Field-measured canopy height may not be as accurate and heritable as believed: evidence from advanced 3D sensing.

Plant Methods

Plant Phenomics Research Centre, Academy for Advanced Interdisciplinary Studies, Collaborative Innovation Centre for Modern Crop Production Co-Sponsored By Province and Ministry, College of Agriculture, Nanjing Agricultural University, Nanjing, 210095, China.

Published: April 2023

AI Article Synopsis

  • - This study investigates the effectiveness of various 3D sensing technologies for measuring canopy height (CH) in crops compared to traditional field measurements, highlighting the importance of CH in crop breeding and production.
  • - It compares data from terrestrial laser scanning (TLS), backpack laser scanning (BLS), gantry laser scanning (GLS), and digital aerial photogrammetry (DAP) across 1920 plots and 120 crop varieties, finding strong correlations between measurements.
  • - The research reveals that while all 3D sensing methods are reliable, those techniques demonstrate even higher heritability values for CH than traditional field measurements, suggesting they could improve accuracy in crop breeding applications.

Article Abstract

Canopy height (CH) is an important trait for crop breeding and production. The rapid development of 3D sensing technologies shed new light on high-throughput height measurement. However, a systematic comparison of the accuracy and heritability of different 3D sensing technologies is seriously lacking. Moreover, it is questionable whether the field-measured height is as reliable as believed. This study uncovered these issues by comparing traditional height measurement with four advanced 3D sensing technologies, including terrestrial laser scanning (TLS), backpack laser scanning (BLS), gantry laser scanning (GLS), and digital aerial photogrammetry (DAP). A total of 1920 plots covering 120 varieties were selected for comparison. Cross-comparisons of different data sources were performed to evaluate their performances in CH estimation concerning different CH, leaf area index (LAI), and growth stage (GS) groups. Results showed that 1) All 3D sensing data sources had high correlations with field measurement (r > 0.82), while the correlations between different 3D sensing data sources were even better (r > 0.87). 2) The prediction accuracy between different data sources decreased in subgroups of CH, LAI, and GS. 3) Canopy height showed high heritability from all datasets, and 3D sensing datasets had even higher heritability (H = 0.79-0.89) than FM (field measurement) (H = 0.77). Finally, outliers of different datasets are analyzed. The results provide novel insights into different methods for canopy height measurement that may ensure the high-quality application of this important trait.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC10069135PMC
http://dx.doi.org/10.1186/s13007-023-01012-2DOI Listing

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