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光谱技术作为一种绿色、快速、高效、准确的无损检测技术,在茶叶及茶制品的理化检测、品质评价等方面显现出较大的应用潜力.综述了近红外光谱及高光谱技术在茶叶理化成分定量分析,茶叶种类、产地及品种的判别以及茶叶等级判别等方面的应用和研究进展,同时对该技术在茶叶上的应用前景进行展望. 相似文献
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油料作物中油酸含量的高低与其品质存在很大关系。光谱技术具有快速、无损地获取目标物光谱数据的优势。从高光谱技术和近红外光谱技术两个方面介绍了光谱技术在油料作物油酸含量检测中的研究进展,分析了目前光谱技术检测油酸含量存在的问题,并对其应用前景进行了展望。 相似文献
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为提高不同海拔茶叶品质近红外光谱技术鉴别方法的精度,提出采用局部线性嵌入法(LLE)和拉普拉斯特征映射法(LE)非线性流形学习方法对近红外光谱数据进行降维处理,并与基于核函数的非线性(KPCA)及线性(PCA)降维方法比较,建立不同海拔茶叶品质的近红外光谱LSSVM鉴别模型。不同降维方法可视化结果表明,KPCA和PCA方法的数据点离散性较大,400~800 m和800~1 200 m的样本点重叠较多,而非线性流形学习方法能将同一类样本点在三维空间很好地聚集在一起,不同海拔的茶叶能较好地区分开,且聚集效果方面LE方法好于LLE方法。模型性能表明,LE_LSSVM模型性能最佳,预测集总体判别率、Kappa系数分别为100%和1.00;相比于PCA_LSSVM、KPCA_LSSVM和LLE_LSSVM,模型预测集总体判别率分别提高1.7%、1.7%、3.3%;Kappa系数分别提高0.025、0.03、0.05。研究表明,LE等非线性流形学习降维方法在近红外光谱数据降维、简化模型复杂度、提高模型精度方面效果很好,为茶叶品质快速检测方法研究提供了一种新思路。 相似文献
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基于近红外光谱技术的春小麦单粒种子活力鉴定 总被引:1,自引:0,他引:1
为研究利用近红外光谱技术鉴定春小麦单粒种子活力的效果,以2013年收获的甘肃春小麦品种宁春4号种子为材料,对300粒小麦种子进行近红外光谱单粒扫描,根据光谱图结合发芽实验结果建立春小麦种子活力预测模型。结果表明,以腹面和背面平均光谱的建模效果要优于单面光谱。最佳建模比例为建模集与检验集之比3∶1。应用近红外光谱定性偏最小二乘分析方法建模,在7 000~8 000cm-1光谱范围内采用中心化预处理,在主成分为5时,模型的建模集和检验集的鉴别率分别为86.36%和91.30%,建模效果最佳;采用近红外光谱偏最小二乘法定量检测小麦种子活力时,建模效果较差。因此,近红外光谱定性偏最小二乘分析方法适于进行春小麦单粒种子活力定性鉴定。 相似文献
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一种国产近红外仪分析油菜籽三种主要品质参数研究 总被引:1,自引:0,他引:1
利用中国农业科学院油料作物研究所研制的NYDL-3000智能型多参数粮油品质速测仪分析了油菜籽含油量、硫甙和芥酸含量,测定结果与传统化学方法进行了比较,其中含油量结果与PC-120核磁共振仪和MATRIX-I傅立叶变换近红外光谱仪做验证。内部交叉验证结果显示:含油量、硫甙和芥酸含量的决定系数R2分别为0.954 3、0.985 3和0.982 3,均方差分别为0.0469 、0.419 8和0.160 4,T检验显示三种品质参数交叉验证集的近红外光谱法(NYDL-3000)预测值和化学值差异均不显著。外部检验结果表明:硫甙含量、含油量两种方法测定值的相关系数分别为0.837 6和0.951 7,平均绝对误差分别为7.54%和0.02%,均在平均绝对误差允许的范围之内;成对数据双尾t检验表明,近红外光谱法和化学法两者结果差异不显著。芥酸分析中,NYDL-3000将342份样品中3份低芥酸材料判定为高芥酸,近红外光谱法和化学法两者结果符合率达99.12%。含油量的测定结果显示:NYDL-3000和PC-120、MATRIX-I结果的相关系数分别为0.956 6和0.901 5,平均绝对误差分别为0.78%和3.06%。研究结果表明,利用NYDL-3000智能型多参数粮油品质速测仪所建立的品质模型可以满足油菜育种对早代材料芥酸、硫甙含量和含油量的快速测定要求。 相似文献
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针对不同产地、不同类型及不同年份的白茶的感官滋味品质特征、滋味特征属性进行深入剖析及基于近红外光谱技术的滋味属性预测评价研究。研究显示甘甜度与醇爽度是白茶滋味品质特征表现的必要评价指标,相同原料及前期工艺条件下陈化度提高可显著提升滋味甘甜度及醇爽度。利用NIRS-PLS法对滋味特征总分、甘甜度、醇爽度及陈化度分别建模,模型定标集校正相关系数Rc为0.837~0.987,预测相关系数Rp为0.748~0.888,均具有较高预测能力,表明利用近红外光谱技术能够实现白茶感官滋味特征属性的快速预测评价。 相似文献
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Feasibility of near infrared spectroscopy for analyzing corn kernel damage and viability of soybean and corn kernels 总被引:1,自引:0,他引:1
Lidia Esteve Agelet David D. Ellis Susan Duvick A. Susana Goggi Charles R. Hurburgh Candice A. Gardner 《Journal of Cereal Science》2012
The current US corn grading system accounts for the portion of damaged kernels, measured by time-consuming and inaccurate visual inspection. Near infrared spectroscopy (NIRS), a non-destructive and fast analytical method, was tested as a tool for discriminating corn kernels with heat and frost damage. Four classification algorithms were utilized: Partial least squares discriminant analysis (PLS-DA), soft independent modeling of class analogy (SIMCA), k-nearest neighbors (K-NN), and least-squares support vector machines (LS-SVM). The feasibility of NIRS for discriminating normal or viable-germinating corn kernels and soybean seeds from abnormal or dead seeds was also tested. This application could be highly valuable for seed breeders and germplasm-preservation managers because current viability tests are based on a destructive method where the seed is germinated. Heat-damaged corn kernels were best discriminated by PLS-DA, with 99% accuracy. The discrimination of frost-damaged corn kernels was not possible. Discrimination of non-viable seeds from viable also was not possible. Since previous results in the literature contradict the current damage-discrimination results, the threshold of seed damage necessary for NIRS detection should be analyzed in the future. NIRS may accurately classify seeds based on changes due to damage, without any correlation with germination. 相似文献
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Prediction of the clover content of red clover- and white clover-grass mixtures by near-infrared reflectance spectroscopy 总被引:1,自引:0,他引:1
This study assesses near-infrared reflectance spectroscopy (NIRS) as a rapid and reliable method for estimating the clover content of clover/grass mixtures. NIRS calibrations were derived both for red clover ( Trifolium pratense ) and white clover ( T. repens ) mixtures. To maximize variability, the set of samples for analysis was selected from field plots receiving a wide range of nitrogen fertilizer application and harvested over 2 years at weekly intervals throughout the growing season. The samples were scanned using a NIR-Systems model 5000 monochromator. A total of 183 white clover/grass and 282 red clover/grass samples were used to calibrate and cross-validate the equations derived. The NIRS calibrations obtained from this study have the potential to be used in research on clover/grass mixtures as well as for advisory work. 相似文献
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为实现向日葵育种材料的品质性状快速预测,选取154份向日葵籽仁样品,结合化学测定值和近红外光谱,利用化学计量学手段建立向日葵籽仁品质指标的近红外模型,评估其在向日葵籽仁粗蛋白、粗脂肪、油酸、亚油酸等重要品质性状测定中的可行性。结果表明,改进偏最小二乘法建模效果最佳,其粗脂肪、粗蛋白、油酸、亚油酸、饱和脂肪酸及不饱和脂肪酸的定标相关系数分别为0.975、0.950、0.973、0.951和0.913,交叉验证相关系数分别 为0.969、0.939、0.915、0.927和0.711。用检验集对模型进行验证,粗脂肪、蛋白质、油酸、亚油酸、饱和及不饱和脂肪酸的外部检验相关系数(R2)分别为0.959、0.950、0.937、0.906和0.930。本研究建立的模型质量较高,能够满足向日葵籽仁品质成分的快速测定,可为向日葵品质育种前期大量、快速的筛选提供技术支持。 相似文献
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Olga Escuredo M. Inmaculada González Martín Guillermo Wells Moncada Susana Fischer José Miguel Hernández Hierro 《Journal of Cereal Science》2014
The high content of amino acids of the quinoa, especially essential amino acids (higher than other cereals) makes a food increasingly demanded by consumers. A total of twelve amino acids (arginine, cystine, isoleucine, leucine, lysine, phenylalanine, proline, serine, threonine, tryptophan, tyrosine and valine) were analyzed in quinoa samples from Chile by near infrared spectroscopy (NIR) with direct application to the samples of a remote fiber-optic reflectance probe. The calibration results using modified partial least squares (MPLS) regression satisfactorily allowed the determination of the concentrations of this amino acid group with high multiple correlation coefficients (RSQ = 0.97–0.71) and low standard prediction errors (SEPC = 0.07–0.20). The prediction capacity (RPD) for the arginine, the cystine, the isoleucine, the lysine, the serine, the threonine, the tryptophan, the tyrosine and the valine ranged between 2.6 and 5.2, for the rest of amino acids were higher to 1.8, indicating that the NIRS equations obtained were applicable to unknown samples. It has confirmed that NIRS technology is a method that may be useful to replace the traditional methods for routine analysis of some amino acids. 相似文献
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Yiftach Vaknin Miriam GhanimShahar Samra Levana DvashEfrat Hendelsman Dan EisikowitchYael Samocha 《Industrial Crops and Products》2011,34(1):1029-1034
The potential of near-infrared reflectance spectroscopy (NIRS) to estimate the oil content, fatty acid composition, and protein content of Jatropha curcas seeds was studied. Seventy-four intact kernels from various sources were scanned by NIRS. All samples were analyzed for oil content (hexane extractions), fatty acid composition (gas chromatography), and protein content (Kjeldahl). Calibration equations were developed for oil content, individual fatty acids (oleic C18:1, linoleic C18:2, stearic C18:0 and palmitic C16:0), and protein content. The performance of the calibration equations was evaluated through external and cross-validation. The results showed that NIRS was a reliable, accurate and nondestructive technique to estimate oil and protein contents, as well as oleic and linoleic fatty acid concentrations in J. curcas kernels; NIRS provides a rapid, simple, and cost-effective alternative method for screening intact J. curcas kernels. 相似文献
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用近红外反射光谱技术测定精米粉样品表观直链淀粉含量的研究 总被引:23,自引:2,他引:21
以约3 g精米粉为测试样品,研究了用近红外反射光谱(NIRS)技术测定稻米表观直链淀粉含量(AAC)的效果及影响校正的一些因素。对3种不同回归统计分析方法校正效果的差异比较表明,用修正的部分最小平方法(MPLS)、部分最小平方法(PLS)和主成分回归法(PCR)进行AAC校正时,校正标准误(SEC)、交叉检验标准误(SECV)和检验工作标准误[SEP(C)]均呈上升趋势,分别为0.83、1.75和1.09 (MPLS);1.73、1.98和1.74 (PLS)以及2.29、2.56和1.72 (PCR);相反,校正决定系数[WTBX]R[WTBZ]2和检验决定系数RSQ呈下降趋势,分别为0.983和0.91 (MLPS);0.927和0.84 (PLS)以及0.870和0.84 (PCR)。由此可见,用MPLS技术建立AAC回归方程效果最佳。而从两种校正群体选定方法对校正效果的结果看,用软件程序SELECT根据样品光谱特征选定的校正群体和用AAC测定值按比例选定的校正群体,在建立AAC回归方程时,前者的SEC、SECV和SEP(C)均比后者要小,而[WTBX]R[WTBZ]2和RSQ相仿,表明根据光谱特征选定校正群体效果略好。 相似文献