Abstract
SummaryRapeseed is the second most important oil crop species and is widely cultivated worldwide. However, overcoming the ‘phenotyping bottleneck’ has remained a significant challenge. A clear goal of high‐throughput phenotyping is to bridge the gap between genomics and phenomics. In addition, it is important to explore the dynamic genetic architecture underlying rapeseed plant growth and its contribution to final yield. In this work, a high‐throughput phenotyping facility was used to dynamically screen a rapeseed intervarietal substitution line population during two growing seasons. We developed an automatic image analysis pipeline to quantify 43 dynamic traits across multiple developmental stages, with 12 time points. The time‐resolved i‐traits could be extracted to reflect shoot growth and predict the final yield of rapeseed. Broad phenotypic variation and high heritability were observed for these i‐traits across all developmental stages. A total of 337 and 599 QTLs were identified, with 33.5% and 36.1% consistent QTLs for each trait across all 12 time points in the two growing seasons, respectively. Moreover, the QTLs responsible for yield indicators colocalized with those of final yield, potentially providing a new mechanism of yield regulation. Our results indicate that high‐throughput phenotyping can provide novel insights into the dynamic genetic architecture of rapeseed growth and final yield, which would be useful for future genetic improvements in rapeseed.
Highlights
Rapeseed (Brassica napus; canola) is a relatively recent allopolyploid species formed by interspecific hybridization between Brassica rapa and Brassica oleracea ~7500 years ago (Chalhoub et al, 2014)
Compared with the other models, the power model (ln (FW) = a + b 9 ln(m)) had a higher R2, and lower mean absolute percentage error (MAPE) and standard deviation of the absolute percentage error (SDAPE), for both dry weight and fresh weight in the two growing seasons (Tables S2 and S3), which was validated by a 10-fold cross-validation approach (Tables S4 and S5)
These results suggested that the i-trait projected area exhibited good correlation with manually measured rapeseed shoot biomass
Summary
Rapeseed is the second most important oil crop species and is widely cultivated worldwide. It is important to explore the dynamic genetic architecture underlying rapeseed plant growth and its contribution to final yield. A high-throughput phenotyping facility was used to dynamically screen a rapeseed intervarietal substitution line population during two growing seasons. We developed an automatic image analysis pipeline to quantify 43 dynamic traits across multiple developmental stages, with 12 time points. The time-resolved i-traits could be extracted to reflect shoot growth and predict the final yield of rapeseed. Broad phenotypic variation and high heritability were observed for these i-traits across all developmental stages. Our results indicate that high-throughput phenotyping can provide novel insights into the dynamic genetic architecture of rapeseed growth and final yield, which would be useful for future genetic improvements in rapeseed
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
