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山藥內(nèi)部品質(zhì)無損快速檢測裝置設(shè)計與實(shí)驗
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國家重點(diǎn)研發(fā)計劃項目(2021YFD1600101-06)


Design and Test of Non-destructive Rapid Testing Device for Internal Quality of Yam
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    摘要:

    隨著山藥加工產(chǎn)業(yè)的發(fā)展,山藥品質(zhì)快速無損檢測分級對產(chǎn)業(yè)鏈的健康發(fā)展具有實(shí)用意義,。以研發(fā)山藥多品質(zhì)無損快速檢測裝置為目的,基于可見/近紅外局部漫透射原理,根據(jù)山藥特殊外觀特點(diǎn)設(shè)計了山藥專用檢測探頭,通過對比實(shí)驗設(shè)計光路,研制了一種手持式山藥多品質(zhì)無損檢測裝置。裝置整體尺寸為150mm×80mm×150mm,質(zhì)量約590g,?;谘邪l(fā)裝置采集了150 個山藥的光譜信息,采集的光譜經(jīng)多元散射校正(Multiplicative scatter correction,MSC)后再利用隨機(jī)蛙跳算法(Shuffled frog leaping algorithm,SFLA)篩選特征波長,建立了山藥干 物質(zhì),、淀粉,、蛋白質(zhì)含量的偏最小二乘回歸(Partial least squares regression,PLSR)預(yù)測模型,其干物質(zhì)、淀粉,、蛋白質(zhì) 含量的驗證集相關(guān)系數(shù)分別為 0.965 3,、0.967 5、0.956 3,均方根誤差( Root mean square error,RMSE) 分別為 1.09% ,、 0.83% ,、0.15% ,剩余預(yù)測偏差(Residual predictive deviation,RPD)分別為3.67、3.50,、3.37,。 基于Qt開發(fā)工具利用C語言編寫了實(shí)時分析控制軟件,并將預(yù)測模型植入裝置中,進(jìn)行了外部驗證。利用研發(fā)裝置對50個未參與建模的山藥樣品干物質(zhì),、淀粉,、蛋白質(zhì)含量進(jìn)行了5次重復(fù)檢測,其變異系數(shù)分別為1.0%~1.2%、1.5%~1.7%,、1.4%~1.6%;50個山藥樣本干物質(zhì),、淀粉,、蛋白質(zhì)含量裝置檢測結(jié)果和標(biāo)準(zhǔn)理化值最大殘差絕對值分別為1.83%、1.64%,、0.26%,。結(jié)果表明,研發(fā)的手持式山藥多品質(zhì)無損檢測裝置可以滿足現(xiàn)場實(shí)時檢測需求。

    Abstract:

    As a tuber crop with the same origin as medicine and food, yam is becoming more and more favored by people. With the development of yam processing industry, rapid non-destructive testing and grading of yam quality is of great practical significance to the healthy development of the industrial chain. For the purpose of developing a multi-quality non-destructive rapid detection device for yam, based on the principle of visible / near-infrared local diffuse transmission, a special detection probe for yam was designed according to the special appearance characteristics of yam, and a hand-held multi-quality nondestructive testing device for yam was developed by designing the optical path through comparative experiments. The overall dimensions of the device were 150 mm × 80 mm × 150 mm and the weight was about 590 g. Based on the spectral information of 150 yams collected by the R&D device, the collected spectra were corrected by multiplicative scatter correction ( MSC ), and then the characteristic wavelengths were screened by the shuffled frog leaping algorithm (SFLA) to establish partial least squares regression (PLSR) prediction model of dry matter, starch and protein content of yams, the correlation coefficients of the validation set of dry matter, starch and protein were 0.965 3, 0.967 5 and 0.956 3, respectively, and the root mean square errors were 1.09% , 0.83% and 0.15% , respectively. Based on the Qt development tool, the real-time analysis and control software was written in C language, and the prediction model was implanted into the device for external verification. The dry matter, starch and protein contents of 50 yam samples not participating in the modeling were detected five times by using the R&D device, and the coefficients of variation were 1.0% ~ 1.2% , 1.5% ~ 1.7% and 1.4% ~ 1.6% , respectively. The absolute values of the maximum residuals of the dry matter, starch and protein of 50 yam samples were 1.83% , 1.64% and 0.26% , respectively. The results showed that the handheld yam multi-quality non-destructive testing device can meet the needs of real-time detection in the field.

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王威,李永玉,彭彥昆,馬劭瑾,吳繼峰,張悅湘.山藥內(nèi)部品質(zhì)無損快速檢測裝置設(shè)計與實(shí)驗[J].農(nóng)業(yè)機(jī)械學(xué)報,2025,56(2):495-502. WANG Wei, LI Yongyu, PENG Yankun, MA Shaojin, WU Jifeng, ZHANG Yuexiang. Design and Test of Non-destructive Rapid Testing Device for Internal Quality of Yam[J]. Transactions of the Chinese Society for Agricultural Machinery,2025,56(2):495-502.

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  • 收稿日期:2024-01-23
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  • 在線發(fā)布日期: 2025-02-10
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