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Method Article
We present a methodology to quantify the starch content in the ovary primordia in sweet cherry (Prunus avium L.) during winter dormancy by using an image analysis system combined with histochemical techniques.
Changes in starch in small structures are associated with key events during several plant developmental processes, including the reproductive phase from pollination to fertilization and the onset of fruiting. However, variations in starch during flower differentiation are not completely known, mainly due to the difficulty of quantifying the starch content in the particularly small structures of the flower primordia. Here, we describe a method for the quantification of starch in the ovary primordia of sweet cherry (Prunus avium L.) by using an image analysis system attached to the microscope, which allows relating the changes in starch content with the different phases of dormancy from autumn to spring. For this purpose, the dormancy status of flower buds is determined by evaluating the bud growth of shoots transferred to controlled conditions at different moments in winter time. For the quantification of starch in the ovary primordia, flower buds are sequentially collected, fixed, embedded in paraffin wax, sectioned, and stained with I2Kl (potassium iodide-iodine). Preparations are observed under the microscope and analyzed by an image analyzer that clearly distinguishes starch from the background. Starch content values are obtained by measuring the optical density of the image that corresponds to the stained starch, considering the sum of the optical density of each pixel as an estimation of the starch content of the frame studied.
Temperate woody perennials adapt to the seasons by modulating their growth and development. While they develop during spring and summer, they stop growing during the autumn to go dormant in winter1. Although dormancy allows them to survive at low winter temperatures, chilling is a prerequisite for a proper budburst in spring2. The important implications of dormancy in temperate fruit production and forestry have led to diverse efforts to determine and predict the dormancy period3. In fruit tree species, empirical experiments transferring shoots to forcing conditions and statistical predictions based on data of flowering are current approaches to determine the date of the breaking of dormancy, which allows researchers to estimate the chilling requirements for each cultivar. However, how to determine the dormancy status based on biological processes remains unclear3.
Flowering in temperate fruit trees, such as sweet cherry (Prunus avium L.), occurs once a year and lasts about a fortnight. However, flowers start to differentiate and develop about 10 months earlier, during the previous summer4. Flower primordia stop growing during the autumn to remain dormant inside the buds during winter. In this period, each cultivar needs to accumulate a particular chilling requirement for proper flowering4. Despite the lack of phenological changes in the buds during winter, flower primordia are physiologically active during dormancy, and the accumulation of chilling temperatures has been recently associated with the dynamic of starch accumulation or decrease within the cells of the ovary primordium, offering a new approach for dormancy determination5. However, the small size and the location of the ovary primordium require a special methodology.
Starch is the major storage carbohydrate in woody plant species6. Thus, changes in starch have been related to the physiological activity of the flower tissues, which need carbohydrates to support their development7,8. Different key events during the reproductive process are also related to variations in starch content in different floral structures, such as anther meiosis9, the growth of the pollen tubes through the style or ovule fertilization10. Histochemical techniques allow the detection of starch in each particular tissue of the flower primordia during dormancy. However, the difficulty remains in quantifying that starch to allow following its pattern of accumulation/decrease over time or comparing the starch content among tissues, cultivars, or years. This is due to the little amount of tissue available for the analytical techniques11. As an alternative, image analysis linked to microscopy12 allows the quantification of the starch in very small samples of plant tissue13.
Approaches combining microscopy and image analysis have been used to quantify the content of different components in plant tissues, such as callose14, microtubes15, or starch16, by measuring the size of the area dyed by specific stains. For starch, it can be easily detected using the potassium iodide-iodine (I2KI) reaction17. This method is highly specific; I2KI intercalates within the laminar structure of starch grains and forms a dark blue or reddish-brown color, depending on the amylose content of the starch18. Sections stained with I2KI stain show adequate contrast between starch and the background tissue, allowing an unequivocal starch detection and the subsequent quantification by the image analysis system19. Although this dye is not stoichiometric, the accumulation of iodine is proportional to the length of the starch molecule, which can highly vary17. Thus, the size of the stained area expressed as the number of pixels may not reflect accurately the content of starch, since high differences in starch content could be found between fields with stained areas of similar size. As an alternative, the starch content may be evaluated by measuring the optical density of the stained granules on black and white images obtained from the microscope, as it has been reported in different tissues in apricot8,13,19, avocado10,20, and olive21.
Here, we describe a methodology that combines the experimental determination of dormancy status with the quantification of starch content in the ovary primordium tissue from autumn to spring in sweet cherry, offering a new tool for the understanding and prediction of dormancy based on the study of the biological mechanisms linked with dormancy.
1. Dormancy Determination and Plant Material Collection
2. Plant Material Preparation for Starch Quantification
3. Quantification of the Starch Content
Dormancy studies require the determination of the moment when the chilling requirements are fulfilled. Despite the lack of phenological changes during winter under field conditions (Figure 1A), cherry trees do not recover the capacity of growth in suitable conditions until they pass a certain period under low temperatures. The regular transference of shoots to a controlled conditions chamber (Figure 1B) during winter time allowed...
Dormancy in woody perennials presents clear implications in fruit production and forestry in a changing climate, although the biological process behind dormancy remains unclear. Dormancy studies can be approached from different points of view, but the research looking for a biological marker for winter dormancy has intensified over the last years. However, most attempts to find an unequivocal indicator showing when a bud has broken dormancy have been unsuccessful3. The methodology described herein...
The authors have nothing to disclose.
The authors gratefully thank Maria Herrero and Eliseo Rivas for their helpful discussion and advice. This work was supported by the Ministerio de Economía y Competitividad — European Regional Development Fund, European Union [grant number BES- 2010-037992 to E. F.]; the Instituto Nacional de Investigación y Tecnología Agraria y Alimentaria [grant numbers RFP2015-00015-00, RTA2014-00085-00, RTA2017-00003-00]; and the Gobierno de Aragón — European Social Fund, European Union [Grupo Consolidado A12-17R].
Name | Company | Catalog Number | Comments |
Precision scale | Sartorius | CP225D | |
Stereoscopic microscope | Leica Microsystems | MZ-16 | |
Drying-stove | Memmert | U15 | |
Paraffin Embedding station | Leica Microsystems | EG1140H | |
Rotatory microtome | Reichert-Jung | 1130/Biocut | |
Microtome blade | Feather | S35 | Stainless steel |
Bright field microscope | Leica Microsystems | DM2500 | |
Digital Camera | Leica Microsystems | DC-300 | |
Image Analysis System | Leica Microsystems | Quantiment Q550 |
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