AgroLD: a knowledge graph for the plant sciences

The demand for food is expected to grow substantially in the coming years. To address this challenge, especially in the context of climate change, a deeper understanding of genotype-phenotype relationships is crucial for improving crop yields. Recent advances in high-throughput technologies have tra...

Descripción completa

Detalles Bibliográficos
Autores principales: Pierre, Larmande, Bertrand, Pittolat, Ndomassi, Tando, Yann, Pomie, Bill Gates, Happi Happi, Guignon, Valentin, Manuel, Ruiz
Formato: Journal Article
Lenguaje:Inglés
Publicado: BioMed Central 2025
Materias:
Acceso en línea:https://hdl.handle.net/10568/177034
Descripción
Sumario:The demand for food is expected to grow substantially in the coming years. To address this challenge, especially in the context of climate change, a deeper understanding of genotype-phenotype relationships is crucial for improving crop yields. Recent advances in high-throughput technologies have transformed the landscape of plant science research. However, there is an urgent need to integrate and consolidate complementary data to understand the biological system. Results We introduce AgroLD, a knowledge graph that uses Semantic Web technologies to seamlessly integrate plant science data. AgroLD is designed to facilitate hypothesis formulation and validation within the scientific community. With approximately 1.08 billion triples, it integrates and annotates data from more than 151 datasets across 19 distinct sources. Conclusion The overarching goal is to provide a specialized knowledge platform addressing complex biological questions in the plant sciences, including gene participation in plant disease resistance and adaptive responses to climate change.