本文選題：羊肉 + pH��； 參考：《石河子大學(xué)》2017年碩士論文

【摘要】：羊肉是我國(guó)西北少數(shù)民族地區(qū)的主要肉類(lèi)消費(fèi)品,隨著人們膳食結(jié)構(gòu)的多樣化和對(duì)羊肉營(yíng)養(yǎng)價(jià)值認(rèn)可度的不斷提高,羊肉已從部分人消費(fèi)轉(zhuǎn)向全民消費(fèi)。冷卻羊肉與冷凍羊肉、熱鮮羊肉相比成熟更加充分,營(yíng)養(yǎng)價(jià)值更高,口感更好,已成為居民消費(fèi)的主流。但由于我國(guó)冷鏈系統(tǒng)不夠完善,冷卻羊肉在加工、儲(chǔ)藏、運(yùn)輸和銷(xiāo)售中易發(fā)生變質(zhì),內(nèi)部組分和外部感官性質(zhì)都會(huì)發(fā)生變化。不同的包裝方式肉的呼吸方式不同,內(nèi)部組分和外部感官特性變化不同,對(duì)肉品貨架期和品質(zhì)變化規(guī)律影響也不同。pH、顏色亮度(L*)和微生物菌落總數(shù)與肉的新鮮度密切相關(guān),三者是評(píng)價(jià)畜肉新鮮度的重要指標(biāo)。傳統(tǒng)檢測(cè)手段已無(wú)法滿(mǎn)足現(xiàn)代畜肉新鮮度大批量、快速無(wú)損檢測(cè)要求,嚴(yán)重制約了新疆冷卻羊肉走高端化發(fā)展路線(xiàn)。本文以新疆冷卻羊肉為研究對(duì)象,通過(guò)實(shí)驗(yàn)和總結(jié)國(guó)內(nèi)外學(xué)者研究成果,分析了光纖結(jié)構(gòu)參數(shù)和采集方式對(duì)光譜的影響。利用近紅外光譜漫反射技術(shù)結(jié)合化學(xué)計(jì)量學(xué)方法對(duì)不同儲(chǔ)藏時(shí)間下真空包裝冷卻羊肉p H、L*和菌落總數(shù)進(jìn)行檢測(cè)研究。比較不同光譜預(yù)處理方法和不同波段下所建模型的效果,優(yōu)選出真空包裝冷卻羊肉新鮮度參數(shù)最佳特征波長(zhǎng)提取方法和最佳定量預(yù)測(cè)模型。為實(shí)現(xiàn)冷卻羊肉新鮮度品質(zhì)近紅外快速無(wú)損檢測(cè)提供理論支撐和技術(shù)支持。研究?jī)?nèi)容和結(jié)果如下:(1)對(duì)光纖傳感器的工作原理進(jìn)行研究,總結(jié)分析國(guó)內(nèi)外學(xué)者關(guān)于光纖結(jié)構(gòu)參數(shù)對(duì)光強(qiáng)調(diào)制特性影響的研究成果并結(jié)合實(shí)驗(yàn),確定了適用于羊肉近紅外光譜采集光纖的選用和設(shè)計(jì)原則,并在指導(dǎo)原則下完成了“9入3出”同軸A型光纖和與VIVO光源匹配的“3出”同軸B型光纖的設(shè)計(jì)。(2)基于VIVO光源、QP400-1-VIS-NIR、QR400-7-VIS-NIR光纖和NIRQuest256-2.5近紅外光譜儀組成的光譜采集系統(tǒng),分析了不同采集參數(shù)、儀器檢測(cè)時(shí)間和采集距離對(duì)光譜采集質(zhì)量的影響。積分時(shí)間越長(zhǎng),光譜的反射值越大,信噪比較好,但積分時(shí)間過(guò)長(zhǎng)導(dǎo)致白參照光譜飽和,引起光譜部分波段變形。增加平滑度,光譜曲線(xiàn)較平滑,噪聲減小,較小波峰波谷丟失。增加平均次數(shù),光譜信號(hào)質(zhì)量增高,但儀器系統(tǒng)誤差增加。儀器檢測(cè)時(shí)間越長(zhǎng),光譜基線(xiàn)漂移越嚴(yán)重。增大光纖探頭與樣本之間的距離,光譜反射值先增大再減小。(3)在1~20天儲(chǔ)藏時(shí)間內(nèi)真空包裝冷卻羊肉pH值先減小后增大再減小。對(duì)比分析不同預(yù)處理方法對(duì)PLSR模型效果的影響,得其最佳光譜預(yù)處理方法為1階導(dǎo)(1D)、15點(diǎn)S-G平滑和中心化(MC)的組合。比較分析不同波段下W-PLSR、GA-PLSR、SPA-MLR、GA-SPA-MLR、SiPLS-PLSR模型效果,發(fā)現(xiàn)經(jīng)GA-SPA方法提取的15個(gè)特征波長(zhǎng)建立的MLR模型效果最優(yōu),相關(guān)系數(shù)Rc、Rcv、Rp分別為0.92、0.89、0.91,均方根誤差RMSEC、RMSECV、RMSEP分別而0.13、0.15、0.13。(4)真空包裝冷卻羊肉顏色亮度(L*)在1~20天的儲(chǔ)藏時(shí)間內(nèi)先增大再減小再增大。其對(duì)應(yīng)的光譜最佳預(yù)處理方法為1階導(dǎo)(1D)、17點(diǎn)S-G平滑和數(shù)值中心化(MC)的組合。分別采用GA、SAP、GA-SPA、SiPLS提取特征波長(zhǎng)建立相應(yīng)PLSR模型和MLR模型并與全波段光譜PLSR模型比較,得GA-SPA提取的18個(gè)特征變量建立的MLR模型效果總體最優(yōu),相關(guān)系數(shù)Rc、Rcv、Rp分別為0.95、0.93、0.91,均方根誤差RMSEC、RMSECV、RMSEP分別位1.36、1.62、1.91。(5)真空包裝冷卻羊肉菌落總數(shù)在儲(chǔ)藏時(shí)間內(nèi)先降低再上升。2階導(dǎo)(2D)、13點(diǎn)S-G平滑和數(shù)值中心化(MC)的組合方法為其光譜最佳預(yù)處理方法。通過(guò)比較分析不同波段下的W-PLSR、GA-PLSR、SPA-MLR、GA-SPA-MLR、SiPLS-PLSR模型效果,得GA-SAP-MLR模型(26個(gè)點(diǎn))預(yù)測(cè)效果最優(yōu),相關(guān)系數(shù)Rc、Rcv分別為0.95、0.92,均方根誤差RMSEC、RMSECV分別位0.45、0.59。(6)GA-SPA方法相較于GA、SPA、SiPLS特征提取方法,其更能有效剔除光譜中的冗余信息得到與理化值相關(guān)的特征波長(zhǎng),能在減少建模所用波長(zhǎng)點(diǎn)的同時(shí)保持模型精度無(wú)顯著差異或略微提升。
[Abstract]:Mutton is the main meat consumption product in the minority areas of Northwest China. With the diversification of the dietary structure and the increasing recognition of the nutritional value of the mutton, mutton has shifted from some people to the whole people. The chilled mutton and frozen mutton are cooled and the hot fresh mutton is more mature, more nutritious and better in taste. But because the cold chain system in China is not perfect enough, the chilled mutton is easily deteriorated in processing, storage, transportation and sales. The internal components and external sensory properties will change. The different ways of breathing are different, the internal components and the external sensory characteristics vary, and the shelf life and quality of the meat products are different. The influence of the change law is also different from.PH, the color brightness (L*) and the total number of microbial colonies are closely related to the freshness of the meat. The three is an important index to evaluate the freshness of the meat. The traditional detection method has not met the large quantity of fresh meat freshness and the rapid nondestructive testing requirement, which seriously restricts the advanced development route of the chilled mutton in Xinjiang. Taking Xinjiang chilled mutton as the research object, the effects of optical fiber structure parameters and collection methods on the spectrum are analyzed by experimentation and summary at home and abroad. Using near infrared diffuse reflectance technology and chemometrics methods, the P H, L* and total colony number of vacuum packed mutton in different storage times are examined and studied. Compared with the effects of different spectral preprocessing methods and the models under different wavelengths, the optimum characteristic wavelength extraction method and the optimal quantitative prediction model of the vacuum packaging cooling lamb fresh degree parameters were optimized. The theoretical support and technical support were provided for the near infrared fast nondestructive testing of the freshness quality of the chilled mutton. The following are as follows: (1) to study the working principle of fiber optic sensors and to summarize and analyze the research results of the influence of optical fiber structural parameters on the optical intensity modulation characteristics of domestic and foreign scholars and to combine experiments to determine the principle of selection and design for the optical fiber of lamb near infrared spectrum acquisition, and to complete the "9 into 3" coaxial A type under the guiding principle. Optical fiber and the design of "3 out" coaxial B optical fiber matched with VIVO light source. (2) a spectral acquisition system based on VIVO light source, QP400-1-VIS-NIR, QR400-7-VIS-NIR optical fiber and NIRQuest256-2.5 near infrared spectrometer. The influence of different acquisition parameters, detection time and acquisition distance on the quality of spectral acquisition is analyzed. The longer the integration time, The greater the reflection value of the spectrum is, the better the signal to noise, but the longer the time of the integration leads to the saturation of the white ginseng spectrum and the deformation of some spectral bands. The smoothness is increased, the spectral curve is smooth, the noise is reduced, the smaller the peak wave valley is lost. The increase of the average number of times, the increase of the spectral signal quality, the increase of the instrument system error. The longer the instrument detection time, the longer the instrument detection, the light is The spectral baseline drift is more serious. Increasing the distance between the optical fiber probe and the sample, the spectral reflection value increases first and then decreases. (3) the pH value of the vacuum packed chilled mutton decreases first and then decreases in 1~20 days storage time. The effect of different pretreatment methods on the effect of the PLSR model is compared and analyzed, and the best spectral preprocessing method is 1 order Guide (1D), 15 The combination of point S-G smoothing and centralization (MC) is used to compare and analyze the effect of W-PLSR, GA-PLSR, SPA-MLR, GA-SPA-MLR, SiPLS-PLSR model under different wavelengths. It is found that the results of the MLR model established by the 15 characteristic wavelengths extracted by GA-SPA method are the best, the correlation coefficient is Rc, Rcv, Rp, respectively. 13. (4) vacuum packed cool lamb color luminance (L*) increases first and then decreases in storage time of 1~20 days. Its corresponding spectral best pretreatment methods are 1 order Guide (1D), 17 point S-G smoothing and numerical centralization (MC). The corresponding PLSR model and MLR model are established by using GA, SAP, GA-SPA, SiPLS to establish the corresponding PLSR model and MLR model, respectively. Compared with the PLSR model of the segment spectrum, the MLR model obtained by 18 characteristic variables extracted by GA-SPA is the best, the correlation coefficient Rc, Rcv, Rp are 0.95,0.93,0.91, the root mean square error RMSEC, RMSECV, RMSEP respectively 1.36,1.62,1.91. (5) vacuum package cooling lamb colonies decrease first and then increase.2 order and 13 point flat. The combination method of sliding and numerical centralization (MC) is the best method of spectral preprocessing. By comparing and analyzing the effects of W-PLSR, GA-PLSR, SPA-MLR, GA-SPA-MLR, SiPLS-PLSR model in different bands, the prediction effect of GA-SAP-MLR model (26 points) is optimal, the correlation coefficient Rc, Rcv are 0.95,0.92, the root mean square error is RMSEC, RMSECV respectively ( 6) the GA-SPA method is better than the GA, SPA, SiPLS feature extraction method. It can effectively eliminate the redundant information in the spectrum and get the characteristic wavelengths associated with the physical and chemical values. It can reduce the wavelength points used in the modeling and keep the model accuracy without significant difference or slightly increase.
【學(xué)位授予單位】：石河子大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2017
【分類(lèi)號(hào)】：TS251.53;O657.33

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