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首页> 外文期刊>Potato Research >Design, Construction, and Testing of an Automated NIR In-line Analysis System for Potatoes. Part I: Off-line NIR Feasibility Study for the Characterization of Potato Composition
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Design, Construction, and Testing of an Automated NIR In-line Analysis System for Potatoes. Part I: Off-line NIR Feasibility Study for the Characterization of Potato Composition

机译：马铃薯自动近红外在线分析系统的设计，构建和测试。第一部分：用于表征马铃薯成分的离线NIR可行性研究

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摘要

An off-line near-infrared reflectance (NIR) feasibility study was conducted to explore the critical steps in the NIR determination of the major potato constituents (dry matter, starch, and protein) in relatively large (10 kg) potato samples. The results were important for the design of an automated industrial analysis system for potatoes with in-line NIR. The 10-kg potato samples were pulped with an industrial rotary saw blade rasp. A critical step in the NIR measurements was the occurrence of phase separation in the potato pulp. Phase separation manifests itself directly after pulping the potatoes and significantly affects the NIR spectrum. Therefore, during the NIR measurements, the potato pulp had to be stirred continuously. The NIR spectra (1,100–2,500 nm) were measured by applying an optical fiber NIR probe (EDAPT-1) connected to the NIR spectrophotometer (Technicon Infralyzer IA 500). NIR models for the concentration of dry matter, starch, and coagulating protein in potatoes have been developed. With the partial least squares regression procedure, promising NIR models were calculated. The NIR models were validated using an independent validation set of potato samples. The root mean square error in prediction of the samples in the validation set was 0.5% (w/w) for dry matter, 0.63 (w/w) for starch concentration, and 0.06% (w/w) for the coagulating protein.
机译：进行了离线近红外反射（NIR）可行性研究，以探索NIR测定相对较大（10 kg）马铃薯样品中主要马铃薯成分（干物质，淀粉和蛋白质）的关键步骤。该结果对于设计具有在线NIR的马铃薯自动化工业分析系统非常重要。将10公斤马铃薯样品用工业旋转锯锉打浆。 NIR测量中的关键步骤是马铃薯浆中发生相分离。在土豆制浆后，相分离立即显现出来，并显着影响近红外光谱。因此，在NIR测量期间，必须连续搅拌马铃薯浆。通过使用连接到近红外分光光度计（Technicon Infralyzer IA 500）的光纤近红外探头（EDAPT-1）来测量近红外光谱（1,100–2,500 nm）。已经开发了马铃薯中干物质，淀粉和凝固蛋白浓度的NIR模型。通过偏最小二乘回归程序，可以计算出有希望的NIR模型。使用独立的马铃薯样品验证集对NIR模型进行了验证。验证集中样品预测的均方根误差为干物质为0.5％（w / w），淀粉浓度为0.63（w / w）和凝结蛋白为0.06％（w / w）。

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