本文選題：便攜式近紅外光譜儀 + 中波近紅外光譜�。� 參考：《光譜學(xué)與光譜分析》2017年06期

【摘要】：應(yīng)用便攜式近紅外光譜儀采集320份生鮮豬肉在近紅外光譜中波區(qū)的光譜信息,采用不同優(yōu)化方法建立豬肉膽固醇預(yù)測模型,并對異常樣品的剔除及組合預(yù)處理方法對模型性能的改善進(jìn)行了分析。研究表明:通過對異常值的二次剔除,并使用SG一階導(dǎo)數(shù)(savitzky-golay first derivative,SG 1st D)、SG平滑(savitzky-golay smoothing,SGS)和正交信號校正(OSC)的組合預(yù)處理方法,可獲得最佳生鮮豬肉膽固醇預(yù)測模型,其參數(shù)如下:校正集相關(guān)系數(shù)(Rc)=0.9137,校正標(biāo)準(zhǔn)差(standard error of calibration,SEC)=2.5607,驗(yàn)證集相關(guān)系數(shù)(Rp)=0.656 7,預(yù)測標(biāo)準(zhǔn)差(standard error of prediction,SEP)=4.985 5,主因子數(shù)(principal factor,PF)=4,范圍誤差比(ratio of performance to standard deviation,RPD)=2.5032,相對預(yù)測標(biāo)準(zhǔn)差(relative standard error of prediction,RSEP)=8.625 4%,SEP/SEC=1.946 8,說明模型在近紅外光譜中波區(qū)對豬肉膽固醇的分辨能力和預(yù)測準(zhǔn)確度較好,通過向校正集中補(bǔ)充代表性樣品可使模型穩(wěn)健性進(jìn)一步改善。對檢驗(yàn)集樣品預(yù)測值(prediction value,PV)與參比值(reference value,RV)的t檢驗(yàn)顯示二者之間無顯著性差異(p0.05),檢驗(yàn)集樣品總體預(yù)測準(zhǔn)確率為62.5%,其中50~70mg·(100g)-1區(qū)段的局部預(yù)測準(zhǔn)確率達(dá)到91.7%,可以用于生鮮豬肉膽固醇濃度的在線快速初步定量分析。該研究將便攜式近紅外光譜用于在近紅外中波區(qū)對生鮮豬肉及肉制品中膽固醇濃度的分析和檢測,通過進(jìn)一步的研究和改進(jìn),可將其應(yīng)用于產(chǎn)品的原料分級、品質(zhì)和過程控制及市售產(chǎn)品的抽檢等。
[Abstract]:A portable near infrared spectrometer was used to collect the spectral information of 320 fresh pork in the wave region of the near infrared spectrum. The prediction model of pork cholesterol was established by different optimization methods. The elimination of abnormal samples and the improvement of the model performance were analyzed. The results showed that the two times of the abnormal value were eliminated, and the results were analyzed. Using the first derivative of SG (Savitzky-Golay first derivative, SG 1st D), SG smoothing (Savitzky-Golay smoothing, SGS) and orthogonal signal correction (OSC), the prediction model of the best fresh pork cholesterol can be obtained. The parameters are as follows: correction set phase relation and calibration standard deviation =2.5607, verify set correlation coefficient (Rp) =0.656 7, predict standard deviation (standard error of prediction, SEP) =4.985 5, principal factor number (principal factor, PF), and relative prediction standard deviation 4%, 8, It shows that the model has good resolution and prediction accuracy for pork cholesterol in the near infrared spectrum, and the robustness of the model can be further improved by adding representative samples to the corrected concentration. The t test of the sample prediction value (prediction value, PV) and the ratio (reference value, RV) of the test set shows that there is no significant difference between the two. P0.05, the overall prediction accuracy of the test set sample is 62.5%, of which the local prediction accuracy of the 50~70mg (100g) -1 section reaches 91.7%, and it can be used for the on-line fast preliminary quantitative analysis of the cholesterol concentration of fresh pork. Through further research and improvement, it can be applied to raw material grading, quality and process control, and sampling inspection of commercial products.
【作者單位】： 中國肉類食品綜合研究中心肉類加工技術(shù)北京市重點(diǎn)實(shí)驗(yàn)室;中國農(nóng)業(yè)大學(xué)食品科學(xué)與營養(yǎng)工程學(xué)院教育部-北京市功能乳品實(shí)驗(yàn)室;
【基金】：國家“十二五”科技支撐計劃項目(2014BAD04B05) 北京市農(nóng)業(yè)科技項目(20150155)資助
【分類號】：O657.33;TS251.51

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