Capsicum annuum L.: Phenological and Yield Performance of Native and Commercial Genotypes Under Open-Field and Low-Technology Greenhouse Hydroponic Systems

1. Introduction

Chili pepper (Capsicum annuum L.) is a crop of global strategic importance, with significant economic, nutritional, and cultural value [1,2]. This species, belonging to the Solanaceae family, exhibits extensive genetic diversity, which confers high phenotypic plasticity and enables adaptation to a wide range of environmental conditions [3]. As a result, its global production exceeds 44 million tons annually, consolidating its role as a key crop in both traditional and intensive production systems [4]. This genetic diversity not only supports its broad geographic distribution but also provides a basis for the selection of genotypes with specific agronomic traits, particularly under varying environmental conditions [5].

Beyond its dietary importance, C. annuum is characterized by a complex biochemical composition that determines its commercial and functional value [6,7,8,9]. From an agronomic perspective, however, the accumulation of these compounds is closely linked to the physiological status of the plant and its response to the growing environment [10]. Therefore, current research focuses on understanding how environmental conditions influence phenotypic expression, particularly in terms of phenology, growth, and yield. In this context, evaluating crop performance under different production systems is essential to optimize crop stability and ensure the expression of genetic potential, as productivity is determined by the interaction between genotype and environment [11].

Under open-field conditions, factors such as climatic variability, temperature fluctuations, water availability, and solar radiation introduce high production uncertainty and limit crop efficiency [12,13,14]. These factors directly affect key physiological processes, including photosynthesis, transpiration, and assimilate partitioning, leading to variation in growth and yield. In particular, high temperatures can reduce photosynthetic efficiency [15], while water deficit limits cell expansion and reproductive development [15,16].

As an alternative, protected agriculture has enabled partial control of the growing environment through the use of greenhouses, thereby improving growing conditions and reducing environmental variability [17]. In these systems, soilless cultivation, including hydroponic systems based on inert substrates, allows more precise management of water and nutrients, promoting the expression of productive potential [18,19]. In addition, these systems can improve resource-use efficiency, reduce the incidence of soil-borne pathogens, and facilitate more uniform crop development [20,21]. However, the performance of protected systems critically depends on environmental control [22]. Under conditions of limited ventilation and high external solar radiation, greenhouses may experience excessive heat accumulation, while plastic covers can reduce the availability of photosynthetically active radiation, jointly inducing abiotic stress [23,24]. In particular, stress derived from these conditions affects key physiological processes such as photosynthesis, cellular integrity, metabolic activity, and pollen viability [25,26], ultimately compromising reproductive development and yield.

In this context, the genotype × environment (G×E) interaction provides a fundamental framework for understanding variability in agronomic performance [27]. This interaction describes the differential response of genotypes under contrasting environmental conditions, which is reflected in changes in key agronomic traits [28]. The magnitude of this interaction depends on both genetic variability and environmental heterogeneity. In particular, phenological stages such as flowering and fruiting are highly sensitive to environmental factors including temperature, radiation, and humidity [29,30], making them useful indicators for identifying adaptation patterns and resource-use strategies among genotypes. These insights are particularly relevant for breeding programs and the conservation of native landraces, as they support the identification of genotypes with enhanced adaptation to specific environmental conditions.

Mexico, as one of the main centers of origin and diversification of C. annuum, harbors extensive genetic diversity represented by native landraces that have been selected under local conditions over generations [31,32]. These materials constitute a valuable genetic resource, particularly in terms of adaptation to variable environments and resilience to abiotic stress [33,34]. However, the adoption of commercial cultivars in intensive systems has contributed to a decline in the use of these native materials [35,36], which may lead to genetic erosion and loss of agricultural diversity, creating a knowledge gap regarding their performance under different production systems.

Under this framework, genotype performance may vary significantly across production systems, reflecting the influence of environmental conditions and management practices on phenological and productive responses. This variability highlights the importance of evaluating genotype behavior under contrasting growing environments to identify adaptation patterns and differences in agronomic performance associated with genotype × environment interaction. Therefore, the objective of this study was to characterize the phenological and productive responses of five C. annuum genotypes (four native landraces and one commercial cultivar) under two contrasting production systems: open-field and a substrate-based hydroponic system under low-technology greenhouse conditions, in order to identify differences in genotype performance across environments. It was hypothesized that contrasting production environments would differentially influence phenological and productive performance, revealing a significant genotype × environment interaction, with the greenhouse system expected to enhance productivity.

2. Materials and Methods

2.1. Experimental Site

The study was conducted in San Agustín Calvario, San Pedro Cholula, Puebla, Mexico, during the 2023 growing season (January–October), under two contrasting production systems: open field (OF) and a substrate-based hydroponic system under low-technology greenhouse conditions (hereafter referred to as the GH) (Figure 1).

Open-field system (OF): The experiment was established in a cooperating farmer’s field located at 19°03′18″ N, 98°20′08″ W, at 2164 m a.s.l. The soil had a pH of 7.30, electrical conductivity (EC) of 0.75 dS·m⁻¹, and organic matter content of 0.74%.

Substrate-based hydroponic system under low-technology greenhouse conditions (GH): The experiment was conducted in a low-technology tunnel-type greenhouse (100 m²), covered with polyethylene (caliber 800; 200 μm) and protected with anti-aphid mesh, located at 19°02′59″ N, 98°20′03″ W, at 2158 m a.s.l. The plastic cover reduced light transmission by approximately 15% and filtered 76% of ultraviolet radiation.

2.2. Plant Material

Five genotypes of C. annuum were evaluated: four native landraces (Diente de Perro, Tía Juanita, Mixteco Largo, and Cola de Ratón) and one commercial cultivar (Serrano Tampico). Taxonomic identity was confirmed by the Botanical Garden of BUAP (herbarium vouchers 88725–88729). Plant morphology is shown in Figure 2.

2.3. Seedling Production

For each genotype, 200 seeds were sown in 200-cavity polystyrene trays filled with commercial substrate (Sunshine^® Mix 3). One seed per cavity was used; no thinning was required. Seedlings were grown under nursery conditions (25 ± 2 °C, 12 h photoperiod) for 80-89 days, and only the most vigorous and uniform seedlings were selected for transplanting. To synchronize plant establishment under each system, sowing dates were adjusted: January 29, 2023 for OF and February 19, 2023 for GH. This offset compensated for differences in early growth rates and ensured uniform vigor at transplanting. Germination percentage was below 100% and is detailed in Section 3.2.1.

2.4. Crop Management

2.4.1. Open-Field System (OF)

Experimental design and transplanting: Transplanting was performed on April 19, 2023 (80 days after sowing, das) under a randomized complete block design (RCBD) with four replicates. Plants were arranged in 6.0 m long rows spaced 0.80 m apart, with 0.50 m between plants, corresponding to a density of 25,000 plants·ha⁻¹. Each experimental unit consisted of one row per genotype within each block (13 plants). The five central plants were evaluated to minimize border effects (20 plants per genotype).

Fertilization: A fertilization rate of 180–100–30 (N–P₂O₅–K₂O) was applied using urea (46% N), diammonium phosphate (DAP; 18% N and 46% P₂O₅), and potassium chloride (60% K₂O). One-third of the nitrogen and all phosphorus and potassium were applied at transplanting; the remaining nitrogen was split at 45 and 90 days after transplanting (dat).

Irrigation: Irrigation followed the farmer’s schedule. Furrow irrigation was initially applied and later replaced by sprinkler irrigation from 50 dat. Soil moisture sensors were not used.

Phytosanitary management: Preventive and corrective strategies were implemented.

Whitefly (Bemisia tabaci) was controlled using imidacloprid (350 g·L⁻¹) applied at 0.75 L·ha⁻¹. Bacterial diseases (Xanthomonas spp.) were managed using copper sulfate pentahydrate (≈25% Cu) at 1 L·ha⁻¹. Soil-borne pathogens were controlled by alternating applications of Trichoderma harzianum (11.5 g·kg⁻¹, 1.15%) at 15 mL·plant⁻¹ with systemic fungicides, including propamocarb (530 g·L⁻¹) + fosetyl-Al (310 g·L⁻¹) applied at 6 L·ha⁻¹, azoxystrobin (46 g·L⁻¹) + chlorothalonil (460 g·L⁻¹) at 3 L·ha⁻¹, and carbendazim (500.76 g·L⁻¹) at 2.5 L·ha⁻¹.

Cultural practices: Periodic manual weeding and one tillage operation at 45 dat were performed to improve root development and weed control.

2.4.2. Substrate-Based Hydroponic System Under Low-Technology Greenhouse Conditions (GH)

This system corresponds to a substrate-based hydroponic scheme using an inert volcanic substrate (tezontle).

Experimental design and transplanting: Transplanting was carried out on May 19, 2023 (89 DAS). The experiment was conducted under a completely randomized design (CRD) with 12 replications. Each experimental unit was a black polyethylene bag (40 × 40 cm) filled with 11 kg of disinfected red tezontle (volcanic substrate), containing two plants, resulting in a density of 6.67 plants·m⁻². One plant per unit was selected for measurements (12 plants per genotype).

Nutrient solution: The Steiner universal nutrient solution (1984) was used, with ionic concentrations (meq·L⁻¹) of 12 NO₃⁻, 1 H₂PO₄⁻, 7 SO₄²⁻, 7 K⁺, 9 Ca²⁺, and 4 Mg²⁺. The solution was prepared using KNO₃, Ca(NO₃)₂, KH₂PO₄, MgSO₄, K₂SO₄, and a micronutrient mix (Fe, Mn, B, Zn, Cu, Mo).

Irrigation and nutrient management: Solution concentration was adjusted according to phenological stage: 25% after transplanting, 50% during early vegetative growth, and 100% from 15 dat onward. Irrigation volume ranged from 250 mL to 1.5 L per plant. Electrical conductivity was maintained at 2.5 dS·m⁻¹ and pH at 6.0 using phosphoric acid. Weekly leaching irrigation with water only was applied to prevent salt accumulation.

Phytosanitary management: Systemic insecticides included imidacloprid (350 g·L⁻¹) applied at 0.75 L·ha⁻¹ and a mixture of imidacloprid (210 g·L⁻¹) + bifenthrin (72 g·L⁻¹), applied in separate applications at 0.75 L·ha⁻¹ during the flowering stage to control whitefly (B. tabaci), aphids (Aphididae), and thrips (Thysanoptera). Additionally, elemental sulfur (800 g·kg⁻¹, 80% p/p) was applied at 2 g·L⁻¹ as a preventive measure against fungal pathogens.

Cultural practices: Plants were supported using trellising with agricultural raffia.

2.5. Harvest Management

Fruits were harvested at physiological maturity, defined by size and characteristic color for each genotype. Eight harvests were performed under OF conditions and six under GH during the experimental period. In OF, harvests occurred between July and September, while in GH they were conducted from August to October 2023. This schedule allowed estimation of cumulative yield per plant.

2.6. Variables Evaluated

Phenological variables. Emergence time was evaluated, defined as the number of days elapsed from sowing until 50% of the seeds of each genotype had emerged. Emergence percentage was calculated as the proportion of seedlings that successfully emerged relative to the total number of seeds sown per genotype. In addition, days to flowering (DF) were recorded, defined as the time elapsed from transplanting to the anthesis of the first flower, and days to fruiting (DFR), corresponding to the time until the appearance of the first fruit. Both variables were determined when 50% of the plants of each genotype reached each stage.

Growth variables. Plant height (PH) and stem diameter (SD) were recorded weekly from transplanting. Plant height was measured as the vertical distance (cm) from the base of the stem to the apex, and stem diameter (mm) was measured using a digital caliper at 2 cm above the substrate level.

Yield variables. The number of fruits per plant (NF) was evaluated, defined as the total number of fruits developed and harvested at physiological maturity. Total yield per plant (YP) was calculated as the total fresh weight of fruits harvested per plant (kg per plant) at the end of the experimental period.

Agroclimatic variables. Agroclimatic variables were recorded continuously and simultaneously, including air temperature (°C), relative humidity (%), and photosynthetically active radiation, expressed as photosynthetic photon flux density (PPFD; μmol·m⁻²·s⁻¹). Measurements were obtained using HOBO^® dataloggers (models MX2301A, MX2202, and MX1104), configured to record data at 60-minute intervals throughout the experimental period.

2.7. Statistical Analysis

Phenological, growth, and yield data were analyzed separately for each production system. In OF, a randomized complete block design (RCBD) was used, while in GH a completely randomized design (CRD) was applied. In both cases, varietal effects were evaluated using analysis of variance (ANOVA), and means were compared using Tukey’s HSD test (α ≤ 0.05) with SAS Studio (SAS^® OnDemand for Academics, version 3.1.0).

Additionally, canonical correlation analysis (CCA) was performed to evaluate relationships between agronomic variables (plant height, days to flowering, number of fruits, and yield) and agroclimatic variables (temperature, relative humidity, and PPFD), grouped by growth stage. Analyses were conducted using XLSTAT (version 2019.2.2) and SAS Studio.

3. Results

Significant genotype effects were detected for phenological, growth, and yield variables in both production systems, allowing characterization of genotype-specific performance within each cropping environment. Detailed results of the analysis of variance (ANOVA), including mean squares, coefficients of variation, and coefficients of determination, are presented in Table S1 (Supplementary Material).

3.1. Agroclimatic Conditions

Agroclimatic variables exhibited distinct patterns within each production system, reflecting substantial differences in the crop microenvironment (Figure 3). Due to differences in experimental design, plant density, and agronomic management, comparisons between systems were addressed descriptively, prioritizing the independent characterization of each environment.

3.1.1. Air Temperature

In the open field (OF), air temperature exhibited a defined seasonal pattern throughout the crop cycle. During the initial period (14–35 dat), the average temperature was 16.2 °C, with a minimum of 9.36 °C. The maximum value of the cycle (32.80 °C) occurred during the vegetative stage, followed by a progressive decrease toward the maturation stage, where an average of 17.3 °C was recorded (Figure 3A).

In the greenhouse hydroponic system (GH), temperature was characterized by higher values throughout the cycle (Figure 3B). During the initial and vegetative stages, maximum temperatures exceeded 30 °C, reaching a peak of 48.78 °C, above the optimal ranges reported for the crop. Toward the final stage of the experimental period (119–154 dat), temperature stabilized, with an average of 22.3 °C, consistent with the seasonal transition toward autumn.

3.1.2. Relative Humidity

Relative humidity (RH) exhibited contrasting patterns between environments (Figure 3C, D). In OF, a marked diurnal variation was observed throughout the cycle, with maximum values during early morning (87–96%) and minimum values at midday (23–35%). During the initial period, the widest range of RH was recorded (23.85–90.88%), with an average of 72.4%. During the vegetative stage, RH decreased to 58.2%, whereas during the maturation stage it increased to 78.3%, with less pronounced daytime minima.

In GH, RH remained relatively high and more stable throughout the cycle (Figure 3D), with average values ranging from 78.2% to 83.7%. During the initial period, the widest range was observed (8.93–92.4%). During the vegetative stage, variation became more restricted, with an average of 77.8% and maximum values close to 94.8%. During reproductive and maturation stages, RH variability decreased further, with minimum values above 30% and maximum values close to 95%, indicating a more humid and stable environment.

3.1.3. Photosynthetic Photon Flux Density (PPFD)

The availability of photosynthetic photon flux density (PPFD) showed marked differences between environments (Figure 3E, F). In OF, the average PPFD during the cycle was 523.4 μmol m⁻² s⁻¹. During the initial period, the average was 458.2 μmol m⁻² s⁻¹, whereas the vegetative stage recorded the highest values (712.8 μmol m⁻² s⁻¹) and the maximum peak of the cycle (1818.8 μmol m⁻² s⁻¹). During the maturation stage, PPFD decreased to 543.6 μmol m⁻² s⁻¹, consistent with seasonal progression.

In GH, the average PPFD was 247.3 μmol m⁻² s⁻¹, representing an approximate 53% reduction relative to OF (Figure 3F). During the initial period, the average was 278.5 μmol m⁻² s⁻¹, with maximum values of 643.2 μmol m⁻² s⁻¹. During the vegetative stage, the highest average (312.8 μmol m⁻² s⁻¹) and the maximum value of the system (657.0 μmol m⁻² s⁻¹) were recorded. Toward the maturation stage, PPFD decreased to 183.6 μmol m⁻² s⁻¹. Radiation attenuation showed seasonal variation, with greater reductions during summer (56–64%) compared to autumn (40–45%), indicating consistent light limitation in GH.

3.2. Phenological Development

3.2.1. Emergence Time and Percentage

Emergence parameters were evaluated under controlled nursery conditions (identical for both production systems) prior to transplanting. Therefore, the data in Table 1 represent baseline seed quality and vigor for each genotype and are not specific to either the OF or GH system.

Significant differences (p ≤ 0.05) were observed in emergence time and percentage among genotypes (Table 1). Serrano Tampico recorded the shortest emergence time (15.25 ± 1.26 days), followed by Diente de Perro (16.25 ± 1.26 days), whereas Tía Juanita and Cola de Ratón showed the longest emergence times (24.75 ± 0.96 and 22.75 ± 2.22 days, respectively).

Emergence percentage was highest in Serrano Tampico (98.50 ± 1.08%), Tía Juanita (97.75 ± 1.55%), and Diente de Perro (93.50 ± 5.15%), whereas Mixteco Largo and Cola de Ratón showed significantly lower values (78.63 ± 6.69% and 75.13 ± 2.66%, respectively). Detailed ANOVA results are presented in Table S1 (Supplementary Material).

3.2.2. Growth Dynamics

Significant differences (p ≤ 0.05) in plant height (PH) and stem diameter (SD) were observed among genotypes within each production system (Figure 4). Detailed ANOVA results are provided in Tables S2 and S3 (Supplementary Material).

In OF, final plant height ranged from 65.45 to 105.44 cm. Tía Juanita showed the highest value (105.44 cm), followed by Cola de Ratón (99.31 cm) and Mixteco Largo (94.53 cm), whereas Serrano Tampico showed the lowest value (65.45 cm). Plant height stabilized from 63 dat onward. In GH, final plant height ranged from 108.33 to 155.04 cm. Tía Juanita showed the highest value (155.04 cm), followed by Mixteco Largo (132.00 cm) and Cola de Ratón (123.57 cm), whereas Serrano Tampico and Diente de Perro showed the lowest values (109.42 and 108.33 cm, respectively).

In OF, stem diameter ranged from 19.77 to 26.41 mm. Tía Juanita showed the highest value (26.41 mm), followed by Mixteco Largo (23.85 mm) and Cola de Ratón (20.89 mm), whereas Serrano Tampico showed the lowest value (19.77 mm). Stem diameter stabilized from 63 dat onward. In GH, stem diameter ranged from 10.90 to 12.86 mm, showing a consistent reduction relative to OF. Tía Juanita and Serrano Tampico showed the highest values (12.86 and 12.25 mm, respectively), whereas Mixteco Largo showed the lowest value (10.90 mm). Stabilization occurred from 119 dat onward.

3.2.3. Days to Flowering and Fruiting

Significant differences (p ≤ 0.05) in reproductive timing were observed among genotypes within each production system (Table 2). Detailed ANOVA results are presented in Tables S2 and S3 (Supplementary Material).

In OF, days to flowering ranged from 51 to 82 dat. Diente de Perro showed the lowest value (51 dat), followed by Serrano Tampico (57 dat), whereas Mixteco Largo (59 dat) and Cola de Ratón (62 dat) showed intermediate values. Tía Juanita showed the highest value (82 dat). In GH, days to flowering ranged from 45 to 77 dat. Diente de Perro (45 dat) and Serrano Tampico (50 dat) showed the lowest values, whereas Mixteco Largo (52 dat) and Cola de Ratón (57 dat) showed intermediate values. Tía Juanita showed the highest value (77 dat).

For fruiting, in OF values ranged from 67 to 92 dat, whereas in GH values ranged from 54 to 85 dat. Diente de Perro and Serrano Tampico showed the lowest values, while Tía Juanita showed the highest values in both systems.

3.3. Yield Components

Significant differences (p ≤ 0.05) were observed in number of fruits per plant and yield among genotypes within each production system (Table 3; Tables S2 and S3 in Supplementary Material).

In OF, fruit number ranged from 289.65 to 642.40 fruits per plant. Mixteco Largo (642.40) and Cola de Ratón (628.60) showed the highest values, whereas Diente de Perro showed the lowest (289.65). In GH, fruit number ranged from 130.00 to 288.33 fruits per plant. Tía Juanita (288.33) and Cola de Ratón (279.92) showed the highest values, whereas Diente de Perro showed the lowest (130.00).

Yield in OF ranged from 0.294 to 1.118 kg per plant. Serrano Tampico showed the highest value (1.118 kg), followed by Cola de Ratón (0.872 kg) and Mixteco Largo (0.759 kg), whereas Tía Juanita (0.294 kg) and Diente de Perro (0.387 kg) showed the lowest values. In GH, yield ranged from 0.181 to 0.603 kg per plant. Serrano Tampico showed the highest value (0.603 kg), followed by Cola de Ratón (0.332 kg), whereas Tía Juanita showed the lowest value (0.181 kg).

Descriptively, yield values in GH were consistently lower than those recorded in OF for all genotypes. Yield reductions relative to the open-field system ranged from 34.1% to 64.0% across genotypes. The largest reductions were observed in Mixteco Largo (64.0%) and Cola de Ratón (61.9%), followed by Serrano Tampico (46.1%) and Tía Juanita (38.4%), whereas Diente de Perro showed the smallest reduction (34.1%).

3.4. Canonical Correlation Analysis

Canonical correlation analysis (CCA) showed genotype-specific associations between environmental and agronomic variables within each production system (Table 4). Canonical correlation coefficients ranged from 0.6002 to 0.9607, indicating moderate to strong relationships.

Environmental variables, particularly temperature and radiation, were associated with growth and yield variables. The magnitude and direction of these associations varied among genotypes and production systems. In OF, associations tended to be positive between temperature and productive variables, whereas in GH more variable patterns were observed, including negative associations with yield. These patterns indicate the presence of genotype × environment interaction in phenological and productive responses. Mean values and direction of associations are presented in Tables S4 and S5 (Supplementary Material).

3.4.1. Interaction Patterns by Genotype

Diente de Perro showed canonical correlation coefficients of 0.8789 in OF and 0.9607 in GH. In OF, maximum (r = 0.52) and minimum temperature (r = 0.55) were associated with plant height (r = 0.76) and number of fruits (r = 0.61). In GH, minimum temperature (r = 0.59) and maximum PPFD (r = 0.46) were negatively associated with plant height (r = −0.49) and days to flowering (r = −0.67).

Tía Juanita showed coefficients of 0.9034 in OF and 0.8760 in GH. In OF, maximum PPFD (r = 0.41) was associated with number of fruits (r = 0.79) and yield (r = 0.51). In GH, maximum PPFD (r = 0.57) and maximum RH (r = 0.43) were negatively associated with yield (r = −0.29).

Mixteco Largo showed coefficients of 0.7095 in OF and 0.8421 in GH. In OF, maximum temperature (r = 0.55) was associated with yield (r = 0.36). In GH, minimum temperature (r = 0.78) was associated with plant height (r = 0.52), while negative associations were observed with yield (r = −0.53) and number of fruits (r = −0.47).

Serrano Tampico showed coefficients of 0.7699 in OF and 0.7582 in GH. In OF, maximum temperature (r = 0.64) and maximum PPFD (r = 0.50) were associated with days to flowering (r = 0.73). In GH, minimum temperature (r = 0.69) was associated with yield (r = 0.32) and number of fruits (r = 0.40), while plant height showed a negative association (r = −0.59).

Cola de Ratón showed coefficients of 0.6002 in OF and 0.8690 in GH. In OF, minimum temperature (r = 0.43) and maximum RH (r = 0.47) were negatively associated with yield (r = −0.46) and days to flowering (r = −0.42). In GH, maximum PPFD (r = 0.69) was associated with plant height (r = 0.34) and days to flowering (r = 0.69).

The structural correlation coefficients of the first three canonical factors for all the variables and genotypes are represented graphically in Figures S1 to S5 of the Supplementary Material, providing an integral visualization of these multivariate interrelations.

4. Discussion

The results obtained showed consistent patterns in the phenological and productive performance of C. annuum across the evaluated environments, with differentiated responses among genotypes depending on the growing conditions. The magnitude of these differences, including yield reductions of up to 64% and an approximate 53% decrease in photosynthetic photon flux density in the GH system, highlights the likely role of genotype × environment interaction (G×E) in the expression of productive potential. In this context, variations in temperature and radiation availability were associated with changes in phenology, plant architecture, and productive efficiency, suggesting that genotypes may differ in their ability to adjust the allocation of resources under contrasting environmental conditions.

It is important to note that the evaluated system corresponded to a low-technology tunnel-type GH with limited passive ventilation, a condition commonly found in production systems in developing regions. Therefore, the results should be interpreted within this specific context and not directly extrapolated to high-technology hydroponic systems with active climate control. Likewise, due to differences in planting density, substrate type, and water management between OF and GH, the observed differences between systems reflect the interaction of multiple factors, including both environmental and agronomic management conditions. Consequently, it is not possible to attribute the observed effects to a single variable in isolation. Under this context, although greenhouse microclimatic conditions were associated with a reduction in yield, this effect cannot be attributed exclusively to those factors, as other uncontrolled variables may also have influenced the observed response.

4.1. Microclimatic Conditions as a Limiting Factor in the Protected System

The microclimatic conditions recorded in the GH, characterized by maximum temperatures of up to 48.78 °C and an approximate 53% reduction in photosynthetically active radiation compared to OF, suggest a potentially restrictive environment for crop development. These conditions suggest that the observed microclimatic conditions may exceed commonly reported ranges favorable for C. annuum growth (18–30 °C) [25,37,38], suggesting a likely simultaneous occurrence of thermal stress and light limitation. The occurrence of these temperatures is consistent with the structural characteristics of the greenhouse, particularly its low height (3 m) and the absence of roof ventilation, conditions that may have limited heat dissipation and air renewal in the upper canopy.

From a physiological perspective, temperatures above 32 °C have been associated with alterations in physiological and reproductive processes in C. annuum, potentially affecting pollen viability and fruit development [39,40,41]. In this study, although direct physiological measurements were not performed, these mechanisms may partially explain the yield reduction observed in the GH. Additionally, the recorded radiation levels (247.3 μmol m⁻² s⁻¹) fall below those commonly associated with high photosynthetic activity in C. annuum, which, according to previous studies, may be linked to reduced net photosynthetic rates and consequently lower availability of photoassimilates for fruit filling [42,43]. This is consistent with studies reporting changes in photosynthesis and yield under reduced radiation conditions [44]. Moreover, the wide variability in relative humidity (8.93–94.78%), outside the optimal range (65–85%) [45], indicates an unstable environment, consistent with potential alterations in plant water balance and transpiration processes, with possible implications for physiological performance [46]. Collectively, these microclimatic conditions suggest potential physiological limitations that may affect key processes such as photosynthesis, photoassimilate partitioning, and reproductive development. In this regard, studies in C. annuum have documented reductions in growth and yield under abiotic stress conditions, particularly when water balance and resource availability are compromised [16].

In contrast, OF presented a less extreme thermal regime and greater radiation availability, conditions that favored a more balanced physiological development and higher productivity levels. In this context, the results contrast with the general assumption that protected systems automatically improve crop performance [47], showing that under low-technology conditions and limited environmental control, the greenhouse may represent a more restrictive environment for crop development. Such conditions have been widely documented in protected production systems [48,49], in some cases being more limiting than open-field conditions. These findings provide empirical evidence that, in low-technology systems, greenhouse environments do not necessarily represent an automatic improvement over open-field conditions, but rather their performance depends critically on the microclimatic conditions generated.

Since the production system was not evaluated as a replicated experimental factor, these differences should be interpreted in terms of the specific environments observed. From this perspective, although the system corresponded to a substrate-based hydroponic scheme, the results suggest that crop performance was mainly associated with the recorded microclimatic conditions rather than with the production technique itself. Additionally, although hydroponic systems typically offer advantages related to controlled water and nutrient supply, allowing greater precision in resource availability [50], these advantages may not have been fully expressed under conditions of thermal stress and light limitation.

4.2. Phenological and Growth Responses: Genotypic Plasticity and Adaptive Strategies

Differences observed in emergence percentage (75.13–98.50%) reflect variability in seed vigor and suggest the presence of intrinsic characteristics associated with the genotypes, particularly in native materials. The greater precocity observed in Serrano Tampico and Diente de Perro indicates faster establishment, whereas lower percentages in Mixteco Largo and Cola de Ratón suggest lower germination uniformity. In this context, the implementation of seed priming strategies could contribute to improving germination, seedling vigor, and establishment uniformity [51,52,53].

At the phenological level, clear differences among genotypes were observed within each production system. In OF, flowering and fruiting times were longer, suggesting a more gradual development compared to protected systems, where these phases tend to be accelerated [54]. This pattern is consistent with reports documenting variations in agronomic performance of C. annuum between open-field and protected conditions [11]. In contrast, the acceleration of the crop cycle observed in GH (4–13 days) is consistent with the higher temperatures recorded in this environment. However, this reduction in cycle duration was not associated with increased yield, indicating that greater precocity does not necessarily translate into higher productive efficiency.

Vegetative growth showed contrasting patterns among genotypes within each production system. In OF, plants exhibited lower height but greater stem diameter, suggesting a more balanced structural development. In GH, greater plant height combined with reduced stem diameter indicates a potential asymmetry in growth. This pattern is consistent with low radiation conditions, which have been associated with modifications in growth and yield in C. annuum [55], and may induce elongation processes as an adaptive response to maximize light interception [56].

Under these conditions, the combination of high temperature and low radiation may have promoted morphophysiological responses associated with a shade avoidance syndrome, where plants prioritize vertical growth over structural thickening [57,58]. These responses may compromise mechanical stability and the ability to support reproductive structures, with direct implications for yield.

Overall, the evaluated genotypes exhibited considerable diversity in their phenological and morphological behavior across both production systems, suggesting different adaptive strategies in response to environmental conditions. The precocity of Serrano Tampico and Diente de Perro may represent an adaptive trait favorable for short-cycle environments, whereas the longer cycle and greater vegetative development of Tía Juanita suggest a strategy oriented toward biomass accumulation, characteristic of genotypes that may perform better under less restrictive conditions.

4.3. Yield Response and Genotype × Environment Interaction

Differences observed in fruit number and yield reflect variations in the efficiency of biomass conversion into marketable yield. In OF, genotypes such as Mixteco Largo and Cola de Ratón produced the highest number of fruits, whereas Serrano Tampico achieved the highest yield (1.118 kg per plant), indicating that a greater number of fruits does not necessarily translate into higher productivity. This decoupling suggests differences in fruit size or individual fruit weight and in the efficiency of photoassimilate allocation, consistent with biomass partitioning patterns described in plants [59,60,61]. In this sense, Serrano Tampico may exhibit greater efficiency in the allocation of photoassimilates toward fruits, allowing it to reach higher yield levels despite not producing the highest number of fruits.

In GH, a generalized reduction in yield (34–64% depending on genotype) was observed, suggesting a consistent limitation in productive efficiency under this system. Although some genotypes such as Tía Juanita and Cola de Ratón maintained relatively high fruit numbers under GH conditions, their yield remained lower, suggesting possible constraints in resource supply for the full development of reproductive structures. This behavior is consistent with the previously described microclimatic conditions, particularly the combination of high temperatures and low radiation availability, factors that have been associated with reductions in fruit set due to alterations in pollen viability, as well as limitations in biomass accumulation during fruit filling under reduced radiation conditions in C. annuum [55,62].

Conversely, Serrano Tampico showed a smaller relative reduction in yield between systems, suggesting greater productive stability and a better capacity to adjust to contrasting environmental conditions. This may indicate higher physiological efficiency in resource use or lower sensitivity to stress conditions present in the protected system.

Overall, these results indicate that yield in C. annuum does not depend exclusively on the number of fruits produced, but rather on the interaction between reproductive structure formation and the availability of resources for their development, highlighting the importance of evaluating productive efficiency under different environmental conditions.

4.4. Environmental Drivers and Functional Relationships of Genotype × Environment Interaction (CCA)

Canonical correlation analysis (CCA) allowed the identification of differentiated associations between environmental and agronomic variables, showing that genotype responses varied depending on the evaluated environmental conditions. The high canonical correlation values observed in several genotypes suggest a strong association between environmental conditions and agronomic performance, supporting the importance of genotype × environment interaction (G×E) [63].

In OF, environmental variables, particularly temperature and radiation, showed predominantly positive associations with productive variables such as fruit number and yield in some genotypes, which is consistent with an environment that favored the expression of productive potential through greater energy availability for photosynthesis and biomass accumulation [64]. In contrast, in GH, more variable patterns were observed, including negative associations between environmental and agronomic variables, consistent with the presence of stress conditions or physiological imbalance.

At the genotypic level, differentiated responses were observed. Diente de Perro showed negative associations between environmental variables and development in GH, indicating greater sensitivity to conditions in this system. In contrast, Serrano Tampico exhibited positive associations with productive variables in both systems, indicating greater stability in its performance. In genotypes such as Mixteco Largo and Cola de Ratón, the observed associations suggest that, under greenhouse conditions, increases in certain environmental variables may not translate into improvements in productivity, indicating possible limitations in the ability of these genotypes to respond favorably to environmental changes.

Overall, the patterns identified through CCA suggest that the evaluated genotypes exhibit different strategies in response to environmental conditions, where some show greater productive stability and others greater sensitivity to specific conditions. These patterns reinforce the importance of considering G×E interaction in the selection of genetic materials and in the design of production systems adapted to specific environmental conditions.

4.5. Agronomic Implications and Perspectives

Varietal selection under contrasting systems: The results indicate that no single genotype was consistently superior across the evaluated environments, highlighting the importance of genotype × environment interaction in yield expression. Under open-field conditions, genotypes such as Mixteco Largo, Cola de Ratón, and Serrano Tampico showed favorable productive performance, suggesting their potential for this system. However, their behavior under protected environments with limited climate control may differ; therefore, their evaluation should consider the specific microclimatic conditions.

Greenhouse management in warm climates: The conditions recorded in the GH, with temperatures exceeding 48 °C and an approximate 53% reduction in photosynthetic photon flux density, suggest that passive systems may generate suboptimal environments. In this context, strategies such as improved ventilation, shading, or evaporative cooling could contribute to moderating the microclimate and improving crop performance [65]. Additionally, the management of light transmission emerges as a key factor for maintaining adequate PPFD levels [66].

Agronomic value of native germplasm: The performance observed in native landraces under open-field conditions suggests processes of local adaptation, highlighting their value as genetic resources in breeding programs aimed at abiotic stress tolerance and yield stability [67].

Future research perspectives: The results identify relevant research directions, including evaluation under systems with active climate control to separate environmental effects, analysis of fruit quality under genotype × environment interaction, and physiological studies focusing on photosynthesis and water-use efficiency. Likewise, strategies to improve germination and early establishment could optimize crop performance.

4.6. Study Limitations and Contextualization of Results

The present study has inherent limitations associated with its experimental design that should be considered when interpreting the results. In particular, the evaluation was conducted over a single growing season and at specific sites; therefore, the findings should be interpreted within the context of the analyzed environments rather than as universal generalizations.

Comparisons between production systems were influenced not only by microclimatic conditions but also by differences in agronomic management, including planting density, substrate type, and irrigation regime, which are integral components of each system. Therefore, the observed differences cannot be attributed exclusively to microclimatic conditions and should be interpreted as the combined effect of these interacting factors.

Additionally, the lack of replication of the production system factor across multiple environments or growing cycles limits the possibility of making statistically generalizable inferences regarding this factor. However, the adopted approach, based on the independent analysis of each system and the use of canonical correlation analysis (CCA), allows the identification of consistent associations between environmental and agronomic variables, providing relevant evidence of genotype × environment interaction.

It is important to emphasize that the evaluated system corresponded to a substrate-based hydroponic system under low-technology greenhouse conditions, with passive ventilation and without active climate control, which conditioned the recorded microclimatic conditions. Therefore, the results should be interpreted within this specific context and should not be directly extrapolated to hydroponic systems with active climate control, where the environment is more precisely regulated.

Overall, this study does not aim to establish absolute superiority between production systems, but rather to provide evidence on the differential performance of genotypes under contrasting environmental conditions. Within this framework, the results provide a solid basis for the formulation of new hypotheses and the design of future studies incorporating environmental replication, multiple evaluation cycles, and systems with greater microclimatic control.

5. Conclusions

The results of this study suggest that the phenological and productive performance of Capsicum annuum was associated with genotype × environment interaction, as reflected in differences in cycle duration, growth, and productive efficiency across growing environments.

In the greenhouse hydroponic system (GH), the recorded microclimatic conditions were associated with a reduction in yield, indicating that, under limited ventilation, the environment may restrict the expression of productive potential. This behavior is particularly relevant in production systems used by smallholder farmers and in developing regions, where environmental control is limited.

In contrast, under the evaluated conditions, the open-field system (OF) showed higher productive performance, highlighting the importance of matching the production system to local environmental conditions.

The patterns identified through canonical correlation analysis confirm a strong genotype × environment interaction, revealing differential responses among genotypes. In this context, Serrano Tampico showed greater productive stability, whereas native genotypes such as Mixteco Largo and Cola de Ratón exhibited better performance under open-field conditions, suggesting specific adaptation to this environment.

Overall, these results demonstrate that yield in Capsicum annuum depends critically on the interaction between genotype and environmental conditions, rather than solely on the production system employed, underscoring the need for management and selection strategies adapted to the specific microclimatic context.