The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/plants13233288/s1 , Figure S1: Quantitative trait loci (QTL) analysis associated with tiller angle in rice using RIL population; Figure S2: QTL distribution for tiller angle across different development stages.
Open resource ↗lines:89-100Unverified paper record
Application of Image-Based Phenotyping for QTL Identification of Tiller Angle in Rice ( Oryza sativa L.).
Plants · 22 Nov 2024 · 10.3390/plants13233288
Abstract
Rice tiller angle is a key agronomic trait that regulates plant architecture and plays a critical role in determining rice yield. Given that tiller angle is regulated by multiple genes, it is important to identify quantitative trait loci (QTL) associated with tiller angle. Recently, with the advancement of imaging technology for plant phenotyping, it has become possible to quickly and accurately measure agronomic traits of breeding populations. In this study, we extracted tiller angle and various image-based parameters from Red-Green-Blue (RGB) images of a recombinant inbred line (RIL) population derived from a cross between Milyang23 (Indica) and Giho (Japonica). Correlations among the obtained data were analyzed, and through dynamic QTL mapping, five major QTLs (qTA1, qTA1-1, qTA2, qTA2-1, and qTA9) related to tiller angle were detected on chromosomes 1, 2, and 9. Among them, 26 candidate genes related to auxin signaling and plant growth, including the TAC1 (Tiller Angle Control 1) gene, were identified in qTA9 (RM257-STS09048). These results demonstrate the potential of image-based phenotyping to overcome the limitations of traditional manual measurements in crop structure research. Furthermore, the identification of key QTLs and candidate genes related to tiller angle provides valuable genetic insights for the development of high-yielding varieties through crop morphology control.
Plant phenotyping relevance
RGB画像からイネの分げつ角度と画像パラメータを抽出する画像ベース表現型解析を、育種集団で実質的に適用・評価しており、表現型取得法が中心です。
abstractRecently, with the advancement of imaging technology for plant phenotyping, it has become possible to quickly and accurately measure agronomic traits of breeding populations.
abstractIn this study, we extracted tiller angle and various image-based parameters from Red-Green-Blue (RGB) images of a recombinant inbred line (RIL) population
abstractThese results demonstrate the potential of image-based phenotyping to overcome the limitations of traditional manual measurements in crop structure research.
Code and data availability
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