【摘要】：隨著人們生活質(zhì)量的不斷提高以及對(duì)身體健康的重視程度越來越強(qiáng),消費(fèi)者對(duì)大米的適口性、營(yíng)養(yǎng)等品質(zhì)方面的需求也隨之提高。大米的品質(zhì)不但能讓消費(fèi)者在感官上特別享受,直接關(guān)系著人們身體對(duì)大米的消化以及吸收,而且在大米的貿(mào)易和相關(guān)科學(xué)領(lǐng)域的研究方面也至關(guān)重要。在大米的品質(zhì)評(píng)定中,水分和蛋白質(zhì)是評(píng)價(jià)大米價(jià)值的關(guān)鍵因素。大米的水分含量不單影響著大米的品質(zhì),更重要的是關(guān)系到公眾的食品安全問題。大米以及它的副產(chǎn)品同時(shí)提供人們每日所需要的能量和蛋白質(zhì),蛋白質(zhì)含量的高低在大米的食味品質(zhì)方面起著重要的作用。因此本文將以此作為著手點(diǎn),采用大米作為研究對(duì)象并利用近紅外光譜技術(shù)結(jié)合其水分和蛋白質(zhì)的含量進(jìn)行圖譜擬合,以求探索快速檢測(cè)實(shí)現(xiàn)的可能性。主要進(jìn)行了如下研究工作:(1)從黑龍江各地收集109個(gè)不同種類的大米樣品,利用Thermo Fisher公司Antaris II近紅外光譜儀對(duì)其進(jìn)行光譜掃描。然后采用傳統(tǒng)的國家標(biāo)準(zhǔn)化學(xué)方法對(duì)主要組成成分水分和蛋白質(zhì)的化學(xué)值進(jìn)行測(cè)定,為后續(xù)的數(shù)據(jù)處理以及模型的建立做好準(zhǔn)備工作。(2)針對(duì)大米蛋白質(zhì)的定量分析模型分別采用霍特林T2統(tǒng)計(jì)、X-Y殘差以及3D視圖分析三種方法進(jìn)行異常樣品的剔除。經(jīng)對(duì)比發(fā)現(xiàn)通過X-Y殘差分析方法剔除異常點(diǎn)后建立模型的RMSECV和R2分別從最初的0.2428和0.7626提升到了0.2060和0.8364。(3)采用The DUPLEX Method將水分和蛋白質(zhì)的樣品劃分為校正集和預(yù)測(cè)集,結(jié)果表明二者不單單在含量的范圍方面十分相近,在對(duì)樣品求得的平均值以及標(biāo)準(zhǔn)差上也十分相似,從而獲得符合實(shí)驗(yàn)要求且均勻分布的校正集和預(yù)測(cè)集,達(dá)到了本研究的預(yù)期效果。(4)對(duì)大米水分的原始光譜圖分別采用導(dǎo)數(shù)、歸一化以及平滑三種方法進(jìn)行去噪處理,經(jīng)對(duì)比發(fā)現(xiàn)平滑點(diǎn)數(shù)采用15點(diǎn)時(shí)去除噪聲后的建模效果最佳。對(duì)大米蛋白質(zhì)的原始光譜圖分別采用一階導(dǎo)數(shù)+平滑、二階導(dǎo)數(shù)+平滑以及正交信號(hào)校正三種去噪方法對(duì)光譜中所含的噪聲進(jìn)行消除,研究表明二階導(dǎo)數(shù)+平滑處理具有最好的去噪效果,其所建立模型的校正集決定系數(shù)R2更趨向于1,同時(shí)有著較低的校正集均方誤差根RMSECV。(5)對(duì)大米水分光譜采用MWPLS和IPLS波長(zhǎng)選擇方法進(jìn)行模型驗(yàn)證,通過對(duì)比發(fā)現(xiàn),MW-IPLS對(duì)水分光譜特征吸收波長(zhǎng)的選取是一種有效的方法。結(jié)合MWPLS和IPLS方法進(jìn)行波長(zhǎng)選擇,確定二者具有交叉的最優(yōu)波長(zhǎng)范圍4108-4386cm-1。在此波段采用PLSR建立大米水分的定量模型,預(yù)測(cè)集均方誤差根RMSEP為0.2753,其決定系數(shù)R2達(dá)到0.8597。(6)分別對(duì)80個(gè)校正集和24個(gè)預(yù)測(cè)集大米樣品的蛋白質(zhì)光譜建立PLSR和PCR模型。通過對(duì)比預(yù)測(cè)集均方根誤差根RMSEP和決定系數(shù)R2可以得出,PCR模型對(duì)大米蛋白質(zhì)含量的預(yù)測(cè)能力上表現(xiàn)更優(yōu),預(yù)測(cè)集均方根誤差根RMSEP和其決定系數(shù)R2達(dá)到0.1288和0.8865。綜上所述,本文利用近紅外光譜技術(shù)針對(duì)大米中水分和蛋白質(zhì)含量所建立的模型精度較高,具有一定的可行性,為今后大米成分的快速檢測(cè)提供新方法。
[Abstract]:With the continuous improvement of people's quality of life and the increasing emphasis on health, consumers'demand for the quality of rice, such as palatability, nutrition and so on, has also increased. Water and protein are the key factors in evaluating the value of rice. The water content of rice not only affects the quality of rice, but also the food safety of the public. The energy and protein needed and the protein content of rice play an important role in the food quality. Therefore, this paper will take this as the starting point, take rice as the research object, and use near infrared spectroscopy to fit the water and protein content of rice, in order to explore the possibility of rapid detection. The main research work is as follows: (1) 109 different kinds of rice samples were collected from Heilongjiang Province and scanned by Antaris II near infrared spectrometer of Thermo Fisher Company. Then the chemical values of water and protein were determined by traditional national standard chemical method for the follow-up. (2) Hotelling T2 statistics, X-Y residuals and 3D view analysis were used to eliminate the abnormal samples for the quantitative analysis model of rice protein. By comparison, the RMSECV and R2 of the model were established after removing the abnormal points by X-Y residuals analysis. (3) The DUPLEX Method was used to divide the water and protein samples into correction set and prediction set. The results showed that the two samples were not only very similar in the content range, but also very similar in the average value and standard deviation obtained from the samples, which accorded with the experimental requirements. (4) Derivative, normalization and smoothing were used to denoise the original spectrogram of rice moisture, and the smoothing point was found to be the best when the smoothing point was 15. The original spectrogram of rice protein was collected separately. Three denoising methods, first derivative + smoothing, second derivative + smoothing and orthogonal signal correction, are used to eliminate the noise contained in the spectrum. The results show that the second derivative + smoothing method has the best denoising effect. The calibration set determinant R2 of the model tends to be 1, and has a lower root mean square error of the calibration set RMSECV. (5) The MWPLS and IPLS wavelength selection methods were used to validate the model of water spectrum of rice. It was found that MW-IPLS was an effective method to select the characteristic absorption wavelength of water spectrum. The root mean square error (RMSEP) of prediction set was 0.2753, and the determination coefficient R2 was 0.8597. (6) PLSR and PCR models were established for protein spectra of 80 correction sets and 24 prediction sets respectively. The RMSEP and its determinant R2 are 0.1288 and 0.8865. In summary, the model established by near infrared spectroscopy for moisture and protein content in rice is more accurate and feasible, which provides a new method for rapid detection of rice components in the future. Method.
【學(xué)位授予單位】：東北農(nóng)業(yè)大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2017
【分類號(hào)】：TS210.7;O657.33

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