Application note
Computer vision under inactinic light for hypocotyl–radicle separation with a generic gravitropism-based criterion

https://doi.org/10.1016/j.compag.2014.12.001Get rights and content

Highlights

  • Seedling heterotrophic growth monitoring is done by means of computer vision.

  • A separation of radicle and hypocotyl is performed in inactinic light.

  • This is obtained with a generic criterion based on gravitropism.

  • This allows high-throughput phenotyping equipment for analysis of seeds quality.

Abstract

This article proposes a computer-vision based protocol, useful to contribute to high-throughput automated phenotyping of seedlings during elongation, the stage following germination. Radicle and hypocotyl are two essential organs which start to develop at this stage, with the hypocotyl growing towards the soil surface and the radicle exploring deeper layers for nutrient absorption. Early identification and measurement of these two organs are important to the characterization of the plant emergence and to the prognosis of the adult plant. In normal conditions, this growth process of radicle and hypocotyl takes place in the soil, in the dark. Identification and measurement of these two organs are therefore challenging, because they need to be achieved with no light that could alter normal growth conditions. We propose here an original protocol exploiting an inactinic green light, produced by a controlled LED source, coupled to a standard low-cost gray-level camera. On the resulting digital images, we devise a simple criterion based on gravitropism and amenable to direct computer implementation. The automated criterion, through comparison with the performance of human experts, is demonstrated to be efficient for the detection and separation of radicle and hypocotyl, and generic for various species of seedlings. Our protocol especially brings improvement in terms of cost reduction over the current method found in the recent literature which resorts to higher-cost passive thermal imaging to perform the same task in the dark, and that we also consider here for comparison. Our protocol connected to automation of image acquisition, can serve to improve high-throughput phenotyping equipments for analysis of seed quality and genetic variability.

Introduction

Seedling heterotrophic growth is a crucial stage of the development of plants. After sowing, two successive stages have to occur starting with germination until the radicle protrudes out of the seed coat and then the heterotrophic growth in the soil until the seedling emerges out of the soil. In field conditions, germination and heterotrophic seedling growth stages Taiz and Zeiger (2010) are not easily observable and diagnosis on sources of seedling emergence failure is thus difficult, especially the separation of the respective impacts of the two stages in sowing failures. Non invasive monitoring of seedling growth that would help for a better analysis of seed quality variations is accessible in laboratory conditions with computer vision machines A common imaging system, reported in Jaffe et al., 1985, Ishikawa and Evans, 1997, Walter et al., 2002, Kimura and Yamasaki, 2003, Wang et al., 2009a, French et al., 2009, Belin et al., 2011, Subramanian et al., 2013 with various levels of automation, consists in monitoring a set of seedlings positioned on a row in a vertically settled box with agar gel. A backlight system associated with a camera then produces sequences of images of seedling during growth. From such image sequences, the temporal evolution of the length of the seedling is measurable with classical image processing such as binary image skeletonisation. The studies, made possible by such computer vision systems, target various biological processes during autotrophic growth and including plant gravitropism (Jaffe et al., 1985, Ishikawa and Evans, 1997, Subramanian et al., 2013), hypocotyl elongation in controlled light and temperature conditions (Walter et al., 2002), root length and diameter measurements (Kimura and Yamasaki, 2003, French et al., 2009), photomorphogenesis (Wang et al., 2009a). When used during the heterotrophic growth, a major limitation of these computer vision tools is the need for light in the image acquisition step. Normally, the seedling grows in the soil in the dark, and if exposed to light, its upper parts stop elongating because of the seedling light receptors, and new leaves expand. Therefore, if light is used to monitor heterotrophic growth of seedling, it has to mimic obscurity for plant, i.e. to be non “perceived” or absorbed by plant cells. We define such a light as inactinic. Some authors use infrared LED to work in absence of light visible to human eye and also because it is known in the autotrophic growth that the leaves of the plants are sensitive to the contrast between red and infrared light (Smith, 2000). This strategy however is not suited to mimic obscurity for plant during heterotrophic growth. Recently, it has been shown that seedling elongation was accessible with computer vision in complete absence of light, thanks to the use of passive thermal imaging (Belin et al., 2011, Belin et al., 2014). From thermal contrasts, Belin et al. (2011) shows that it is possible to segment the seedling in the dark and also that it is possible to discriminate in the seedling two sub parts: the radicle and the hypocotyl. Following a gravitropic response, the upper part of the seedling, the hypocotyl, grows to reach the light and activates photosynthesis, while the lower part of the seedling, the radicle, grows deeper to anchor in the soil and provide access to water and nutrients. It is important for plant phenotyping to identify hypocotyl and radicle early after their formation in the seedling, and to follow their development during seedling elongation. Such observations carry useful relevance for the better understanding of variations in plant emergence. The elongation rates of the radicle and the hypocotyl have been demonstrated as key input parameters to predict crop emergence in the soil in various models, e.g. Forcella et al., 2000, Dürr et al., 2001, Brunel-Muguet et al., 2011. The separation of radicle and hypocotyl obtained from thermal contrasts established in Belin et al. (2011) can be used as a reference for very precise measurements, but there are limitations in the use of thermal imaging to monitor seedling growth which are the high cost of thermal imaging and the rather limited spatial resolution of thermal cameras impacting the throughput of such phenotyping systems.

In this study, we address the separation of the hypocotyl and radicle of seedling in elongation with a high resolution imaging system working with inactinic lighting conditions in the visible spectrum. We consider a green LED technology for the imaging system and propose to investigate the inactinic properties of such lighting. We introduce an image processing algorithm based on the prior information of gravitropism to separate radicle and hypocotyl in these lighting conditions, and demonstrate results in accordance with the thermal contrasts and with the visual appreciation by human experts. The computer vision tool presented is shown generically efficient for various seedling species.

Section snippets

Imaging systems

We use two different imaging systems. The main imaging system is an original system we propose with inactinic green light and gravitropism-based image processing criterion to distinguish two organs: radicle and hypocotyl. The second imaging system based on thermal imaging is only used to compare results obtained with main imaging system according to the distinction between organs. The two different imaging systems are acquiring images at a sampling time period of 2 h during time periods of 50 to

Inactinic properties of green LED lighting

We first demonstrate the inactinic properties of green LED light. As visible in Table 1, the study, realized on 30 seedlings of M. truncatula, shows no significant effect of green LED on seedlings development by comparison with development in darkness. This is specially true after 4 days which approximately corresponds to the duration of the monitoring presented in this article.

Validation of automated measurements by confrontation with experts notation

Since no impact of the green LED light is observed on seedlings development, we now assess the image processing

Conclusion

For the automated phenotyping of seedling by computer vision the separation between hypocotyl and radicle is an important step not routinely handled by standard image analysis systems. To contribute on this important phenotyping task, we have proposed here a green LED imaging system associated with a simple criterion based on the recording of the germination point. We have tested the validity and robustness of this criterion by performing hypocotyl–radicle separation on computer images from

Acknowledgment

This work received supports of “Région des Pays de la Loire” in the framework of Phenotic project and from the French Government supervised by the “Agence Nationale de la Recherche” in the framework of the program “Investissements d’Avenir” under reference ANR-11-BTBR-0007 (AKER program). Landry BENOIT gratefully acknowledges financial support from Angers Loire Métropole and GEVES-SNES for the preparation of his PhD. We are grateful to Lydie LEDROIT for her precious technical assistance.

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    The first three authors contributed equally to the work.

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