SPICY: towards automated phenotyping of large pepper plants in the greenhouse
Gerie van der Heijden A E , Yu Song B , Graham Horgan C , Gerrit Polder A , Anja Dieleman A , Marco Bink A , Alain Palloix D , Fred van Eeuwijk A and Chris Glasbey BA Wageningen UR, Droevendaalsesteeg 1, 6708 PB, Wageningen, The Netherlands.
B BioSS, King’s Buildings, Edinburgh EH9 3JZ, UK.
C BioSS, Rowett Institute, Aberdeen AB21 9SB, UK.
D INRA, UR1052 GAFL, BP 94, F-84143 Montfavet cedex, France.
E Corresponding author. Email: gerie.vanderheijden@wur.nl
Functional Plant Biology 39(11) 870-877 https://doi.org/10.1071/FP12019
Submitted: 20 January 2012 Accepted: 2 April 2012 Published: 29 May 2012
Abstract
Most high-throughput systems for automated plant phenotyping involve a fixed recording cabinet to which plants are transported. However, important greenhouse plants like pepper are too tall to be transported. In this research we developed a system to automatically measure plant characteristics of tall pepper plants in the greenhouse. With a device equipped with multiple cameras, images of plants are recorded at a 5 cm interval over a height of 3 m. Two types of features are extracted: (1) features from a 3D reconstruction of the plant canopy; and (2) statistical features derived directly from RGB images. The experiment comprised 151 genotypes of a recombinant inbred population of pepper, to examine the heritability and quantitative trait loci (QTL) of the features. Features extracted from the 3D reconstruction of the canopy were leaf size and leaf angle, with heritabilities of 0.70 and 0.56 respectively. Three QTL were found for leaf size, and one for leaf angle. From the statistical features, plant height showed a good correlation (0.93) with manual measurements, and QTL were in accordance with QTL of manual measurements. For total leaf area, the heritability was 0.55, and two of the three QTL found by manual measurement were found by image analysis.
Additional keywords: heritability, image analysis, stereovision, time-of-flight range imaging, QTL.
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