[1]张平平,张瑜,唐果,等.近红外光谱技术检测小麦谷蛋白大聚体含量[J].江苏农业学报,2017,(06):1207-1211.[doi:doi:10.3969/j.issn.1000-4440.2017.06.002]
　ZHANG Ping-ping,ZHANG Yu,TANG Guo,et al.Measurement of SDS-unextractable polymeric protein content in wheat flour based on near-infrared spectroscopy (NIRS) technique[J].,2017,(06):1207-1211.[doi:doi:10.3969/j.issn.1000-4440.2017.06.002]
点击复制

近红外光谱技术检测小麦谷蛋白大聚体含量()
分享到：

江苏农业学报[ISSN:1006-6977/CN:61-1281/TN]

卷:
期数:
2017年06期
页码:
1207-1211
栏目:
遗传育种·生理生化
出版日期:
2017-12-30

文章信息/Info

Title:
Measurement of SDS-unextractable polymeric protein content in wheat flour based on near-infrared spectroscopy (NIRS) technique
作者:
张平平1; 张瑜1; 唐果2; 姚金保1; 马鸿翔1
(1.江苏省农业科学院/江苏省农业生物学重点实验室/江苏省现代作物生产协同创新中心,江苏南京210014;2.波通瑞华科学仪器（北京）有限公司上海分公司,上海200000)
Author(s):
ZHANG Ping-ping1; ZHANG Yu1; TANG Guo2; YAO Jin-bao1; MA Hong-xiang1
(1.Jiangsu Academy of Agricultural Sciences/Jiangsu Provincial Key Laboratory for Agrobiology/Jiangsu Collaborative Innovation Center for Modern Crop Production, Nanjing 210014, China;2.Perten Instrument Corporation (China )，Shanghai 200000, China)
关键词:
近红外光谱; 小麦面粉; 不溶性谷蛋白大聚体
Keywords:
near-infrared spectroscopy (NIRS); wheat flour; SDS-unextractable polymeric protein (UPP)
分类号:
S512.103.2
DOI:
doi:10.3969/j.issn.1000-4440.2017.06.002
文献标志码:
A
摘要:
对120份来源广泛的小麦品种籽粒样品进行了制粉，用磷酸缓冲提取液提取面粉不溶性谷蛋白大聚体。利用高效液相色谱法测定提取液不溶性谷蛋白大聚体含量化学值，同时利用反射式近红外光谱仪采集提取液光谱数据。采用Unscrambler化学计量学软件，结合偏最小二乘法建立了不溶性谷蛋白大聚体含量预测的校准模型，并对模型进行了验证。结果表明，该定标模型决定系数为089，交互验证标准偏差为3640 AU/mg，模型验证预测值和化学值决定系数为086。可见，近红外光谱方法可作为低成本高通量的面粉不溶性谷蛋白大聚体含量评价方法。
Abstract:
One hundred and twenty cultivars or advanced lines were selected from different wheat growing regions, and were milled into flour. The real content of SDS-unextractable polymeric protein (UPP) in the flour extracted by phosphate buffer was quantified by high performance liquid chromatograph method. At the same time, the spectrum data of UPP in the phosphate buffer was collected based on near infrared reflectance spectroscopy technique. The calibration model was created based on Unscrambler software and partial least squares(PLS) algorithm, and was validated. In the calibration model of UPP, the coefficient of determination and root mean square error of cross validation (RMSECV) was 089 and 3640 AU/mg, respectively. The correlation coefficient between real content and predicted content in the validation set was 086. It was showed that near-infrared spectroscopy (NIRS) method was a low-cost and high-throughput method to quantify the UPP of wheat flour.

参考文献/References:

[1]张晓芳，俞信，阎吉祥，等. 近红外反射技术开放式检测棉籽中水分和油含量的研究[J]. 光谱学与光谱分析， 2007， 27（3）：473-476.
[2]黄庄荣，沙莎，荣正勤，等. 基于近红外技术快速无损分析整粒棉籽中的脂肪酸含量[J]. 分析化学， 2013， 41（6）：922-926.
[3]张兵，范泽华，姚江河，等．基于近红外光谱与多元模型的小麦氮含量估算[J].江苏农业科学，2016,44(9):374-378.
[4]COSTA G B, FERNANDES D D, GOMES A A, et al. Using near infrared spectroscopy to classify soybean oil according to expiration date[J]. Food Chemistry, 2016, 196(7):539-543.
[5]王一丁，赵铭钦 ，付博，等. 基于可见光-近红外光谱技术的烤烟品种鉴别研究[J].山东农业科学,2016，48(2)：119-124.
[6]HUANG Y, MIN S, DUAN J, et al. Identification of additive components in powdered milk by NIR imaging methods[J]. Food Chemistry, 2014, 145(4):278-283.
[7]杜雪燕,王迅,柴沙驼,等. 基于近红外光谱的天然牧草 CNCPS 组分分析与预测[J]. 江苏农业学报,2015,31(5):1115-1123.
[8]ANJUM F M, KHAN M R, DIN A, et al. Wheat gluten: high molecular weight glutenin subunits-structure, genetics, and relation to dough elasticity[J]. Journal of food Science, 2007,72(3):56-63.
[9]ZHU J, KHAN K. Effects of genotype and environment on glutenin polymers and bread making quality[J]. Cereal Chemistry, 2001, 78(2):125-130.
[10]TSILO T J, HARELAND G A, OHM J, et al. Polymeric proteins and their association with grain yield in hard red spring wheat lines[J]. Euphytica, 2013, 194(2):187-196.
[11]ZHANG P P, HE Z H, XIA X C, et al. Effect of percent SDS-unextractable polymeric protein (%UPP) on end-use quality in Chinese bread wheat cultivars[J]. Cereal Chemistry, 2008, 85(5):696-700.
[12]刘丽，周阳，何中虎，等. Glu-1和Glu-3等位变异对不溶性谷蛋白含量的影响[J]. 作物学报，2004，30（11）：1086-1092.
[13]BEAN S R, LYNE R K, TILLEY K A, et al. A rapid method for quantitation of insoluble polymeric proteins in flour[J]. Cereal Chemistry, 1998, 75(3):374-379.
[14]FU B X, SAPIRSTEIN H D. Procedure for isolating monomeric proteins and polymeric glutenin of wheat flour[J]. Cereal Chemistry, 1996, 73(1):143-152.
[15]LARROQUE O R, GIANIBELLI M C, GOMEZ S M, et al. Procedure for obtaining stable protein extracts of cereal flour and whole meal for size exclusion HPLC analysis[J]. Cereal Chemistry, 2000, 77(4):448-450.

相似文献/References:

[1]仇逊超.红松仁脂肪的近红外光谱定量检测[J].江苏农业学报,2018,(03):692.[doi:doi:10.3969/j.issn.1000-4440.2018.03.031]
　QIU Xun-chao.Quantitative detection of fat in peeled Korean pine seeds using near infrared spectroscopy[J].,2018,(06):692.[doi:doi:10.3969/j.issn.1000-4440.2018.03.031]
[2]彭雅玲,邱雪,张海红,等.近红外光谱技术检测灵武长枣果肉硬度和贮藏时间[J].江苏农业学报,2019,(01):182.[doi:doi:10.3969/j.issn.1000-4440.2019.01.026]
　PENG Ya-ling,QIU Xue,ZHANG Hai-hong,et al.Near-infrared spectroscopy for the determination of hardness and storage time of jujube fruit[J].,2019,(06):182.[doi:doi:10.3969/j.issn.1000-4440.2019.01.026]
[3]张津源,张德贤,张苗.基于连续投影算法的小麦蛋白质含量近红外光谱预测分析[J].江苏农业学报,2019,(04):960.[doi:doi:10.3969/j.issn.1000-4440.2019.04.030]
　ZHANG Jin yuan,ZHANG De xian,ZHANG Miao.Prediction and analysis of wheat protein content by nearinfrared spectroscopy based on successive projections algorithm[J].,2019,(06):960.[doi:doi:10.3969/j.issn.1000-4440.2019.04.030]
[4]曲歌,陈争光,张庆华.基于无信息变量消除法的水稻种子发芽率测定[J].江苏农业学报,2019,(05):1015.[doi:doi:10.3969/j.issn.1000-4440.2019.05.002]
　QU Ge,CHEN Zheng-guang,ZHANG Qing-hua.Study on germination rate of rice seed based on uninformation variable elimination method[J].,2019,(06):1015.[doi:doi:10.3969/j.issn.1000-4440.2019.05.002]
[5]孙晓明,陈小龙,余向阳,等.基于近红外光谱分析技术的水蜜桃产地溯源[J].江苏农业学报,2020,(02):507.[doi:doi:10.3969/j.issn.1000-4440.2020.02.035]
　SUN Xiao-ming,CHEN Xiao-long,YU Xiang-yang,et al.Traceability of honey peach origin using near infrared spectroscopy analysis techniques[J].,2020,(06):507.[doi:doi:10.3969/j.issn.1000-4440.2020.02.035]
[6]方瑶,谢天铧,郭渭,等.基于近红外光谱的金鲳鱼新鲜度快速检测技术[J].江苏农业学报,2021,(01):213.[doi:doi:10.3969/j.issn.1000-4440.2021.01.028]
　FANG Yao,XIE Tian-hua,GUO Wei,et al.Rapid detection technology of pomfret freshness based on near infrared spectroscopy[J].,2021,(06):213.[doi:doi:10.3969/j.issn.1000-4440.2021.01.028]
[7]谢文涌,柴琴琴,林旎,等.基于Stacking集成学习的马兜铃酸及其类似物鉴别[J].江苏农业学报,2021,(02):503.[doi:doi:10.3969/j.issn.1000-4440.2021.02.028]
　XIE Wen-yong,CHAI Qin-qin,LIN Ni,et al.Discrimination of aristolochic acid and its analogues based on stacking ensemble learning[J].,2021,(06):503.[doi:doi:10.3969/j.issn.1000-4440.2021.02.028]
[8]沈广辉,曹瑶瑶,刘馨,等.近红外高光谱成像结合特征波长筛选识别小麦赤霉病瘪粒[J].江苏农业学报,2021,(02):509.[doi:doi:10.3969/j.issn.1000-4440.2021.02.029]
　SHEN Guang-hui,CAO Yao-yao,LIU Xin,et al.Identification of Fusarium damaged kernels using near infrared hyperspectral imaging and characteristic bands selection[J].,2021,(06):509.[doi:doi:10.3969/j.issn.1000-4440.2021.02.029]
[9]仇逊超,张春越,张怡卓,等.流形学习在红松籽仁蛋白质含量近红外检测中的应用[J].江苏农业学报,2023,(01):246.[doi:doi:10.3969/j.issn.1000-4440.2023.01.028]
　QIU Xun-chao,ZHANG Chun-yue,ZHANG Yi-zhuo,et al.Application of manifold learning in quantitative detection of protein in Korean pine seed kernels using near-infrared quantitative detection[J].,2023,(06):246.[doi:doi:10.3969/j.issn.1000-4440.2023.01.028]

备注/Memo

备注/Memo:
收稿日期：2017-07-03 基金项目：国家自然科学基金项目(31671690)；江苏省自然科学基金项目(BK20161375)；国家重点研发计划项目(2016YFD0100500)；国家小麦产业技术体系项目(CARS-03) 作者简介：张平平（1977-），男，山西阳泉人，博士，研究员，主要从事小麦遗传育种研究。（Tel）025-84390257，（E-mail）pp_zh@126.com
更新日期/Last Update: 2018-01-03