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Use of diffusion magnetic resonance imaging to correlate the developmental changes in grape berry tissue structure with water diffusion patterns.

Dean RJ, Stait-Gardner T, Clarke SJ, Rogiers SY, Bobek G, Price WS - Plant Methods (2014)

Bottom Line: A diffusion tensor image of a post-harvest olive demonstrated that the technique is applicable to tissues with high oil content.It was shown that macroscopic diffusion anisotropy patterns correlate with the microstructure of the major pericarp tissues of cv.Semillon grape berries, and that changes in grape berry tissue structure during berry development can be observed.

View Article: PubMed Central - PubMed

Affiliation: Nanoscale Organisation and Dynamics Group, University of Western Sydney, Penrith, NSW 2751 Australia.

ABSTRACT

Background: Over the course of grape berry development, the tissues of the berry undergo numerous morphological transformations in response to processes such as water and solute accumulation and cell division, growth and senescence. These transformations are expected to produce changes to the diffusion of water through these tissues detectable using diffusion magnetic resonance imaging (MRI). To assess this non-invasive technique diffusion was examined over the course of grape berry development, and in plant tissues with contrasting oil content.

Results: In this study, the fruit of Vitis vinfera L. cv. Semillon at seven different stages of berry development, from four weeks post-anthesis to over-ripe, were imaged using diffusion tensor and transverse relaxation MRI acquisition protocols. Variations in diffusive motion between these stages of development were then linked to known events in the morphological development of the grape berry. Within the inner mesocarp of the berry, preferential directions of diffusion became increasingly apparent as immature berries increased in size and then declined as berries progressed through the ripening and senescence phases. Transverse relaxation images showed radial striation patterns throughout the sub-tissue, initiating at the septum and vascular systems located at the centre of the berry, and terminating at the boundary between the inner and outer mesocarp. This study confirms that these radial patterns are due to bands of cells of alternating width that extend across the inner mesocarp. Preferential directions of diffusion were also noted in young grape seed nucelli prior to their dehydration. These observations point towards a strong association between patterns of diffusion within grape berries and the underlying tissue structures across berry development. A diffusion tensor image of a post-harvest olive demonstrated that the technique is applicable to tissues with high oil content.

Conclusion: This study demonstrates that diffusion MRI is a powerful and information rich technique for probing the internal microstructure of plant tissues. It was shown that macroscopic diffusion anisotropy patterns correlate with the microstructure of the major pericarp tissues of cv. Semillon grape berries, and that changes in grape berry tissue structure during berry development can be observed.

No MeSH data available.


Related in: MedlinePlus

The physical characteristics of the grape berries. The concentrations of soluble solids of the grape berries (Green ♦), as well as the fresh weight (Blue ▲) and dry weights (Red ▼) of the berries, are presented with respect to the number of days after flowering. A sigmoidal function (solid green curve) of the form a1 + (a2 - a1)/(1 + exp(-(DAF - x0)/w)) was fitted to the soluble solids values by nonlinear regression (adjusted R2 = 0.99), where a1 = 26.1 (the approximate maximum soluble solids value), a2 = 3.9 (the approximate minimum soluble solids value), x0 = 69.7 (the inflection point) and w =7.4 (the change in DAF which yielded the greatest change in the soluble solids value). The error bars are given by the standard deviation of soluble solids values at each time point.
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Fig3: The physical characteristics of the grape berries. The concentrations of soluble solids of the grape berries (Green ♦), as well as the fresh weight (Blue ▲) and dry weights (Red ▼) of the berries, are presented with respect to the number of days after flowering. A sigmoidal function (solid green curve) of the form a1 + (a2 - a1)/(1 + exp(-(DAF - x0)/w)) was fitted to the soluble solids values by nonlinear regression (adjusted R2 = 0.99), where a1 = 26.1 (the approximate maximum soluble solids value), a2 = 3.9 (the approximate minimum soluble solids value), x0 = 69.7 (the inflection point) and w =7.4 (the change in DAF which yielded the greatest change in the soluble solids value). The error bars are given by the standard deviation of soluble solids values at each time point.

Mentions: The grape berries increased in size and weight and then declined as the berries progressed through the ripening and senescence phases (Figure 3). The post-harvest olive had a fresh weight of 3.30 g and dry weight of 1.63 g. The concentration of soluble solids in the grape berries increased sigmoidally with respect to time (adjusted R2 = 0.99). Véraison occurred at approximately 60 – 65 DAF, and full ripeness was placed at 95 DAF (based on the mean concentration of soluble solids of the sampled berries which plateaued at 26 °Brix).Figure 3


Use of diffusion magnetic resonance imaging to correlate the developmental changes in grape berry tissue structure with water diffusion patterns.

Dean RJ, Stait-Gardner T, Clarke SJ, Rogiers SY, Bobek G, Price WS - Plant Methods (2014)

The physical characteristics of the grape berries. The concentrations of soluble solids of the grape berries (Green ♦), as well as the fresh weight (Blue ▲) and dry weights (Red ▼) of the berries, are presented with respect to the number of days after flowering. A sigmoidal function (solid green curve) of the form a1 + (a2 - a1)/(1 + exp(-(DAF - x0)/w)) was fitted to the soluble solids values by nonlinear regression (adjusted R2 = 0.99), where a1 = 26.1 (the approximate maximum soluble solids value), a2 = 3.9 (the approximate minimum soluble solids value), x0 = 69.7 (the inflection point) and w =7.4 (the change in DAF which yielded the greatest change in the soluble solids value). The error bars are given by the standard deviation of soluble solids values at each time point.
© Copyright Policy - open-access
Related In: Results  -  Collection

License 1 - License 2
Show All Figures
getmorefigures.php?uid=PMC4232727&req=5

Fig3: The physical characteristics of the grape berries. The concentrations of soluble solids of the grape berries (Green ♦), as well as the fresh weight (Blue ▲) and dry weights (Red ▼) of the berries, are presented with respect to the number of days after flowering. A sigmoidal function (solid green curve) of the form a1 + (a2 - a1)/(1 + exp(-(DAF - x0)/w)) was fitted to the soluble solids values by nonlinear regression (adjusted R2 = 0.99), where a1 = 26.1 (the approximate maximum soluble solids value), a2 = 3.9 (the approximate minimum soluble solids value), x0 = 69.7 (the inflection point) and w =7.4 (the change in DAF which yielded the greatest change in the soluble solids value). The error bars are given by the standard deviation of soluble solids values at each time point.
Mentions: The grape berries increased in size and weight and then declined as the berries progressed through the ripening and senescence phases (Figure 3). The post-harvest olive had a fresh weight of 3.30 g and dry weight of 1.63 g. The concentration of soluble solids in the grape berries increased sigmoidally with respect to time (adjusted R2 = 0.99). Véraison occurred at approximately 60 – 65 DAF, and full ripeness was placed at 95 DAF (based on the mean concentration of soluble solids of the sampled berries which plateaued at 26 °Brix).Figure 3

Bottom Line: A diffusion tensor image of a post-harvest olive demonstrated that the technique is applicable to tissues with high oil content.It was shown that macroscopic diffusion anisotropy patterns correlate with the microstructure of the major pericarp tissues of cv.Semillon grape berries, and that changes in grape berry tissue structure during berry development can be observed.

View Article: PubMed Central - PubMed

Affiliation: Nanoscale Organisation and Dynamics Group, University of Western Sydney, Penrith, NSW 2751 Australia.

ABSTRACT

Background: Over the course of grape berry development, the tissues of the berry undergo numerous morphological transformations in response to processes such as water and solute accumulation and cell division, growth and senescence. These transformations are expected to produce changes to the diffusion of water through these tissues detectable using diffusion magnetic resonance imaging (MRI). To assess this non-invasive technique diffusion was examined over the course of grape berry development, and in plant tissues with contrasting oil content.

Results: In this study, the fruit of Vitis vinfera L. cv. Semillon at seven different stages of berry development, from four weeks post-anthesis to over-ripe, were imaged using diffusion tensor and transverse relaxation MRI acquisition protocols. Variations in diffusive motion between these stages of development were then linked to known events in the morphological development of the grape berry. Within the inner mesocarp of the berry, preferential directions of diffusion became increasingly apparent as immature berries increased in size and then declined as berries progressed through the ripening and senescence phases. Transverse relaxation images showed radial striation patterns throughout the sub-tissue, initiating at the septum and vascular systems located at the centre of the berry, and terminating at the boundary between the inner and outer mesocarp. This study confirms that these radial patterns are due to bands of cells of alternating width that extend across the inner mesocarp. Preferential directions of diffusion were also noted in young grape seed nucelli prior to their dehydration. These observations point towards a strong association between patterns of diffusion within grape berries and the underlying tissue structures across berry development. A diffusion tensor image of a post-harvest olive demonstrated that the technique is applicable to tissues with high oil content.

Conclusion: This study demonstrates that diffusion MRI is a powerful and information rich technique for probing the internal microstructure of plant tissues. It was shown that macroscopic diffusion anisotropy patterns correlate with the microstructure of the major pericarp tissues of cv. Semillon grape berries, and that changes in grape berry tissue structure during berry development can be observed.

No MeSH data available.


Related in: MedlinePlus