Plant phenotyping is the comprehensive assessment of complex plant traits including their architecture. Classical methods are used to study variability, adaptation to environmental conditions and pace of growth during the vegetation period. So far, plant phenotyping has been mainly limited to crop plants or the model plant Arabidopsis thaliana
(L.) Heynh [1
]. In many cases, classical biometric measurement methods are sufficient. However, there are plants whose complex spatial structure and susceptibility to damage make employing conventional measurement techniques impossible or exceedingly difficult. Therefore, there is a need for new platforms and solutions that enable phenotypic evaluation of such species. In such cases, non-contact measurement techniques need to be used: preparation of a three-dimensional (3D) computer model (digitalization) and capturing plant traits based on it [1
One group of plants that has not been used as an object for 3D phenotyping is xerophytes. Representatives of this remarkable group are interesting for several reasons. These plants show various morphological, anatomical and physiological adaptations to living in dry conditions and in sustaining an intensive herbivory [3
]. They constitute the main vegetation in some desert and semi-desert environments and are therefore a subject of intensive ecological study [8
]. Their medicinal properties are recognized by both traditional and contemporary medicine as well as veterinary science [9
Xerophytes are also desirable ornamental plants worldwide. The demand for these plants is so high that their existence in the wild is threatened [13
]. Therefore, many xerophytes, including the whole cacti family and genera Aloe
L. and Pachypodium
], are protected by international law under the Washington Convention (CITES) as well as by national laws. Therefore, customs officers must be able to recognize them properly to prevent illegal traffic. The diversity of these plants is, however, so great that only specialists are able to recognize them and classify them accordingly. Comprehensive virtual guides that would enable rapid and simple identification of these plants do not exist.
Climate change as well population growth have created an urgent need for sustainable high-yield crop production. Phenotypic studies of plants adapted to difficult environmental conditions can be helpful in finding new ways for crop improvement [16
Various types of scanners make non-contact plant digitalization possible. Most often they work by casting structured light in various patterns onto the object and recording the images (Figure 1
]. On the basis of disruptions in the pattern caused by the object’s surface, a three-dimensional point cloud is determined, which is further triangulated into the form of a triangle mesh. The triangle mesh computer model is then processed to determine morphological parameters of interest.
Non-contact measurements of selected characteristics are possible using the Ubiquitous Sensor Network proposed by Suk et al. [18
]. An example of image-based plant phenotyping on a much larger scale was presented by Kircherer et al. [19
], and numerous additional examples can be found [1
Scanning larger objects is feasible with the use of, for instance, a Kinect scanner [24
]. Recently, the photogrammetric method for creating computer models has been gaining popularity. It uses a previously captured set of images. There are no limits to the size of objects: the only restriction is the ability to take a photograph. Professional photographic equipment is not required, only a digital camera is necessary [25
]. These scanning methods require relatively low-cost devices which offer acceptable metrological characteristics. Extensive metrological and usability descriptions of those devices for plant measurement have been published [26
]. Better results in scanning plants of very complex shapes have been achieved with hand-held scanners, e.g., Artec S [28
] or HandyScan EXASCAN [29
]. Also, triangulation scanners (typically more accurate), mounted on special measuring arms [30
], can be used for this purpose, e.g., Artec S and Perceptron ScanWorks V5 with the Romer Infinite 2.0 arm. However, their prices are far higher than those of hand-held devices.
One frequently measured parameter in plant biology is S/V (surface to volume ratio). It is easy to determine it for a flat-leaved plant when the surface and thickness of a leaf are measured. It is also possible to measure in situ
with a portable scanner, e.g., Portable Living Leaf Area Meter [32
]. For geometrically more complex plants, determination of S/V requires calculation of the surface and volume.
The present work verifies certain non-contact measurement methods of certain plant morphological parameters (length, width, area and volume of leaf) that are otherwise very difficult or impossible to determine with traditional techniques.
The paper also describes difficulties in plant scanning due to complicated surfaces, the presence of thorns or prickles that diffuse light, as well as hard-to-reach fragments that make it impossible to recreate the surface.
Computer models make it possible to determine the area and volume precisely, which lets the researcher calculate the S/V ratio. A method of approximating the S/V ratio by using geometrical primitives exists [44
], but computer models can calculate the S/V ratio more accurately. This is especially important for the ecological studies of succulents [20
], and such an accurate method has never been used so far.
Three scanners were assessed (DAVID Laserscanner, EXASCAN, and Kinect). The best results for shape and completeness (no missing features, e.g., as in Figure 7
and Figure 10
) were obtained with the DAVID Laserscanner. Scan time, which takes approximately 40 min for one plant (with around 35 to 40 scans), is the only disadvantage of working with this device.
A detailed comparison of the DAVID 3D and Kinect scanners has been reported [26
]. Phantoms of known geometrical shapes (plane and sphere), and models of plants scanned with the Perceptron v5 coupled to the Romer Infinite 2.0 arm as a “ground truth”, were used to estimate measurements errors. The error for the DAVID 3D device was less then ±1 mm, which is comparable with the manufacturer’s specifications, and is appropriate for phenotyping and parameterization.
Determination of the shortest path in a triangle mesh with the use of Dijkstra’s method has the advantage of correct calculation compared with results from commercial software RapidForm. This method is not suitable for twisted objects such as Welwitschia mirabilis
leaves, in which the shortest path should be determined as a center line. For such objects it is necessary to use the more sophisticated method presented in Section 2.2.2
A robust 3D structured light scanning system with a set of five stereo cameras and software focused on whole plant phenotyping has been reported [45
]. The use of a motorized table and a multiple-camera set spread over a plant allows us to scan the whole plant in one process. It is not possible with the DAVID Laserscanner which is composed of one camera and one structured light source.
A hand-held scanner (Artec S) has been reported to give a good resolution [5
]. However, based on our experience with the EXASCAN device, we feel otherwise. It should, however, be noted that EXASCAN is no longer a state-of-the-art device. Advantages of the DAVID Laserscanner when scanning plants are also reported [24
], and they are for Kinect device as well; however, we did not see these. Scanning results obtained by authors with the use of the Kinect sensor (Figure 7
B) were not satisfactory. The model is incomplete, which makes it impossible to measure leaf characteristics and to compare with the other scanner. Another approach to Kinect sensor data processing has been described [45
]. Segmentation of stems and leaves is performed in 2D depth and image color space instead of 3D scanning.
Non-invasive methods of morphological studies of plants are especially important in studies of plants which are endangered and therefore protected by law. With new methods, it is possible to measure their dimensions and consequently also estimate their age, which has not been possible so far. Exact measures of plants with complicated surfaces and leaf structure are now possible, thanks to phenotyping methods.