本文選題：雞蛋　切入點：新鮮度　出處：《光譜學(xué)與光譜分析》2016年08期

【摘要】：借助高光譜成像儀采集貯期白殼雞蛋的透射高光譜數(shù)據(jù),對比測量常規(guī)表征新鮮度的哈夫單位值,用Matrix Laboratory(MATLAB)和Statistical Analysis System(SAS)等軟件,同時結(jié)合化學(xué)計量法對樣品雞蛋的高光譜數(shù)據(jù)進(jìn)行分析處理,建立了基于高光譜技術(shù)的雞蛋新鮮度預(yù)測模型。選用高光譜500~1000nm的波段作為敏感波段進(jìn)行研究,用馬氏距離剔除雞蛋異常樣本數(shù)據(jù),并對雞蛋高光譜數(shù)據(jù)進(jìn)行了微分校正,通過比較發(fā)現(xiàn)高光譜二階微分與雞蛋哈夫單位值之間的線性度高,因此選用高光譜二階微分?jǐn)?shù)據(jù)來進(jìn)一步研究,并對其進(jìn)行了小波去噪、光滑處理及標(biāo)準(zhǔn)化處理。選用近年新提出來的competitive adaptive reweighted sampling(CARS)變量選取法對高光譜進(jìn)行降維,提取出32個特征參數(shù),建立了白殼蛋基于全波段的偏最小二乘法(partial least square,PLS)預(yù)測模型和基于特征參數(shù)的多元回歸模型,驗證集的相關(guān)系數(shù)分別為0.88,0.93,均方誤差分別為7.565,6.44。用驗證集的蛋對基于高光譜二階微分全波段的偏最小二乘法預(yù)測模型、基于特征參數(shù)的多元回歸模型分別進(jìn)行驗證,兩個模型判別白殼蛋新鮮和不新鮮的最高準(zhǔn)確率達(dá)100%,88%。
[Abstract]:The transmission hyperspectral data of white shell eggs during storage period were collected by means of hyperspectral imager, and Haff unit values, which were used to characterize freshness, were compared and measured. The software such as Matrix Laboratory MATLAB and Statistical Analysis system saps were used to measure the freshness of eggs.At the same time, the hyperspectral data of sample eggs were analyzed and processed by chemometrics, and a prediction model of egg freshness based on hyperspectral technology was established.Using the band of hyperspectral 500~1000nm as the sensitive band, the abnormal sample data of eggs are eliminated by Markov distance, and the hyperspectral data of eggs are corrected by differential correction.It is found that the linearity between the second order differential of hyperspectral and the unit value of egg Have is high, so the hyperspectral second order differential data is selected for further study, and wavelet denoising, smoothing and standardization are carried out.The hyperspectral dimensionality reduction is carried out by using competitive adaptive reweighted sampling method, which has been proposed in recent years, and 32 characteristic parameters are extracted. The prediction model and multivariate regression model of white shell egg based on partial least square method and feature parameter are established.The correlation coefficient of the verification set is 0.880.93, and the mean square error is 7.565 ~ 6.44.A partial least square prediction model based on hyperspectral second-order differential full-band method is used to predict the eggs of the verification set, and the multivariate regression model based on the characteristic parameters is verified respectively. The highest accuracy of the two models in judging the fresh and unfresh white shell eggs is 100% and 8888% respectively.
【作者單位】： 華中農(nóng)業(yè)大學(xué)工學(xué)院;國家蛋品加工技術(shù)研發(fā)分中心華中農(nóng)業(yè)大學(xué);
【基金】：國家自然科學(xué)基金項目(31371771) 公益性行業(yè)(農(nóng)業(yè))科研專項(201303084) 國家科技支撐計劃項目(2015BAD19B05)資助
【分類號】：O657.3;TS253.7

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本文編號：1718816