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使用近红外光谱学和多变量回归方法预测玉米料的类可降解性和化学成分

Pauliane Pucetti¹, Sebastião de Campos Valadares Filho¹, Jussara Valente Roque²

¹Department of Animal Sciences, Universidade Federal de Viçosa, Viçosa, Minas Gerais, Brazil.

|April 18, 2024

概括

近红外光谱 (NIR) 能够有效地预测玉米料成分和反动物降解参数,为营养学家提供快速的实地工具. 模型准确地估计了大多数属性,不包括有机物质,具有高相关系数.

科学领域:

农业科学农业科学
分析化学分析化学
动物营养动物营养

背景情况:

准确评估玉米料 (CS) 的营养价值对于动物养至关重要.
近红外光谱 (NIR) 为化学分析提供了一种快速,非破坏性的方法.
开发可靠的预测模型,用于CS组成和反动物降解,对于实际应用至关重要.

研究的目的:

开发和验证回归模型,用NIR光谱来预测玉米料的化学成分.
开发和验证回归模型,以使用NIR光谱学预测玉米料的反体降解参数.
评估NIR作为营养学家的实地工具的潜力.

主要方法:

94个玉米料样本使用湿化学分析了化学成分.
进一步分析了23个样本,以检测动物降解参数.
采集和分析NIR光谱 (900-1700nm) 使用部分最小平方 (PLS) 回归和有序预测器选择 (OPS).

主要成果:

回归模型准确地预测了大多数玉米料成分参数 (P>0.05),除了有机物 (OM).
无法开发OM和原蛋白的潜在可降解分数以及OM的降解率的预测模型.
动物降解参数模型显示校准相关系数在0.530到0.985.5之间.

结论:

尼尔射线光谱显示,在快速预测玉米料化学成分方面,有很大的潜力.
对于营养学家来说,NIR是一个有希望的实用农场工具,用于估计关键的反动物降解参数.
为了准确预测特定参数,如有机物和某些降解分数,可能需要进一步的细化.

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