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Development of ANN models based on combined UV‐vis‐NIR spectra for rapid quantification of physical and chemical properties of industrial hemp extracts
Phytochemical Analysis ( IF 3.3 ) Pub Date : 2020-08-14 , DOI: 10.1002/pca.2979
Davor Valinger 1 , Tamara Jurina 1 , Adela Šain 1 , Nikolina Matešić 1 , Manuela Panić 2 , Maja Benković 1 , Jasenka Gajdoš Kljusurić 1 , Ana Jurinjak Tušek 1
Affiliation  

The aim of this study was to develop artificial neural network (ANNs) models for prediction of physical (total dissolved solids, extraction yield) and chemical (total polyphenolic content, antioxidant activity) properties of industrial hemp extracts, prepared by two different extraction methods (solid‐liquid extraction and microwave‐assisted extraction) based on combined UV‐VIS‐NIR spectra. Spectral data were gathered for 46 samples per extraction method.

中文翻译:

基于紫外可见近红外光谱的人工神经网络模型的开发,可对工业大麻提取物的物理和化学性质进行快速定量

这项研究的目的是开发一种人工神经网络(ANN)模型,用于预测工业大麻提取物的物理(总溶解固体,提取率)和化学(总多酚含量,抗氧化活性)的物理性质,该模型是通过两种不同的提取方法制备的(固液萃取和微波辅助萃取)。每种提取方法收集了46个样品的光谱数据。
更新日期:2020-08-14
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