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Record W4414486746 · doi:10.1016/j.solener.2025.114006

Transparency effects in agrivoltaics lettuce cultivation using uniform/non-uniform semitransparent photovoltaic modules in controlled environments

2025· article· en· W4414486746 on OpenAlexafffundabout
Uzair Jamil, Md Motakabbir Rahman, Koami Soulemane Hayibo, Linda Alrayes, Eric Fordjour, Raymond Thomas, Joshua M. Pearce

Bibliographic record

VenueSolar Energy · 2025
Typearticle
Languageen
FieldEnvironmental Science
TopicPhotovoltaic Systems and Sustainability
Canadian institutionsWestern University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsTransparency (behavior)Photovoltaic systemPhotosynthetically active radiationCadmium telluride photovoltaicsYield (engineering)TransmittanceSolar energyRadiation

Abstract

fetched live from OpenAlex

Agrivoltaic systems offer a dual-use solution to land constraints by integrating food and energy production, yet the influence of light distribution characteristics—particularly uniformity—on crop performance remains poorly understood. This study investigates the physiological and yield responses of lettuce under two contrasting agrivoltaic lighting strategies while maintaining comparable transparency: (1) uniform illumination from cadmium telluride (CdTe) thin-film photovoltaic (PV) modules and (2) non-uniform illumination from bifacial crystalline silicon (c-Si) PV modules with alternating cell and glass regions. Experiments were conducted using CdTe modules at 40 %, 50 %, and 70 % transparency and bifacial c-Si modules at 44 % and 69 % transparency. Key parameters measured include photosynthetically active radiation (PAR), gas exchange metrics (photosynthesis rate, stomatal conductance, intercellular CO 2 , transpiration), and morphological traits (plant height, leaf count, fresh weight). Results reveal that 69 % transparent c-Si modules not only preserved lettuce yield relative to open-field controls but achieved a 3.6 % enhancement. Conversely, CdTe modules of similar transparency caused a 6 % yield reduction, underscoring the importance of light non-uniformity in optimizing plant response. These findings demonstrate that spatial light heterogeneity – characteristic of c-Si systems – can enhance crop performance, presenting an opportunity for sustainable intensification. Scaling this technology across Canada’s lettuce-growing regions could generate 1,200 MW of solar power while boosting agricultural revenue by CAD $20 million annually, with an additional CAD $30 million from solar land leasing. This study supports the integration of non-uniform, semi-transparent PV modules as a viable pathway toward synergistic energy-agriculture systems for a sustainable future.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.006
GPT teacher head0.223
Teacher spread0.217 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations10
Published2025
Admission routes3
Has abstractyes

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