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Application Of Nonlinear Optical Imaging In The Study Of Plant Carotene

Posted on:2022-09-24Degree:MasterType:Thesis
Country:ChinaCandidate:T WangFull Text:PDF
GTID:2480306509477624Subject:Optics
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Carotene plays an important role in the life activities of animals and plants.Exploring the form,distribution,content and other parameters of carotene is of great significance to plant breeding and animal health.At present,the main methods of studying carotene in plants are Raman spectroscopy,chromatography and transmission electron microscopy.However,these methods have many problems such as the inability to quantitatively analyze and the use of solvents during sample preparation to change the structure of carotene.Non-linear optical imaging methods are widely used in the research of animal and plant tissues because of their non-destructive,good penetration depth and in-situ live detection.This article mainly uses nonlinear optical imaging methods to systematically study the spatial position,content,deposition form,size,etc.of carotene in three plants(carrots,nectarines,sweet potatoes).The experimental results may be use in many areas,such as plant breeding or producing and selecting carotene supplements.The research results mainly include the following three aspects:This article systematically studied the carotene in four kinds of carrots(normal orange,mini,red,and purple)commonly used in daily life.The experimental results of Raman spectroscopy show that these four carrots are rich in ?-carotene.In order to obtain information on the content of carotene,the coherent anti-Stokes Raman spectroscopy(CARS)imaging was performed on the center of the phloem of all carrots to establish the spectrum database.Through the analysis of the database,combined with the statistical results of Image J software,the following conclusions are drawn.Among the four kinds of carrots,ordinary carrots have the most carotene content,followed by mini carrots and red carrots,and purple carrots have the least carotene content.Thanks to the high-resolution properties of CARS spectroscopy,the experimental results confirmed that carotene is deposited in the cells in the form of crystals.The main shapes of the crystals are needles,rods,and spheres.At the same time,the number of crystals is proportional to the content of carotene,indicating that the size of carotene crystals in different types of carrots is basically the same.The results of Raman mapping show the difference in carotene content of different types of carrots from the perimeter of the skin to the center of the xylem.In order to quantitatively analyze this difference,we established a CARS spectral database of the phloem and xylem.The analysis results show that the carotene content in phloem is three times that of xylem.Carotene is one of the main nutrients of nectarines.Due to the high percentage of water content of nectarines,traditional imaging methods such as Raman spectroscopy or electron microscopy analysis after slicing pose certain challenges.In this paper,three-dimensional CARS is used to analyze carotene of nectarine which close to the core and close to the core.The same volume of pulp of the two areas is imaged,and a spectral database is established.According to Image J statistics,the carotene content in the pulp near the peel is about twice that of the pulp near the core.In terms of crystal size,the size of carotene in nectarines is significantly smaller than that in carrots.Sweet potatoes are rich in a variety of nutrients.In this paper,CARS and second harmonic(SHG)are used to study carotene and starch in sweet potatoes.These two nonlinear methods can achieve imaging at the level of single starch particles.The experimental results revealed that in sweet potatoes,part of the carotene is attached to the starch granules.The research on sweet potato proves that nonlinear optical methods can also be applied to the research of plants with a variety of nutrients,and it is expected to be extended to the research of other carotene-rich plants.
Keywords/Search Tags:Carotene, Nonlinear Optical Imaging, Raman Spectral Imaging, Quantitative detection
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