揭示潜力:利用光谱技术提高小麦谷物和面粉中的蛋白质和质含量预测
1School of Biosystems and Food Engineering, University College Dublin (UCD), Belfield, Dublin, D04 V1W8, Ireland.
Current research in food science
|April 25, 2025
概括
可见范围高光谱成像 (HSI) 准确预测全谷物中的小麦蛋白和质含量. 这种非破坏性方法消除了研磨的需要,为小麦行业提供了更快,更精确的质量评估.
科学领域:
- 农业科学 农业科学
- 频谱学是一种光谱学.
- 食品质量分析 食品质量分析
背景情况:
- 在该行业中,小麦质量至关重要,蛋白质和质含量是关键参数.
- 测量这些品质的传统方法需要将小麦粒研磨成面粉,这是一个破坏性和耗时的过程.
研究的目的:
- 研究非破坏性高光谱成像 (HSI) 技术的潜力,以直接预测全麦谷物中的蛋白质和质含量.
- 为了准确的质量评估,比较不同频谱分析方法和仪器的性能.
主要方法:
- 收集了38种小麦品种的谷物样本.
- 使用传统方法测量蛋白质,湿和干质含量.
- 采用可见近红外HSI,短波红外HSI和富里埃变换近红外光谱在全谷物和面粉上获取的光谱数据.
- 应用部分最小平方回归 (PLSR) 和高斯过程回归 (GPR) 带有光谱预处理.
- 使用邻近组件分析来选择波长.
主要成果:
- 可见范围HSI使用高斯过程回归在整个内核数据上实现了蛋白质和质含量的高预测准确性 (R2>0.97).
- 该模型确定了可见光谱中的四个关键波长,以便准确预测.
- 对全谷物的非破坏性分析显示出非常高的精度,与传统方法相美.
结论:
- 可见范围超光谱成像非常适合直接,非破坏性预测小麦蛋白和质含量.
- 这种方法通过消除样品研磨的需要,大大简化了质量评估过程.
- 可见光谱信息对于准确确定小麦中的蛋白质和质相关参数至关重要.
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