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Non-destructive determination and visualisation of insoluble and soluble dietary fibre contents in fresh-cut celeries during storage periods using hyperspectral imaging technique

机译:使用高光谱成像技术对鲜切芹菜中的不溶性和可溶性膳食纤维含量进行无损测定和可视化

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The feasibility of using hyperspectral imaging technique to non-destructively determine insoluble dietary fibre (IDF) and soluble dietary fibre (SDF) contents in fresh-cut celeries and visualise their spatial distribution during 28-day storage periods was investigated. Genetic synergy interval partial least square (GA-Si--PIS) algorithm was developed to establish calibration model, which, superior to the PIS and Si-PLS developed models, achieved the prediction performance with R-p of 0.9638 and 0.9756, and RMSEP of 1.180 and 0.336, respectively. The developed GA-Si-PLS models were then applied pixel-wise to visualise the spatial distribution of IDF and SDF contents during storage, which clearly showed that the IDF content increased with storage time, while the SDF content kept decreasing. The study provides the basis for further understanding of the spatial-temporal variation of IDF and SDF contents during storage, demonstrating that HSI could be useful in real-time IDF and SDF contents monitoring in vegetable research and industry. (C) 2017 Elsevier Ltd. All rights reserved.
机译:研究了使用高光谱成像技术无损确定鲜切芹菜中不溶性膳食纤维(IDF)和可溶性膳食纤维(SDF)含量并可视化它们在28天存储期内的空间分布的可行性。开发了遗传协同区间偏最小二乘(GA-Si--PIS)算法建立校准模型,该模型优于PIS和Si-PLS开发的模型,具有0.9638和0.9756的Rp和1.180的RMSEP的预测性能。和0.336分别。然后将开发的GA-Si-PLS模型逐像素应用于存储过程中IDF和SDF含量的空间分布,这清楚地表明IDF含量随存储时间增加而SDF含量持续下降。该研究为进一步了解储存期间IDF和SDF含量的时空变化提供了基础,证明了HSI在蔬菜研究和工业中对IDF和SDF含量的实时监测中可能有用。 (C)2017 Elsevier Ltd.保留所有权利。

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