MICRO-STRUCTURE ANALYSIS OF PLANT TISSUES - Lublin

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that the image of a structure after the preparation is a true representation of the structure in undisturbed tissue. It is obvious that any operation on the tissue, even just a slice through the structure, disturbs the true image of the tissue. However, we should aim at such a development of the sample preparation methods that would eliminate that phenomenon. Fig. 2.18. Potato tuber tissue. The image originates from an optical microscope with 10X magnification. The sample was 1mm thick and was sliced with a razor blade. The focal plane and the out-of-focus areas above and below the focal plane can be seen. This results in limited contrast and interference with information from the focal plane. For the above reasons the development of new types of microscopes, such the transmission electron microscope, the scanning electron microscope and the tunnel microscope caused the classic optical microscope to cease being the basic tool in the study of biological structures. However, the development of numerous procedures for sample staining and preparation helps maintain its usefulness in routine studies of various materials. 44
Fig. 2.19. Potato tuber tissue. The image originates from an optical microscope with 10X magnification. The sample was 2 µm thick and it was sliced with a microtome after preparation: dehydration in a series of alcohols, setting in paraffin, slicing and paraffin removal. Focal place clearly seen; out-offocus areas visible to a lesser degree than in Fig .2.18. The preparation caused breaks and deformation of cell walls. 2.2.2. Confocal microscope principle of operation The operating principle of the confocal microscope was presented to the patent office in 1957 by Martin Minsky, postdoctoral fellow at the Harvard University (Minsky 1957). In the design proposed by Minski, the conventional condenser was replaced with a lens identical to the main lens of the microscope. The original schematic of the microscope operation is presented in Fig. 2.20. Light (1) illuminating the object studied is limited by a diaphragm (2) located exactly in the optical axis of the microscope. Then the light passing beam is focused by the condenser (3) on the object viewed (4) located in the focal point. The second separation of the light takes place at the second diaphragm (6). This happens in such a manner that the light beam, having passed through the object viewed, is focused by the lens (5) in the plane of the second diaphragm (6). Then light coming from beyond the focal point (A) in the object viewed 45
Page 1 and 2: MICRO-STRUCTURE ANALYSIS OF PLANT T
Page 3 and 4: MICRO-STRUCTURE ANALYSIS OF PLANT T
Page 5 and 6: PREFACE The subject matter of resea
Page 7 and 8: PREFACE ...........................
Page 9 and 10: 1. THE GOAL OF IMAGE ANALYSIS OF PL
Page 11 and 12: within an object, caused e.g. by a
Page 13 and 14: 1.4. Analysis of plant tissue struc
Page 15 and 16: 2. MICROSCOPES AND SAMPLE PREPARATI
Page 17 and 18: focusing mechanism permitting the a
Page 19 and 20: 3 5 9 6 7 8 4 2 1 Fig. 2.4. The str
Page 21 and 22: 2.1.3. Mechanical elements Microsco
Page 23 and 24: 2.1.4. Image generation in optical
Page 25 and 26: 2.1.5. Resolution of the microscope
Page 27 and 28: a) 1 b) Relative refractive index 3
Page 29 and 30: 2.1.7. Microscopy studies Microscop
Page 31 and 32: One should take care, however, that
Page 33 and 34: may be difficult and the objects fi
Page 35 and 36: Object slicing and application of s
Page 37 and 38: them to straighten out without dama
Page 39 and 40: Fig. 2.15. Reconstruction of the tr
Page 41 and 42: Fig. 2.16. Images of the same part
Page 43 and 44: Fig. 2.17. Images of the structure
Page 45: 2.2. Confocal Microscopy Artur Zdun
Page 49 and 50: Fig. 2.21. Confocal Microscope oper
Page 51 and 52: Fig. 2.22. Potato tuber tissue. Ima
Page 53 and 54: in spite of the different original
Page 55 and 56: estimated that for most animal tiss
Page 57 and 58: However, because of the broadening
Page 59 and 60: 2.3. Electron Microscopy Andrzej Kr
Page 61 and 62: Due to the high vacuum inside the m
Page 63 and 64: Fig. 2.38 presents an image of aggr
Page 65 and 66: Fig. 2.38. Aggregation of starch gr
Page 67 and 68: a) b) c) d) Fig. 2.40. Schematics o
Page 69 and 70: Fig. 2.42. Schematic of ESEM detect
Page 71 and 72: Table 2.1. TECHNOLOGY LIMITING FACT
Page 73 and 74: 3. DIGITAL IMAGES AND THE POSSIBILI
Page 75 and 76: Fig. 3.1. Image processing and anal
Page 77 and 78: Table 3.1. Comparison of selected f
Page 79 and 80: 300 dpi, which corresponds to the p
Page 81 and 82: If we consider a recording element
Page 83 and 84: Fig. 3.4. Comparison of a circular
Page 85 and 86: Fig. 3.6. Changing depth of digital
Page 87 and 88: Fig. 3.7. Change in the appearance
Page 89 and 90: Fig. 3.8. Comparison of an image in
Page 91 and 92: Fig. 3.10. Determination of the num
Page 93 and 94: Maximum width This measurement can
Page 95 and 96: Fig. 3.11. Counting particles visib
Page 97 and 98:
Let us analyse the distribution of
Page 99 and 100:
An example of the application of co
Page 101 and 102:
Fig. 3.16. The process of binarizat
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Image analysis software packages fr
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image is marked with the letter a).
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The effect of operation of these fi
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And another example of a filter: -1
Page 111 and 112:
3.8. Mathematical morphology Morpho
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and the whole operation is repeated
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The simplest problem is presented i
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Fig. 3.29 illustrates the phenomeno
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Fig. 3.31. Model of RGB. Descriptio
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And substitution is an operation th
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increase decrease 255 contrast + 40
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Fig. 3.37. Application of normaliza
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4.1.2. Fixation of tissue structure
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The format most frequently used for
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Fig. 4.4. Histogram of grey levels
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orderline of two or three cells. Th
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Shape can also be described by mean
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Fig. 4.11. Image of the parenchyma
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4.2. Analysis of images obtained wi
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lens. However, the realization of t
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is now extremely easy, as all the w
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Fig. 4.16. Combination of erosion,
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Fig. 4.20. Division of binary image
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Fig. 4.24. Image labelling (AphImgC
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Fig. 4.28. Repeat watershed detecti
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as 60%), then the source of error i
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in natural state maintaining high s
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Therefore, the tasks of the compute
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Fig. 4.36. Result of Watershed oper
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and 5617 after correction. For carr
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Fig. 4.38. Histograms of cell area,
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should be analyzed separately. An e
Page 167 and 168:
) Fig. 4.42. Result of reconstructi
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