Repeatability and Heritability of UAV-Derived Canopy Traits in a Cassava Breeding Population Using Time-Series Data from Two Consecutive Growing Seasons

Abstract

Cassava is a major staple crop in tropical regions, particularly in Sub-Saharan Africa, yet its productivity remains constrained by genetic and agronomic limitations. A major bottleneck in cassava breeding is the difficulty of accurately phenotyping agronomic traits under field conditions using conventional, labor-intensive methods. Here, we evaluated the potential of uncrewed aerial vehicle (UAV)-based phenotyping to quantify canopy growth traits and assess their genetic relevance under realistic field conditions. For this, multi-temporal UAV imagery was collected over two growing seasons (2018-2019 and 2019-2020) in a panel of 46 cassava genotypes planted in fields of the International Institute for Tropical Agriculture (IITA), Nigeria. Canopy height, canopy volume, and their relative growth rates (RGRh and RGRv) were extracted at the plot-level, and their seasonal dynamics and canopy-yield relationships were further assessed across developmental stages and environmental conditions. Repeatability (R) and broad-sense heritability (H2) were estimated using a linear mixed model (LMM) that partitioned genetic, genotype-by-year, and residual variance components, enabling the evaluation of both measurement reliability and genetic signal. Overall, UAV-derived growth dynamics were found to exhibit comparable patterns across genotypes, reflecting shared seasonal growth trajectories, while canopy-yield relationships varied with developmental stage and environmental conditions. In terms of genetic metrics, R was high for all UAV-derived traits (R = 0.68-0.69), indicating reliable genotype-level assessment across replicates and seasons. In contrast, H2 differed substantially among traits. Canopy volume (H2 = 0.64) and canopy height (H2 = 0.58) exhibited moderate-to-high heritability, reflecting strong genotype effects and comparatively moderate genotype-by-year interactions. However, their relative growth rates showed near-zero H2 values, driven primarily by genotype-by-year interaction, indicating a dominant environmental influence. These results demonstrate that UAV-derived canopy height and volume provide a consistent basis for genetic differentiation of cassava genotypes across environments, supporting their use in selection, whereas growth-rate traits are better suited for characterizing growth plasticity and genotype-by-environment interactions.

Plant phenotyping relevance

UAV画像からキャッサバの樹冠高さ・体積・相対成長率を抽出し、再現性と遺伝率を検証することが研究の中心であり、実質的な植物フェノタイピング手法の評価に該当する。

Code and data availability

The supplied blocks describe UAV imagery collection, trait extraction, and mixed-model analysis, but contain no data availability statement, public repository deposit, or author code/workflow URL. The NASA POWER weather portal is a generic external data source, not a paper-specific asset.

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