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Light detection and ranging (lidar) scanning tools are available that can make rapid digital estimations of biomass. Voxelization and convex hull are two algorithms used to calculate the volume of the scanned plant canopy, which is correlated with biomass, often the primary trait of interest. Voxelization splits the scans into regular-sized cubes, or voxels, whereas the convex hull algorithm creates a polygon mesh around the outermost points of the point cloud and calculates the volume within that mesh. In this study, digital estimates of biomass were correlated against hand-harvested biomass for field-grown corn, broom corn, and energy sorghum. Voxelization (r = 0.92) and convex hull (r = 0.95) both correlated well with plant dry biomass. Lidar data were also collected in a large breeding trial with nearly 900 genotypes of energy sorghum. In contrast to the manual harvest studies, digital biomass estimations correlated poorly with yield collected from a forage harvester for both voxel count (r = 0.32) and convex hull volume (r = 0.39). However, further analysis showed that the coefficient of variation (CV, a measure of variability) for harvester-based estimates of biomass was greater than the CV of the voxel and convex-hull-based biomass estimates, indicating that poor correlation was due to harvester imprecision, not digital estimations. Overall, results indicate that the lidar-based digital biomass estimates presented here are comparable or more precise than current approaches. [ABSTRACT FROM AUTHOR]

Societal Impact Statement: Transformative agricultural strategies like agrivoltaics (AV) are essential for addressing the pressing global issues of sustainable energy and food production in a changing climate. Conservation‐agrivoltaics (Conservation‐AV) provides the potential to meet these needs while reinforcing natural resources and protecting the environment. It could enhance the ecological benefits of AV by improving soil health and biodiversity. It could create economic opportunities for farmers and increase the resilience and diversity of food crops under changing climate conditions. Furthermore, it could inform stakeholders about the benefits and challenges of implementing conservation agriculture management practices (CAMP) in AV and encourage further exploration and adoption of this innovative approach. Summary: Transformative strategies in agriculture are needed to address urgent global challenges related to energy and food production while reinforcing natural resources and the environment. Agrivoltaics (AV) has emerged in the past decade as one solution to this fundamental challenge of improving energy and food security. AV is defined as the co‐location of solar photovoltaic (PV) panels and crops on the same land to optimize food and energy production simultaneously and sustainably. Here, we propose that AV, together with conservation agriculture management practices (CAMP) strategies can help to intensify food security and energy production while reinforcing natural resources and the environment. Our main assertions in this opinion article are that: (1) AV systems need to overcome several agronomical, environmental, and ecological challenges to intensify food and energy production sustainably; (2) CAMP applied to AV systems can preserve the environment and ensure climate‐resilient food production; (3) implementation of CAMP in AV can lead to long‐term carbon sequestration, lower greenhouse gas emissions, and maintain or increase crop yields while preserving soil health and biodiversity; and (4) adoption of CAMP in AV can bring economic benefits, although challenges need to be overcome. This opinion article proposes a new ecosystem approach to integrate renewable energy and sustainable food production and encourages research on the effects of CAMP on AV systems. [ABSTRACT FROM AUTHOR]

This document is a response to concerns raised by Reershemius and Suhrhoff regarding a study conducted by Kantola et al. The authors of the response acknowledge that Reershemius and Suhrhoff did not find any faults with the derivation in the paper, which they state are factually true. They also mention that Reershemius and Suhrhoff arrived at a similar result in their own unpublished work. The response addresses specific implementation details raised by Reershemius and Suhrhoff and argues that these concerns lack merit. The authors appreciate the constructive engagement and transparency of data. [Extracted from the article]