近红外光谱法快速测定烤烟漂浮育苗基质中的有机质和水分

为确定烤烟漂浮育苗基质中有机质和水分的近红外快速检测方法,应用傅立叶变换近红外漫反射光谱仪,扫描了全国200多个基质样品,建立了近红外光谱与育苗基质有机质和水分含量间的数学模型,对12个样品进行预测.结果表明,各成分近红外预测值与实测值之间的平均偏差:有机质为0.21,水分为-0.07;且近红外预测值与化学法不存在显著性差异.近红外光谱分析技术可初步用于育苗基质中部分成分的快速定量分析,具有简便、快速、低成本、无污染以及样品的非破坏性和多组分同时测定等优点.     

在线近红外光谱仪在膨化大豆粉质量控制中的应用

为了指导生产,实现膨化大豆粉生产线在线检测水分、粗蛋白质和粗脂肪含量,在膨化大豆粉生产线安装近红外光谱仪,并将在线检测数据与国标方法(人工取样)检测数据进行了对比。结果表明：在线近红外光谱仪测定膨化大豆粉样品的水分、粗蛋白质、粗脂肪含量结果与国标方法接近,符合国标允许误差要求;配套的全自动镜头吹扫系统可有效去除黏附在采集窗口上的膨化大豆粉,保证了检测结果的准确性。实践证明,将在线近红外光谱仪应用于膨化大豆粉生产上,完全能满足膨化大豆粉加工行业在线实时监控的需求。     

红外光谱法快速测定烤烟漂浮育苗基质中的有机质和水分

为确定烤烟漂浮育苗基质中有机质和水分的近红外快速检测方法,应用傅立叶变换近红外漫反射光谱仪,扫描了全国200多个基质样品,建立了近红外光谱与育苗基质有机质和水分含量问的数学模型,对12个样品进行预测。结果表明,各成分近红外预测值与实测值之间的平均偏差：有机质为0．21,水分为-0.07;且近红外预测值与化学法不存在显著性差异。近红外光谱分析技术可初步用于育苗基质中部分成分的快速定量分析,具有简便、快速、低成本、无污染以及样品的非破坏性和多组分同时测定等优点。     

近红外光谱技术在烟用香精招标质量评价中的应用

为提高烟用香精招标过程质量评价的时效,通过扫描香精的近红外光谱,采用一致性评价方法建立了395种烟用香精的质量判别模型,并应用于投标香精的质量一致性评价。结果表明：(1)选择波长范围为4 000～9 000 cm-1,一阶导数结合标准正态变换预处理光谱,一致性指数（CI）阈值为3;(2)近红外光谱相似性匹配度（M）阈值设置为90%“,拒真”的概率极低;(3)应用于烟用香精招标评价,92.2%的投标样品（364种）实现了快速准确的判别。模型能准确地表征样品与标样的相似性,与色谱指纹图谱分析结果一致。该方法快速准确、实用性强,适宜作为香精香料招标质量评价的快检手段。     

近红外光谱技术及其在白酒质量控制中的应用展望

论述了近红外光谱技术的原理及特点、近红外光谱技术应用现状及在白酒行业质量控制过程的应用前景。     

不同分光原理近红外光谱仪光谱标准化方法在小麦粉品质检测中的应用

为探究不同分光原理的近红外光谱仪的光谱标准化方法,降低光谱差异性,实现模型共享,以小麦粉的粗蛋白为检测指标,以3台不同原理的近红外光谱仪采集的小麦粉样品近红外光谱为研究对象,分别采用直接标准化(DS)、分段直接标准化(PDS)和一元线性回归直接标准化(SLRDS)算法进行近红外光谱标准化研究,通过欧氏距离(D)、光谱标准化误差率(SSER)等指标分析主、从机光谱间的光谱差异性,以预测相关系数(R_p)、标准偏差(RMSEP)和相对标准偏差(RPD)等参数,评估模型转移后的预测效果;结果表明:1)经3种算法的光谱标准化,从机与主机之间的光谱差异性显著降低,转移后模型的从机预测效果大幅度提升,其中从机S₂的预测效果优于从机S₁;2)3种算法中,光谱经DS算法标准化后2台从机的预测误差率均最小,其中从机S₁的SSER_ave和SSER_max分别为0.9057和3.3667,R_p、RMSEP、RPD分别为0.8949,0.7052,2.2408,...     

近红外透射光谱技术用于烟用香精的品质控制

使用近红外透射光谱(near-infrared transmittance spectroscopy,NITS)结合马氏距离法考察近红外透射光谱技术对烟用香精样品变化的敏感度,通过稀释试验、放置时间试验及与色谱指纹图谱的比对试验验证了近红外透射光谱技术用于烟用香精品质控制的可行性.通过主成分分析-马氏距离法,建立了烟用香精的品质控制模型,所建立的模型能够准确鉴别出不良样品.     

近红外光谱技术在食品检测与质量控制中的应用

近红外光谱技术是近年来迅速发展的,可实现无损检测的快速分析技术,在国外已经成功地应用到诸多行业中,并在其中发挥了巨大的作用。文中阐述了近红外光谱技术在酒类、乳粉类、肉类、食用植物油、调味品及其它日常食品门类质量检测领域的国内外最新研究进展,介绍了近红外光谱技术在食品生产加工环节质量控制及成品检测方面的应用情况,提出了该技术在实际应用中存在的一些不足,并展望了其在中国食品市场的研究应用发展前景。     

烤烟新型育苗基质对烟苗生长的影响

采用漂浮育苗方式研究了保水剂与珍珠岩配比基质对烟苗出苗率和生长的影响,为新型烤烟育苗基质在生产实际中的示范和应用推广奠定理论基础。试验结果表明,在保水剂中添加30%的珍珠岩的新型烤烟育苗基质与普通基质相比,出苗率持平,烟苗前期的生育期进程提前,成苗期提早0～2 d,获得持平或更高的农学性状及干物质重,叶绿素含量增加0.24 mg/g,根系硝酸还原酶和超氧化物歧化酶分别增加1.73μg/g.h和31.3μg/g.h。保水剂中添加30%的珍珠岩配制的新型烤烟育苗基质可以替代以草炭、泥炭为主的常规基质。     

烟梗草炭在烟草漂浮育苗基质中的应用

为探索废弃烟梗作为烟草漂浮育苗基质原料的可行性,用自制的烟梗草炭(TSP)为烟草栽培基质,进行了烟草漂浮育苗试验.结果表明:TSP 1号(烟梗草炭50％+天然草炭50％)、TSP 2号(烟梗草炭50％+椰糠50％)、TSP 3号(烟梗草炭50％+天然草炭25％+椰糠25％)均可替代天然草炭用于烟草漂浮育苗基质中,其中TSP 3号替代的效果较好,烟苗综合长势优于天然草炭配方基质;烟梗草炭l号和2号替代天然草炭育苗,其烟苗长势均与天然草炭配方基质相当.因此,利用废弃烟梗替代天然草炭作为烟草漂浮育苗基质的方法可行.     

Application of near infrared reflectance spectroscopy to predict meat and meat products quality: A review

Over the past three decades, near infrared reflectance (NIR) spectroscopy has been proved to be one of the most efficient and advanced tools for the estimation of quality attributes in meat and meat products. This review focuses on the use of NIR spectroscopy to predict different meat properties, considering the literature published mainly in the last decade. Firstly, the potential of NIR to predict chemical composition (crude protein, intramuscular fat, moisture/dry matter, ash, gross energy, myoglobin and collagen), technological parameters (pH value; L*, a*, b* colour values; water holding capacity; Warner–Bratzler and slice shear force) and sensory attributes (colour, shape, marbling, odour, flavour, juiciness, tenderness or firmness) are reviewed. Secondly, the usefulness of NIR for classification into meat quality grades is presented and thirdly its potential application in the industry is shown. The review indicates that NIR showed high potential to predict chemical meat properties and to categorize meat into quality classes. In contrast, NIR showed limited ability for estimating technological and sensory attributes, which may be mainly due to the heterogeneity of the meat samples and their preparation, the low precision of the reference methods and the subjectivity of assessors in taste panels. Hence, future work to standardize sample preparation and increase the accuracy of reference methods is recommended to improve NIR ability to predict those technological and sensory characteristics. In conclusion, the review shows that NIR has a considerable potential to predict simultaneously numerous meat quality criteria.     

Use of near infrared spectroscopy to evaluate the intensity of extrusion-cooking processing of pea flour

Twenty-five different pea extrudates were produced using a Clextral BC45 twinscrew extruder. Near infrared reflectance (NIR) spectra of the extrudates were recorded between 1100 and 2500 nm. the application of principal component analysis (PCA) on these spectral data permitted discrimination between the extrudates produced under moderate, intermediate or severe conditions of extrusion-cooking. the study of protein quality through solubility experiments, polyacrylamide gel electrophoresis, determination of available basic amino acids and brown colour measurement showed that, under moderate conditions of extrusion-cooking, protein was only slightly affected. All protein subunits could be restored after solubilization in phosphate buffer containing a detergent and a reducer of disulphide bonds. However, under severe conditions of extrusion-cooking, the extrudates exhibited a relatively intense brown colour and all protein fractions were implicated in non-disulphide covalent bonds and underwent some macromolecular degradation. Therefore, the spectral discrimination between pea extrudates which was related to the processing parameters, could also be related to the degree of transformation of these extrudates. Thus, the method may be used to classify an extrudate produced under unknown conditions by projecting its spectrum on the similarity maps obtained by PCA on a known collection of extrudates.     

枇杷内部品质近红外光谱无损检测

利用近红外光谱技术(near infrared spectroscopy,NIRS)对101个枇杷样品进行无损检测,测得样品的可溶性固形物(total soluble sdid,TSS)、可滴定酸和Vc含量,结合偏最小二乘法(partial least squares,PLS)分别建立TSS、可滴定酸和Vc含量的定标模型。采用定标模型分别对TSS、可滴定酸和Vc的验证集样品进行预测,预测决定系数Rp2分别为0.906,0.745,0.554,预测均方根误差(root-meansquare error of prediction,RMSEP)分别为0.628,0.048,2.230,且TSS的相对分析误差(relative prediction deviation,RPD)为3.31,可滴定酸和Vc的RPD分别为2.00,1.52。表明建立的枇杷TSS的定标模型可用于实际检测,枇杷的可滴定酸和Vc含量可采用近红外光谱进行检测,但检测精度有待于进一步的提高。     

近红外光谱分析技术在苹果品质检测中的应用进展

苹果营养丰富,是大众水果之一,苹果的品质安全问题一直是社会关注的热点。本研究综述了2012~2016年我国近红外光谱分析技术在苹果品质检测中的研究和应用进展,包括基于近红外光谱的苹果品质检测、模型传递、分类与分级及在线检测系统研制4个方面。对今后我国近红外光谱分析技术在苹果品质检测中的应用提出建议,技术研究方面应不断建立和维护模型数据库,提高模型通用性;技术应用方面应研制在线检测系统和推进软硬件+互联网相结合,使近红外光谱分析技术在苹果品质检测中得到长足的发展。     

苹果有效酸度的近红外无损检测研究

为了更好的对苹果的有效酸度进行检测,实验应用波长范围为643.26～985.11nm的Purespect近红外透射光谱仪对100个富士苹果的校正集样品和20个预测集样品进行了光谱扫描,比较了不同的光谱预处理方法和不同建模波段对模型的影响,最终确立的模型相关系数(RC)为0.925,校正均方根误差(RMSEC)为0.0395。对模型预测性能的验证结果表明:建立的苹果有效酸度模型性能较稳定,能满足实际应用的要求。      

基于近红外光谱和随机森林方法鉴别蜂蜜真伪

目的建立蜂蜜样品真伪鉴别的近红外光谱快速检测方法,为今后蜂蜜检验工作提供可靠参考依据。方法采用积分球透反射模式采集样品近红外光谱数据,以Savitzky-Golay 1阶微分方法对原始光谱进行预处理,以随机森林方法建立光谱数据与蜂蜜真伪的定性判别模型。结果所建立的判别模型中训练样本判别正确率为100%,测试样本判别正确率为95%。结论近红外透反射光谱技术应用于蜂蜜真伪鉴别的可行性,同其他分析方法相比具有操作简单、速度快、效率高、无污染、费用低、无需复杂前处理等优点。     

Application of reflectance near infrared spectroscopy for bread analyses

The feasibility of using near infrared spectroscopy (NIRS) for prediction of nutrients in a wide range of bread varieties mainly produced from wheat and rye was investigated. Calibration was performed on samples collected over a 3-year-period and the calibration equations were tested on samples collected the subsequent year. Bread samples were dried, crushed, ground and measured in a rotating sample cup in the wavelength range 1100–2500 nm. Full range or segmented reflectance data was used for calibration based on partial least square (PLS) regression. Protein, fat, dietary fibre, sugar, ash, saturated fatty acids (SFA), monounsaturated fatty acids (MUFA), polyunsaturated fatty acids (PUFA) and Na could be determined directly with r² values of 0.99, 0.99, 0.89, 0.96, 0.91, 0.90, 0.91, 0.92 and 0.76, respectively. The total contents of carbohydrates and energy was calculated from NIR data with r² values of 0.98 and 0.99. The ratios between analyte variation range standard deviation (SD) and the root mean square error of cross validation (RMSECV) were 8.3 (protein), 9.1 (fat), 3.0 (dietary fibre), 4.7 (sugar), 3.0 (ash), 3.1 (SFA), 3.3 (MUFA), 3.5 (PUFA), 1.9 (Na), 7.2 (carbohydrates) and 8.4 (energy). Equivalent ratios were obtained on an independent test set. It is concluded that the applied NIRS methodology is suitable for routine analysis of wheat and rye based bread for the investigated organic properties and ash. The technique may also give a rough estimate of the Na content.     

Application of near infrared spectroscopy to peanut grading and quality analysis: overview

Techniques using near infrared (NIR) spectroscopy for quality measurements are becoming more popular in food processing and quality inspection of agricultural commodities. NIR spectroscopy has several advantages over conventional physical and chemical analytical methods of food quality analysis. It is a rapid and non destructive method and provides more information about the components and its structure present in the food products. It can measure more than one parameter simultaneously. The NIR spectrum includes wavelengths from 750 to 3000 nm that follow immediately after the visible region (400–700 nm). Many organic compounds can be well-defined by NIR reflectance, transmittance or diffuse reflectance system. This paper reviews the application of NIR spectroscopy to several oil seeds and examines the feasibility of using this technique for peanut quality analysis. The NIR spectroscopic instrumentation has been explained briefly for a better understanding. Also needs and limitations in use of NIR spectroscopy for peanut quality analysis and grading were explained.     

枇杷蜂蜜中饴糖的近红外光谱检测

实验通过对纯枇杷蜂蜜及主动掺入1%、2%……30%饴糖的假枇杷蜂蜜进行近红外光谱扫描,采用TQAnalysisv6对数据进行预处理,建立饴糖含量的定性及偏最小二乘法和主成分回归法定量分析模型,并将模型应用于蜂蜜样品的分析预测。结果显示,采用原始光谱或一阶微分处理建立的判别分析模型均能够较好地区分掺饴糖蜂蜜与纯蜂蜜。根据PLS算法、PCR算法建立的定量模型相关系数分别为0.99771、0.98654,用于预测的蜂蜜样品实际值与预测值之间的决定系数分别为0.992、0.974。由此可见,用近红外光谱技术鉴别蜂蜜中是否添加饴糖是可行的,在实际操作中可以采用近红外光谱法快速定性判别蜂蜜中是否含有饴糖,也可根据化学计量法确定饴糖的含量,为蜂蜜打假提供依据。