近红外光谱技术快速检测籼稻主要成分及新陈度的研究
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摘要
近红外光谱技术(Near Infrared Spectroscopy NIRS)是近年来为各国学者深入研究并应用于实际检测中的一种快速检测技术。近红外光谱主要由分子内基团振动的倍频吸收和合频吸收产生,只有含氢官能团如C-H, N-H, S-H和O-H的伸缩振动才能被检测到。近红外光谱检测技术具有分析速度快、分析效率高、分析成本较低等优点,因此被广泛应用于农产品、食品、生物科学、化工矿产等领域。稻米是我国重要战略物资和维系人民正常生活的重要保障,其品质的控制关乎国计民生。然而近年陈米冒充新米流入市场销售的恶性事件频发,严重影响着我国稻米的正常流通和公众的食品安全。因此将近红外光谱快速检测技术应用于稻米新陈度和品质检测具有重要的实际意义。
本文以湖南常德、益阳两地的不同新陈度早籼稻为研究对象,以对籼稻品质影响较大的脂肪酸值和直链淀粉含量为指标,对不同新陈度籼稻贮藏过程中的品质变化进行了研究；同时开展了近红外光谱技术快速检测籼稻新陈度的定量定性研究。在人工陈化条件下,总体籼稻样本的脂肪酸值和直链淀粉含量均有不同程度的增加,脂肪酸值的增幅为5.39-19.77mg/100g,变化差异显著；直链淀粉含量的增幅为1.34%-6.66%,与脂肪酸值相比变化差异较小。其中在不同新陈度籼稻样本的平均脂肪酸值增幅比较中,07年籼稻样品的增幅最大(15.13mg/100g),09年次之(10.54mg/100g),08年最小(6.40mg/100g)；在不同新陈度籼稻样本的平均直链淀粉含量增幅比较中,09年籼稻样品的增幅最大(4.42%),08年次之(2.81%),07年最小(2.33%)。
采用PLS方法建立近红外技术检测籼稻脂肪酸值和直链淀粉含量的定量模型。确定了不同籼稻成分建模最优系数分别为：脂肪酸值：全谱波段范围+一阶导数+Norris平滑为最佳,此时脂肪酸值模型相关系数r,内部验证标准差(RMSEC),交叉验证标准差(RMSECV)分别为0.85934,1.78,2.35。直链淀粉含量：全谱波段范围+一阶导数+多元散射校正(MSC)+Norris平滑为最佳,此时直链淀粉含量模型相关系数r,内部验证标准差(RMSEC),交叉验证标准差(RMSECV)分别为0.92775,1.49,1.65。
采用判别分析法建立近红外技术检测籼稻新陈度的分析模型。利用主因子分析结合马氏距离判定构建预测模型,确立了建模最优系数为：全谱波段+原始光谱MSC方法预处理,最佳主成分为10,此时模型判别正确率最高,可以达到96.7%。
研究结果表明：采用近红外光谱分析技术快速检测籼稻主要成分和新陈度是可行的。
Near infrared spectroscopy,which as a rapid detection technology has been deeply studied by scholars from various countries. The near infrared spectroscopy mainly produced by molecular vibration frequency within the group absorption and frequency absorption harmony, and only hydrogen-containing functional groups such as C-H, N-H, S-H, and O-H' stretching vibration can be detected. Near infrared spectroscopy analytical technique has its own advantages,such as rapid analysis of high efficiency and low cost and because of them, the Near-infrared technology has been widely used in agricultural, food, biological sciences, chemical mining and other fields now. Rice is an important strategic materials and an vital guarantee for maintaining people's lives, their quality control related to people's livelihood. However, in recent years, there are some sharpshooters who were posing old rice as the new rice into marketing, this has serious impact on the normal circulation of rice and the public food safety. Therefore, rapid detection of near infrared spectroscopy technology in rice freshness and quality testing has important practical significance.
In this paper, there are 30 different fresh early season rice which place of origins are Changde and Yiyang have been used in the research and the amylose and fatty acid content has been used as the index to study the variance of rice samples' quality during storage and near infrared spectroscopy technique has been used for the detection of rice samples' quantitative and qualitative research. Under the conditions of artificial aging, all the rice samples' fatty acid and amylose content increased in varying degrees, fatty acid in rice changed significantly different which increased in the rang of 5.39-19.77mg/100g; amylose content in rice changed less significantly different which increased in range of 1.34%-6.66%. In the comparison of rice sample in different freshness:the average increase in fatty acid of rice shows that the 07 rice samples' growth were highest(15.13mg/100g), the 09 rice samples' growth were higher (10.54mg/100g) and the 08 rice samples' increase in the minimum(6.40mg/100g);the average increase in amylose content of rice shows that the 09 rice samples' growth were highest(4.42%), the 08 rice samples' growth were higher(2.81%) and the 07 rice samples'increase in the minimum(2.33%).
PLS quantitative model for rice freshness has been established.Different region pretreatment methods for spectrum model were compared.The model's optimal coefficients were:fatty acids:the full spectrum wavelength region+first derivative+ Norris smoothing; then the fatty acid model correlation coefficient r, Root mean Square Error of Calibration(RMSEC), Root mean Square Error of Cross-Validation (RMSECV) were 0.85934,1.78,2.35; Amylose content:the full spectrum wavelength region+first derivative+multiplicative scatter correction+Norris smoothing,then the correlation coefficient r, Root mean Square Error of Calibration(RMSEC), Root mean Square Error of Cross-Validation(RMSECV) were 0.92775,1.49,1.65.
This paper also studied the construction of discriminant analysis modef for qualitative analysis of rice freshness by using NIRS and Principle Component Analysis(PCA)-Mahalanobis Distance.The optimal model coefficients were:the full spectrum wavelength region+multiplicative scatter correction, the optimal main component was 10,At this point the model had the highest rates of discrimination which can reach 96.7%.
The results show that:using near infrared spectroscopy technique for detection of rice basis and freshness is possible.
本文以湖南常德、益阳两地的不同新陈度早籼稻为研究对象,以对籼稻品质影响较大的脂肪酸值和直链淀粉含量为指标,对不同新陈度籼稻贮藏过程中的品质变化进行了研究；同时开展了近红外光谱技术快速检测籼稻新陈度的定量定性研究。在人工陈化条件下,总体籼稻样本的脂肪酸值和直链淀粉含量均有不同程度的增加,脂肪酸值的增幅为5.39-19.77mg/100g,变化差异显著；直链淀粉含量的增幅为1.34%-6.66%,与脂肪酸值相比变化差异较小。其中在不同新陈度籼稻样本的平均脂肪酸值增幅比较中,07年籼稻样品的增幅最大(15.13mg/100g),09年次之(10.54mg/100g),08年最小(6.40mg/100g)；在不同新陈度籼稻样本的平均直链淀粉含量增幅比较中,09年籼稻样品的增幅最大(4.42%),08年次之(2.81%),07年最小(2.33%)。
采用PLS方法建立近红外技术检测籼稻脂肪酸值和直链淀粉含量的定量模型。确定了不同籼稻成分建模最优系数分别为：脂肪酸值：全谱波段范围+一阶导数+Norris平滑为最佳,此时脂肪酸值模型相关系数r,内部验证标准差(RMSEC),交叉验证标准差(RMSECV)分别为0.85934,1.78,2.35。直链淀粉含量：全谱波段范围+一阶导数+多元散射校正(MSC)+Norris平滑为最佳,此时直链淀粉含量模型相关系数r,内部验证标准差(RMSEC),交叉验证标准差(RMSECV)分别为0.92775,1.49,1.65。
采用判别分析法建立近红外技术检测籼稻新陈度的分析模型。利用主因子分析结合马氏距离判定构建预测模型,确立了建模最优系数为：全谱波段+原始光谱MSC方法预处理,最佳主成分为10,此时模型判别正确率最高,可以达到96.7%。
研究结果表明：采用近红外光谱分析技术快速检测籼稻主要成分和新陈度是可行的。
Near infrared spectroscopy,which as a rapid detection technology has been deeply studied by scholars from various countries. The near infrared spectroscopy mainly produced by molecular vibration frequency within the group absorption and frequency absorption harmony, and only hydrogen-containing functional groups such as C-H, N-H, S-H, and O-H' stretching vibration can be detected. Near infrared spectroscopy analytical technique has its own advantages,such as rapid analysis of high efficiency and low cost and because of them, the Near-infrared technology has been widely used in agricultural, food, biological sciences, chemical mining and other fields now. Rice is an important strategic materials and an vital guarantee for maintaining people's lives, their quality control related to people's livelihood. However, in recent years, there are some sharpshooters who were posing old rice as the new rice into marketing, this has serious impact on the normal circulation of rice and the public food safety. Therefore, rapid detection of near infrared spectroscopy technology in rice freshness and quality testing has important practical significance.
In this paper, there are 30 different fresh early season rice which place of origins are Changde and Yiyang have been used in the research and the amylose and fatty acid content has been used as the index to study the variance of rice samples' quality during storage and near infrared spectroscopy technique has been used for the detection of rice samples' quantitative and qualitative research. Under the conditions of artificial aging, all the rice samples' fatty acid and amylose content increased in varying degrees, fatty acid in rice changed significantly different which increased in the rang of 5.39-19.77mg/100g; amylose content in rice changed less significantly different which increased in range of 1.34%-6.66%. In the comparison of rice sample in different freshness:the average increase in fatty acid of rice shows that the 07 rice samples' growth were highest(15.13mg/100g), the 09 rice samples' growth were higher (10.54mg/100g) and the 08 rice samples' increase in the minimum(6.40mg/100g);the average increase in amylose content of rice shows that the 09 rice samples' growth were highest(4.42%), the 08 rice samples' growth were higher(2.81%) and the 07 rice samples'increase in the minimum(2.33%).
PLS quantitative model for rice freshness has been established.Different region pretreatment methods for spectrum model were compared.The model's optimal coefficients were:fatty acids:the full spectrum wavelength region+first derivative+ Norris smoothing; then the fatty acid model correlation coefficient r, Root mean Square Error of Calibration(RMSEC), Root mean Square Error of Cross-Validation (RMSECV) were 0.85934,1.78,2.35; Amylose content:the full spectrum wavelength region+first derivative+multiplicative scatter correction+Norris smoothing,then the correlation coefficient r, Root mean Square Error of Calibration(RMSEC), Root mean Square Error of Cross-Validation(RMSECV) were 0.92775,1.49,1.65.
This paper also studied the construction of discriminant analysis modef for qualitative analysis of rice freshness by using NIRS and Principle Component Analysis(PCA)-Mahalanobis Distance.The optimal model coefficients were:the full spectrum wavelength region+multiplicative scatter correction, the optimal main component was 10,At this point the model had the highest rates of discrimination which can reach 96.7%.
The results show that:using near infrared spectroscopy technique for detection of rice basis and freshness is possible.
引文
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