photosynthetic photons cumulated at the same time points.

2.6. Stomatal Conductance

Measurements of stomatal conductance (mmol m−2 s−1) were performed on the third fully expanded leaf using a leaf porometer (ΔP4, Delta-T Devices, Cambridge, UK) at 15, 22, 29 DAS for lettuce, and at 22 and 29 DAS for basil.

2.7. Relative Chlorophyll Content

The relative content of chlorophyll in leaves was estimated at 15, 22, and 28 DAS using a hand-held leaf chlorophyll meter (SPAD-502, Konica Minolta, Chiyoda, Tokyo, Japan) by performing three measurements for each of the two most developed leaves.

2.8. Experimental Design and Treatments

The experiment was conducted using a completely randomized design across five ebb-and-flow cultivation sectors, each consisting of three stacked levels (Figure 1A). Seeds of both species were sown in 104-hole polyethylene trays (30 cm wide × 51 cm long × 5 cm high) filled with a peat and vermiculite mixture (70:30 v:v). The trays were then placed in the ebb-and-flow system for cultivation. After germination (1 week after sowing), for both crops, thinning was carried out to achieve the three tested planting densities: 123 plants m−2 (low density, LD), 237 plants m−2 (medium density, MD), and 680 plants m−2 (high density, HD). For both basil and lettuce, the HD treatment was consistently grouped within a sector, with each crop allocated to its own tray for replication, while the other treatments (LD and MD) were randomly assigned to individual sectors (two trays were used for each replication) (Figure 1B). Each treatment was replicated three times. At the three sampling times (15, 22, and 29 DAS), measures were carried out on 15 plants per treatment, with border plants used to replace sampled plants to minimize edge effects and avoid modifications in density treatments, ensuring that border plants were excluded from the sampling process.

2.9. Statistical Analysis

All statistical analyses were conducted in R Studio (Version 4.2.2), and graphical presentations were created using Microsoft Excel (version 2108). Data that were normally distributed and homogeneous were analyzed using one-way ANOVA, followed by Tukey’s post hoc test at a 5% significance level. For data not fulfilling the assumption of normality, data transformations were applied with the orderNorm function from the bestNormalize package to achieve normalization. This approach was applied to lettuce (fresh yield, LAI, L-EUE, LUE, and chlorophyll content at 22 DAS) and basil (fresh yield, L-EUE, and chlorophyll content at 15 and 29 DAS, stomatal conductance, and dry weight at 22 DAS, LAI, LUE at 22 and 29 DAS). For data that did not meet the assumption of homogeneity of variances, Welch’s ANOVA was used instead, followed by Games–Howell post hoc comparisons, also at a 5% significance level.

3. Results

3.1. Effect of Planting Density on Biomass Production

Figure 2 shows the effects of planting densities on agronomic, morphological, and physiological responses of lettuce and basil plants at three different harvesting dates (15, 22, and 29 DAS). At 15 DAS, lettuce and basil grown under HD exhibited the highest fresh yield (kg FW m−2) (Figure 2A,E). However, the fresh weight per plant (g FW plant−1) was the lowest at HD for both species (Table 1), indicating a trade-off between overall yield and individual plant growth. In addition, lettuce showed higher dry weight (g DW plant−1) production in LD (0.05 g DW plant−1) as compared to MD and HD (0.04 and 0.02 g DW plant−1, respectively), while in basil, the greater dry weight was observed in both LD and MD (0.04 g DW plant−1 on average) as compared to HD (0.02 g DW plant−1) (Table 1). Furthermore, dry matter content (DMC) was remarkably higher in lettuce grown at LD (6.39%) as compared to MD (5.56%), while HD (6.18%) did not differ significantly from either LD or MD (Figure 2B). Interestingly, basil at MD achieved the highest DMC (11.05%) as compared to both LD and HD treatments (average of 9.79%) (Figure 2F).
At 22 DAS, the responses to the variation in planting densities were quite similar to those observed at 15 DAS. Indeed, for both lettuce and basil, fresh yield resulted to be the highest at HD (Figure 2A,E), despite featuring lower plant fresh and dry weights as compared with LD treatment (Table 1). Specifically, the fresh yield of lettuce and basil increased by 2.7- and 3.4-fold, respectively, when comparing HD to LD at 22 DAS (Figure 2A,E). In lettuce, a decreasing trend as a response to increasing planting density was observed for DMC, with the highest value recorded in LD (5.27%), followed by MD (4.69%) and HD (4.12%) (Figure 2B). For basil, the highest and lowest DMC were observed in LD (9.99%) and HD (8.9%), respectively, while MD did not show significant differences with other densities (Figure 2F).
At 29 DAS, both species showed consistent yield patterns similar to the previous harvest (Figure 2A,E). Specifically, basil achieved the highest fresh yield under HD, reaching 3.35 kg FW m−2, which was 4.1-fold greater than the yield at LD (0.81 kg FW m−2) (Figure 2E). The MD fresh yield (1.63 kg FW m−2) also demonstrated a substantial increase, roughly 2-fold as compared to LD (Figure 2E). Similarly, lettuce recorded the highest fresh yield at HD, approximately 9 kg FW m−2, which was significantly higher as compared to LD (3 kg FW m−2) and MD (4.21 kg FW m−2) (Figure 2A). The highest dry weight per plant was recorded in LD, while the lowest was noted in HD and followed by MD-grown lettuce (Table 1). Conversely, in basil, significant differences in dry weight production were only visible between LD (1.23 g plant−1) and HD (0.54 g plant−1) (Table 1). Moreover, the DMC was significantly influenced by planting density, being the highest in LD, with values of 5.1% for lettuce (Figure 2B), whereas in basil (9.95%), it did not differ from values observed at HD (Figure 2F).

3.2. Effect of Planting Density on Plant Morphological Response

At 15, 22, and 29 DAS, both lettuce and basil plants showed similar LAI increasing trends in response to the greater planting densities, with the exception of lettuce at 29 DAS (Figure 2C), where differences were only visible between HD and the other two treatments (MD and LD). Furthermore, while lettuce plants were significantly taller at the lowest planting density at the early stages (15 DAS), plants grown under HD were the highest at the end of the cycle (29 DAS), featuring 14.8 cm (Table 1). In basil plants, at 15 and 22 DAS, the highest planting density was associated with the shortest plant height, while no differences were detected between the planting densities at 29 DAS (Table 1).

3.3. Effect of Planting Density on Leaf Chlorophyll Content and Stomatal Conductance

Considering relative chlorophyll content, significant differences across planting densities in lettuce were only visible starting from 22 DAS, with the lowest values observed at the highest density (Figure 2D). More specifically, at 29 DAS, HD planting resulted in a SPAD reading of 25.9, approximately 17.5% lower than the MD reading of 31.4 and 22.7% lower than the LD reading of 33.5 (Figure 2D). Conversely, in basil, despite some differences between MD and LD at 15 DAS, chlorophyll content did not vary in response to planting density at successive measurements (Figure 2H). Stomatal conductance was not significantly affected by planting densities at 15 DAS in lettuce and at 22 DAS in both species (Table 1). However, at 29 DAS, lettuce grown under HD planting exhibited higher stomatal conductance as compared to LD planting (Table 1). Conversely, basil showed the opposite trend, with lower stomatal conductance noted in HD-grown plants, as compared to either LD or MD treatments (Table 1).

3.4. Effect of Planting Density on Relative Growth Rate

For lettuce, RGR did not show statistically significant differences across different planting densities at 22 or 29 DAS, with average values of 0.28 and 0.15 g g−1 d−1, respectively (Figure 3A). On the other hand, basil RGR showed a diverse response to planting density variation according to the harvesting time (Figure 3B). Accordingly, at 22 DAS planting density increase resulted in a reducing RGR (−12.7% moving from LD to HD) (Figure 3B). At 29 DAS, the only statically significant difference was observed between MD and HD, with higher values at HD (+43.5%) (Figure 3B).

3.5. Effect of Planting Density on Light and Energy Use Efficiencies

In both species, high-density planting (HD) achieved the greatest light use efficiency (LUE) and light energy use efficiency (L-EUE) at different stages of the growth period (Figure 4). At 15 DAS, lettuce cultivated at the highest planting density (HD) showed a significant 2.6-fold improvement in LUE compared to lower-density planting (LD). At the same time, moderate-density planting (MD) (0.05 g DW mol−1) did not differ significantly from other densities (Figure 4A). For basil, LUE improved as planting density increased, with HD (0.09 g DW mol−1) showing 1.6-fold and 3.6-fold gains over MD and LD planting, respectively (Figure 4C). Similarly, L-EUE was the highest at HD for both lettuce and basil, with 2.7-fold and 3.7-fold improvements over LD, respectively (Figure 4B,D).
At 22 DAS, the responses to planting density variations were similar to those observed at 15 DAS (Figure 4A,C). For both lettuce and basil, LUE was significantly greater at HD planting (0.42 g DW mol−1 for lettuce, 0.30 g DW mol−1 for basil), while the lowest values were achieved at LD planting (0.20 g DW mol−1 for lettuce, 0.10 g DW mol−1 for basil, Figure 4A,C). In a similar pattern, L-EUE was the highest at HD planting, with values of 43.8 g FW kWh−1 for lettuce and 14.4 g FW kWh−1 for basil (Figure 4B,D).
At 29 DAS, the LUE for lettuce was 2.4-fold higher at HD planting as compared to LD planting (Figure 3A). Similarly, in basil, LUE under HD was 2.4- and 3.9-fold higher as compared to MD and LD treatments, respectively (Figure 4C). L-EUE significantly improved with the adoption of different planting densities for both species (Figure 4B,D). For lettuce, no statistically significant difference was observed for L-EUE between LD and MD (average value of 45.5 g FW kWh−1), whereas the adoption of the HD resulted in a substantial increase (116.2 g FW kWh−1, Figure 4B). In basil, moving from LD to MD resulted in a 2-fold increase (10.3 and 20.6 g FW kWh−1, respectively), with the highest value (42.2 g FW kWh−1) observed under HD (Figure 4D).

4. Discussion

To date, extensive research has addressed the optimization of growth conditions and productivity of leafy greens in controlled environments. The application of Taguchi’s method combines engineering and statistical approaches to provide a solid framework for designing and analyzing experiments [22]. In addition, plant growth models aim to enhance light utilization, driving further improvements in crop performance [23]. In VFs, planting densities used for growing leafy greens vary widely, ranging from approximately 15 to 1300 plants m−2 [12]. A recent study by Carotti et al. [4] focused on optimizing resource use of lettuce cultivation in VFs, considering three different planting densities (140, 270, and 733 plants m−2), which are similar to those used in this study. The study highlighted that increasing planting density significantly enhanced fresh yield. Our findings confirm that the highest planting density tested (680 plants m−2) led to substantial increases in both lettuce and basil fresh yield (Figure 2A,E). However, this comes at the expense of lower fresh and dry weight per individual plant. This is primarily due to limited space and, consequently reduced access to light, which constrained photosynthesis [24]. This trade-off aligns with prior research emphasizing that denser planting improves overall yield but compromises individual plant growth (Table 1) [14]. Dry biomass production is linked to greater light interception, increased photosynthesis, and resource use efficiency (RUE), typically resulting in improved economic performance [25]. RUE reflects the cumulative response of the crop to various factors that influence photosynthesis and respiration throughout the growing season or during specific growth phases [26]. At the lowest planting density (123 plants m−2), higher dry weight was produced in individual lettuce plants, whereas basil maintained stable dry weight accumulation up to 237 plants m−2 (MD, Table 1). This suggests species-specific tolerance to light limitations, possibly linked to differences in plant architecture or physiological adaptation (Table 1) [27]. Lettuce dry matter content (DMC) decreased by 23% as planting density increased from low to high (Figure 2B), in line with previous research that reported a decline of up to 26% in DMC as density increased from 15 to 30 plants m−2 [28]. In contrast, basil showed no such under similar conditions (Figure 2F), suggesting greater adaptability to light fluctuations. Previous research supports this observation, indicating that basil maintains stable DMC at light intensities as low as 100 µmol m−2 s−1 compared to higher intensities of up to 300 µmol m−2 s−1 [10]. This underscores light’s critical role as an environmental factor regulating plant development and species-specific behavior [29]. Light availability to leaves is often limited in more dense planting due to the proximity of neighboring plants. At 29 DAS, this limitation prompts lettuce to prioritize rapid elongation growth over chlorophyll maintenance as a competitive strategy for light (Table 1). Consequently, lettuce plants grow taller, but exhibit reduced chlorophyll content (Figure 2D), which can impair photosynthesis and overall growth [28,29]. In contrast, basil maintained stable biomass, chlorophyll content, and stomatal conductance across planting densities up to MD (237 plants m−2) (Table 1). These results suggest that increasing planting density in basil could enhance yield per unit area without compromising plant performance, offering a strategy for more efficient resource utilization and increased productivity in vertical farming systems. Stomatal opening and closing are primarily influenced by several environmental factors, including light availability (both the intensity and quality of light), temperature fluctuations, CO2 concentration [30], and vapor pressure deficit (VPD) [31]. Additionally, air humidity is known to affect stomatal behavior; however, the mechanisms by which plants sense and respond to humidity remain a topic of ongoing debate [32]. This complexity highlights the intricate nature of stomatal regulation, which is influenced by both environmental conditions and internal physiological processes. In this study, increasing planting density (HD, 680 plants m−2) in lettuce resulted in significantly higher stomatal conductance compared to the lower density planting (LD, 123 plants m−2) (Table 1). This phenomenon can be attributed to several interrelated factors, including the potential for a denser canopy to increase humidity levels around the leaves. Elevated humidity reduces transpiration rates and promotes stomatal opening, thereby enhancing stomatal conductance. In contrast, lower dense (LD) basil plants benefited from spacing, which allowed for enhanced light capture, which may as well contribute to higher stomatal conductance (Table 1). These findings underscore the complex interplay between canopy structure, light availability, and stomatal regulation. Denser planting in an area can enhance yields and reduce costs by optimizing resource use and improving the efficacy of lighting, cooling, and heating [33]. This is particularly crucial early in the growth stage when the leaf surface area is too small to efficiently capture incident light [34]. LAI, defined as the total leaf area relative to the ground area (m2 m−2), is a critical measure of the plant’s capacity to intercept light. Achieving an optimal leaf area significantly enhances crop photosynthesis and water use efficiency by maximizing light interception while minimizing self-shading [35]. Numerous studies indicate that, within greenhouse environments, an optimum LAI ranging from 3 to 4 can intercept approximately 95% of the incident light, while an LAI of 2 captures roughly 80% [33]. Values exceeding this optimum range or even similar values do not confer significant advantages in light interception or growth due to factors related to leaf structure and genotypic-based leaf angle features [36]. In this study, higher LAI values were observed with increased planting density in both species, consistent with previous research showing that increasing planting density from 20 to 50 plants m−2 in lettuce and from 10 to 40 plants m−2 in basil also led to an increase in overall leaf area [37,38]. However, it is important to consider the potential trade-offs associated with canopy structure, resource allocation, and overall plant growth. The relative growth rate (RGR) of plants typically declines with age as a result of increased competition among individuals within the population, even well-spaced plants [39]. In this study, the RGR of basil decreased significantly at the highest planting tested (680 plants m−2) in the early growth stage (22 DAS, Figure 3B). Conversely, lettuce showed no significant response to planting density at either 22 or 29 DAS, suggesting species-specific tolerance to crowding and resource competition (Figure 3A). This aligns with prior research indicating that some crops maintain stable growth across varying densities due to differences in canopy architecture and resource use efficiency [27]. The LUE of crops grown in VFs covers a wide range, with maximum theoretical values estimated between 1.26 and 1.81 g DW mol−1, although such values are rarely achieved under controlled experimental conditions [40]. Previous studies on basil and lettuce grown under similar experimental conditions—with light intensity (expressed as the PPFD) of 250 μmol m−2 s−1 for basil and 200 μmol m−2 s−1 for lettuce—achieved LUE values of 1.03 g DW mol−1 for lettuce at 14 days after transplanting (DAT) and 0.5 g DW mol−1 for basil at 21 DAT, both at a planting density of 100 plants m−2 [10]. In the present study, increasing plant density (680 plants m−2) enhanced light use efficiency (LUE) in both lettuce and basil, leading to improved growth performance (Figure 4A,C). During the later growth period (at 29 DAS), LUE was the highest under HD planting (680 plants m−2), with 1.09 and 0.94 g DW mol−1 for lettuce and basil, respectively, and the lowest under LD planting (123 plants m−2), with 0.45 and 0.24 g DW mol−1, respectively (Figure 4A,C). This disparity can be attributed to differences in planting density and transplanting strategies throughout the growth cycle, from germination to harvest, as well as inefficient light interception at the highest planting densities. With regard to the efficiency of transforming electricity into fresh biomass production, Carotti et al. [41] reported light energy use efficiency (L-EUE) values of 24.73 ± 1.35 g FW kWh−1 for lettuce at 29 DAS with a planting density of 153 plants m−2. In comparison, our results for LD planting (123 plants m−2) yielded a higher L-EUE of 37.9 g FW kWh−1 (Figure 4B,D). However, HD planting achieved significantly higher L-EUE values: 116.2 g FW kWh−1 for lettuce and 42.2 g FW kWh−1 for basil at 29 DAS (Figure 4B,D). These findings align with, Pennisi et al. [10], who reported L-EUE values of 110 g FW kWh−1 for lettuce and 45 g FW kWh−1 for basil at 14 DAT under a PPFD of 250 μmol m−2 s−1. The observed improvements in L-EUE under HD planting highlight the economic feasibility of increasing planting density to maximize resource use efficiency in VFs.

5. Conclusions

This study provides new insights into the effects of planting density on lettuce and basil cultivation in vertical farms. Both crops benefitted from the highest planting density tested (HD, 680 plants m−2) in terms of yield. Accordingly, at 29 DAS, both crops showed an increasing trend moving from LD to HD in LUE (3.9- and 2.1-fold increase for basil and lettuce, respectively), and L-EUE (4- and 2.5-fold increase for basil and lettuce, respectively).
Planting density increase resulted in a reduction in fresh and dry weight per individual plant in both species. However, in basil, fresh and dry weight per plant at MD resulted comparable to LD. This suggests that basil may be more resilient than lettuce under higher planting densities, making it a suitable candidate for maximizing productivity in space-constrained vertical farming systems. These findings highlight the potential of optimizing planting density as a strategy to improve resource use efficiency and crop productivity in vertical farming systems.
Future research should focus on refining density-based cultivation strategies across different growth stages and exploring their applicability to a broader range of crops. Additionally, studies on integrating dynamic environmental controls (e.g., adaptive lighting systems and nutrient delivery optimization) with high-density planting could further enhance productivity while minimizing resource inputs. Finally, assessing the long-term sustainability implications of high-density vertical farming practices will be critical for scaling up these systems to meet global food security challenges.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/horticulturae11040343/s1.

Author Contributions

Conceptualization, V.J.; methodology, V.J.; validation, G.P., F.O. and A.P.; formal analysis, V.J.; investigation, V.J. and T.G.; resources, F.O. and M.G.; data curation, V.J. and T.G.; writing—original draft preparation, V.J.; writing—review and editing, G.P., F.O. and G.G.; visualization, V.J.; supervision, G.P., F.O. and G.G.; funding acquisition, F.O. All authors have read and agreed to the published version of the manuscript.

Funding

The research leading to this publication received funding from the Italian Ministry of Education and Research (MUR) within the call for Research Projects of National Interest (PRIN) under the project “VFARM—Sustainable Vertical Farming” (Project code: 2020ELWM82, CUP: J33C20002350001). It was carried out within the Agritech National Research Center and received funding from the European Union’s NextGenerationEU program (PNRR—MISSIONE 4 COMPONENTE 2, INVESTIMENTO 1.4—D.D. 1032, 17 June 2022, CN00000022).

Data Availability Statement

Data are available in the Supplementary Materials.

Conflicts of Interest

The authors declare the following financial interests/personal relationships that could be considered potential competing interests: Marco Ghio reports a relationship with Germina s.r.l., including employment.

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Horticulturae 11 00343 g001
Figure 1. (A) The ebb-and-flow cultivation system employed within AlmaVfarm, an experimental vertical farm at the Department of Agricultural and Food Science at the University of Bologna, Italy. (B) Completely randomized allocation of treatments for each crop (L = lettuce, B = basil), with low-density (LD: 123 plants m2), medium-density (MD: 237 plants m2), and high-density (HD: 680 plants m2) treatments. Different colored growing spaces (sectors) in the scheme distinguish between treatments for each crop (white, LD; grey, MD; black, HD), with red-highlighted sectors representing areas not used in this study.
Figure 1. (A) The ebb-and-flow cultivation system employed within AlmaVfarm, an experimental vertical farm at the Department of Agricultural and Food Science at the University of Bologna, Italy. (B) Completely randomized allocation of treatments for each crop (L = lettuce, B = basil), with low-density (LD: 123 plants m2), medium-density (MD: 237 plants m2), and high-density (HD: 680 plants m2) treatments. Different colored growing spaces (sectors) in the scheme distinguish between treatments for each crop (white, LD; grey, MD; black, HD), with red-highlighted sectors representing areas not used in this study.
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Horticulturae 11 00343 g002
Figure 2. Effect of different planting densities (LD: 123 plant m−2; MD: 237 plant m−2; HD: 680 plant m−2) on fresh yield (kg FW m−2), dry matter content (%), leaf area index (LAI, m2 m−2), and chlorophyll content (SPAD unit) of lettuce (A–D) and basil (E–H) plants at different times (15, 22, and 29 days after sowing, DAS) along the growing cycle. Data represent mean ± standard error (n = 15). Different letters on the same sampling date indicate significant differences between planting densities at p ≤ 0.05.
Figure 2. Effect of different planting densities (LD: 123 plant m−2; MD: 237 plant m−2; HD: 680 plant m−2) on fresh yield (kg FW m−2), dry matter content (%), leaf area index (LAI, m2 m−2), and chlorophyll content (SPAD unit) of lettuce (A–D) and basil (E–H) plants at different times (15, 22, and 29 days after sowing, DAS) along the growing cycle. Data represent mean ± standard error (n = 15). Different letters on the same sampling date indicate significant differences between planting densities at p ≤ 0.05.
Horticulturae 11 00343 g002
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Figure 3. Effect of different planting densities (LD: 123 plant m−2; MD: 237 plant m−2; HD: 680 plant m−2) on relative growth rate (RGR, g g−1 d−1) of lettuce (A) and basil (B) plants at 22 and 29 days after sowing. Data represent mean ± standard error (n = 15). Different letters on the same sampling date indicate significant differences between planting densities at p ≤ 0.05.
Figure 3. Effect of different planting densities (LD: 123 plant m−2; MD: 237 plant m−2; HD: 680 plant m−2) on relative growth rate (RGR, g g−1 d−1) of lettuce (A) and basil (B) plants at 22 and 29 days after sowing. Data represent mean ± standard error (n = 15). Different letters on the same sampling date indicate significant differences between planting densities at p ≤ 0.05.
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Figure 4. Effect of different planting densities (LD: 123 plant m−2; MD: 237 plant m−2; HD: 680 plant m−2) on light use efficiency (LUE, g DW mol−1) and light energy use efficiency (L-EUE, g FW kWh−1) of lettuce (A,B) and basil (C,D) plants at 15, 22 and 29 days after sowing. Data represent mean ± standard error (n = 15). Different letters on the same sampling date indicate significant differences between planting densities at p ≤ 0.05.
Figure 4. Effect of different planting densities (LD: 123 plant m−2; MD: 237 plant m−2; HD: 680 plant m−2) on light use efficiency (LUE, g DW mol−1) and light energy use efficiency (L-EUE, g FW kWh−1) of lettuce (A,B) and basil (C,D) plants at 15, 22 and 29 days after sowing. Data represent mean ± standard error (n = 15). Different letters on the same sampling date indicate significant differences between planting densities at p ≤ 0.05.
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Table 1. Effect of different planting densities (LD: 123 plants m−2, MD: 237 plants m−2, HD: 680 plants m−2) on morphological and physiological parameters of indoor-grown lettuce and basil at different harvest stages (15, 22, and 29 days after sowing, DAS). Each value represents the mean of 15 replicate plants. Different letters indicate significant differences at p ≤ 0.05.
Table 1. Effect of different planting densities (LD: 123 plants m−2, MD: 237 plants m−2, HD: 680 plants m−2) on morphological and physiological parameters of indoor-grown lettuce and basil at different harvest stages (15, 22, and 29 days after sowing, DAS). Each value represents the mean of 15 replicate plants. Different letters indicate significant differences at p ≤ 0.05.
Growth Cycle
(DAS)		Planting DensityFresh Weight
(g FW plant−1)		Dry Weight
(g DW plant−1)		Plant Height
(cm)		Stomatal Conductance
(mmol m−2 s−1)
Lettuce
15LDa 0.84a 0.05a 5.36a 231
MDa 0.72b 0.04b 4.77a 267
HDb 0.41c 0.02c 4.23a 256
22LDa 8.01a 0.42a 8.68a 245
MDb 6.30b 0.29b 8.05a 249
HDc 3.88c 0.15a 8.69a 223
29LDa 24.3a 1.12b 11.6b 206
MDb 17.7b 0.73b 11.5ab 221
HDc 13.6c 0.54a 14.8a 257
Basil
15LDa 0.36a 0.04a 5.47-
MDa 0.38a 0.04a 5.20-
HDb 0.25b 0.02b 4.20-
22LDa 2.09a 0.21a 10.6a 161
MDa 2.30a 0.21a 9.80a 145
HDb 1.28b 0.11b 8.07a 163
29LDa 6.62a 1.23a 18.6a 299
MDa 6.89ab 0.73a 17.6a 284
HDb 4.93b 0.54a 17.8b 246
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MDPI and ACS Style

Jadhav, V.; Grondona, T.; Pistillo, A.; Pennisi, G.; Ghio, M.; Gianquinto, G.; Orsini, F. Optimizing Planting Density for Increased Resource Use Efficiency in Baby-Leaf Production of Lettuce (Lactuca sativa L.) and Basil (Ocimum basilicum L.) in Vertical Farms. Horticulturae 2025, 11, 343. https://doi.org/10.3390/horticulturae11040343

AMA Style

Jadhav V, Grondona T, Pistillo A, Pennisi G, Ghio M, Gianquinto G, Orsini F. Optimizing Planting Density for Increased Resource Use Efficiency in Baby-Leaf Production of Lettuce (Lactuca sativa L.) and Basil (Ocimum basilicum L.) in Vertical Farms. Horticulturae. 2025; 11(4):343. https://doi.org/10.3390/horticulturae11040343

Chicago/Turabian Style

Jadhav, Vivek, Tiziano Grondona, Alessandro Pistillo, Giuseppina Pennisi, Marco Ghio, Giorgio Gianquinto, and Francesco Orsini. 2025. "Optimizing Planting Density for Increased Resource Use Efficiency in Baby-Leaf Production of Lettuce (Lactuca sativa L.) and Basil (Ocimum basilicum L.) in Vertical Farms" Horticulturae 11, no. 4: 343. https://doi.org/10.3390/horticulturae11040343

APA Style

Jadhav, V., Grondona, T., Pistillo, A., Pennisi, G., Ghio, M., Gianquinto, G., & Orsini, F. (2025). Optimizing Planting Density for Increased Resource Use Efficiency in Baby-Leaf Production of Lettuce (Lactuca sativa L.) and Basil (Ocimum basilicum L.) in Vertical Farms. Horticulturae, 11(4), 343. https://doi.org/10.3390/horticulturae11040343

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