ArticlePlants (Basel, Switzerland)2024
High-Throughput Phenotyping for Agronomic Traits in Cassava Using Aerial Imaging.
Article in Plants (Basel, Switzerland), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
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Who cites it
2 citing papers in PubMed.
- Advances and prospects of genomic-assisted breeding in roots, tubers, and banana crops.Frontiers in plant science · 2026Review
- Orchid mycorrhizal fungus from the Brazilian Cerrado exhibits biocontrol activity against Meloidogyne javanica.Mycorrhiza · 2025Article
Corrections and comments
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Authors and funding
6 authors.
Funding
Abstract
Large-scale phenotyping using unmanned aerial vehicles (UAVs) has been considered an important tool for plant selection. This study aimed to estimate the correlations between agronomic data and vegetation indices (VIs) obtained at different flight heights and to select prediction models to evaluate the potential use of aerial imaging in cassava breeding programs. Various VIs were obtained and analyzed using mixed models to derive the best linear unbiased predictors, heritability parameters, and correlations with various agronomic traits. The VIs were also used to build prediction models for agronomic traits. Aerial imaging showed high potential for estimating plant height, regardless of flight height (
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Registered trials
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