Design and Implementation of a Small-Scale Hydroponic Chamber for Sustainable Vegetative Propagation from Cuttings: A Basil (Ocimum basilicum L.)

Abstract

Urban agriculture in space-constrained cities requires compact, reproducible propagation systems. Therefore, the aim of this Technical Note is to design, implement, and functionally validate a low-cost, modular hydroponic chamber (SSHG) for early-stage vegetative propagation. This system couples DHT11-based temperature/RH monitoring with rule-based actuation—irrigation 4×/day and temperature-triggered ventilation—under the control of an Arduino Uno microcontroller; LED lighting was not controlled nor analyzed. Two 15-day trials with basil (Ocimum basilicum L.) yielded rooting rates of 61.7% (37/60) and 43.3% (26/60) under a deliberate minimal-input configuration without nutrient solutions or rooting hormones. Environmental summaries and spatial survival maps revealed edge-effect patterns and RH variability that inform irrigation layout improvements. The chamber, bill of materials, and protocol are documented to support replication and iteration. Thus, the SSHG provides a transferable baseline for educators and researchers to audit, reproduce, and improve small-footprint, controlled-environment propagation. Beyond its technical feasibility, the SSHG contributes to sustainability by leveraging low-cost, readily available components, enabling decentralized seedling production in space-constrained settings, and operating under a minimal-input configuration. In line with widely reported hydroponic efficiencies (e.g., lower water use relative to soil-based propagation), this open and replicable platform aligns with SDGs 2, 11, 12, and 13.

1. Introduction

By 2050, about two thirds of the global population will live in cities [1,2,3], posing major challenges to food security and the sustainability of agricultural systems [4]. Ongoing urbanization is projected to expand urban land and further reduce agrarian areas [2,5], implying that the agri-food sector must increase production capacity by at least 70% to meet global demand [1,2,6,7]. This urban expansion, coupled with severe space constraints for production, underscores the need for compact, reproducible propagation systems in constrained settings. In dense urban contexts, limited footprint and the scarcity/cost of compact propagation facilities remain recurring barriers to local seedling production. While controlled-environment agriculture can mitigate siting constraints, adoption is often limited by capital intensity and energy costs—underscoring the value of low-cost, modular, and reproducible propagation chambers for space-limited settings [8]. In this context, urban agriculture (UA) has emerged as a mitigation strategy that contributes to food supply, promotes healthier diets, reduces transportation costs, and strengthens local food systems, resilience, and sustainable food security in cities [7,9,10]. The re-evaluation of traditional farming has led to alternative approaches [8,11,12], with studies reporting productivity gains exceeding 100% in urban systems compared with conventional methods [1]. Among these approaches, hydroponics stands out as a versatile and efficient technique, increasingly enabled by irrigation automation and environmental control, and suitable for small productive units [6,12,13,14,15,16,17]. The availability of low-cost sensors and microcontrollers has further democratized its deployment and facilitated replication across small-scale settings [12,15,18].

However, many developments focus on seed-based cultivation, leaving a technical gap in solutions tailored to vegetative propagation by cuttings, where crop loss is common. Although more demanding in environmental terms, this reproductive modality enables cloning of desirable genotypes, shortens production cycles, and improves phenotypic uniformity [19,20,21]. Its implementation requires stable environmental conditions, continuous monitoring of temperature and relative humidity, and precise irrigation.

In previous work, we developed a low-cost automated chamber to maintain mother plants in a permanent vegetative state as a reliable source of cuttings [22]. Building on that research, this study introduces a complementary system for the rooting of those cuttings: the Small-Scale Hydroponic Growth Chamber (SSHG). This chamber provides a controlled environment to develop seedlings from cuttings under a deliberate minimal-input configuration (no nutrient solutions or rooting hormones). It integrates low-cost electronics (temperature and humidity sensors) controlled by an Arduino Uno, automated irrigation, forced ventilation, and LED lighting—the latter not controlled nor functionally analyzed during testing. The structure uses standard, accessible materials suitable for implementation in educational, citizen, or applied research contexts, and includes internal cameras for visual monitoring and qualitative evaluation.

Although multiple domestic hydroponic systems exist, few of these systems specifically target the vegetative rooting stage. For instance, the system reported in [15] is adequate for seed germination; a patented apparatus such as Daas [23] optimizes plant conditions via mechanical motion; other approaches emphasize general environmental monitoring in smart greenhouses [24] or focus on proprietary household growing systems [25]. These solutions typically involve trade-offs in cost or complexity, proprietary architectures, or the lack of integrated automation and environmental monitoring, which limits replication in small laboratories and classrooms. In contrast, our work pursues a low-cost, modular, and open-source solution explicitly aimed at the vegetative propagation from cuttings, delivering precise environmental control within a static, enclosed chamber. Together, these cost/complexity and proprietary-architecture constraints—often coupled with limited documentation—hamper replication in small labs and classrooms; the present Technical Note is designed to mitigate precisely those barriers.

This proposal aligns with several Sustainable Development Goals (SDGs): SDG 2 (Zero Hunger), by strengthening food security in urban and rural environments; SDG 11 (Sustainable Cities and Communities), by integrating food production into urban fabrics; SDG 12 (Responsible Consumption and Production), by improving resource efficiency and shortening supply chains; and SDG 13 (Climate Action), by reducing transport-related carbon footprints [4,26,27,28].

Hydroponic systems are frequently highlighted for their sustainability potential—most notably reduced water consumption through recirculation and lower evaporative losses compared with soil-based methods—while open-source, low-cost designs improve social accessibility in educational, community, and small-lab contexts. Within this lens, the SSHG targets the early, resource-sensitive stage of vegetative propagation, providing an affordable, replicable chamber that supports local, small-footprint production under controlled conditions [29].

This Technical Note addresses the under-documented early-stage, small-scale vegetative propagation in compact chambers by combining (i) a low-cost, modular architecture; (ii) environmental monitoring with rule-based actuation for irrigation/ventilation; (iii) spatial survival mapping to reveal uniformity gaps; and (iv) a replicable bill of materials and protocol. Rather than claiming horticultural optimization, we contribute a transferable baseline that can be reproduced, audited, and iteratively improved by educators, designers, and researchers under minimal-input conditions. As such, this Technical Note offers a cohesive, ready-to-replicate package—design, control thresholds, and evaluation workflow—rarely reported as an integrated whole for cuttings-based propagation in controlled environments.

Therefore, the aim of this study is to design, construct, and functionally validate a modular, automated hydroponic chamber for vegetative propagation from cuttings under a minimal-input configuration, using basil (Ocimum basilicum) as a model plant.

2. Materials and Methods

2.1. Structural Design and Construction of the SSHG

The Small Scale Hydroponic Growth Chamber (SSHG) was designed and built at the Laboratory of Inventions Applied to Industry of the Autonomous University of Zacatecas (liai@uaz.edu.mx). Its main objective is to facilitate plant propagation from cuttings using an automated, low-cost, resource-efficient, and easily replicable system.

Aluminum profiles formed the main structure, creating a rectangular frame that was 6 mm thick, and semi-translucent polycarbonate plates then covered the frame laterally. A 6 mm transparent glass panel forms the ceiling, and three 121 cm long, 30 W LED lamps were placed on it, spaced 9 cm apart and positioned 2 cm above the glass, supported by arches of aluminum profiles. The vertical distance from the lamps to the culture trays is 32 cm. The overall dimensions of the chamber are 130 cm in length, 44 cm in width, and 72 cm in height. Figure 1 shows the technical drawings of the prototype, with its key structural dimensions.

Two plastic containers with lids are placed on top of the structure, which serve as propagation trays. The lids were perforated to directly accommodate 30 hydroponic baskets in each container, allowing for a total of 60 cuttings per experimental cycle. In the lower part of the chamber, a 20-L water tank supplies the irrigation system via a high-pressure diaphragm pump (72 W, 12 V). The sprinkler irrigation system consists of 16 sprinklers, which are evenly distributed (eight per container). We arranged these sprinklers in this manner to ensure homogeneous coverage in both trays. Figure 2 illustrates the spatial distribution of sprinklers within the chamber.

The chamber incorporates four main subsystems: (i) an artificial lighting system composed of three 30 W LED lamps; whose structural presence ensured adequate internal visibility during the trials but was neither automated nor included in the functional evaluation; LED lighting was installed for illumination but was neither controlled nor logged; and photometric data were therefore excluded from analysis; (ii) a ventilation module with two 4 × 4 cm DC fans (model VN4-012P, 12 V), located on opposite doors, responsible for regulating airflow based on internal temperature; (iii) an image capture system using two SmartCam C960 4K cameras (EMEET, Hong Kong, China), mounted at the top of each door to document the morphological development of the cuttings; and (iv) an automated control system, based on an Arduino Uno microcontroller linked to a central processing unit (CPU), which governs the operation of actuators and records environmental data through temperature and humidity sensors. The Arduino Uno microcontroller was selected due to its low cost, open-source architecture, and ease of integration, allowing full customization and straightforward replication in similar applications.

The interrelationship between these components is illustrated schematically in Figure 3, which depicts the inner workings of the SSHG system, including the connections between subsystems and the flow of energy, water, and data.

Figure 4 presents a rendered CAD model of the SSHG system, which enables a three-dimensional visualization of the physical layout of the main structural and electronic elements, including the frame, containers, irrigation system, LED lamps, fans, monitoring cameras, and the control module. This representation facilitates an understanding of the system’s functional integration and can serve as a basis for technical documentation or replication in other contexts.

The system enables the replication of controlled microclimate conditions that are favorable for rooting of cuttings in various urban, rural, educational, or experimental environments due to its modular design and use of affordable materials. This flexibility, coupled with its low-cost automation system, makes it a sustainable, scalable, and appropriate solution for accessible innovation initiatives, applied research, or small-scale plant production.

In order to facilitate technical replication and provide a clear reference for future implementations,

Table 1. Bill of materials (BoM) for the SSHG system construction.

Component	Specification	Manufacturer/Model (Location)	Estimated Cost (USD)
Structural frame	Aluminum profiles (6 mm thick)	Generic/OEM	78.00
Covering panels	Polycarbonate (lateral), glass (top)	Generic/OEM	42.00
Irrigation system	16 sprinklers, diaphragm pump 72 W (12 V)	Generic/OEM	23.00
Lighting system	3 x LED lamps (30 W each)		25.00
Ventilation	2 × DC fans, 4 × 4 cm, 12 V, 2.4 W each	Generic/OEM (VN4-012P)	9.00
Control and sensors	Arduino Uno Microcontroller, DHT11 temp/RH, relay module	Lionchip (Arduino Uno); ASAIR (DHT11); Generic/OEM (Nuevo Leon, Mexico)	12.00
Image capture	USB webcams (2 unit)	EMEET SmartCam C960 (Hong Kong, China)	62.00 1
Hydroponic pots + lids	Net pots Ø 5 cm	Generic/OEM (pots); In-house 3D-printed lids	18.00
Rockwool	Commercial rooting substrate cubes	Owens Corning (Ohio, United States of America)	10.00
Total Estimated Cost			279.00 2

¹ The image capture module (two cameras) was included for demonstrative and monitoring purposes and is not essential for the core propagation function. It may be omitted or replaced in simplified or commercial implementations without affecting the propagation functionality. ² Cost estimates reflect materials acquired locally in Zacatecas, Mexico (2024). USD values were converted from MXN; prices may vary by region, exchange rates, and availability. Note: For Generic/OEM rows, functionally equivalent components meeting the listed specifications are acceptable for replication.

presents a summarized bill of materials (BoM) for the construction of the SSHG system. This includes the main structural, hydraulic, electronic, and control components used in the prototype, along with their specifications and estimated costs in USD. These values are based on local retail prices in Mexico and may vary slightly depending on regional availability.

2.2. Vegetative Propagation Protocol and Control Parameters

The SSHG system was designed to facilitate the asexual propagation using herbaceous cuttings in a controlled hydroponic environment. We used basil (Ocimum basilicum) —a fast-growing, soilless-adaptable species with broad environmental tolerance—selected for its natural robustness, gastronomic value, and medical properties [30,31,32]. This choice enabled the evaluation of the system’s functionality under controlled conditions.

Cutting preparation and morphology: Healthy mother plants were pre-selected based on their vigor and uniformity. Cutting tools were disinfected with 70% ethanol for 30 s and air-dried prior to use. Branches were carefully cleaned, briefly rubbing the cutting with a cotton ball soaked in sterile distilled water and 70% ethanol before cutting, to eliminate pollution and pests. Each cutting consisted of a single stem section cut at 45° (Figure 5a). Cutting length ranged 7–15 cm, the node was intentionally removed to standardize the sample, the apical meristem was retained, and a leaf-trimming policy (e.g., of two leaves halved) was used to reduce transpiration, following common hydroponic propagation practices [33,34]. No rooting hormone was applied.

Rooting criterion: A cutting was classified as “rooted” when visible adventitious roots ≥ 2 mm were present and the stem showed stable anchorage to the rockwool cube under gentle traction.

Rockwool and pot assembly: Rockwool—an inorganic medium with high water-holding capacity and aeration [35]—was pre-moistened with tap water, and each cutting was inserted into a hydroponic net pot (Ø 5 cm). Each pot was covered with a 3D-printed radial-pattern lid to reduce evaporation and standardize exposure around the stem base, which also enabled the top-view visual monitoring of foliar development (Figure 5b–d). This configuration stabilized the micro-environment around the stem base and supported rooting.

Spatial layout: Cuttings were arranged inside plastic containers in a 5-row × 6-column matrix (two trays), with ~2.5 cm spacing between rows and 5 cm between columns. Each position was numbered to enable individual tracking during the trials and to analyze edge effects and spatial variability in rooting (Figure 6).

Automated control: An Arduino Uno- controlled irrigation and ventilation (Arduino IDE) were utilized. Although the chamber included LED lighting, it was neither controlled nor logged; photometric data were therefore excluded from analysis.

Table 2. Activation logic and operational schedule for the two automated subsystems of the SSHG (irrigation and ventilation). Timers and environmental thresholds were implemented through an Arduino Uno microcontroller.

Subsystem	Activation Logic	Schedule or Condition
Irrigation	Timer-controlled	Four 4 times per day: 00:00–00:15 06:00–06:10 12:00–12:15 18:00–18:15
Ventilation	Temperature-controlled (conditional)	Fan 1 (inlet): activates if T ≤ 26 °C Fan 2 (exhaust): activates if T $>$ 26 °C

details only the irrigation and ventilation subsystems. Irrigation was activated four times daily (00:00, 06:00, 12:00, 18:00 h), with 10–15 min per event. Ventilation was temperature-conditioned: the inlet fan (Fan 1) activated when T ≤ 26 °C, and the exhaust fan (Fan 2) activated when T > 26 °C, using a small hysteresis to pre-vent rapid on/off cycling.

Environmental monitoring: A DHT11 digital sensor (temperature, relative humidity) inside the chamber provided continuous monitoring. Data were sampled every 60 s and logged every 5 min; records outside the sensor’s specifications were discarded.

Table 3. Technical specifications of the DHT11 sensor.

Characteristic	Range	Accuracy
Temperature	0–50 °C	±2 °C
Humidity	20–90% RH	±5% RH

summarizes the DHT11 operating range and accuracy. These measurements supported the assessment of microclimate stability during the 15-day trials and its relation to rooting outcomes.

Experimental trials: Two independent 15-day trials were conducted: 1–15 October 2024, and 1–15 November 2024.

A complementary adaptability test with poinsettia cuttings is reported in Appendix A; it was not part of the main basil protocol or statistics.

3. Results

3.1. Enviromental Control and Monitoring

Throughout both propagation tests, temperature and relative humidity (RH) were continuously monitored to assess the chamber’s ability to maintain a stable internal microclimate. The automated subsystems operated as specified in Table 2: irrigation was activated four times per day (00:00, 06:00, 12:00, 18:00) for 10–15 min per event, and ventilation was conditionally triggered by temperature thresholds. Although the chamber included LED lighting, it was not controlled nor functionally analyzed; therefore, no lighting data are reported. Unless otherwise stated, environmental values are reported as mean ± SD (minimum, maximum). Per the programmed schedule in Table 2 (55 min/day), the total irrigation ON-time amounted to 825 min (13.75 h) per 15-day cycle, executed as scheduled across both trials.

As summarized in

Table 4. Summary of environmental conditions recorded inside the chamber during Test 1.

Parameter	Minimum	Maximum	Average	SD (±)
Temperature (°C)	23.0	28.0	24.47	2.76
Relative Humidity (%)	47	73	59.19	13.00

, during Test 1, the average temperature was 24.47 ± 2.76 °C (min 23.0 °C, max 28.0 °C) and the average RH was 59.19 ± 13.00% (min 47%, max 73%), and these values were consistent with the conditions commonly used for Ocimum basilicum rooting. As shown in

Table 5. Summary of environmental conditions recorded inside the chamber during Test 2.

Parameter	Minimum	Maximum	Average	SD (±)
Temperature (°C)	23.0	29.0	24.76	3.00
Relative Humidity (%)	33	98	47.71	32.50

Table notes: Average = mean; SD = standard deviation; minimum/maximum are sample extremes within each 15-day trial.

, during Test 2, the average temperature was 24.76 ± 3.00 °C (min 23.0 °C, max 29.0 °C), while RH exhibited greater variability, with an average of 47.71 ± 32.50% (min 33%, max 98%). This higher RH variability may have contributed to the lower rooting performance observed in Test 2; given this Technical Note’s scope, we refrain from causal claims beyond these descriptive trends.

For transparency beyond summary statistics, Figure 7 and Figure 8 depict the day-by-day profiles for each 15-day cycle. In Figure 7 (temperature) and Figure 8 (relative humidity), the solid lines show two-sided exponential weighted moving averages (EWMAs; span = 3) to attenuate noise while preserving the day-to-day trend. Semi-transparent circular markers represent the daily means computed from all readings of each calendar day. Test 1 is shown in orange and Test 2 in green, with markers matching their corresponding smoothed line. The x-axis is day 1–15; the y-axis is expressed in °C for Figure 7 and % RH for Figure 8. Considering the DHT11 accuracy (±2 °C; ±5% RH; Table 3), short-term deviations within these bounds should be interpreted within the sensor’s uncertainty; lighting variables are omitted due to the lack of photometric control.

3.2. Vegetative Propagation Outcomes and Survival Distribution

Two independent 15-day trials were conducted to assess the rooting and survival of basil (Ocimum basilicum) cuttings. As defined in Section 2.2, a cutting was classified as rooted when visible adventitious roots of ≥2 mm were present and the stem showed stable anchorage to the rockwool cube. In both trials, no chemical rooting agents, hormone regulators, or nutrient solutions were used; this minimal-resource configuration aligns with the Technical Note scope and is further clarified in the Discussion (Scope/Limitations). A system schematic and a CAD overview are provided in Methods (Figure 3 and Figure 4) to support reproducibility of the hardware layout.

As described in Section 2.2, cuttings were distributed across two trays (5 × 6 each; n = 60 cuttings per cycle) with position numbering to enable spatial tracking. This layout allowed the analysis of putative edge effects.

Test 1: Figure 9 shows the spatial survival map at day 15: 37 cuttings rooted (blue squares) and 23 failed (orange circles), for a rooting rate of 61.7%. Figure 10 provides internal camera views (days 5 and 15) from two angles, documenting qualitative progression and overall plant health under controlled conditions.

Test 2: Conditions were replicated from Test 1 (same spatial distribution and control parameters). Figure 11 shows the spatial survival map at day 15: 26 rooted and 34 failed, for a rooting rate of 43.3%. Figure 10 complements sensor-based monitoring with qualitative views (days 5 and 15). The internal view of the chamber is visible in Figure 12, where it is possible to appreciate the evolution of the cuttings in the second test.

A more detailed inspection in Figure 13, indicates that several of the cuttings in both trials were located near container walls, where the sprinkler positions relative to net pots and failed seedlings; dashed pink boxes mark regions of suspected irrigation deficiency, consistent with an edge-effect hypothesis.

To illustrate individual trajectories, Figure 14 (Test 1, cutting #59) shows successful rooting with pale leaf coloration suggestive of mild chlorosis [36], potentially related to nutrient limitation [37]; Figure 15 (Test 2, cutting #49) shows vigorous leaf expansion by day 15. These cases complement the quantitative outcomes, underscoring the value of visual monitoring alongside environmental data

Quantitatively (

Table 6. Summary of propagation outcomes during both experimental tests.

Test	Cuttings Planted (P)	Rooted Seedlings (R)	Success Rate (%) (R/P × 100)	95% CI (Wilson)
Test 1	60	37	61.7%	49.0–72.9
Test 2	60	26	43.3%	31.6–55.9

Notes: Success defined per Section 2.2 (roots ≥ 2 mm + anchorage). Confidence intervals computed with the Wilson method. Percentages are rounded to one decimal place.

), Test 1 achieved 61.7% rooting (37/60; 95% CI: 49.0–72.9%) and Test 2 43.3% (26/60; 95% CI: 31.6–55.9%). Across the two cycles, the mean rooting percentage was 52.5%, with a standard deviation of 13.0%. Given this Technical Note’s scope, we report these descriptive statistics and interpret negative outcomes as design diagnostics to inform irrigation coverage and environmental stability for subsequent iterations.

Beyond basil, a complementary 15-day test with poinsettia (Euphorbia pulcherrima) achieved a rooting rate of 70.0% (42/60; 95% CI: 57.5–80.1%) under the same minimal-input configuration (Appendix A). These data are illustrative and were not included in Table 6.

4. Discussion

The two 15-day trials demonstrate the feasibility of using a sensor-based hydroponic chamber (SSHG) for basil vegetative propagation under controlled conditions. Rooting performance was 61.7% in Test 1 and 43.3% in Test 2 (Table 6), indicating functional feasibility while also revealing opportunities for system optimization.

Environmental summaries (Table 4 and Table 5) show similar average temperature in both trials, whereas RH variability was markedly higher in Test 2. Although this study was not designed for causal inference, the greater RH dispersion in Test 2 is consistent with the lower rooting percentage observed in that cycle. RH is a critical variable for cuttings (transpiration, turgor, adventitious root formation); hence, stability is a practical target for iteration in compact chambers. Given the DHT11 accuracy (±2 °C; ±5% RH, Table 3), short-term fluctuations within these bounds are interpreted within sensor uncertainty, and we focus on consistent trends across cycles.

The survival maps (Figure 9 and Figure 11) suggest edge-effect patterns, with recurrent failures near container walls where sprinkler reach may be reduced. The top view (Figure 13) shows sprinklers arranged in parallel lines, which may limit peripheral coverage. These “negative” outcomes are treated as design diagnostics, motivating a redesign of the hydraulic layout (e.g., higher-angle micro-sprinklers, flow/pressure balance at line ends) to achieve more uniform droplet distribution.

No pump or fan failures were logged during the trials. The pronounced RH dispersion observed in Test 2 may reflect reduced extraction efficiency or localized condensation rather than a systemic malfunction; future iterations will regulate fan RPM and/or upgrade sensing to disambiguate these effects.

Both trials remained within an acceptable temperature range (23–29 °C, Table 4 and Table 5). In Test 2, the combination of slightly higher peaks and lower RH could have contributed to a more stressful environment. Figure 14 (cutting #59) shows mild chlorosis—potentially from nutrient limitation or uneven illumination—yet with successful rooting, suggesting individual resilience. Figure 15 (cutting #49, Test 2) shows vigorous leaf expansion by day 15.

The absence of nutrient salts and rooting hormones was a deliberate, minimal-resource design constraint to validate chamber functionality over a short, 15-day window. We do not claim sustained growth without supplementation; rather, we isolated mechanical/environmental performance (irrigation uniformity, ventilation response) before considering agronomic optimizations. Future iterations will test nutrient regimens and photoperiod control to optimize rooting and early growth.

We provide the bill of materials, wiring schematic, Arduino sketch (control thresholds/timers), and CAD files of the chamber to enable independent replication and auditing (see Data Availability Statement). These materials mirror the configuration reported here and can be adapted to local component availability.

Sustainability implications of the SSHG. From a sustainability standpoint, the SSHG underscores three practical contributions: (i) resource efficiency, insofar as hydroponic approaches commonly achieve lower water use than soil-based propagation due to recirculation and reduced evaporative losses; (ii) economic accessibility, as documented by the bill-of-materials (Table 1; ~USD 279) and the use of off-the-shelf, locally available components; and (iii) decentralization and resilience, by enabling compact, in situ seedling propagation that can shorten supply chains and reduce transport dependence in urban and peri-urban contexts. In this Technical Note we do not meter energy consumption; future iterations will instrument the chamber to report per-cycle energy (kWh), enabling a fuller sustainability accounting.

To position the SSHG relative to recent research,

Table 7. Comparative overview of selected studies on vegetative propagation using hydroponic systems, highlighting methodological differences and rooting outcomes.

Feature	SSHG (This Study)	Zhao et al. (2021) [33]	Mejía-Londoño et al. (2023) [38]	Caplan et al. (2018) [39]
Target species	Ocimum basilicum (Basil)	Medicago sativa (Alfalfa)	Cannabis sativa (Cannabis)	Cannabis sativa (Cannabis)
Type of propagation	Asexual (cuttings)	Asexual (cuttings)	Asexual (cuttings)	Asexual (cuttings)
Substrate	Rockwool	NR	Peat	NR
Nutrient solution/rooting aids	None (tap water only)	Yes (specific solution)	No regulators, peat (salts NR)	Fertilizers used
Automation	Yes (irrigation, ventilation)	No	No	No
Environmental monitoring	Yes (temperature, RH)	No	No	Yes (temperature control)
Lighting control	Not controlled/analyzed	NR	NR	NR
Image capture	Yes (2 internal cameras, qualitative)	No	No	No
Replication (n, cycles)	n = 60, 2 × 15-day cycles	NR	No	NR
Rooting criterion	Roots ≥ 2 mm + anchorage	NR	NR	NR
Rooting rate (%)	61.7% (95% CI: 49.0–72.9); 43.3% (95% CI: 31.6–55.9)	$>93\%$ (with solution)	73.33% (no regulators; peat)	84% (with fertilizers)
Estimated cost	Low (accessible, local materials, see BoM)	Medium	Medium	Medium
Scope/applicability	Functional validation (minimal inputs); educational and research; replicable	Germplasm conservation	Cannabis research	Cannabis research

Rates are not directly comparable due to differences in species, substrates, inputs, and study scope (optimization vs. functional validation). NR = not reported. Low/medium cost tiers refer to relative bill of materials; for this study, see the BoM (Table 1).

summarizes representative studies differing in species, nutrient use, and automation/monitoring. For example, Zhao et al. [33] achieved >93% rooting in alfalfa using specific nutrient solutions (without integrated monitoring/automation), while Mejía-Londoño et al. [38] reported 73.33% survival in cannabis without growth regulators (peat substrate). Caplan et al. [39] explored biological drivers of rooting but did not delve into the environmental control of the growth environment. In contrast, the SSHG integrates sensors and actuators (Arduino-based), rule-based actuation for irrigation/ventilation, spatial survival mapping, and visual capture, delivering a replicable package suitable for academic and experimental contexts. Although the rooting rates here (61.7% and 43.3%) are lower than those in optimized systems, the comparison is not direct because our scope is functional validation under minimal inputs, deliberately without rooting aids or nutrient solutions. Accordingly, Table 7 is intended as a qualitative context rather than a direct performance benchmark, given the differences in species, substrates, and inputs across studies.

Hydroponic approaches can substantially reduce water consumption relative to soil cultivation due to recirculation and lower evaporation losses [1], and LED lighting can improve energy efficiency compared with legacy technologies (e.g., HPS/fluorescent) [14,40]. The SSHG emphasizes local availability of components, low cost, and straightforward replication, making it attractive for educational institutions, community projects, or small laboratories.

The SSHG emphasizes a compact footprint and unattended operation: the timer-based irrigation replaced 60 scheduled manual watering events per 15-day cycle (4×/day), while ventilation was triggered automatically by temperature thresholds. Although time-and-motion and energy consumption were not quantified in this study, the low material cost (see BoM, Table 1) and the minimal-input configuration support its use in educational and small-laboratory contexts.

Although basil was the model species, the SSHG allows adjustments in height, substrate, irrigation distribution, and light intensity to accommodate diverse morphologies. A complementary poinsettia (Euphorbia pulcherrima) test (Appendix A) showed favorable functional behavior under the current configuration, supporting system flexibility. Transferability to other species will likely require parameter tuning (photoperiod, irrigation schedules, substrate).

Limitations and future work: (i) Lighting was not controlled nor functionally analyzed; photometric control will be added in future iterations. (ii) Sensor resolution/accuracy (DHT11) limits detection of fine-scale fluctuations; higher-grade sensing and logging are planned. (iii) The study reports two 15-day cycles (n = 60 each); while adequate for a Technical Note, broader replication would enable stronger generalization. (iv) The no-nutrient constraint was specific to feasibility testing; subsequent studies will incorporate nutrient solutions and/or rooting aids and evaluate species transferability beyond Ocimum basilicum. We therefore refrain from generalizing beyond basil. Appendix A provides an illustrative poinsettia case, and future studies will evaluate species-specific parameterization.

5. Conclusions

The experimental results demonstrate the technical feasibility of the proposed system for early-stage vegetative propagation under controlled conditions. Across two 15-day cycles with Ocimum basilicum, rooting success reached 61.7% (Test 1) and 43.3% (Test 2) without the use of nutrient solutions, hormone regulators, or commercial rooting agents. Integrated environmental monitoring and spatial survival mapping helped identify factors that constrain performance—notably relative humidity variability (higher in Test 2) and an edge effect attributable to non-uniform irrigation coverage—thus providing actionable design diagnostics for the next iteration.

This study shows that the low-cost, modular, open-source SSHG can facilitate root development in cuttings and offers a replicable baseline for educators and researchers. Achieving 61.7% rooting in basil within 15 days under minimal inputs underscores the practicality of the platform for the functional validation of the chamber’s design. The architecture based on accessible components (e.g., Arduino) and the documented workflow (bill of materials, rule-based actuation, environmental logging, and spatial mapping) support replication and scalability in diverse research and community settings. We provide the bill of materials, wiring schematic, Arduino sketch (control thresholds/timers), and CAD files of the chamber to support independent replication and auditing (see Data Availability Statement).

From a sustainability and cost perspective, the system uses readily available materials and has a low material cost (see BoM, Table 1) while leveraging inherently efficient components. Although energy consumption was not quantified in this study, future work will characterize operational costs and environmental impact in detail. In practical terms, the timer-based irrigation schedule replaces approximately 60 manual watering events per 15-day cycle (4×/day), reducing routine labor; energy consumption will be quantified in future work.

Several technical improvements are planned. Priorities include redesigning the hydraulic circuit (e.g., higher-angle micro-sprinklers and/or flow balance at line ends) to improve irrigation uniformity and reduce edge effects; adding drainage to avoid residual water accumulation; optimizing structural support and access (load-bearing walls with service gates); and integrating a lighting control module to program adjustable photoperiods and log photometric parameters with specific sensors. These upgrades will enhance efficiency, reinforce environmental monitoring capabilities, and broaden applicability—while preserving simplicity and low cost.

Beyond its experimental function, the SSHG has high potential to strengthen urban production schemes—rooftops, patios, compact greenhouses, and community spaces—and is well suited for educational and applied research contexts. While the form factor and control parameters are adaptable for cuttings-based propagation, transferability beyond Ocimum basilicum will require species-specific parameterization. Appendix A provides an illustrative poinsettia case.

A complementary adaptability test with poinsettia (Euphorbia pulcherrima), reported in Appendix A, corroborated the system’s versatility under the same minimal-input configuration, achieving a positive rooting outcome and reinforcing the feasibility of adapting the chamber to species with different physiological sensitivities.

In addition to its technical validation, the SSHG represents a sustainable alternative for compact propagation: it leverages a low material cost (see BoM, Table 1), replaces routine manual watering with scheduled automation (4 events/day; ~60 events per 15-day cycle), and supports decentralized seedling production in space-limited environments. Although energy use was not measured here, future iterations will quantify per-cycle energy and operating costs to complete the sustainability assessment.