A Study of the Reliability and Accuracy of the Real-Time Detection of Forage Maize Quality Using a Home-Built Near-Infrared Spectrometer.
A Study of the Reliability and Accuracy of the Real-Time Detection of Forage Maize Quality Using a Home-Built Near-Infrared Spectrometer.
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DOI：
10.3390/foods11213490
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发表时间：
2022-11-03
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影响因子：
--
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中科院分区：
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为研究光栅式近红外光谱在线检测系统对饲用玉米品质的实时检测能力，建立了基于光栅式近红外光谱在线检测系统的饲用玉米品质检测模型。对影响在线近红外光谱采集的因素参数进行了分析，结果表明：检测光路为12 cm，传送带速度为10 cm s-1，扫描次数为32次为最佳参数。以饲用玉米的粗蛋白和水分为品质指标，通过与常规近红外光谱仪的对比，验证了自制近红外在线光谱仪的可靠性。建立了基于偏最小二乘法（PLS）的饲用玉米品质近红外在线多元分析预测模型，并对模型的可靠性、适用性和稳定性进行了探讨。结果表明，自行研制的光栅式近红外在线系统对饲用玉米品质的实时预测具有较好的准确性和可重复性。
The current study was conducted to explore the real-time detection capability of a home-built grating-type near-infrared (NIR) spectroscopy online system to determine forage maize quality. The factor parameters affecting the online NIR spectrum collection were analyzed, and the results indicated that the detection optical path of 12 cm, conveyor speeds of 10 cm s−1, and number of scans of 32 were the optimal parameters. Choosing the crude protein and moisture of forage maize as quality indicators, the reliability of the home-built NIR online spectrometer was confirmed compared with other general research NIR instruments. In addition, an NIR online multivariate analysis model developed using the partial least squares (PLS) method for the prediction of forage maize quality was established, and the reliability, applicability, and stability of the NIR model were further discussed. The results illustrated that the home-built grating-type NIR online system performed satisfying and comparable accuracy and repeatability of the real-time prediction of forage maize quality.
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