Research on the Independent Model and General Quantitative Model of Commercial Goat Milk Powder Quality Index Based on Near Infrared Spectroscopy Technology

QIAO Chunyan; ZHANG Xueru; ZHENG Weimin; LI Ling; LIU Yongfeng

doi:10.13386/j.issn1002-0306.2021030153

Volume 42 Issue 22

Nov. 2021

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Science and Technology of Food Industry > 2021 > 42(22): 297-305. > DOI: 10.13386/j.issn1002-0306.2021030153

QIAO Chunyan, ZHANG Xueru, ZHENG Weimin, et al. Research on the Independent Model and General Quantitative Model of Commercial Goat Milk Powder Quality Index Based on Near Infrared Spectroscopy Technology[J]. Science and Technology of Food Industry, 2021, 42(22): 297−305. (in Chinese with English abstract). doi: 10.13386/j.issn1002-0306.2021030153.

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Research on the Independent Model and General Quantitative Model of Commercial Goat Milk Powder Quality Index Based on Near Infrared Spectroscopy Technology

1.
College of Food Engineering and Nutrition Science, Shaanxi Normal University, Xi'an 710119, China
2.
Xi'an Cow Breeding Center, Xi'an 710075, China

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Received Date: March 11, 2021
Available Online: September 08, 2021

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Abstract

Abstract

In order to achieve online monitoring of the quality index in the production of goat milk powder, a generic model and an independent model for protein, fat, lactose, moisture, acidity and total ash of goat milk powder were established based on NIR spectroscopy. The six quality indexes near infrared spectral data were preprocessed in 28 different ways combined seven smoothing methods and four algorithms based on modified partial least square method(MPLS), including the general model of all goat milk powder and two independent models of Shaanxi province goat milk powder and pure sheep milk powder. It was aimed to obtain the prediction performance of the three models and the applicability of the general model to the two independent models. The results showed that the standard deviations(SEP) of the 2 independent models based on the 6 quality indicators of Shaanxi goat milk powder and pure goat milk powder were 0.043~0.412 and 0.027~0.304, and the prediction coefficient of determination(RSQ) were 0.889~0.998 and 0.977~0.998, respectively. The SEP and RSQ of the 6 indicators of the universal quantitative model were 0.034~0.732 and 0.970~0.999, respectively. They all have good predictive ability. The applicability verification results of the general model showed that the general model prediction ability of protein, fat, moisture and acidity of Shaanxi goat milk powder and the acidity of pure goat milk powder was all improved when compared with the independent model. These results confirmed that the general model and independent model were feasible for fast and non-destructive prediction of the quality indicators of goat milk powder on the market. The general model had improved the predictive ability of some indicators of the two independent models, which could realize more economic online monitoring the different goat milk powder.
- near infrared spectroscopy,
- goat milk powder,
- quality,
- derivative processing,
- modified partial least square method,
- calibration model

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[1]	罗军, 史怀平, 王建民, 等. 中国奶山羊产业发展综述——各省发展水平及建议[J]. 中国奶牛,2019(10):6−13. [LUO J, SHI H M, Wang J M, et al. Overview of China's dairy goat industry development-provincial development level and suggestions[J]. China Dairy Cattle,2019(10):6−13.
[2]	崔磊, 黄米妮, 张力, 等. 功能性奶粉国内市场现状及发展趋势分析[J]. 江苏农业科学,2011,39(4):8−11. [CUI L, HUANG M N, ZHANG L, et al. Analysis of the status quo and development trend of functional milk powder domestic market[J]. Jiangsu Agricultural Sciences,2011,39(4):8−11. doi: 10.3969/j.issn.1002-1302.2011.04.003
[3]	杨晶晶. 市售不同品牌全脂山羊奶粉品质特性的研究[D]. 呼和浩特: 内蒙古农业大学, 2014. YANG J J. Study on the quality characteristics of different brands of whole goat milk powder on the market[D]. Hohhot: Inner Mongolia Agricultural University, 2014.
[4]	张华秀, 李晓宁, 范伟, 等. 近红外光谱结合Boosting-PLS快速检测奶粉中蛋白质含量[J]. 计算机与应用化学,2010,27(9):1197−1200. [ZHANG H X, LI X N, FAN W, et al. Fast measurement of protein content in milk powder by NIR combined with boosting-PLS[J]. Computers and Applied Chemistry,2010,27(9):1197−1200. doi: 10.3969/j.issn.1001-4160.2010.09.008
[5]	DOUGLAS H M, REGINALD W, ARVO K, et al. Comparison of two infrared spectroscopic methods for cheese analysis[J]. Talanta,1995,42:2007−2015. doi: 10.1016/0039-9140(95)01685-6
[6]	吴钰蔚, 邓云, 郑远荣, 等. 射频处理对婴儿奶粉氨基酸、形貌和吸附特征的影响[J]. 中国食品学报,2019,19(5):122−128. [WU Y W, DENG Y, ZHENG Y R, et al. Effect of radio frequency treatment on amino acid composition, morphology and adsorption characteristics of infant milk powder[J]. Journal of Chinese Institute of food Science and Technology,2019,19(5):122−128.
[7]	赵瑾, 许喜林, 张勇, 等. 不同发酵条件对酸奶粉影响的研究[J]. 食品工业科技,2008(11):203−204, 207. [ZHAO J, XU J L, ZHANG Y, et al. Study on the influence of different fermentation methods on yoghurt powder[J]. Science and Technology of Food Industry,2008(11):203−204, 207.
[8]	LAVERROUX S, PICARD F, ANDUEZA D, et al. Vitamin B2 concentration in cow milk: Quantification by a new UHPLC method and prediction by visible and near-infrared spectral analysis[J]. Food Chemistry,2020:128310.
[9]	RENATA L G, ANA L S, PEDRO P B, et al. Production and evaluation of a reference material for moisture, ash, and total fat mass fractions, and titratable acidity in whole milk powder[J]. Accreditation and Quality Assurance,2016,21(1):47−55. doi: 10.1007/s00769-015-1179-3
[10]	GASTÉLUM-BARRIOS A, SOTO-ZARAZÚA G M, GARCÍA-TREJO J F, et al. A new method for total fat detection in raw milk based on dual low-coherence interferometer[J]. Sensors,2019,19(20):4562. doi: 10.3390/s19204562
[11]	李双红, 刘永峰, 韩裕睿, 等. 不同胎次奶牛乳中乳蛋白含量的近红外光谱定量分析[J]. 食品工业科技,2014,35(4):60−65. [LI S H, LIU Y F, HAN Y R, et al. Quantitative analysis of milk protein content in different parities cows based on near infrared spectroscopy[J]. Science and Technology of Food Industry,2014,35(4):60−65.
[12]	CHEN H, TAN C, LIN Z, et al. Classification and quantitation of milk powder by near-infrared spectroscopy and mutual information-based variable selection and partial least squares[J]. SpectrochimicaActa Part A: Molecular and Biomolecular Spectroscopy,2018,189:183−189. doi: 10.1016/j.saa.2017.08.034
[13]	王宁宁, 申兵辉, 关建军, 等. 近红外光谱分析技术识别奶粉中淀粉掺假的研究[J]. 光谱学与光谱分析,2015,35(8):2141−2146. [WANG N N, SHEN B H, GUAN J J, et al. Detection of adulteration in milk powder with starch near infrared[J]. Spectroscopy and Spectral Analysis,2015,35(8):2141−2146. doi: 10.3964/j.issn.1000-0593(2015)08-2141-06
[14]	徐玲玲, 李卫群, 朱慧, 等. 近红外光谱法检测奶粉掺假[J]. 食品安全质量检测学报,2016,7(8):3133−3137. [XU L L, LI W Q, ZHU H, et al. Detection of adulteration of milk powder by near infrared spectroscopy[J]. Journal of Food Safety and Quality,2016,7(8):3133−3137.
[15]	何佳艳, 李亭, 郭长凯, 等. 近红外光谱法快速无损测定奶粉的脂肪含量[J]. 食品与发酵工业,2017,43(10):228−233. [HE J Y, LI T, GUO C K, et al. Rapid nondestructive determination of milk power fat content by near-infrared spectroscopy[J]. Food and Fermentation Industries,2017,43(10):228−233.
[16]	杨福臣, 孙兆远, 孙芝杨. 乳粉中蛋白质和脂肪近红外测定模型研究[J]. 食品研究与开发,2017,38(2):169−173. [YANG F C, SUN Z Y, SUN Z Y, et al. Research on near infrared determination model of milk powder protein and fat[J]. Food Research and Development,2017,38(2):169−173. doi: 10.3969/j.issn.1005-6521.2017.02.038
[17]	邹婷婷, 何佳艳, 齐庆璇, 等. 采用正交投影偏最小二乘法快速无损分析乳粉蛋白质含量[J]. 食品与发酵工业,2016,42(4):179−182. [ZOU T T, HE J Y, QI Q X, et al. The research of fast nondestructive analysis of the protein content in milk powder based on OPLS algorithm[J]. Food and Fermentation Industries,2016,42(4):179−182.
[18]	吴静珠, 王一鸣, 张小超, 等. 基于近红外的奶粉品质检测技术研究[J]. 光谱学与光谱分析,2007(9):1735−1738. [WU J Z, WANG Y M, ZHANG X C, et al. Study on quality detection of milk powder based on near infrared spectroscopy[J]. Spectroscopy and Spectral Analysis,2007(9):1735−1738.
[19]	第五鹏瑶, 卞希慧, 王姿方, 等. 光谱预处理方法选择研究[J]. 光谱学与光谱分析,2019,39(9):2800−2806. [DI W P Y, BIAN X H, WANG Z F, et al. Study on the selection of spectral preprocessing methods[J]. Spectroscopy and Spectral Analysis,2019,39(9):2800−2806.
[20]	郭涛, 黄右琴, 兰贵生, 等. 利用近红外光谱技术分析玉米秸秆和小麦秸秆的营养成分[J]. 草业科学,2020,37(6):1204−1214. [GUO T, HUANG Y Q, LAN G S, et al. Quantitative analysis of nutrients in corn straw and wheat straw using nearinfrared spectroscopy[J]. Pratacultural Science,2020,37(6):1204−1214. doi: 10.11829/j.issn.1001-0629.2019-0446
[21]	刘永峰, 李双红, 库婷, 等. 应用近红外光谱法定量检测牛奶中尿素氮的研究[J]. 西北农林科技大学学报(自然科学版),2020,37(11):2374−2381. [LIU Y F, LI S H, KU T, et al. Rapid prediction of nutrient content of alfalfa hay by using near infrared spectroscopy[J]. Pratacultural Science,2020,37(11):2374−2381.
[22]	AYKAS D P, MENEVSEOGLU A. A rapid method to detect green pea and peanut adulteration in pistachio by using portable FT-MIR and FT-NIR spectroscopy combined with chemometrics[J]. Food Control,2021,121:107670. doi: 10.1016/j.foodcont.2020.107670
[23]	NICOLAI B M, BEULLENS K, BOBELYN E, et al. Nondestructive measurement of fruit and vegetable quality by means of NIR spectroscopy: A review[J]. Postharvest Biology and Technology,2007,46(2):99−118. doi: 10.1016/j.postharvbio.2007.06.024
[24]	GASTÉLUM-BARRIOS A, SOTO-ZARAZÚA G M, ESCAMILLA-GARCÍA A, et al. Optical methods based on ultraviolet, visible, and near-infrared spectra to estimate fat and protein in raw milk: A review[J]. Sensors,2020,20(12):3356. doi: 10.3390/s20123356
[25]	BALABIN R M, SMIRNOV S V. Melamine detection by mid-and near-infrared(MIR/NIR) spectroscopy: A quick and sensitive method for dairy products analysis including liquid milk, infant formula, and milk powder[J]. Talanta,2011,85(1):562−568. doi: 10.1016/j.talanta.2011.04.026
[26]	张娜, 徐冰, 贾帅芸, 等. 丹参提取过程多源信息融合建模方法研究[J]. 中草药,2018,49(6):1304−1310. [ZHANG N, XU B, JIA S Y, et al. Modeling extraction process of Salvia miltiorrhiza based on multi-source information fusion technology[J]. Chinese Traditional and Herbal Drugs,2018,49(6):1304−1310. doi: 10.7501/j.issn.0253-2670.2018.06.011
[27]	吕建波. 液态纯牛奶可见/近红外漫反射光谱PLS鉴别[J]. 现代电子技术,2011,34(17):166−168. [LV J B. Brand discrimination of liquid pure milk using visible/near infrared diffuse reflectance spectroscop[J]. Modern Electronics Technique,2011,34(17):166−168. doi: 10.3969/j.issn.1004-373X.2011.17.051
[28]	严衍禄. 近红外光谱分析基础与应用[M]. 北京: 中国轻工业出版社, 2005. YAN Y L. Fundamentals and applications of near infrared spectroscopy[M]. Beijing: China Light Industry Press, 2005.
[29]	郭涛, 黄右琴, 郭龙, 等. 利用近红外光谱技术快速预测苜蓿干草营养成分含量[J]. 草业科学,2020,37(11):2374−2381. [GUO T, HUANG Y Q, GUO L, et al. Rapid prediction of nutrient content of alfalfa hay by using near infrared spectroscopy[J]. Pratacultural Science,2020,37(11):2374−2381.

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