Unverified paper record
RGB-image method enables indirect selection for leaf spot resistance and yield estimation in a groundnut breeding program in Western Africa.
Frontiers in Plant Science · 4 Aug 2022 · 10.3389/fpls.2022.957061
Abstract
L.) destructive diseases in Ghana. Accurate phenotyping and genotyping to develop groundnut genotypes resistant to Leaf Spot Diseases (LSD) and to increase groundnut production is critically important in Western Africa. Two experiments were conducted at the Council for Scientific and Industrial Research-Savanna Agricultural Research Institute located in Nyankpala, Ghana to explore the effectiveness of using RGB-image method as a high-throughput phenotyping tool to assess groundnut LSD and to estimate yield components. Replicated plots arranged in a rectangular alpha lattice design were conducted during the 2020 growing season using a set of 60 genotypes as the training population and 192 genotypes for validation. Indirect selection models were developed using Red-Green-Blue (RGB) color space indices. Data was collected on conventional LSD ratings, RGB imaging, pod weight per plant and number of pods per plant. Data was analyzed using a mixed linear model with R statistical software version 4.0.2. The results showed differences among the genotypes for the traits evaluated. The RGB-image method traits exhibited comparable or better broad sense heritability to the conventionally measured traits. Significant correlation existed between the RGB-image method traits and the conventionally measured traits. Genotypes 73-33, Gha-GAF 1723, Zam-ICGV-SM 07599, and Oug-ICGV 90099 were among the most resistant genotypes to ELS and LLS, and they represent suitable sources of resistance to LSD for the groundnut breeding programs in Western Africa.
Plant phenotyping relevance
RGB画像を用いた高スループット表現型解析法を開発・検証し、葉斑病評価と収量構成要素推定への有効性を比較検証しており、表現型取得・推定手法が研究の中心である。
abstractexplore the effectiveness of using RGB-image method as a high-throughput phenotyping tool to assess groundnut LSD and to estimate yield components
abstractIndirect selection models were developed using Red-Green-Blue (RGB) color space indices.
abstractThe RGB-image method traits exhibited comparable or better broad sense heritability to the conventionally measured traits.
Code and data availability
The paper's raw phenotyping data (conventional LSD ratings, RGB imaging indices, pod yield traits) are not deposited in any public repository; the data availability statement says they will be provided by the authors on request. The tools mentioned (Breedpix 2.0/CIMMYT plugin, Fiji, R corrplot) are third-party generic,
No evidence-backed public reproduction asset is currently recorded.
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