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米豆-阿祖基豆多特征近红外反射光谱预测模型:一种快速挖掘工具,用于特征特定的生殖质

Racheal John¹, Arti Bartwal², Christine Jeyaseelan¹

¹Amity Institute of Applied Science, Amity University, Noida, India.

Frontiers in nutrition

|January 1, 2024

概括

没有充分利用的米豆和阿兹基豆提供了高营养和气候适应性. 接近红外光谱 (NIRS) 与化学测量相结合,提供了一种快速,准确的方法来评估它们的营养含量,支持它们在粮食安全中的作用.

科学领域:

农业科学农业科学
食品科学食品科学食品科学
分析化学分析化学

背景情况:

由于气候适应性和高营养价值,未充分利用的豆类如大米豆和阿兹基豆对于粮食安全至关重要.
传统的营养分析是昂贵和耗时的,需要更快,非侵入性的方法.

研究的目的:

开发一个结合的近红外反射光谱 (NIRS) 预测模型,用于估计大米豆和阿祖基豆粉中的多种营养成分.
评估NIRS作为一种快速而准确的工具,用于对这些未充分利用的豆类进行营养评估的潜力.

主要方法:

为每种作物 (大米豆和阿祖基豆) 选择了20种不同的接入方式.
利用了15次用于培训和5次用于验证NIRS模型的访问.
应用化学测量技术,优化导数,间隙,光滑和散射校正方法,用于NIRS数据分析.

主要成果:

实现了高准确性 (RSQ>0.9) 预测大多数营养参数,包括总粉,蛋白质,糖,植物酸盐,食纤维和素.
对于验证组中的矿物质,脂肪和含量,NIRS模型的准确性较低 (RSQ < 0.6).
确定了针对特定营养特征的最佳NIRS模型参数 (衍生品,差距,光滑,分散校正).

结论:

开发的NIRS模型提供了一种快速有效的方法,用于对大米豆和阿祖基豆的营养概况.
这些模型可以促进利用未充分利用的豆类作为促进健康的功能性食品.
对于未充分利用的豆类作物的质量控制和营养评估,NIRS技术显示出显著的前景.

关键词:

在RPD中使用RPD.在 RSQ RSQ 里面.在SNV-DT标准中,正常的变化是决定变化的.这是WMSC的WMSC.的确定系数.矿物质是矿物质中的一种.这是一个回归回归的回归.权重的乘法散射校正加权的分散校正.

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