CN111272695A - 青花菜粉状原料中抗肿瘤成分前体物质3-甲基吲哚基硫苷含量的无损检测方法 - Google Patents
青花菜粉状原料中抗肿瘤成分前体物质3-甲基吲哚基硫苷含量的无损检测方法 Download PDFInfo
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Abstract
本发明提供一种青花菜粉状原料中抗肿瘤成分前体物质3‑甲基吲哚基硫苷(GBC)含量的无损检测方法。所述方法包括：建立预测青花菜粉状原料样品中GBC含量的近红外模型；2)对待测青花菜粉状原料样品进行近红外光谱检测，采用建立好的近红外模型对检测得到的光谱数据进行分析，预测青花菜粉状原料样品中GBC含量。本发明利用近红外光谱检测系统实现青花菜粉状原料样品中抗肿瘤成分前体物质GBC含量的快速无损预测，具有原料无损、检测过程高效快捷、预测数据相对准确等优点，为以后的青花菜粉状原料样品品质指标的快速检测提供了一个切实可行的技术参考，用于农业或食品工业，可以实现高营养品质青花菜粉状原料快速高效的筛选。
Description
技术领域
本发明属于农业及食品工业领域，具体涉及青花菜粉状原料中抗肿瘤成分前体物质3-甲基吲哚基硫苷含量的无损检测方法。
背景技术
植物活性物质是蔬菜中天然存在的、含量较少的一类具有抗氧化、抗病、抗突变、调节机体免疫系统或其它生理活性的化学物质，如类胡萝卜素、硫代葡萄糖苷、黄酮类、萜烯类化合物等。硫代葡萄糖苷(glucosinolates，GLS，简称硫苷)是一类含硫化合物，是十字花科蔬菜中重要的次生代谢产物。人类流行病学针对硫苷的研究结果表明，经常食用十字花科蔬菜，如青花菜、甘蓝、花椰菜等可以有效地预防乳腺癌、结肠癌、肺癌、前列腺癌等多种癌症的发生。在已发现的十字花科蔬菜防癌物质中，有一个抗肿瘤作用较突出的是3-甲基吲哚基硫苷(GBC)的降解产物吲哚-3-甲醇(indole-3-carbinol，I3C)，而I3C的前体物质GBC在青花菜中含量丰富。
目前有大量研究证明I3C可通过多种途径发挥其抗肿瘤作用，其抗肿瘤作用机制较为全面，具有巨大的应用潜力。顶尖学术期刊《Science》在2019年刊登了一篇重磅论文，由哈佛大学科学家领衔的一支科研团队发现，I3C可以抑制肿瘤生长。在众多抑癌基因中，PTEN是人类癌症里最常发生突变的基因之一，一旦它的功能受到影响，就会损害人体的抑癌能力。在小鼠模型和人类细胞中，科学家们做了一系列的实验，他们发现一种叫做WWP1的E3泛素连接酶会与PTEN蛋白直接结合。而通过给PTEN蛋白添加泛素，WWP1能够阻碍PTEN的双聚化和膜定位，从而影响它的抑癌功能。该研究中，这些小鼠模型接受一个月的I3C治疗后，肿瘤的体积显著缩小；而生化实验也表明，I3C可以抑制WWP1对PTEN的泛素化修饰，从而让PTEN回到它应出现的部位，实现它应有的抑癌功能。
近红外光谱分析技术(Near infrared reflectance spectroscopy technique，简称NIRS)可通过测定样品的近红外吸收光谱，达到同时分析样品中的多种成分的效果。虽然我国对近红外光谱技术的研究及应用起步较晚，但因其快速、无损伤、分析费用低等优点，NIRS技术在农业、石油化工、制药与临床医学和食品工业等领域均已得到广泛应用。目前还没有利用近红外光谱技术测定青花菜原料中硫苷组分的文献报道。
发明内容
本发明的目的是提供一种利用近红外光谱分析技术(Near infraredreflectance spectroscopy technique，简称NIRS)测定青花菜粉状原料中抗肿瘤成分前体物质3-甲基吲哚基硫苷(GBC)含量的方法。
本发明所提供的利用近红外光谱技术测定青花菜粉状原料中抗肿瘤成分前体物质3-甲基吲哚基硫苷(GBC)含量的方法，包括如下步骤：
1)建立预测青花菜粉状原料样品中GBC含量的近红外模型；
2)对待测青花菜粉状原料样品进行近红外光谱检测，采用建立好的近红外模型对检测得到的光谱数据进行分析，预测出青花菜粉状原料样品中GBC含量。
上述方法步骤1)中，建立预测青花菜粉状原料样品中GBC含量的近红外模型的方法，包含以下几步：
a)搜集大量青花菜花球样品，冷冻干燥，粉碎成粉状原料；
b)采用高效液相色谱法(HPLC)测定各青花菜粉状原料样品中GBC的含量；
c)通过近红外光谱仪扫描样品，采集样品的光谱数据；
d)筛选不同的数学处理方式得到定标方程，建立近红外模型：将HPLC方法得到的硫苷含量输入仪器配套的化学计量学软件，对光谱进行分析处理；在偏最小二乘回归法的基础上，采用标准正态变量变换(SNV)+二阶导数(SD)处理作为预处理方法，对青花菜样品中GBC组分进行建模，得到预测青花菜粉状原料样品中GBC含量的近红外模型。
上述建立预测青花菜粉状原料样品中GBC含量的近红外模型的方法a)中，所述青花菜样品可为50-300份，具体可为90份；
b)中，高效液相色谱法(HPLC)所采用的色谱条件为：
HPLC分析条件：Nova-PakR C18色谱柱，3.9×150mm，50μm，检测波长229nm，流速1.0mL/min，常温，进样量20μL，梯度洗脱如表1。
A液：1g四甲基氯化铵(TMACl)溶于2L双蒸水中，混匀，抽滤
B液：1g四甲基氯化铵(TMACl)溶于1.6L双蒸水中，加入400mL色谱纯乙腈，混匀抽滤
表1梯度洗脱条件
采用苯甲基硫苷作为内标，根据保留时间和峰面积对硫苷组分定量测定。利用内标和响应因子计算硫苷的含量，以μmol·g-1DW为单位。
硫苷含量计算公式：
图1为采用高效液相色谱法测定青花菜粉状原料样品中硫代葡萄糖苷的图谱，由图1可知，青花菜粉状原料样品中硫代葡萄糖苷组分在30min内全部出峰，分离较为完全，其中6号峰为：3-甲基吲哚基硫苷(GBC)；
通过高效液相色谱法测定步骤1)中青花菜粉状原料样品中GBC的含量变化范围为0.249～10.794μmol/g；
c)中，所述通过近红外光谱仪扫描样品的操作为：将青花菜粉状原料干粉平铺在样品杯中，固定于样品室，然后对样品进行静态扫描；
所有样品重复扫描3次，以减少仪器波动和装样对光谱扫描的干扰。
d)中，使用近红外仪器配套的WinISI III定标软件对光谱数据进行处理，
具体操作如下：将HPLC方法得到硫苷含量输入仪器配套的化学计量学软件，在偏最小二乘回归法的基础上，采用不同散射处理方式(SNV；Detrend；SNV+Detrend)和导数处理方式(FD；SD)对光谱数据进行预处理，得到不同的定标方程；考察所得定标方程的RSQ(定标相关系数)和1-VR(内部交叉验证相关系数)值，发现经SNV+SD预处理后得到的定标方程的RSQ和1-VR值分别为0.912和0.892更接近1，选择将SNV+SD处理作为预处理方法，对青花菜样品中GBC组分进行建模；
建模后的效果如图2所示，由图2可知，样品无规律的分布在直线的两侧，整体的趋势呈均匀离散的状态，没有出现大的偏差情况，说明模型较准确；
上述建立预测青花菜粉状原料样品中GBC含量的近红外模型的方法还可进一步包括步骤e)：使用外部样品集检验确认所述近红外模型的可靠性，具体操作如下：基于已建立的模型，随机选择多个与建模样品无关的样品作为验证集对模型进行外部验证，
其中，所述多个与建模样品无关的样品可为20个建模样品无关的样品。
本发明利用近红外光谱检测系统实现青花菜粉状原料样品中抗肿瘤成分前体物质3-甲基吲哚基硫苷(GBC)含量的快速无损预测，具有原料无损、检测过程高效快捷、预测数据相对准确等优点，为以后的青花菜粉状原料样品品质指标的快速检测提供了一个切实可行的技术参考，用于农业或食品工业，可以实现高营养品质青花菜粉状原料快速高效的筛选。
本发明适用于农业和食品加工业，提供一种操作简单、原料无损失且稳定可靠的快速检测粉状原料中3-甲基吲哚基硫苷含量的方法。
附图说明
图1为采用高效液相色谱法测定青花菜粉状原料中硫代葡萄糖苷的图谱。
图2为本发明建立的预测青花菜粉状原料样品中GBC含量的近红外模型效果图。
具体实施方式
下面通过具体实施例对本发明进行说明，但本发明并不局限于此。
下述实施例中所使用的实验方法如无特殊说明，均为常规方法；下述实施例中所用的试剂、材料等，如无特殊说明，均可从商业途径得到。
实施例1
1、青花菜样品的搜集和处理
搜集大量青花菜花球样品110份，其中90份作为定标集，20份作为验证集，将其冷冻干燥，再进一步粉碎成粉状原料；
2、采用HPLC测定青花菜硫苷组成和含量
用高效液相色谱法测定原料中硫代葡萄糖苷图谱如图1所示，原料中硫代葡萄糖苷组分在30min内全部出峰，分离较为完全，满足试验要求，其中6号峰代表GBC。
90份青花菜样品的GBC平均含量为4.428μmol/g，变化范围为0.249～10.794μmol/g，含量变化范围较大，适合作为定标集。
3、近红外光谱扫描样品
近红外仪器开机预热30min，进行光谱和噪声诊断，当诊断结果通过后开始扫描。将样品干粉均匀平铺在样品杯，然后固定在样品室中心，对样品进行静态扫描。
4、筛选不同的数学处理方式得到定标方程，建立模型
使用近红外仪器配套的WinISI III定标软件对光谱数据进行处理。将HPLC方法得到硫苷含量输入仪器配套的化学计量学软件，在偏最小二乘回归法的基础上，采用不同散射处理方式(SNV；Detrend；SNV+Detrend)和导数处理方式(FD；SD)对光谱数据进行预处理，得到不同的定标方程。RSQ是定标相关系数，1-VR是内部交叉验证相关系数，都是越接近于1越好。通过筛选可知，内部交叉检验效果较好，经过SNV+SD处理过后的RSQ和1-VR值分别为0.912和0.892。
在偏最小二乘回归法的基础上，将SNV+SD处理作为预处理方法，对青花菜样品中GBC组分进行建模。建模后的效果如图2示，样品无规律的分布在直线的两侧，整体的趋势呈均匀离散的状态，没有出现大的偏差情况，说明模型较准确。
表2不同光谱预处理方法对比
5、模型验证
基于已建立的模型，随机选择20个与建模样品无关的样品作为验证集对模型进行外部验证。
表3外部检验结果
注：Lab是化学方法检测数据，NIR是近红外快速预测数据
如表3所示，通过验证集进行外部检验，GBC的相关系数为0.960，检验偏差仅有0.064，模型效果较好。
实施例2
在北京地区青花菜种植基地随机采摘8种青花菜，带回实验室，将其冷冻干燥后粉碎待用。近红外仪器开机预热30min左右，进行光谱和噪声诊断，当诊断结果通过后可以开始扫描。将样品干粉均匀平铺在样品杯中，用盖子压实，对样品进行静态扫描。然后使用HPLC法对这8个样品中GBC含量进行分析检测，检测数据和预测数据对比如下表4，相对误差在3.63％-24.28％之间。
表4随机样品预测结果
本发明利用近红外光谱检测系统可以实现青花菜粉状原料样品中3-甲基吲哚基硫苷(GBC)含量的快速无损预测，具有原料无损、检测过程高效快捷、预测数据相对准确等优点，为以后的青花菜蔬菜粉营养品质指标的快速检测提供了一个切实可行的技术参考，用于农业、食品工业或医药行业，可以实现高营养品质青花菜粉状原料快速高效的筛选。
Claims (6)
1.一种建立预测青花菜粉状原料样品中抗肿瘤成分前体物质3-甲基吲哚基硫苷含量的近红外模型的方法，包含以下几步：
a)搜集大量青花菜花球样品，冷冻干燥，粉碎成粉状原料；
b)采用高效液相色谱法测定各青花菜粉状原料样品中GBC的含量；
c)通过近红外光谱仪扫描样品，采集样品的光谱数据；
d)筛选不同的数学处理方式得到定标方程，建立近红外模型：
将HPLC方法得到的硫苷含量输入仪器配套的化学计量学软件，在偏最小二乘回归法的基础上，采用标准正态变量变换+二阶导数作为预处理方法，对青花菜样品中硫代葡萄糖苷中GBC组分进行建模，得到预测青花菜蔬菜粉样品中GBC含量的近红外模型。
2.根据权利要求1所述的方法，其特征在于：a)中，所述青花菜样品为50-300份。
3.根据权利要求1或2所述的方法，其特征在于：c)中，所述通过近红外光谱仪扫描样品的操作为：
将青花菜蔬菜粉样品干粉平铺在样品杯中，固定于样品室，然后对样品进行静态扫描；所有样品重复扫描3次，以减少仪器波动和装样对光谱扫描的干扰。
4.根据权利要求1-3中任一项所述的方法，其特征在于：d)中，使用近红外仪器配套的WinISI III定标软件对光谱数据进行处理；
操作如下：将HPLC方法得到硫苷含量输入仪器配套的化学计量学软件，在偏最小二乘回归法的基础上，采用不同散射处理方式(SNV；Detrend；SNV+Detrend)；和导数处理方式(FD；SD)对光谱数据进行预处理，得到不同的定标方程；考察所得定标方程的RSQ和1-VR值，发现经SNV+SD预处理后得到的定标方程的RSQ和1-VR更接近1，选择将SNV+SD处理作为预处理方法，对青花菜样品中GBC组分进行建模。
5.根据权利要求1-4中任一项所述的方法，其特征在于：所述建立预测青花菜蔬菜粉样品中GBC含量的近红外模型的方法还进一步包括步骤e)：使用外部样品集检验确认所述近红外模型的可靠性，
操作如下：基于已建立的模型，随机选择多个与建模样品无关的样品作为验证集对模型进行外部验证。
6.一种利用权利要求1-5中任一项所述方法建立的预测青花菜粉状原料样品中GBC含量的近红外模型测定青花菜粉状原料中GBC含量的方法，包括如下步骤：
对待测青花菜粉状原料样品进行近红外光谱检测，利用权利要求1-5中任一项所述方法建立的近红外模型对检测得到的光谱数据进行分析，预测青花菜粉状原料样品中抗肿瘤成分前体物质3-甲基吲哚基硫苷的含量。
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Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102279168A (zh) * | 2011-07-20 | 2011-12-14 | 浙江大学 | 基于近红外光谱技术快速无损分析整粒棉籽营养品质的方法 |
| JP2013072726A (ja) * | 2011-09-27 | 2013-04-22 | Chikuno Shokuhin Kogyo Kk | 近赤外分光法を用いた玄米中のトリアシルグリセロールの定量方法 |
| CN104542910A (zh) * | 2015-01-23 | 2015-04-29 | 北京市农林科学院 | 一种有效保留硫代葡萄糖苷的脱水西兰花的制备方法 |
| CN104792722A (zh) * | 2015-04-30 | 2015-07-22 | 华南农业大学 | 一种沉香含油率近红外光谱预测模型的建立 |
| US20170010210A1 (en) * | 2014-03-28 | 2017-01-12 | Knu-Industry Cooperation Foundation | Method of simultaneously analyzing amount of nutritional component in various foods having different physicochemical properties and compositions by near-infrared reflectance spectroscopy |
| CN108572154A (zh) * | 2018-05-31 | 2018-09-25 | 福建医科大学 | 一种基于近红外光谱技术快速检测桃汁原汁含量的方法 |
-
2020
- 2020-02-26 CN CN202010118846.0A patent/CN111272695A/zh active Pending
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102279168A (zh) * | 2011-07-20 | 2011-12-14 | 浙江大学 | 基于近红外光谱技术快速无损分析整粒棉籽营养品质的方法 |
| JP2013072726A (ja) * | 2011-09-27 | 2013-04-22 | Chikuno Shokuhin Kogyo Kk | 近赤外分光法を用いた玄米中のトリアシルグリセロールの定量方法 |
| US20170010210A1 (en) * | 2014-03-28 | 2017-01-12 | Knu-Industry Cooperation Foundation | Method of simultaneously analyzing amount of nutritional component in various foods having different physicochemical properties and compositions by near-infrared reflectance spectroscopy |
| CN104542910A (zh) * | 2015-01-23 | 2015-04-29 | 北京市农林科学院 | 一种有效保留硫代葡萄糖苷的脱水西兰花的制备方法 |
| CN104792722A (zh) * | 2015-04-30 | 2015-07-22 | 华南农业大学 | 一种沉香含油率近红外光谱预测模型的建立 |
| CN108572154A (zh) * | 2018-05-31 | 2018-09-25 | 福建医科大学 | 一种基于近红外光谱技术快速检测桃汁原汁含量的方法 |
Non-Patent Citations (4)
| Title |
|---|
| 代梅等: "西兰花中硫代葡萄糖苷的研究进展", 《食品研究与开发》 * |
| 吴炜: "《基于学习的图像增强技术》", 西安：西安电子科技大学出版社 * |
| 李施蒙等: "甘蓝型油菜脂肪酸组分近红外分析模型构建", 《广东农业科学》 * |
| 王耐红等: "甘蓝型油菜硫苷组分近红外检测模型的建立", 《西南大学学报(自然科学版)》 * |
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