Work

Mechanical feature-based modeling for an agricultural plant-leaf geometry: A novel approach

Year: 2026
Type: article
Abstract: Constructing a three-dimensional (3D) accurate model of a plant leaf is becoming more and more important in agriculture because the 3D model has the potential to advance our understanding of the relationship between plant growth and living conditions by means of numerical predictions. The current endeavors are unable to implement the prediction, although they can model the 3D leaf geometry. Inspired by the similar attributes and morphology (though this may be a different concept) between plants and mechanical systems, this study has proposed to try applying feature-based modeling in mechanical engineering to construct the 3D model of a leaf in agriculture for further predictions. To achieve this, the authors used a combination of the mechanical feature modeling and the multi-level comparisons based on a leaf sample inserted from the Shu-ChaZao tea tree as a research object. First, all the leaf geometries, affecting the numerical prediction, were recognized and chosen. Next, the chosen geometries were measured by using a digital microscope and a vernier caliper with high accuracy, respectively. Next, the feature-based modeling, including the feature-based solid modeling (such as cutting, stretching, and sweeping) and the feature-based surface modeling (such as texture mapping, rotation transforming, symmetric transforming, and rendering), was used for the construction of the leaf geometry. Finally, the constructed leaf geometry was compared with the real sample, and then with the past measurements through numerical prediction. The demonstration case studies indicate the validity of the mechanical feature modeling used in agriculture and provide guidelines for modeling a large variety of plant leaves for numerical predictions.
Source: AIP Advances
Language: English
Subfield: Plant Science
Open Access status: gold
Estimated APC paid: $1,350
Award: G257683502
OpenAlex ID: W7151967705
FWCI:
Cites: 22
Cited by:
Related to: