2.4.1 Principle of OCT
The OCT technique is a purely optical, non-destructive, non-invasive, and contactless high resolution imaging method applicable to semi-transparent and turbid media (Drexler and Fujimoto, 2008). It allows for the acquisition of three-dimensional (3D) depth resolved image data of (sub)surface regions in situ and in real-time with resolution as good as one micrometre.
This technique detects the discontinuities in refractive index corresponding to the boundaries between different types of tissues (Landahl et al., 2012). To capture an OCT image, the sample is irradiated with near-infrared light and the light beam is back- scattered from different layers of sub-surface tissue structures such as pores and cells. A depth scan is obtained by comparing the arrival times of the light path scattered from the sample with the light path reflected from a reference mirror. Cross-sectional images are obtained by scanning the light laterally across the surface of the sample and a 3D volume is generated by several depth scans at adjacent lateral positions (Verboven et al., 2013). OCT provides excellent axial resolution with an accuracy of a few micrometers. The penetration depth however depends on the scattering and absorption properties of the tissue. In fruit media the penetration depth is up to 2 mm with 5 – 20 μm resolution (Meglinski et al., 2010; Verboven et al., 2013).
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2.4.2 Image acquisition
Depth scans can be obtained either by moving the reference mirror (time- domain OCT, TD-OCT) or, by spectral analysis of the interference signal with the reference mirror kept fixed and subsequent fast Fourier transformation (spectral-domain OCT, SD-OCT; Fercher et al., 1995) .
In SD-OCT, a dispersive element such as a grating is used for spectral analysis and depth scans are acquired quasi-instantaneously by a line scan camera within a few milliseconds. This technique allows for high acquisition rates as required in real-time measurements. However, for two-dimensional (2D) images the light beam needs to be scanned laterally in one dimension. Single depth scans and cross-sections are classified as A- and B-scans, respectively. The 3D measurements require 2D scanning across both lateral directions. The scanning process can be performed by different means, such as by one (2D image) or two galvanometer mirrors (3D data). Single (2D) images acquired by SD-OCT are always cross-section images. A schematic diagram of a SD-OCT system is depicted in Fig. 2.7.
Figure 2.7 Schematic diagram of a spectral-domain OCT (SD-OCT) system. The boxes represent portable and independent modules. DC: directional coupler; BS: beam-splitter; GM: Galvanometer mirror; L: lens; DG: diffraction grating; CCD: charged coupled device (Podoleanu, 2012; Verboven et al., 2013). Image used with permission.
35 Figure 2.8 illustrates the image capture of a kiwifruit sample using the commercial TELESTO™ SD-OCT imaging system (Thorlabs, Lübeck, Germany). Real-time visualisation of the sample in 2D and 3D is available from the software accompanying this system. However, for high level image processing, sophisticated image processing software such as Matlab® (MathWorks, Inc., Natick, USA). and Avizo® (Visualization Sciences Group, France) are usually required, in order to allow display, modification and quantification of the images.
2.4.3 Applications of OCT in horticultural products
The OCT has the advantages of minimal sample preparation in comparison to conventional optical methods and it enables the potential for repeated measurements on the same sample matured over a period of time. Although OCT has already been widely applied in biomedical areas such as dermatology and ophthalmology, this technique has also found an increasing number of applications in assessment of horticultural products. Clements et al. (2004) used OCT to compare hull layer thickness of four genotypes of lupin seeds, and were able to distinguish between different species of
Figure 2.8 Schematic diagram of a commercial SD-OCT system: Variable-Rate TELESTO™ OCT Imaging System operating at 1325nm (Thorlabs, Lübeck, Germany). Axial resolution: 7.5 μm. Lateral resolution: 15 μm. Operating rates: 5.5 kHz, 28 kHz, and 91 kHz.
Processor Probe Head and Fibre Optics
Translation Stage
Image Processing Software
SD-OCT Engine Sample
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lupins and also identify thin-hulled seeds from normal seeds. Meglinski et al. (2010), Ford et al. (2012) and Landahl et al. (2012) demonstrated the use of OCT to detect defects, rots and diseases in onions based on visualisation and quantification of 2D OCT images. Loeb and Barton (2003) produced OCT images of kiwifruit showing some thin- walled parenchyma cells in the outer pericarp (Fig. 2.9a). However, the images were not obtained from intact kiwifruit samples but from a radial transverse section removed from the equator of the fruit. Magwaza et al. (2013) investigated the feasibility of using OCT in the visualization of histological and microstructural features in intact rind tissues of mandarins. Image processing enabled the development of 3D models of oil glands, which is associated with progressive rind breakdown in mandarins (Fig. 2.9b). Rizzolo et al. (2013) reported the differences in mechanical and acoustic characteristics between two types of air-dried apple rings were due to different subsurface structure as found with OCT analysis (Fig. 2.9c). Verboven et al. (2013) used OCT to visualise peel structural differences between apples and measured structural changes that occur during storage (Fig. 2.9d).
Figure 2.9 OCT images of (a) sectioned kiwifruit (Loeb and Barton, 2003); (b) mandarin with moderate degree of RBD (Magwaza et al., 2013); (c) untreated air- dried apple ring (Rizzolo et al., 2013); and (d) ‘Royal Gala’ apple (Verboven et al., 2013). Images used with permission. Scale bars = 0.1 mm
(a) (b)
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