近红外光谱及高光谱技术在茶叶上的应用

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.     

文献摘要

近红外光谱分析技术在茶叶品质属性甄别中的应用 利用近红外光谱分析技术,结合不同的化学计量学方法（偏最小二乘法、标准法）,对茶叶进行快速无损检测,从而判定类别。结果表明,基于提取的茶叶近红外光谱数据,利用偏最小二乘法（PLS）的甄别效果优于标准法,可以直观地将59个来自不同产地、品种和加工工艺的茶叶样品进行准确的分类判定。     

近红外技术在茶叶上的研究进展

主要介绍了国内外近红外检测分析技术在茶叶上的研究的进展情况,分析了目前近红外技术与其他检测分析相比存在的优缺点及限制其发展的主要原因,对近红外技术在茶叶上的应用前景和方向作出了展望,为近红外技术在茶叶上的应用和发展提供参考依据。     

化学指纹图谱在茶叶中的应用

针对目前市场上茶叶产品较为混乱,对目前在茶叶品种与产地鉴别以及质量监控中具有广阔应用前景的化学指纹图技术做一综述,介绍基于高效液相色谱、近红外光谱、质谱、核磁共振等技术的指纹图谱在茶叶识别中的作用,并对指纹图谱的解析方法做了简要介绍,总结了化学指纹图谱在茶叶中的应用前景。     

光谱技术在茶叶理化指标检测中的研究进展

光谱技术由于其快速、无损、便捷的特点,是目前发展较快,应用较广的技术之一,本文介绍了紫外可见光谱、近红外光谱、荧光光谱、拉曼光谱、高光谱成像等多种光谱技术的原理,着重介绍了其在茶叶分类、成分检测、品质评价等方面的应用情况和研究进展。     

指纹图谱技术在茶叶研究上的应用

茶叶品质难辨易形成混乱的市场局面,制约了茶产业现代化发展进程。近年来,指纹图谱技术在茶叶感官品评、质量控制和产地判别等方面的应用越来越多,为茶叶的品质鉴定提供了有效的技术支撑。文章就茶叶指纹图谱技术方法进行了综述,包括气相色谱(GC)、高效液相色谱(HPLC)、毛细管电泳(CE)、红外(IR)及近红外光谱(NIR)、核磁共振(NMR)等,并对指纹图谱技术在茶叶应用上存在的问题进行了分析,对其今后的发展做出了展望,为指纹图谱技术在茶叶上的进一步应用提供理论基础和参考依据。     

近红外光谱分析技术在茶叶品质属性甄别中的应用

利用近红外光谱分析技术,结合不同的化学计量学方法(偏最小二乘法、标准法),对茶叶进行快速无损检测,从而判定类别。结果表明,基于提取的茶叶近红外     

茶叶检测评审研究进展与关键技术分析

为促进我国茶叶评审技术的研究和发展,综述了国内茶叶评审的研究现状,对传统茶叶评审方法如人工感官评审和理化检验进行了综述分析;对电子鼻、电子舌、计算机视觉、近红外光谱、拉曼光谱和高光谱成像等智能感知检测技术进行了讨论和分析,在总结研究成果的基础上,指出茶叶评审今后发展的趋势。     

非线性流形降维方法结合近红外光谱技术快速鉴别不同海拔的茶叶

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。     

2014年度茶树育种技术发展报告

本文综述了2014年度国内外茶树育种技术研究进展。国外在茶树育种鉴定技术研究有较大进展,开发了超高压液相色谱(UHPLC)和近红外反射光谱(NIRS)技术快速检测茶树品种样品的儿茶素类等品质成分,开发溶剂辅助香气蒸发(SAFE)技术检测茶叶的香气物质以及酶技术鉴定茶树品种抗茶叶轮斑病的能力。我国茶树育种的重要进展主要在:古茶树资源保护和开发利用技术研究、分子生物学技术在茶树育种鉴定中的应用以及新品种选育和品种保护。     

Monitoring the staling of wheat bread using 2D MIR-NIR correlation spectroscopy

Staling of bread is a major source of food waste and efficient monitoring of it can help the food industry in the development of anti-staling recipes. While the staling fingerprint in the mid-infrared region is fairly well established this paper set out to find the most informative parts of the near-infrared spectra with respect to staling. For this purpose, two-dimensional correlation spectroscopy on near- and mid-infrared spectra of wheat bread crumb during aging was employed for the first time. The important mid-infrared absorption band at 1047 cm⁻¹ related to amylopectin retrogradation was found to correlate positively with increased bread hardness and to co-vary with the near-infrared band at 910 nm in the short wavelength region (r² = 0.88 to hardness), the near-infrared band at 1688 nm in the 1. overtone region (r² = 0.97 to hardness) and to the near-infrared band in the long wavelength region at 2288 nm (r² = 0.97 to hardness). The spectral information from the first principal component on near-infrared and the first principal component on mid-infrared was found to be highly correlated by a r² = 0.98. It is demonstrated that the major bread staling processes such as amylopectin retrogradation and water loss can be followed with both near- and mid-infrared spectroscopy.     

Discrimination of weed seedlings, wheat (Triticum aestivum) stubble and sunflower (Helianthus annuus) by near-infrared reflectance spectroscopy (NIRS)

The potential of using near-infrared reflectance spectroscopy (NIRS) to discriminate between seven broadleaf weed species, sunflower and wheat stubble was evaluated. Our results showed that the spectral window between 750 and 950 nm, which corresponds to near-infrared wavelength, was able to discriminate among wheat stubble, sunflower and the most problematic “hard-to-control” weeds in no-till sunflower, i.e. Little mallow (Malva parviflora L.) and Ecballium elaterium L. These results are promising for further work in real-time remote sensing identification of weed patches in sunflower fields.     

近红外透射光谱法(NITS)分析大豆品质的研究

为了研究大豆品质性状的快速测定方法,以我国东北部四省区572份大豆样品为材料,采用近红外透射(NITS)技术非破坏性测定大豆的粗蛋白质、粗脂肪含量.调选出的校正集样品经实验室常规分析测定,建立其吸收光谱与化学成分间的关系模型,校正并优化原有测定方程.校正方程经预测获得了较高的预测集决定系数0.9757(蛋白质)、0.9549(脂肪)和较低的标准误差2.18(蛋白质)、0.88(脂肪).结果表明近红外透射光谱技术可广泛应用于大豆品种品质普查、大豆品质育种材料筛选和商品大豆质量分类分级.本研究试验用样品数量多、来源分布均匀、品种信息丰富,因此,所建立的近红外透射预测模型适用范围广.     

Research progress on the origin traceability of edible oils

The origin traceability of edible oil is an effective way to protect the legitimate rights and interests of producers and consumers. This review briefly summarizes research progress on origin traceability technologies for edible oils including stable isotope ratio mass spectrometry, mineral element fingerprint analysis, organic component fingerprint analysis, near-infrared spectroscopy, nuclear magnetic resonance technology and biochemical analysis. Moreover, the development trends in edible oil origin traceability technology were proposed.     

Assessment of Potato Dry Matter Concentration Using Short-Wave Near-Infrared Spectroscopy

The utility of short-wavelength near-infrared spectroscopy (over the wavelength region 750–950 nm), used in a partial transmittance optical geometry, was assessed as a means of estimating the dry matter concentration of potato tubers. The sampling optics did not involve contact with the sample, and could be used on a moving stream of product. A prediction accuracy of R ² (correlation coefficient of determination) of 0.85 with a root mean square error of prediction (RMSEP) of 1.52% for intact, whole tubers and R ² = 0.95 and RMSEP = 0.50% for sliced tubers was achieved. We conclude that short-wavelength near-infrared technology using a partial transmittance optical sampling geometry can be a useful tool for rapid assessment of tuber dry matter concentration prior to processing.     

Study of the near-infrared transmission of woven fabrics based on statistical analysis

47 kinds of woven fabrics were prepared with different fibers, thicknesses, weights per square meter and percentage covers. Statistical analysis method was employed to study the influence of the material and structure parameters on near-infrared transmission of these fabrics. Firstly, the effect of materials on near-infrared transmittance was determined through the contingency table analysis. Then the parameters significantly influencing near-infrared transmittance were found out and correlations among them were discussed by direct correlation and partial correlation analysis. Finally, regression equation of the near-infrared transmittance was established using factor analysis and principal component extraction. Results show that materials have little influence on near-infrared transmittance of woven fabrics. However, thickness, weight per square meter and percentage cover of the fabrics are closely related to near-infrared transmittance. Because there are correlations among thickness, weight per square meter and percentage cover, two new factors are extracted to establish the regression equation. The equation has an error rate of less than 5 % and thus can predict near-infrared transmittance precisely.     

利用小孢子培养技术创建高含油量甘蓝型油菜

以具备高含油量品质的甘蓝型油菜品系1481、1489以及1481×206的F1代为供体材料，对影响游离小孢子胚胎发生的部分因素——供体植株基因型、小孢子培养密度、小孢子培养的合适时期进行了研究，同时采用近红外反射光谱分析技术对高含油量甘蓝型油菜品系1481和1489获得的DH系种子含油量进行了测定。研究结果表明：材料1481的小孢子产胚量较高，达34.9个/蕾；三种材料的小孢子培养合适密度均为3蕾/皿；大田种植的甘蓝型油菜产胚量以初花至初花后1周左右的时间最高；所获得的40个DH系含油量中有21个DH系的含油量与对照中双4号的含油量之间存在显著差异，有13个DH系的含油量比供体亲本高，其中WD-33、WD-34两个DH系的含油量高达47%以上，可以作为选育或转育高含油量新品种的材料。     

近红外光谱技术在茶叶品控与装备创制领域的研究进展

茶叶是中国特色的经济作物和高附加值的天然饮品,快速、准确的营养诊断和品质监控是保证茶叶制品质量的必然要求。本文分析了传统茶叶质量评价方法和近年来涌现出的快速检测技术的局限性,介绍了近红外光谱技术的特性和该技术应用于茶叶领域的研究论文关键词的演变过程,详细评述了该技术在茶制品关键组分快速检测、茶制品质量控制、数字化光谱快速分析仪创制和技术标准开发中的研究进展,并对该技术在茶叶分析中的发展方向进行了展望。     

Prediction of the clover content of red clover- and white clover-grass mixtures by near-infrared reflectance spectroscopy

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.