Predicting the Buckwheat Flour Ratio for Commercial Dried Buckwheat Noodles Based on the Fluorescence Fingerprint
Predicting the Buckwheat Flour Ratio for Commercial Dried Buckwheat Noodles Based on the Fluorescence Fingerprint
复制标题
基于荧光指纹图谱预测商品荞麦干面的荞麦粉比
DOI：
10.1271/bbb.110091
复制
发表时间：
2011
期刊：
影响因子：
--
通讯作者：
H. Sakabe
中科院分区：
文献类型：
--
作者：
Mario Shibata;K. Fujita;J. Sugiyama;Mizuki Tsuta;Mito Kokawa;Yoshitane Mori;H. Sakabe
利用荧光指纹图谱和偏最小二乘回归建立了荞麦挂面中荞麦粉含量的快速预测方法。校正模型与验证数据的拟合结果显示R2 =0.78，SEP= 12.4%。通过删除几个含有额外成分的样品，对模型进行了改进，以获得更好的拟合。剔除醋、绿色茶、海藻、多糖增稠剂和山药后，得到最佳拟合（R2 =0.84，SEP=10.4%）。该结果表明，基于材料组成相似的样品，可以构建具有高精度的校准模型。所开发的方法不需要复杂的预处理，能够快速测量，样品量少，因此将适合于实际应用于食品工业。
A rapid method for predicting the buckwheat flour ratio of dried buckwheat noodles was developed by using the fluorescence fingerprint and partial least squares regression. Fitting the calibration model to validation datasets showed R 2=0.78 and SEP=12.4%. The model was refined for a better fit by deleting several samples containing additional ingredients. The best fit was finally obtained (R 2=0.84 and SEP=10.4%) by deleting the samples containing vinegar, green tea, seaweed, polysaccharide thickener, and yam. This result demonstrates that a calibration model with high accuracy could be constructed based on samples similar in material composition. The developed methodology requires no complex preprocessing, enables rapid measurement with a small sample amount, and would thus be suitable for practical application to the food industry.
食品研究所
DOI：
--
发表时间：
2004
期刊：
影响因子：
--
作者：
通讯作者：
--
通过激发发射矩阵成像三维可视化大豆种子发芽过程中的内部结构变化
DOI：
--
发表时间：
2007
期刊：
Transactions of the ASABE 50(6)
影响因子：
--
作者：
M. Tsuta;K. Miyashita;T. Suzuki;S. Nakauchi;Y. Sagara;J. Sugiyama
通讯作者：
J. Sugiyama