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在Javadi cv.中进行质量参数的非破坏性评估. 桃子使用Vis/NIR光谱和多重回归分析
Vali Rasooli Sharabiani1, Nadia Saadati1, Fatemeh Alizadeh1
1Department of Biosystem Engineering, Faculty of Agriculture and Natural Resources, University of Mohaghegh Ardabili, Ardabil, Iran.
这项研究使用光谱辐射计来非破坏性地预测贾瓦迪桃子的质量,包括pH值,可定位酸 (TA) 和可溶性固体 (SSC). 该方法为水果质量评估提供了一种快速且具有成本效益的替代方法,而不是破坏性测试.
科学领域:
- 农业科学 农业科学
- 食品科学与技术 食品科学与技术
- 频谱学是一种光谱学.
背景情况:
- 评估水果质量传统上涉及破坏性方法,这些方法耗时且昂贵.
- 非破坏性技术,特别是光谱,为快速质量评估提供了一个有希望的替代方案.
- 贾瓦迪桃需要高效的质量评估方法来满足市场需求.
研究的目的:
- 开发和验证用于预测贾瓦迪桃子关键质量参数的非破坏性方法.
- 为了评估电容阵列 (CCD) 光谱辐射仪的有效性,用于质量评估.
- 为了比较各种光谱数据处理技术在预测桃子质量属性的性能.
主要方法:
- 使用CCD光谱辐射仪 (350-1150nm) 来获取光谱数据.
- 使用多变量部分最小平方 (PLS) 回归模型进行预测.
- 应用光谱数据处理技术,包括萨维茨基-戈利平滑 (SG),第一个导数 (D1),乘法散射校正 (MSC),标准正常变量 (SNV) 和基线校正.
主要成果:
- 在预测pH (rp=0.94) 方面取得了高准确性,对于可定位酸 (TA) (rp=0.86) 和可溶性固体 (SSC) (rp=0.85) 的中等准确性.
- 对于总 (TP) 和可提取的素 (EA),模型性能各不相同,标准偏差比率 (SDR) 低于1.5.5.
- 使用特定的光谱处理技术 (例如,pH的原始光谱,TA的D1,SSC的MSC) 的优化模型显示出良好的预测能力.
结论:
- 非破坏性光谱辐射计,加上适当的数据处理和PLS回归,是有效的预测关键质量参数在贾瓦迪桃.
- 这种方法为传统的破坏性质量评估方法提供了快速,经济有效和非破坏性的替代方案.
- 可能需要进一步的研究来提高TP和EA等参数的预测准确性.
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