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Evaluating carotenoid changes in tomatoes during postharvest ripening using Raman chemical imaging

机译：使用拉曼化学成像评估收获后成熟期间番茄中的类胡萝卜素变化

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Lycopene is a major carotenoid in tomatoes and its content varies considerably during postharvest ripening. Hence evaluating lycopene changes can be used to monitor the ripening of tomatoes. Raman chemical imaging technique is promising for mapping constituents of interest in complex food matrices. In this study, a benchtop point-scanning Raman chemical imaging system was developed to evaluate lycopene content in tomatoes at different maturity stages. The system consists of a 785 nm laser, a fiber optic probe, a dispersive imaging spectrometer, a spectroscopic CCD camera, and a two-axis positioning table. Tomato samples at different ripeness stages (i.e., green, breaker, turning, pink, light red, and red) were selected and cut before imaging. Hyperspectral Raman images were acquired from cross sections of the fruits in the wavenumber range of 200 to 2500 cm-1 with a spatial resolution of 1 mm. The Raman spectrum of pure lycopene was measured as reference for spectral matching. A polynomial curve-fitting method was used to correct for the underlying fluorescence background in the Raman spectra of the tomatoes. A hyperspectral image classification method was developed based on spectral information divergence to identify lycopene in the tomatoes. Raman chemical images were created to visualize quantity and spatial distribution of the lycopene at different ripeness stages. The lycopene patterns revealed the mechanism of lycopene generation during the postharvest development of the tomatoes. The method and findings of this study form a basis for the future development of a Raman-based nondestructive approach for monitoring internal maturity of the tomatoes.
机译：番茄红素是番茄中的主要类胡萝卜素，在收获后成熟期间其含量差异很大。因此，评估番茄红素的变化可用于监测番茄的成熟度。拉曼化学成像技术有望用于绘制复杂食品基质中的目标成分。在这项研究中，开发了台式点扫描拉曼化学成像系统，以评估不同成熟阶段番茄中番茄红素的含量。该系统由785 nm激光器，光纤探头，色散成像光谱仪，光谱CCD相机和两轴定位台组成。选择不同成熟阶段（即绿色，破碎，转弯，粉红色，浅红色和红色）的番茄样品，并在成像前进行切割。从水果的横截面中以200到2500 cm-1的波数范围获取高光谱拉曼图像，空间分辨率为1 mm。测量纯番茄红素的拉曼光谱作为光谱匹配的参考。多项式曲线拟合方法用于校正番茄拉曼光谱中的潜在荧光背景。开发了一种基于光谱信息差异的高光谱图像分类方法，以鉴定番茄中的番茄红素。创建拉曼化学图像以可视化不同成熟阶段番茄红素的数量和空间分布。番茄红素模式揭示了番茄收获后发育过程中番茄红素生成的机理。这项研究的方法和发现为将来开发基于拉曼的无损监测西红柿内部成熟度的方法奠定了基础。

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