MICRO-STRUCTURE ANALYSIS OF PLANT TISSUES - Lublin

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of various types of microscopes available, e.g. optical, confocal, electron, acoustic, X-ray, with the abundance of accessories, optional equipment and software that provide routine operation with very good results for a variety of materials, create extensive possibilities also for the research on plant tissue. However, while the selection of suitable equipment is not an easy task, it is frequently of decisive importance for the success of solving a given problem, and can help economize on both the time and the cost of studies. The most important is the definition of the objective of the study, i.e. concentration on the significant elements of the structure with the exclusion of unnecessary details and assurance of methodological correctness. For example, the application of initial preparation of specimens, from simple slicing to fixation of structure, may introduce disturbance to the structures observed, which has to be taken into consideration in subsequent stages of the study and in the formulation of conclusions. In the study of the physical properties of plant tissue methods are sought for obtaining such an image of the tissue structure that will clearly show cell walls which determine the dimensions of the whole cell. The arrangement of cells on the surface observed provides information on the spatial organization of elements of the structure, and also on possible changes to the structure, resulting from processes under study. Studies as well as comparative observations of plant tissue require numerous measurements, therefore there is a growing tendency of employing computer methods for the purpose. For images with good quality, analysis can be conducted automatically with the help of professional dedicated software. Images of structure for computer analysis should be of good quality, and primarily with very good contrast. Elements of structure that are of interest should be clearly identifiable, countable and measurable. This is not an easy task in the case of plant tissue that has little colour and sometimes is even transparent and, additionally, due to the high content of water, subject to rapid drying and deformation during observation. Quantitative description of cellular structure requires the development of suitable methods for the study of a given object. Even with very good procedures, however, the experience and knowledge on the part of the observer is essential for proper interpretation of information contained in structure images. 10
1.4. Analysis of plant tissue structure images The use of image analysis software may seem an easy task, especially in the situation of easy access to professional software and to encouraging results for other materials. However, it turns out that the task is a complex one and requires experience and knowledge not only about the object itself, but also about methods of obtaining images, their acquisition and processing, and – finally – analysis. In spite of the continual advances in specialist knowledge concerning image analysis and, sometimes, the resultant problems with its understanding, it is absolutely indispensable at a basic level for every user in order to avoid errors that may result in irreversible effects at the final stage of formulation of conclusions. Similar problems are faced by everyone who undertakes the study of the cellular structure of plant tissue. The authors of this monograph also had to face similar problems in their work, but they also have already some practical experience. Several years ago, at the Laboratory of Mechanics of Plant Materials, we started work on the quantitative description of cellular structures of plant media. Many times in our work we made use of the achievements of stereology – a totally different branch of science but very much open to new research challenges. Thanks to the high activity of the Polish Stereological Society we could take advantage of specialized publications, conferences and workshops, as well as of individual consultations that facilitated for us the understanding of very difficult problems of stereology. It was during the 6th European Congress of Stereology in Prague in 1993 that we established cooperation with the creators of an original confocal microscope which met our expectations related to the observation of cellular plant structures – from a thin slice specimen under the surface of a transparent object, in natural state without initial preparation, in real time, with the possibility of 3D reconstruction of the structure. The equipment set that was developed then is still in use and, in spite of the increasing competitiveness of numerous newer types of microscopes, still fulfils its function well. To date, in our research we have also been using a confocal laser microscope permitting the observation of selected elements of the structure thanks to suitable staining of specimens, a classical optical microscope for the observation of cellular structure of fixed specimens in transmitted light, and also a scanning electron microscope for qualitative estimation of the structures under observation. The microscope images obtained are used primarily for the study of the geometric features of the cellular skeleton as the fundamental characteristic of the structure of plant tissues. The parameters determined that quantitatively describe the size and shape of cells as well as their distributions, permit the identification 11
Page 1 and 2: MICRO-STRUCTURE ANALYSIS OF PLANT T
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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: within an object, caused e.g. by a
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 and 46: 2.2. Confocal Microscopy Artur Zdun
Page 47 and 48: Fig. 2.19. Potato tuber tissue. The
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
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Fig. 2.38 presents an image of aggr
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Fig. 2.38. Aggregation of starch gr
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a) b) c) d) Fig. 2.40. Schematics o
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Fig. 2.42. Schematic of ESEM detect
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Table 2.1. TECHNOLOGY LIMITING FACT
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3. DIGITAL IMAGES AND THE POSSIBILI
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Fig. 3.1. Image processing and anal
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Table 3.1. Comparison of selected f
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300 dpi, which corresponds to the p
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If we consider a recording element
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Fig. 3.4. Comparison of a circular
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Fig. 3.6. Changing depth of digital
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Fig. 3.7. Change in the appearance
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Fig. 3.8. Comparison of an image in
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Fig. 3.10. Determination of the num
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Maximum width This measurement can
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Fig. 3.11. Counting particles visib
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Let us analyse the distribution of
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An example of the application of co
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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
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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
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) Fig. 4.42. Result of reconstructi
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MICRO-STRUCTURE ANALYSIS OF PLANT TISSUES - Lublin

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