Non-destructive plant phenotyping using a mobile hyperspectral system to assist breeding research: first results

Abstract

Hybrid plants feature a stronger vigor, an increased yield and a better environmental adaptability than their parents, also known as heterosis effect. Heterosis of winter oilseed rape is not yet fully understood and conclusions on hybrid performance can only be drawn from laborious test crossings. Large scale field phenotyping may alleviate this process in plant breeding. The aim of this study was to test a low-cost mobile ground-based hyperspectral system for breeding research to easily access important information on crop status and development. Quantitative relationships between vegetation parameters (above ground fresh and dry matter, leaf area index; FM, DM, LAI) and field reflectance measurements were set up using partial least squares regression. At the time, our data set consists of 102 measurements which were acquired during two growing seasons between 2014 and 2016. Models were first set up using the full spectral range as a best case scenario (400-2400nm). Subsequently, performance was evaluated with reduced range (400-800nm) according to the ground-based mobile system. Model validation was performed by means of leave-one-out cross validation (cv). Rcv² of the PLSR models for FM and DM based on full spectral range was 0.82. For LAI, Rcv² was only 0.52. Confining the spectral range increased prediction errors by 15%, 9%, and 5% respectively. Models were successfully applied to three data sets acquired in April 2015 by our mobile ground-based system.

Plant phenotyping relevance

移動式ハイパースペクトル計測を用いて作物状態・発達を推定し、植生パラメータとの定量関係を構築・検証しており、表現型取得法が研究の中心である。

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