Ontology-Based Approach for Modeling Plant Growth Experiments

Understanding the complexities of plant growth experiments is crucial for advancements in agriculture and environmental science. However, the lack of standardized methods for documenting and analyzing plant growth experiments often hinders the reproducibility and comparability of research findings. To address this, we developed a specialized ontology that provides a structured framework for capturing key elements of plant growth studies. Our approach began with a thorough literature review to identify core components such as plant species, environmental conditions, treatments, and observations. These components aligned with existing ontologies within the Open Biological and Biomedical Ontologies (OBO) framework to ensure consistency with current standards. The developed ontology was implemented using experimental data, demonstrating its practical utility in organizing and interpreting complex experimental data. Validation of the ontology confirmed its effectiveness in enhancing the clarity, reproducibility, and comparability of plant growth experiments. This research offers a valuable tool for researchers, contributing to more standardized and reliable plant science studies.