Real-time, non-destructive and in-field foliage yield and growth rate measurement in perennial ryegrass (Lolium perenne L.)

作者：Kioumars Ghamkhar, Kenji Irie, M. Hagedorn, Jeffrey Hsiao, Jaco Fourie, Steve Gebbie, Valerio Hoyos‐Villegas, Richard George, Alan V. Stewart, Courtney Inch, Armin Werner, Brent Barrett · 发表于：Plant Methods · 年份：2019 · DOI：10.1186/s13007-019-0456-2 · 被引用次数：30 · 研究领域：Remote Sensing and LiDAR Applications、Forest ecology and management、Plant Water Relations and Carbon Dynamics

In-field measurement of yield and growth rate in pasture species is imprecise and costly, limiting scientific and commercial application. Our study proposed a LiDAR-based mobile platform for non-invasive vegetative biomass and growth rate estimation in perennial ryegrass ( Lolium perenne L.). This included design and build of the platform, development of an algorithm for volumetric estimation, and field validation of the system. The LiDAR-based volumetric estimates were compared against fresh weight and dry weight data across different ages of plants, seasons, stages of regrowth, sites, and row configurations. The project had three phases, the last one comprising four experiments. Phase 1: a LiDAR-based, field-ready prototype mobile platform for perennial ryegrassrecognition in single row plots was developed. Phase 2: real-time volumetric data capture, modelling and analysis software were developed and integrated and the resultant algorithm was validated in the field. Phase 3. LiDAR Volume data were collected via the LiDAR platform and field-validated in four experiments. Expt.1: single-row plots of cultivars and experimental diploid breeding populations were scanned in the southern hemisphere spring for biomass estimation. Significant ( P < 0.001) correlations were observed between LiDAR Volume and both fresh and dry weight data from 360 individual plots (R 2 = 0.89 and 0.86 respectively). Expt 2: recurrent scanning of single row plots over long time intervals of a few weeks...