Register      Login
Functional Plant Biology Functional Plant Biology Society
Plant function and evolutionary biology
RESEARCH ARTICLE

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 B
+ Author Affiliations
- Author Affiliations

A 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.


References

Alenya G, Dellen B, Torras C (2011) 3D modelling of leaves from color and ToF data for robotized plant measuring. In ‘Robotics and automation (ICRA), IEEE International Conference’. pp. 3408–3414. Available at: http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=5980092

Barchi L, Lefebvre V, Sage-Palloix AM, Lanteri S, Palloix A (2009) QTL analysis of plant development and fruit traits in pepper and performance of selective phenotyping. Theoretical and Applied Genetics 118, 1157–1171.
QTL analysis of plant development and fruit traits in pepper and performance of selective phenotyping.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BD1MXktFektrg%3D&md5=f2674993b4a585d1877e8141cdca6b77CAS |

Bink MCAM, van Eeuwijk FA (2009) A Bayesian QTL linkage analysis of the common dataset from the 12th QTLMAS workshop. BMC Proceedings 3, 8

Bink MCAM, Boer MP, ter Braak CJF, Jansen J, Voorrips RE, de Weg WEV (2008) Bayesian analysis of complex traits in pedigreed plant populations. Euphytica 161, 85–96.
Bayesian analysis of complex traits in pedigreed plant populations.Crossref | GoogleScholarGoogle Scholar |

Biskup B, Scharr H, Schurr U, Rascher U (2007) A stereo imaging system for measuring structural parameters of plant canopies. Plant, Cell & Environment 30, 1299–1308.
A stereo imaging system for measuring structural parameters of plant canopies.Crossref | GoogleScholarGoogle Scholar |

Furbank RT (2009) Plant phenomics: from gene to form and function. Functional Plant Biology 36, V–VI.

Granier C, Aguirrezabal L, Chenu K, Cookson SJ, Dauzat M, Hamard P, Thioux J-J, Rolland G, Bouchier-Combaud S, Lebaudy A, Muller B, Simonneau T, Tardieu F (2006) PHENOPSIS, an automated platform for reproducible phenotyping of plant responses to soil water deficit in Arabidopsis thaliana permitted the identification of an accession with low sensitivity to soil water deficit. New Phytologist 169, 623–635.
PHENOPSIS, an automated platform for reproducible phenotyping of plant responses to soil water deficit in Arabidopsis thaliana permitted the identification of an accession with low sensitivity to soil water deficit.Crossref | GoogleScholarGoogle Scholar |

Kolukisaoglu U, Thurow K (2010) Future and frontiers of automated screening in plant sciences. Plant Science 178, 476–484.
Future and frontiers of automated screening in plant sciences.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BC3cXlt1Sju74%3D&md5=997d0fef2c5e4e419a537d9735acea29CAS |

Konishi A, Eguchi A, Hosoi F, Omasa K (2009) 3D monitoring spatio-temporal effects of herbicide on a whole plant using combined range and chlorophyll a fluorescence imaging. Functional Plant Biology 36, 874–879.
3D monitoring spatio-temporal effects of herbicide on a whole plant using combined range and chlorophyll a fluorescence imaging.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BD1MXhtlOgs7rJ&md5=d798808e5b10a15735b4ff4a78c5090cCAS |

Meuwissen THE, Hayes BJ, Goddard ME (2001) Prediction of total genetic value using genome-wide dense marker maps. Genetics 157, 1819–1829.

Polder G, van der Heijden GWAM, Glasbey CA, Song Y, Dieleman JA (2009) Spy-see – advanced vision system for phenotyping in greenhouses.’ (National Physical Laboratory: London)

Rajendran K, Tester M, Roy SJ (2009) Quantifying the three main components of salinity tolerance in cereals. Plant, Cell & Environment 32, 237–249.
Quantifying the three main components of salinity tolerance in cereals.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BD1MXjsVKlsL4%3D&md5=6c1e55ee61a57066f799c2f0f3be9265CAS |

Reuzeau C (2007) TraitMill (TM): a high throughput functional genomics platform for the phenotypic analysis of cereals. In Vitro Cellular & Developmental Biology. Animal 43, S4

Song Y, Glasbey CA, van der Heijden GWAM, Polder G, Dieleman JA (2011) Combining stereo and time-of-flight images with application to automatic plant phenotyping image analysis. In ‘Proceedings of the 17th Scandinavian Conference on Image Analysis. Vol. 6688’. (Eds A Heyden, F Kahl) pp. 467–478. (Springer-Verlag: Berlin)

van Eeuwijk FA, Bink M, Chenu K, Chapman SC (2010) Detection and use of QTL for complex traits in multiple environments. Current Opinion in Plant Biology 13, 193–205.
Detection and use of QTL for complex traits in multiple environments.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BC3cXlsFahs70%3D&md5=e64a0b811713183497f5b948fede8647CAS |

Voorrips RE, Palloix A, Dieleman JA, Bink MCAM, Heuvelink E, Heijden GWAM, van der Vuylsteke M, Glasbey C, Barócsi A, Magán J, van Eeuwijk FA (2010) Crop growth models for the -omics era: the EU-SPICY project. In ‘Advances in genetics and breeding of capsicum and eggplant. Proceedings of the XIVth EUCARPIA Meeting on genetics and breeding of capsicum and eggplant’. (Eds J Prohens, A Rodríguez-Burruezo) pp. 315–321. (Editorial Universidad Politécnica de Valencia: Valencia, Spain)

Walter A, Scharr H, Gilmer F, Zierer R, Nagel KA, Ernst M, Wiese A, Virnich O, Christ MM, Uhlig B, Jünger S, Schurr U (2007) Dynamics of seedling growth acclimation towards altered light conditions can be quantified via GROWSCREEN: a setup and procedure designed for rapid optical phenotyping of different plant species. New Phytologist 174, 447–455.
Dynamics of seedling growth acclimation towards altered light conditions can be quantified via GROWSCREEN: a setup and procedure designed for rapid optical phenotyping of different plant species.Crossref | GoogleScholarGoogle Scholar |