CN108872133A - 一种基于中红外光谱的转基因玉米鉴别方法 - Google Patents
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Abstract
本发明公开一种基于中红外光谱的转基因玉米快速鉴别方法,该方法应用中红外光谱仪采集转基因玉米及非转基因玉米样本的光谱信息,经过预处理后,采用连续投影算法(SPA)选择特征波长。分别将预处理后的全谱及特征波长作为输入,样本的类别作为输出,建立PLS‑DA,KNN及ELM判别分析模型,模型的建模集及预测集识别率均在90%以上,尤其是基于全谱的ELM模型判别效果最佳,建模集和预测集的识别率分别达到了100%及98.75%。本发明实现了转基因玉米的快速鉴别,检测速度快,鉴别精度高、操作简单、成本低,能为高效的转基因安全管理提供参考。
Description
技术领域
本发明涉及转基因玉米鉴别技术,尤其涉及一种基于中红外光谱的转基因玉米的快速鉴别方法。
背景技术
随着现代生物技术的发展,转基因技术的研究得到飞速发展和推广。运用转基因技术能培育高产、高抗、优质,适应不良生态环境的优良品种,同时降低农药化肥的施用量,有利于环境保护。但是,由于外源基因的导入,转基因作物及食品存在一定的安全隐患。因此,转基因产品检测技术的研究对实施系统、高效的转基因安全管理显得尤为重要。传统的转基因检测主要有聚合酶链反应技术,蛋白质免疫印迹法,酶联免疫吸附等。这些方法虽然具有较高的准确性和灵敏度,但在样本检测时需提取DNA和蛋白质导致样本破坏,而且费时费力,程序复杂,成本较高,非专业人员难以胜任,无法满足转基因与非转基因农产品的实时在线快速鉴别的要求。
针对转基因玉米的识别,公开号CN106778074A的发明专利申请提供一种转基因玉米检测方法,该方法包括:采集待检测样本的第一红外光谱数据,所述待检测样本包括玉米植株的任一部分;对所述第一红外光谱数据进行去噪处理;根据去噪处理后的所述第一红外光谱数据和预先建立的判别模型,确定所述待检测样本是否为转基因玉米。上述的方法是针对玉米植株进行检测。
中红外光(mid-infrared,MIR)指的是波长在2500到25000nm的电磁波,这些波长与物质的官能团对应,通过分析官能团信息,可以获取物质的物理性质及化学成分。中红外光谱检测技术操作简便,分析时所需样品少,检测速度快,已广泛的应用于农业及食品领域。
发明内容
本发明公开了一种基于中红外光谱的转基因玉米快速鉴别方法。具有成本低,检测速度快,识别精度高等特点。
本发明的具体技术方案如下:
一种基于中红外光谱的转基因玉米快速鉴别方法,包括:
1)制备实验样本,分别取等量的转基因与非转基因的玉米籽粒碾磨成粉并压成片,每片为一个样本,得到相等数量的转基因与非转基因的样本,并用不同的整数值标记两类样本,记为Y;
2)将压片的样本放置于中红外光谱仪的检测平台上,获取样本的光谱数据记为X;
3)采用小波变换对所获取的信号进行降噪处理,经过处理的数据记为X’;
4)针对上述的实验样本,用经过预处理的数据X’进行主成分分析;
5)采用连续投影算法进行特征波长选择;
6)通过k-means方法采用2:1的比例划分建模集和预测集;分别基于全谱和选择的特征波长,建立PLS-DA、KNN、ELM判别分析模型。
本技术方案中,建立的判别分析模型基于不同的原理和方法对样本进行判别分析,判别效果不同,可以从中选择最优的模型进行应用。
作为优选的,步骤2)中光谱仪扫描次数设定为32,得到32次扫描光谱数据的平均值作为样本的光谱数据。
作为优选的,步骤3)小波变换中选择db5小波进行10尺度分解消除噪声。
作为优选的,步骤5)中采用SPA算法挑出19个特征波长,分别为708.2294cm- 1716.9075cm-1,776.69cm-1,810.9203cm-1,961.8228cm-1,992.6782cm-1,1063.067cm-1,1147.438cm-1,1172.026cm-1,1482.027cm-1,1530.238cm-1,1540.363cm-1,1559.165cm-1,1709.586cm-1,1745.744cm-1,2429.868cm-1,2844.006cm-1,2925.484cm-1,3613.947cm-1。
作为优选的,步骤6)中PLS-DA判别分析模型中,采用留一交互验证防止模型的过拟合。
相对于现有技术,本发明具有的有益效果是:
(1)实现了转基因玉米的识别。
(2)利用LIBS技术进行转基因玉米鉴别,具有操作简单,成本低、快速高效等特点。有效克服了传统检测方法程序复杂,成本较高,对样品破坏大等缺点。
(3)选择了具有代表性的特征波长,有利于便携式传感仪器的开发。
附图说明
图1为转基因及非转基因玉米样本前三个主成分的得分图。
具体实施方式
下面结合实施例和附图来详细说明本发明,但本发明并不仅限于此。
一种基于激光诱导击穿光谱的转基因玉米快速鉴别方法,包括:
(1)制备实验样本,从浙江省农科院质量标准研究所获取转双价基因(cry1Ab/cry2Aj-G10evo)玉米籽粒及其亲本玉米。然后分别取转基因与非转基因的玉米籽粒600颗,取5粒玉米碾磨成粉,取0.2g玉米粉压成片,每片为一个样本,得到转基因与非转基因的压片样本各120个。
(2)采集样本的中红外光谱信号。将光谱仪扫描次数设定为32,得到32次扫描光谱数据的平均值作为样本的光谱数据。
(4)对所获取的信号进行小波变换降噪处理,选择db5小波进行10尺度分解消除噪声,经过预处理后的光谱数据记为X’。
(5)对预处理后得到的光谱数据X’进行主成分(PCA)分析,获得样本前三个主成分的得分图,如图1所示,图中转基因玉米和非转基因玉米样本都成簇分布。
(6)采用SPA算法选择出19个特征波长,分别为708.2294cm-1716.9075cm-1,776.69cm-1,810.9203cm-1,961.8228cm-1,992.6782cm-1,1063.067cm-1,1147.438cm-1,1172.026cm-1,1482.027cm-1,1530.238cm-1,1540.363cm-1,1559.165cm-1,1709.586cm-1,1745.744cm-1,2429.868cm-1,2844.006cm-1,2925.484cm-1,3613.947cm-1。
(7)将预处理后得到的光谱数据X’及挑选出的19个特征波长作为输入,分别建立基于全谱及特征波长的PLS-DA,KNN,ELM判别分析模型,结果如表1所示。
表1基于全谱及特征波长的PLS-DA,KNN,ELM模型结果
在全谱和特征波长的判别分析模型中,ELM模型效果最优,全谱的建模集和预测集的准确率达到了100%和98.75%。特征波长的建模集和预测集的准确率分别达到了98.75%和97.5%。上述结果表明,本发明的方法能够快速有效的识别转基因玉米,具有良好的应用前景和可观的市场价值。
以上所述仅为本发明的较佳实施举例,并不用于限制本发明,凡在本发明精神和原则之内,所作的任何修改、等同替换、改进等,均应包含在本发明的保护范围之内。
Claims (6)
1.一种基于中红外光谱的转基因玉米快速鉴别方法,其特征在于,包括步骤:
1)制备实验样本,分别取等量的转基因与非转基因的玉米籽粒碾磨成粉并压成片,每片为一个样本,得到相等数量的转基因与非转基因的样本,并用不同的整数值标记两类样本,记为Y;
2)将压片的样本放置于中红外光谱仪的检测平台上,获取样本的光谱数据记为X;
3)采用小波变换对所获取的信号进行降噪处理,经过处理的数据记为X’;
4)针对上述的实验样本,用经过预处理的数据X’进行主成分分析;
5)采用连续投影算法进行特征波长选择;
6)按比例划分建模集和预测集;分别基于全谱和选择的特征波长,建立PLS-DA、KNN、ELM判别分析模型。
2.如权利要求1所述的基于中红外光谱的转基因玉米快速鉴别方法,其特征在于,所述步骤2)中光谱仪扫描次数设定为32,得到32次扫描光谱数据的平均值作为样本的光谱数据。
3.如权利要求1所述的基于中红外光谱的转基因玉米快速鉴别方法,其特征在于,所述步骤3)的小波变换选择db5小波进行10尺度分解消除噪声。
4.如权利要求1所述的基于中红外光谱的转基因玉米快速鉴别方法,其特征在于,所述步骤5)中选择的特征波长分别为708.2294cm-1,716.9075cm-1,776.69cm-1,810.9203cm-1,961.8228cm-1,992.6782cm-1,1063.067cm-1,1147.438cm-1,1172.026cm-1,1482.027cm-1,1530.238cm-1,1540.363cm-1,1559.165cm-1,1709.586cm-1,1745.744cm-1,2429.868cm-1,2844.006cm-1,2925.484cm-1,3613.947cm-1。
5.如权利要求1所述的基于中红外光谱的转基因玉米快速鉴别方法,其特征在于,所述步骤6)中采用留一交互验证防止PLS-DA模型的过拟合。
6.如权利要求1所述的基于中红外光谱的转基因玉米快速鉴别方法,其特征在于:在步骤6)中,通过k-means方法采用2:1的比例划分建模集和预测集。
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CN106338488A (zh) * | 2016-10-31 | 2017-01-18 | 浙江大学 | 一种转基因豆奶粉的快速无损鉴别方法 |
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