Using Sensors and Unmanned Aircraft Systems for High-Throughput Phenotyping of Biomass in Perennial Ryegrass Breeding Trials

Abstract

Increasing herbage biomass is the predominant objective for pasture plant breeding programs. Three types of field trials are commonly involved during forage plant breeding, i.e. individually spaced plants, row plot, and sward trials. Assessments of biomass production at individual plant, row plot and sward plot levels are through visual scoring and/or cutting of biomass manually or mechanically. Both visual scoring and cutting of plants are laborious, time consuming and costly. The development of sensor technology such as multispectral sensors and unmanned aircraft systems (UAS) provide the opportunity to accelerate the process of biomass evaluation and to increase throughput, improve resolution, reduce time and cost. We tested either the handheld Trimble GreenSeeker® or Parrot Sequoia multispectral sensors attached to a 3DR Solo Quadcopter to assess biomass in perennial ryegrass field trials sown as spaced individual plants, row plots, and simulated sward plots. Significant correlations were observed between visual score and normalized difference vegetation index (NDVI) in a spaced plant field trial and between biomass yield and NDVI in row plot and sward trials. NDVI obtained from multispectral sensors and UAS can replace visual scoring in spaced plant trials. It was also a valuable proxy for yield estimation in row plot and sward trials. The ranking of cultivars by NDVI was correlated with the ranking by biomass, although the ranking order was not in complete agreement. Multispectral sensors and UAS also allow tracking productivity over time for perennial pasture, in particular, the regrowth after grazing or clipping and to explore seasonal changes and responses to environmental factors such as precipitation. These technologies will assist in transition for the forage grass breeding from pen and notepad to digital and data era.

Plant phenotyping relevance

多光谱センサーとUASを用いて、育種試験における植物バイオマスをNDVIから推定・評価する方法を開発および検証しており、表現型取得が研究の中心である。

Code and data availability

The supplied blocks contain no public phenotype datasets, images, code, models, or supplement links for this paper. The only URL present is the article's own DOI, and the text mentions in-house segmentation code and GenStat analysis without any availability statement or public repository.

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