Abstract

Agrivoltaics, the integration of solar energy generation with agricultural production, offers a sustainable solution to the growing competition for land between food production and renewable energy. Solar panels installed a couple of meters above the ground allow space for crops to grow beneath them, providing shade that can affect crop yield. The extent and nature of this effect vary by crop type and environmental conditions, and understanding these dynamics is crucial to optimizing agrivoltaic systems. This study investigates the impact of shade on crop yield across different crop types and climatic zones, focusing on how varying levels of reduction in solar radiation (RSR) influence agricultural productivity in agrivoltaic systems. The research employed a multiple linear regression model to analyze data from a meta-analysis of crop yield responses to shading, exploring interactions between RSR, crop type, and plant hardiness zones. The findings reveal that yield responses to shade are significantly different across crop types. Additionally, while climatic factors such as plant hardiness zones were considered, they did not show clear trends in yield response, suggesting that other environmental variables may play a more significant role in explaining yield variability. This analysis classified crops into three categories based on their shade sensitivity: berries, fruits, and fruity vegetables are categorized as shade benefiting, C3 cereals, forages, leafy vegetables are shade tolerant, and maize and grain legumes are shade susceptible. These results highlight the importance of crop-specific considerations in agrivoltaic design to maximize agricultural productivity while supporting renewable energy generation.

Advisor

Huang, Qimin

Department

Statistical and Data Sciences

Disciplines

Data Science | Environmental Sciences | Statistical Models | Sustainability

Publication Date

2025

Degree Granted

Bachelor of Arts

Document Type

Senior Independent Study Thesis

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