Study site.

For this study, an experimental PV array was installed in an existing production field. Four single-pile, fixed tilt racking systems were custom built (RC Rab Corporation, Albuquerque, NM, USA) and mounted with four decommissioned PV panels (Trinasolar TSM-240PA05; New Mexico State University, Solar Experiment Station, Las Cruces, NM, USA). The PV module installation faced limitations due to field’s orientation and the goal of using low-impact procedures to minimize soil disturbance. The field is oriented at 224.67° southwest, and the PV modules were aligned accordingly and installed outside the last row (Fig. 1) with 12.2 m spacing between each pile. To minimize soil compaction in the production area, the modules were installed along the edge of the field rather than within the field itself. Each module was pile-driven into the ground without using a concrete foundation.

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The installed PV modules could be manually tilted to various angles (Fig. 2). When farm machines were in the field, all modules were in the stow position (Fig. 3). During the experimental period, all modules were set to the experimental position with an 11° tilt, facing east.

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Experimental design.

In both years, the plots were arranged in a randomized complete block design, with PV module shade and full sun as the treatments. There was one full sun and four PV module replications 2023. In 2023, there was only one complete sun replication because several plants died and had to be replanted. In 2024, there were four PV module and full sun replications (Fig. 4).

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Each replication consisted of three rows: row 1 closest to the pile, row 2 in the middle; and row 3 furthest from the pile. Rows 1 and 3 were border rows, while the innermost part of row 2 was designated the sample row. The sample area was 3.7 m long by 1 m wide (3.7 m²; Fig. 5). The sample area was further divided into four transects to accurately represent the environmental variation across the area. Each transect was 0.9 m long by 1 m wide (0.9 m²).

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Plant material and field management.

‘NuMex Odyssey’, a green chile pod-type cultivar developed for mechanical harvest (Walker et al. 2021), was selected for this study. In 2023 and 2024, ‘NuMex Odyssey’ was seeded in the greenhouse at the Fabian Garcia Research Center in Las Cruces, NM, USA, on 10 Mar 2023 and 11 Mar 2024, respectively. The seeds were planted into a commercial peatmoss−vermiculite soil mixture (RediEarth Plug and Seedling Mix; Sun Gro Horticulture, Bellevue, WA, USA) in polyethylene trays (TOD812; T.O. Plastics, Clearwater, MN, USA). Transplants were hardened off under a shade house starting on 20 Apr 2023 and 19 Apr 2024. The seedlings were transplanted into the Plant Science Research Center field on 10 May 2023 and 1 May 2024 in single rows with 30.5 cm between-plant spacing with a single line of subsurface drip irrigation tubing [12 inches emitter spacing, 0.23 gal/100 ft per hour at 10.0 psi (Netafim, Fresno, CA, USA)]. The proximity of row 1 to the PV modules prevented the mechanical burial of subsurface drip irrigation, so this border row used surface drip irrigation. Composite soil tests were completed on 20 Mar 2023 and 26 Mar 2024 (Ward Laboratories, Kearney, NE, USA).

Soil tests indicated that preplant fertilizer was unnecessary; however, fertilizer was applied through the drip irrigation system throughout each season to meet the nutrient demands of the chile (Bosland and Walker 2014). For both years N-pHuric with 28N−0P−0K+9(S) (Helena Chemical Company, Albuquerque, NM, USA) was applied at 156 lb/acre (25.4 kg/4046.86 m²) Hand cultivation was performed twice at the beginning of each season, while hand weeding was completed weekly throughout the season.

Light intensity and ambient air temperature.

Light intensity (lux) and ambient air temperature (°C) measurements were taken every hour using in situ self-logging sensors (Hobo Pendant MX2202; Onset, Bourne, MA, USA) mounted on fence posts 1 m above the ground. All replications had four light/temperature sensors; each sensor was positioned in the center of each of the transects within the sample area (Fig. 6).

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Beet leafhopper abundance.

Beet leafhopper population numbers were collected using yellow sticky trap cards measuring 10 cm wide and 25 cm long (250 cm²) with adhesive on both sides (Pest Trap; Hummert International, Earth City, MO, USA). Sticky cards were placed 61 cm above the ground attached to a wooden post (Creamer 2003). There were two sticky trap locations, 61 cm from the centers of row 3 and row 1, respectively (Fig. 5). Sticky cards were replaced every 2 weeks throughout the season until harvest. Sticky traps were examined, and beet leafhoppers were counted.

Photosynthesis.

Leaf-level net carbon dioxide assimilation (A_net) was measured at peak vegetative stage using a portable photosynthesis system (LI-6800; LI-COR Biosciences, Lincoln, NE, USA). The same three randomly selected plants were measured from each replication six times, from 1000 to 1300 HRon 10, 12, and 13 Jul in 2023 and 15, 16, and 17 Jul 2024 (Fig. 7). All measurements were made on recently mature, fully expanded, upper canopy leaves. The LI-6800 was equipped with a 3-cm × 3-cm cuvette head and a red−blue LED light source. During all measurements, the following settings were maintained: a constant flow rate of 500 μmol·s⁻¹, relative humidity at 60%, carbon dioxide concentration at 400 μmol·s⁻¹, a fan speed of 1000 with the mixing fan activated, light intensity at 1500 μmol·s⁻¹, and a stomatal ratio of 0.5.

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Plant growth measurements.

Plant architecture measurements were taken every 3 weeks starting at the initial transplantation. Measurements were taken on all 12 plants from the sample area. Measurements included plant height (cm) and basal diameter (mm). Plant height was taken from the ground level at the base of the plant to the highest meristem. Basal stem diameter was taken at the base of the stem directly above ground level using a digital caliper (Absolute Digimatic Caliper; Mitutoyo, Aurora, IL, USA). Due to differences in season length, plant architecture measurements were collected four times in 2023 and five times in 2024. This variation in sampling frequency was addressed in the analysis by evaluating each year separately.

Harvested fruit.

The fresh weight of chile was taken at harvest on 25 Aug 2023 and 29 Aug 2024. All plants were hand harvested from the 3.7-m² sample area. Harvested fruit were sorted into several categories; 1) marketable green, intact whole unblemished fruit that is at a horticulturally mature green stage and is suitable for market; 2) blossom end rot (BER) affected fruit with BER symptoms, blackened apex (Goldberg 1995); 3) red fruit, intact whole unblemished fruit at ripe red stage; 4) diseased fruit, whole unmarketable fruit that has blemishes and indication of disease; 5) immature fruit, green fruit with malleable pericarps; and 6) BCTV-affected fruit, abnormal block-shaped small fruit (Fig. 8).

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Statistical analysis.

The experiment did not follow any standard design, and for that reason, during the data analysis, some correlations structures were included to account for the lack of randomization. The PV module study site was established in 2023 and used again in 2024. In the first year, the full sun treatment was replicated once, while the PV module treatment had four replications. In the second year, all treatments were evenly replicated. At replication level, a spatial correlation structure was added into the model to account for lack of randomization on the assignation of treatments to the plots. Each replication was further divided into transects or locations to account for the light variability across each replication. At the location level, an additional random component was included to account for spatial correlation due to the lack of randomization. To accurately model the collected data, different statistical models were applied based on the measurement structure of each variable. The following section of the article details the models used. The analyses were conducted using the statistical software PROC GLIMMIX (SAS ver. 9.3; SAS Institute Inc., Cary, NC, USA) and R Software (version 4.4.2; R Core Team, Boston, MA, USA) with tailored functions coded in Armadillo C++. The latter software was used for Bayesian analyses.

Harvested yield statistical analyses.

For all yield variables, except BCTV-affected fruit yields, the model has the following components: treatment, year, and their interaction as fixed effects, while replications are treated as random with spatial correlation to account for lack of randomization (Pinheiro and Douglas 2000). A normal distribution was assumed for all the yield and fruit morphology variables. Because randomization did not occur across years, two random components were included in the model to explain lack of randomization over the levels of the time factor. An extra random effect was included to explain the spatial correlation of the observations collected across locations. The spatial dependences were modeled through an exponential correlation structure, with its corresponding subsample random component (Schabenberger and Gotway 2017). Significant variable means were separated using the Tukey–Kramer test (P ≤ 0.05), which is used for pairwise comparisons when sample sizes are unequal (Kramer 1956).

The BCTV-affected fruit yields resulted with excess of zeros that cannot be explained by standard models or distributions. The excess zeros occurred because many replications had either BCTV-affected fruit or none at all. To address this, an adapted Student t delta model within a Bayesian framework was implemented. This model includes all the random components described for the other harvested yield categories, except that the BCTV-affected fruit yield is treated as a mixture of distributions to account for the zero inflation (Ridout et al. 1998). Instead of P values, conclusions are drawn from 90% credible intervals, as is standard in Bayesian analysis (Gelman et al. 1995).

Beet leafhopper abundance analysis.

The beet leafhopper count data were log-transformed and analyzed using the same experimental design as described for yield. Two sticky traps per replication were monitored, with counts recorded biweekly. To account for temporal correlation, a random effect with an unstructured covariance structure was included in the model (Zuur et al. 2009). Significant variable means were separated using Tukey–Kramer tests (P ≤ 0.05).

Plant height and basal stem diameter analysis.

A three-parameter logistic nonlinear model was used to describe plant measurements and their relationship with time. The model follows a hierarchical structure. At the first level, plant height and basal stem diameter are modeled as a function of time, with the three-parameter logistic model treatment specific. At the second level, the design factors and all previously mentioned random components are incorporated, and the logistic model parameters serve as the response variables (Paine et al. 2012). The parameters of the logistic nonlinear model were: 1) final height, maximum height of the plants at the end of the season; 2) growth rate (slope) of the sigmoidal curve, indicating how quickly the plant grew during the most rapid phase of development; and 3) inflection point, the time at which growth rate is maximized (Thornley and Johnson 1990). The analysis was conducted within a Bayesian framework, with conclusions drawn from 95% credible intervals rather than P values.

Photosynthesis analysis.

The net rates of carbon dioxide assimilation data were analyzed with the model for the nonstandard design with treatment, time, date, and their interactions as fixed effects. This response variable was assumed to follow a normal distribution. Replication was included as a random factor with a spatial correlation structure to account for lack of randomization. Because multiple measurements were taken within each date, the time variable distinguishes these observations, effectively creating a split-split-plot design. To account for temporal dependencies, time and date were modeled with a compound symmetry correlation structure (Pinheiro and Douglas 2000).

Light intensity and ambient air temperature.

Due to the orientation of the existing field, the PV module shade-covered transects 1, 2, 3, and 4 had varying amounts of shade between 0630 and 1330 HR throughout the season (Fig. 9). The spatial variability in light across replications was accounted for in the statistical analysis. On average, the mean light intensity across all transects was 11% lower in the PV module shaded replications compared with full sun conditions.

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Marrou et al. (2013a) investigated the performance of lettuce (Lactuca sativa), cucumbers (Cucumis sativus), and durum wheat (Triticum durum L.) under an agrivoltaic system. In this system, the PV panels provided most of the shade to crops during the morning hours, between 0700 and 1100 HR. In arid climates, the most cumulative photosynthesis typically occurs during the morning hours (Lambers and Oliveira 2019). Therefore, shading crops during this period may negatively affect growth. However, midday depression of photosynthesis—a decline in photosynthetic rates occurring around midday due to high light intensity and temperature (Yokoyama et al. 2019)—can significantly constrain crop growth and yield potential. To mitigate the effects of midday depression while preserving morning photosynthesis, strategies such as providing selective protection from excessive light and heat can be implemented.

Savalle-Gloire et al. (2022) demonstrated that providing PV-induced shade in the afternoon significantly increased the marketable yield of tomatoes. This finding underscores the importance of optimizing shading strategies to mitigate the adverse effects of high irradiance and temperature on plant physiology. Photosynthetic activity can decline during periods of excessive irradiance, when photosynthesis becomes light saturated and photo-oxidative stress occurs (Chapin et al. 2011). Under such high-light conditions, stomatal conductance is often increased to alleviate carbon dioxide limitations for photosynthesis. This adaptation also results in substantial transpirational water loss, which can be particularly detrimental to plants growing in arid environments characterized by high temperatures and low humidity. To conserve water under these conditions, stomata close, reducing transpiration but concurrently restricting the uptake of carbon dioxide and, consequently, photosynthesis (Chapin et al. 2011).

Shading can modify plant acclimation to such environmental stressors. Plants growing under shaded conditions often exhibit lower photosynthetic capacity per unit leaf area as an adaptive strategy (Lambers and Oliveira 2019). When these shade-adapted plants are suddenly exposed to increased irradiance, their limited photosynthetic capacity restricts their ability to capitalize on the enhanced light availability. These dynamics highlight the complex interplay between light, temperature, water use, and photosynthetic efficiency, particularly in hot, dry, high-light climates, where the balance between water conservation and carbon assimilation is critical for plant productivity.

In this study, shading was restricted to the morning hours due to the fixed orientation of the AVS and the existing field infrastructure. This constraint underscores a critical consideration for farmers and developers when integrating AVS technology into agricultural systems: should modifications to existing infrastructure prioritize maximizing shading for crop production or optimizing energy generation? The orientation and configuration of PV panels play a pivotal role in determining the timing and distribution of shade, which directly influences crop microclimates and, consequently, plant physiological responses.

The limitations inherent in this study highlight the need for adaptive experimental designs. Specifically, reconfiguring the AVS installation to provide afternoon shading would enable a more comprehensive investigation into its impact on crop growth, yield, and physiological responses. Afternoon shading has been demonstrated to mitigate heat stress and enhance productivity in certain crops (Savalle-Gloire et al. 2022). However, the effects afternoon shade remain underexplored across a diverse range of crops, climates, and AVS configurations.

Ambient air temperature.

The ambient air temperature underneath the PV modules was observed to be less than the full sun replications, with about a 2% difference in temperature (Fig. 10). Previous studies have reported mixed findings regarding temperature differences in agrivoltaic systems. Some studies observed no significant temperature differences (Marrou et al. 2013b), while others documented measurable variations (Weselek et al. 2019). Factors influencing temperature differences between PV module and full sun replications may include the size, height, and spatial arrangement of the PV modules (Mamun et al. 2022). In this study, the PV system was installed following an open field agrivoltaic design. The setup consisted of four PV modules with a hinge point height of 1.6 m and spaced 12.2 m apart. This configuration was not selected to optimize agrivoltaic performance but rather to enable an initial analysis under practical field conditions.

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Beet leafhopper abundance.

The interaction between treatment (PV module vs. full sun) and year was not statistically significant (P = 0.278), indicating that the effect of the treatment did not vary significantly across different years. Beet leafhopper abundance had consistent patterns under both treatments over the years. The main effect of PV module shade and full sun was significant (P = 0.023), with 21% more beet leafhoppers observed in the full sun treatment compared with the PV module–shaded replications (Table 2). This result aligns with previous studies, such as those by Oldfield et al. (1991), which demonstrated that beet leafhoppers exhibit a preference for full sun environments. These findings suggest that the shading provided by PV modules can influence the spatial distribution and movement of pests within agricultural systems, something that has not been identified previously (Walston et al. 2023). This has important implications for pest management strategies, because PV module shade may reduce the need for pesticide applications by discouraging pest activity in shaded areas. Furthermore, this shift in pest behavior could potentially mitigate the spread of pest-associated plant diseases (Cooke et al. 2006). The analysis revealed a significantly higher abundance of beet leafhoppers in 2024 compared with 2023 (P = 0.001). This result is consistent with previous research, which has documented seasonal fluctuations in beet leafhopper populations and highlighted their tendency to exhibit considerable interannual variability (Lehnhoff and Creamer 2020).

Table 2. Beet leafhopper [Circulifer (Neoaliturus) tenellus Baker] abundance in photovoltaic (PV) module–shaded and full sun replications in 2023 and 2024 at the Leyendecker Plant Science Research Center, Las Cruces, NM, USA.

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Photosynthesis.

The main effect of year on net carbon dioxide assimilation (A_net) was statistically significant (P = 0.0001), indicating that A_net varied significantly between years. As a result, data from each year were analyzed separately to account for these annual differences. However, the interaction between year × date × time was not significant (P = 0.392), suggesting that the temporal patterns of A_net across dates and times within each year were consistent and did not differ significantly between years. This implies that while absolute values of A_net varied by year, the underlying trends over time were similar across the study period. A significant interaction was observed between treatment (PV module shade vs. full sun) and measurement time (1000, 1100, 1200, and 1300 HR) (P = 0.017), indicating that the effect of treatment on A_net varied depending on the time of measurement. Pairwise comparisons revealed key differences: at 1000 and 1100 HR, A_net was significantly lower in PV module–shaded plants compared with full sun plants (P = 0.0001 and 0.038 respectively; Fig. 11). However, at 1200 and 1300 HR, there were no significant differences in A_net between the two treatments (P = 0.077 and 0.083 respectively; Fig. 11).

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Although this is not a complete light response curve (Taiz et al. 2022), the findings provide valuable insight into the photosynthetic response of chile plants cultivated under PV module plots (Busch et al. 2024). Previous studies on bell peppers (C. annuum) have reported a diurnal pattern in photosynthesis characterized by an increase in the morning, followed by a slight midday dip and a plateau in the midafternoon (Goo et al. 2024). Our results indicate that shading the chile plants in the morning under PV modules reduces their photosynthetic rate until ∼1100 HR. By 1200 HR, however, the shaded plants are assimilating carbon at a rate comparable to that of chile plants grown in full sun. This observation suggests that the shaded plants may be adapting to the dynamic light environment, optimizing their photosynthetic efficiency across varying light intensities (Lambers and Oliveira 2019). It remains critical, however, to further investigate how afternoon shading influences the photosynthetic dynamics observed in the morning. Additionally, evaluating the extent to which afternoon shading mitigates photoinhibition and thermal stress during periods of intense afternoon radiation will provide a more comprehensive understanding of the benefits and trade-offs associated with PV shading. These findings could have significant implications for optimizing agrivoltaic systems to improve crop productivity and resilience under variable light conditions.

Plant growth measurements.

Plant height and basal stem diameter were modeled using a three-parameter logistic nonlinear model to comprehensively capture the dynamics of the growth curve across all developmental stages. This approach allowed for the characterization of key growth parameters, including the final height (maximum plant height at maturity), the growth rate (steepness of the curve during the exponential phase), and the inflection point (time at which the growth rate is maximized). No statistically significant differences were observed in final plant height, growth rate, or inflection point between full sun and PV module–shaded replications in either 2023 or 2024, as indicated by 95% credible intervals (Fig. 12). This suggests that plants in both full sun and PV module–shaded conditions exhibited similar growth rates throughout the study period.

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These findings contrast with those of Weselek et al. (2021), who reported that plant heights under PV module shading and full sun conditions were initially comparable early in the growing season but diverged later, with shaded plants growing taller in environments with a 30% reduction in photosynthetically active radiation. The phenomenon of taller plants under shaded conditions is often attributed to an increased demand for photosynthates as plants expand, leading to elongation as a strategy to enhance photosynthetic efficiency per unit area under reduced light availability (Díaz-Pérez 2013; Taiz et al. 2022). The absence of such an effect in this study may be explained by the relatively modest 11% reduction in light intensity, coupled with the timing of shading, which occurred exclusively during morning hours. This limited reduction in light intensity may have been insufficient to trigger the elongation response typically observed under more pronounced shading conditions.

Stem diameter, a critical indicator of lodging risk, is an important trait in chile plants (Bosland and Votava 2012). Plants with smaller stem diameters are less capable of supporting heavy fruit loads and are more prone to lodging (McCullough et al. 1993). No statistically significant differences were observed in final basal stem diameter, growth rate, or inflection point between full sun and PV module–shaded replications in either 2023 or 2024, as indicated by 95% credible intervals (Fig. 13). This suggests that chile plants can be grown under PV module shade without an increased risk of lodging due to smaller stem diameters.

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Harvested fruit.

Statistical analysis revealed that treatment × year interactions were not significant for any of the yield categories evaluated (Table 3). This suggests that the effects of the applied treatments on yield components remained consistent across the study years, with no substantial variation attributable to annual environmental fluctuations or management practices. Among the yield categories, green marketable yield was significantly higher in full sun replicates compared with those under 11% PV module shading (P = 0.025). This finding highlights the sensitivity of green chile yield to light availability, as even moderate shading from PV modules had a measurable impact on marketable fruit production. This difference in green yield occurred despite the absence of significant differences in final plant height or basal stem diameter between PV module and full sun replicates (Figs. 12 and 13). This suggests that while vegetative growth parameters were unaffected by shading, reproductive output, specifically the production of marketable green fruits, was compromised under reduced light conditions.

Table 3. Yield categories of ‘NuMex Odyssey’, a New Mexico pod-type green chile (C. annuum) in photovoltaic (PV) module–shaded and full sun replications in 2023 and 2024 at the Leyendecker Plant Science Research Center, NM, USA.

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Similar reductions in the marketable yield of bell peppers and jalapeño (C. annuum) grown under PV modules have also been documented (Asa’a et al. 2024). Green chile crops grown in New Mexico are well adapted to environments with high light intensity and temperatures (Barchenger and Bosland 2019). Conversely, in Arizona, the yield of ‘Chiltepin’ (C. annuum) was reported to be three times higher under PV systems than in open-field cultivation (Barron-Gafford et al. 2019). This increased yield is likely due to the crop’s adaptation to the shaded understory of forests in Mexico (Pickersgill 2016), making it more suitable for shaded environments.

The genetic adaptations of crops play a critical role in their productivity under PV module systems. There is potential for breeding green chile varieties better suited to shaded environments created by PV modules (Pourkheirandish et al. 2020). In this study, the orientation of the PV modules provided shade primarily in the morning. Morning shade coincides with the period when vegetables in hot, arid climates are most photosynthetically active (Lambers and Oliveira 2019). A different yield impact might occur if shade were provided in the afternoon when green chile plants are subject to the highest levels of light and heat stress (Trommsdorff et al. 2022).

In contrast to the significant reduction observed in green marketable yield under PV module shading, other yield categories—including red fruits, fruits affected by BER, diseased fruits, and immature fruits—did not exhibit significant differences between PV module and full sun replicates (Table 3). This suggests that the shading effect was specific to green marketable yield, with no substantial impact on the proportions of nonmarketable yield components. These findings align with previous agrivoltaic studies, which have predominantly focused on marketable yield rather than diseased or nonmarketable yields (Mamun et al. 2022). The absence of significant differences in diseased yields between shaded and full sun replicates is particularly noteworthy, as it indicates that PV module shading does not exacerbate disease incidence in green chile production. This represents a potential benefit for farmers, as it mitigates concerns that reduced light availability might create microclimatic conditions favoring pathogen proliferation. However, the mechanisms underlying this observation remain unclear and warrant further investigation.

The year 2024 demonstrated a significant increase in overall yield across multiple categories (Table 3), including marketable green, red, and BER fruits (P = 0.002, 0.05, and 0.01, respectively). This temporal variation in yield performance may be attributed to the higher proportion of full sun replicates in 2024, which increased the overall amount of harvested area.

The yield category of fruits affected by BCTV exhibited significant temporal variability across the study years. In 2024, a statistically significant difference was observed, with full sun replicates demonstrating a higher incidence of BCTV-affected fruit compared with PV module–shaded replicates (Fig. 14). This suggests that environmental or microclimatic conditions associated with full sun exposure may have influenced the prevalence or severity of BCTV infection during this growing season.

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In contrast, no significant difference in BCTV-affected fruit yield was detected between full sun and PV module replicates in 2023 (Fig. 14). However, a similar trend was observed, with full sun replicates showing a numerically higher incidence of BCTV-affected fruit compared with shaded plots. This consistent pattern across both years, although statistically significant only in 2024, implies that the full sun conditions may create a more favorable environment for BCTV transmission or symptom expression.

This is particularly significant for producers, as BCTV-affected fruit is entirely unmarketable. The observed reduction in beet leafhopper populations and BCTV-affected fruit under PV modules highlights the potential for these systems to serve as an IPM tool. However, further research is necessary to elucidate the underlying mechanisms driving these observations. Key areas of investigation should include the role of microclimatic conditions under PV module shading, such as temperature, humidity, and light intensity, which may influence disease dynamics. Additionally, more in-depth studies on beet leafhopper (Circulifer tenellus) behavior, including vector activity and feeding patterns, are essential to understanding BCTV transmission.