AOTF-NIR快速检测田间生长烟叶中主要化学成分
应用AOTF-NIR（AOTF-近红外光谱分析技术）建立田间生长烟叶中5种化学成分的快速无损检测方法。以182个样品组成校正集标准样品,采用偏最小二乘回归法建立了近红外光谱信息与各成分含量之间的关联定量校正数学模型,并对30个验证集样品进行预测。预测结果表明：烟碱、总氮、总糖、还原糖、钾的平均预测相对误差分别为3.73%、3.89%、3.78%、2.88%、4.37%。对验证集样品的原始化学值和预测值进行成对数据t测验,检测结果显示,差异不显著,说明建立的数学模型是可用的,该方法分析结果准确可靠,重现性好,方便无损。可用于快速定量检测田间生长烟叶中的烟碱、还原糖、总糖、总氮、钾。...
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| Published in | 江西农业学报 Vol. 24; no. 1; pp. 60 - 62 |
|---|---|
| Main Author | |
| Format | Journal Article |
| Language | Chinese |
| Published |
四川省烟草公司凉山州分公司,四川西昌615000%国家烟草栽培生理生化研究基地,河南郑州,450002%四川省烟草技术中心,四川西昌,615000%四川省烟草公司凉山州分公司,四川西昌,615000%四川省烟草公司凉山州分公司会东营销部,四川会东,615200
2012
国家烟草栽培生理生化研究基地,河南郑州450002 |
| Subjects | |
| Online Access | Get full text |
| ISSN | 1001-8581 |
| DOI | 10.3969/j.issn.1001-8581.2012.01.020 |
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| Abstract | 应用AOTF-NIR（AOTF-近红外光谱分析技术）建立田间生长烟叶中5种化学成分的快速无损检测方法。以182个样品组成校正集标准样品,采用偏最小二乘回归法建立了近红外光谱信息与各成分含量之间的关联定量校正数学模型,并对30个验证集样品进行预测。预测结果表明：烟碱、总氮、总糖、还原糖、钾的平均预测相对误差分别为3.73%、3.89%、3.78%、2.88%、4.37%。对验证集样品的原始化学值和预测值进行成对数据t测验,检测结果显示,差异不显著,说明建立的数学模型是可用的,该方法分析结果准确可靠,重现性好,方便无损。可用于快速定量检测田间生长烟叶中的烟碱、还原糖、总糖、总氮、钾。 |
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| AbstractList | S572; 应用AOTF-NIR(AOTF-近红外光谱分析技术)建立田间生长烟叶中5种化学成分的快速无损检测方法.以182个样品组成校正集标准样品,采用偏最小二乘回归法建立了近红外光谱信息与各成分含量之间的关联定量校正数学模型,并对30个验证集样品进行预测.预测结果表明:烟碱、总氮、总糖、还原糖、钾的平均预测相对误差分别为3.73％、3.89％、3.78％、2.88％ 、4.37％.对验证集样品的原始化学值和预测值进行成对数据t测验,检测结果显示,差异不显著,说明建立的数学模型是可用的,该方法分析结果准确可靠,重现性好,方便无损.可用于快速定量检测田间生长烟叶中的烟碱、还原糖、总糖、总氮、钾. 应用AOTF-NIR（AOTF-近红外光谱分析技术）建立田间生长烟叶中5种化学成分的快速无损检测方法。以182个样品组成校正集标准样品,采用偏最小二乘回归法建立了近红外光谱信息与各成分含量之间的关联定量校正数学模型,并对30个验证集样品进行预测。预测结果表明：烟碱、总氮、总糖、还原糖、钾的平均预测相对误差分别为3.73%、3.89%、3.78%、2.88%、4.37%。对验证集样品的原始化学值和预测值进行成对数据t测验,检测结果显示,差异不显著,说明建立的数学模型是可用的,该方法分析结果准确可靠,重现性好,方便无损。可用于快速定量检测田间生长烟叶中的烟碱、还原糖、总糖、总氮、钾。 |
| Author | 徐明康 王聪 张建慧 钱宇 刘国 高峻 吴福如 于建军 |
| AuthorAffiliation | 国家烟草栽培生理生化研究基地,河南郑州450002 四川省烟草公司凉山州分公司,四川西昌615000 四川省烟草技术中心,四川西昌615000 四川省烟草公司凉山州分公司会东营销部,四川会东615200 |
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| Author_FL | LIU Guo YU Jian-jun QIAN Yu GAO Jun ZHANG Jian-hui WU Fu-ru WANG Cong XU Ming-kang |
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| ClassificationCodes | S572 |
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| Copyright | Copyright © Wanfang Data Co. Ltd. All Rights Reserved. |
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| DOI | 10.3969/j.issn.1001-8581.2012.01.020 |
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| Discipline | Agriculture |
| DocumentTitleAlternate | Rapid Detection of Main Chemical Components of Growing Tobacco Leaf in Field by AOTF-NIR Method |
| DocumentTitle_FL | Rapid Detection of Main Chemical Components of Growing Tobacco Leaf in Field by AOTF-NIR Method |
| EndPage | 62 |
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| Keywords | 田间生长烟叶 无损检测 AOTF-NIR 化学成分 |
| Language | Chinese |
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| Notes | 36-1124/S XU Ming-kang,WANG Cong,ZHANG Jian-hui,QIAN Yu,LIU Guo,GAO Jun,WU Fu-ru,YU Jian-jun（1.National Tobacco Cultivation,Physiology and Biochemistry Research Station,Zhengzhou 450002,China;2.Liangshan Branch of Sichuan Tobacco Corporation,Xichang 615000,China;3.Tobacco Technology Center of Sichuan Province,Xichang 615000,China;4.Huidong Marketing Center,Liangshan Branch of Sichuan Tobacco Corporation,Huidong 615200,China） AOTF-NIR; Nondestructive detection; Growing tobacco leaf in field; Chemical component In this paper,AOTF-NIR（AOTF-Near Infrared Reflectance Spectroscopy） technique was used to establish a rapid and nondestructive detection method for the determination of 5 chemical components of growing tobacco leaf in the field.Partial least square regressive method was used to build the calibration mathematical models between the NIR spectra information and the content of each chemical component based on the calibration set which consisted of 182 samples,and 30 samples in the validation set were predicted. |
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| PublicationTitle | 江西农业学报 |
| PublicationTitleAlternate | Acta Agriculturae Jiangxi |
| PublicationTitle_FL | Acta Agriculturae Jiangxi |
| PublicationYear | 2012 |
| Publisher | 四川省烟草公司凉山州分公司,四川西昌615000%国家烟草栽培生理生化研究基地,河南郑州,450002%四川省烟草技术中心,四川西昌,615000%四川省烟草公司凉山州分公司,四川西昌,615000%四川省烟草公司凉山州分公司会东营销部,四川会东,615200 国家烟草栽培生理生化研究基地,河南郑州450002 |
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| Title | AOTF-NIR快速检测田间生长烟叶中主要化学成分 |
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