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Rapid analysis of chemical composition in intact and milled rice cookies using near infrared spectroscopy

机译:近红外光谱法快速分析完整和研磨米饼干中的化学成分

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摘要

This study has investigated the potential of near infrared (NIR) spectroscopy to predict the content of moisture, protein, fat and gluten in rice cookies in different sample forms (intact and milled samples). Gluten-free (n = 48) and gluten (n = 48) rice cookies were formulated with brown and white rice flours in which butter was substituted with fat replacer at 0, 15, 30 and 45%. With regard to gluten cookies, rice flour was substituted with wheat gluten at 1, 3 and 5%. Partial least squares regression modeling produced models with coefficient of determination (R-2) values greater than 0.88 from NIR spectra of intact samples and greater than 0.92 for milled samples. These models were able to predict the four components with a ratio of prediction to deviation greater than 2.7 and 3.8 in intact and milled samples, respectively. The results suggest that the models obtained from the intact samples can be successfully applied for chemical composition of rice cookies and are reliable enough use for potential quality control programs.
机译:本研究研究了近红外(NIR)光谱的潜力,以预测不同样品形式(完整和研磨样品)的水稻饼干中水分,蛋白质,脂肪和麸质的含量。无麸质(n = 48)和麸质(n = 48)水稻饼干配制,用棕色和白米粉配制,其中黄油以0,15,30和45%的脂肪替代品取代。关于麸质饼干,米粉在1,3和5%的小麦面筋取代。局部最小二乘性建模,其产生的模型具有大于0.88的确定系数(R-2)值,从完整样品的NIR光谱大于0.92,用于研磨样品。这些模型能够分别预测预测与预测比率比2.7和3.8在完整和研磨的样本中的四个组件。结果表明,从完整样品中获得的模型可以成功地应用于水稻饼干的化学成分,并且可以对潜在的质量控制计划可靠地使用。

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