Matthias Meier

Agrophotovoltaic (APV) systems provide a unique opportunity for improving agricultural land-use efficiency by combining crop production with solar energy capture via photovoltaic panels. In-depth information on plant growth patterns within the spatially heterogenous microclimate created by APVs would enable better planning and management within such unconventional systems. Thus, the present study demonstrates the implementation of a customized robot-mounted 3D-multispectral imaging system for monitoring the growth and spectral reflectance patterns of a conventional soybean cultivar ‘Eiko’ (EK) and a chlorophyll-deficient mutant variety ‘MinnGold’ (MG) under an APV system. Weekly trends in canopy morphometric features revealed significant variations in canopy height, surface area, light penetration, and volume across the APV field depending on the proximity to the overhead solar panels for both EK and MG, with plants receiving adequate rainfall and intermittent shade performing the best. Furthermore, although spectral indices exhibited variations between EK and MG due to intrinsic differences in pigmentation, symptoms of stress could be detected for both genotypes within rain-shaded areas of the APV plot. Hence, the present investigation reveals the potential for complementary usage of robotics and machine vision for high-precision high-throughput crop monitoring under APVs, which would help improve crop management within such non-homogenous cultivation systems.

Agrophotovoltaic (APV) systems provide a unique opportunity for improving agricultural land-use efficiency by combining solar energy capture via photovoltaic panels with crop production. However, in-depth information on plant growth patterns within the spatially heterogenous microclimate created by the intermittent shading of APVs is largely missing. In the present study, we implement a customized robot-mounted 3D-multispectral imaging system to closely monitor the growth and spectral reflectance patterns of a conventional soybean cultivar “Eiko” (EK) and a chlorophyll-deficient mutant variety MinnGold (MG) under an APV system. Weekly trends in canopy morphometric features revealed significant variations in plant height, 3D leaf area, light penetration, and canopy volume across the APV field depending on the proximity with the overhead solar panels for both EK and MG, with plants receiving adequate rainfall and intermittent shade performing the best. Furthermore, although spectral indices exhibited variations between EK and MG due to intrinsic differences in pigmentation, symptoms of stress could be detected for both genotypes within rain-shaded areas of the APV plot. Hence, the present investigation depicts the potential for complementary usage of robotics and machine vision for high-precision high-throughput crop monitoring under APVs, which would enable better crop management within such non-homogenous cultivation systems.

Genotype by environment (G × E) interaction is a magnitude change in the performance of a genotype when grown in contrasting environments. The sensitivity of a genotype to different environmental conditions is an important determinant of its suitability for cultivation in a specific environment or across multiple environments. In many nations of the world, where the drive to achieve a net-zero CO₂ emission by 2030 has spurred significant investments in clean energy sources such as photovoltaics with a resultant conversion of some agricultural lands to photovoltaic facilities, there is a need to find the right balance between addressing the food and energy crises. Agri-photovoltaics (APV) offer a sustainable solution by allowing crops to grow underneath photovoltaic panels. However, selection efficiency and repeatability of APV experimental results could be marred by the presence of G × E interaction. The study objective was to identify mungbean genotype(s) with a high yield potential and broad adaptability across APV environments. Five mungbean (Vigna radiata L.) genotypes, Tvr18, Tvr28, Tvr65, Tvr79, and Tvr 83, were assessed under six contrasting APV environments, EPV-R, EPV-D, NPV-R, NPV-D, WPV-R, and WPV-D, at the Agri-PV Food and Energy Training Center, University of Nigeria, Nsukka. The experiment was a split-plot design, with the environment as the whole-plot factor while genotype was the sub-plot factor with five replications. The additive main effects and multiplicative interaction (AMMI) and the Finlay and Wilkinson joint regression analysis confirmed significant genotype, environment, and G × E interaction effects for mungbean seed yield. Two genotypes, Tvr28 and Tvr83 expressed broad adaptability to the APV environments with higher yields (2.60 and 2.50 t ha⁻¹), ranking first and second, respectively. In contrast, the Tvr79 genotype displayed the highest sensitivity (2.95) to environmental variation and was unstable across the environments with higher IPCA1 and ASV scores of −1.17 and 1.39, respectively. The EPV-R recorded the highest yield (2.61) with low interaction effect (0.38), whereas the WPV-D environment had the least yield (1.71) and was the most unstable (−0.48). Conclusively, the Tvr28 and Tvr83 genotypes and the EPV-R environment were the ideal genotypes and environment, respectively, and are therefore recommended for use in APV facilities.

Background: The push for net-zero CO ₂ emission in the energy sector by 2030 has led to massive investments in clean energy sources in several countries. One such investment is in photovoltaics which are substances that convert solar energy into electricity. Due to the large land requirement for the installation of photovoltaic plants, a significant portion of agricultural lands have been converted to photovoltaic facilities in recent times. Land use conflicts between food and energy production are becoming an increasing concern that needs addressing. Agrivoltaics presents an opportunity to integrate crops underneath photovoltaic panels sustainably. The objective of this study was to select genotypes with superior yield advantage and greater stability underneath the APV system. Methods: Five mungbean genotypes, Tvr18, Tvr28, Tvr65, Tvr79, and Tvr 83 were assessed under contrasting APV microenvironments, WPV, EPV and NPV at the National Center for Energy Research, University of Nigeria, Nsukka. The experiment was a split-plot design with APV as the whole-plot factor while genotype was the sub-plot factor with five replications. Results: The additive main effects and multiplicative interaction (AMMI) analysis showed significant genotype, environment, GxE, IPCA1, and IPCA2 effects ( p < 0.05) for seed weight. Two genotypes, Tvr28 (9.92 g) and Tvr83 (9.58 g) recorded higher seed weights across environments. The EPV environment recorded higher seed weight per plant (10.51 g) than NPV (7.58 g) and WPV (5.44 g) environments, respectively. Tvr18 and Tvr65 were the most unstable genotypes across the APV-environments with higher IPCA1 (−1.75 and 1.30, respectively) and ASV (4.02 and 3.00, respectively) scores in contrast to Tvr83 and Tvr28 with the least IPCA1 (0.19 and 0.09) and ASV (1.23 and 1.18, respectively) scores. Hence, Tvr83 and Tvr28 were more stable across the APV microenvironments and were the best in seed yield.

In recent years, more agricultural lands are been converted to photovoltaic (PV) power plants for better return on investment. However, prioritizing energy generation over food production poses a significant threat to the well-being of the rapidly growing global population. Agro-photovoltaics (APV) provide an opportunity to integrate crop production under PV panels. The objective of this study was to investigate the effect of APV system on microclimate, photosynthesis, and agronomic performance of mungbean in a tropical environment. Five mungbean genotypes, Tvr18, Tvr28, Tvr65, Tvr79 and Tvr83 were assessed under three APV micro environments, East-west facing PV (WPV), West-east facing PV (EPV), and no PV (NPV) in a split plot design with 5 replications. Results obtained showed significant reduction (p < 0.05) in photosynthetic active radiation (5–47%), leaf temperature (3–9%), and in the proportion of potentially harmful unregulated energy reaching the reaction centers (19–23%) under the PV (% reduction in WPV > EPV). Relative humidity, photochemical energy conversion, plant height, number of leaves, pods, and seeds were increased significantly (p < 0.05) underneath the EPV compared to NPV. Seed weight also increased non-significantly under EPV while flowering and podding behaviour, leaf area and stem diameter were comparable (p > 0.05) in NPV and EPV. We report for the first time that microclimate, growth, photochemistry and yield performances of mungbean were improved under APV system in a tropical environment. The improved performances of mungbean under EPV compared to WPV suggest that PV orientation is important and should not be overlooked in APV system designs.

We present a new Agri-Horti-PV system installed at the end of 2021 in the brown coal area of North Rhine-Westphalia near Jülich, Germany. The system contains different PV installations: Standard south oriented PV modules with a rainwater harvesting set up and east-west tracker modules, of which one is equipped with a rainwater harvesting setup. For the investigation of plant growth under the PV panels and on the reference areas without PV installations a novel rail system allowing for automatic camera movement is integrated in the Agri-Horti-PV park. Using the camera setup plant growth measurements with high spatio-temporal resolution will be possible. The scientific investigations of crop growth and the influence of variable shading conditions controlled by the tracking system started in the growth season of 2022. Here we present the technical details of the system as well as first results of an experiment carried out with faba beans, assessing impact of the Horti-PV system on growth dynamics and leaf morphology.

The galloping rise in global population in recent years and the accompanying increase in food and energy demands has created land use crisis between food and energy production, and eventual loss of agricultural lands to the more lucrative photovoltaics (PV) energy production. This experiment was carried out to investigate the effect of organic photovoltaics (OPV) and red-foil (RF) transmittance on growth, yield, photosynthesis and SPAD value of spinach under greenhouse and field conditions. Three OPV levels (P0: control; P1: transmittance peak of 0.11 in blue light (BL) and 0.64 in red light (RL); P2: transmittance peak of 0.09 in BL and 0.11 in RL) and two spinach genotypes (bufflehead, eland) were combined in a 3 × 2 factorial arrangement in a completely randomized design with 4 replications in the greenhouse, while two RF levels (RF0: control; RF1: transmittance peak of 0.01 in BL and 0.89 in RL) and two spinach genotypes were combined in a 2 × 2 factorial in randomized complete block design with four replications in the field. Data were collected on growth, yield, photosynthesis and chlorophyll content. Analysis of variance (ANOVA) showed significant reduction in shoot weight and total biomass of spinach grown under very low light intensities as a function of the transmittance properties of the OPV cell used (P2). P1 competed comparably (p > 0.05) with control in most growth and yield traits measured. In addition, shoot to root distribution was higher in P1 than control. RF reduced shoot and total biomass production of spinach in the field due to its inability to transmit other spectra of light. OPV-RF transmittance did not affect plant height (PH), leaf number (LN), and SPAD value but leaf area (LA) was highest in P2. Photochemical energy conversion was higher in P1, P2 and RF1 in contrast to control due to lower levels of non-photochemical energy losses through the Y(NO) and Y(NPQ) pathways. Photo-irradiance curves showed that plants grown under reduced light (P2) did not efficiently manage excess light when exposed to high light intensities. Bufflehead genotype showed superior growth and yield traits than eland across OPV and RF levels. It is therefore recommended that OPV cells with transmittance properties greater than or equal to 11% in BL and 64% in RL be used in APV systems for improved photochemical and land use efficiency.

In the present work, we investigate light-management concepts applied subsequent to the passivation of the Si wafer of planar Si heterojunction solar cells. As a first concept, we apply amorphous silicon based nanophotonic textures at the back side of the Si wafer to realize efficient light trapping. As a second concept, we use a nanoimprint lithography based front side anti-reflection coating to improve the incoupling of light into the solar cell absorber. Both concepts allow for efficient improvements in the short-circuit current densities without degrading the planar passivation layers. As the highlight of this work, we demonstrate planar silicon heterojunction solar cells (thickness ∼ 280 μm) with high passivation quality as well as a short-circuit current density of 38.8 mA/cm².

We investigate the influence of surface texture on the effectiveness of reflectance by intermediate reflectors in thin-film tandem solar cells. Two distinct angular reflection regimes are identified. For large surfaces with large aspect ratios, frustrated total internal reflection or photon tunneling is found to be the dominating mechanism. We show that the parasitic reflection losses of commonly used randomly textured surfaces are explained by these distinct regimes and introduce a spectral reflectance parameter, which serves as a guideline for designing optimized spectrally selective intermediate reflectors.