共查询到20条相似文献,搜索用时 15 毫秒
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Nondestructive evaluation of jujube quality by visible and near-infrared spectroscopy 总被引:2,自引:0,他引:2
This study compared prediction ability of interactance, transmission measurements of visible and near-infrared (Vis/NIR) spectroscopy in detecting the soluble solids content (SSC) of jujubes. Calibration models relating Vis/NIR spectra to SSC were developed based on partial least squares regression (PLSR) with respect to the logarithms of the reciprocal absorbance (log (1/R)), its first and second derivatives (D1log (1/R), D2log (1/R)). The PLSR models for prediction samples resulted correlation coefficients (rp) of 0.74-0.91 and root mean square error of prediction (RMSEP) of 2.018-3.200 °Brix for interactance; rp of 0.63-0.73 and RMSEP of 3.517-3.863 °Brix for transmission, respectively. The results indicate that interactance displays an obvious advantage over transmission measurement.The reflectance measurement was used to access the discrimination potential in sorting external insect-infested jujubes from intact class. Stepwise discriminant analysis (SDA) was performed to identify the effective wavelengths that best discriminated the insect-infested jujubes from intact jujubes and to derive a discriminant function in classifying the jujubes showing external infestation and those that were free of infestation. The results showed that log (1/R) had better correct classification rate than D1log (1/R), and D2log (1/R) for classifying intact, insect-infested and stem-end classes. 相似文献
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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。 相似文献
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Nondestructive Determination of Soluble Solids in Tomatoes using Near Infrared Spectroscopy 总被引:1,自引:0,他引:1
A nondestructive optical method for determining the soluble solids content of fresh whole tomatoes was investigated. The method, based upon near infrared spectrophotometric techniques, could predict the soluble solids content of tomatoes (r = 0.92, SEC = 0.27°Brix). Tomatoes from more than 30 popular fresh market cultivars at stages of maturity from mature green to ripe red fruit were studied. 相似文献
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目的:使用超声波无损检测技术对脐橙的主要内部品质参数进行检测。方法:在搭建完超声波无损检测平台后,将同一批脐橙分为实验组与对照组,对两组分别进行为期20 d的检测,每次检测间隔24 h。根据检测结果,建立超声波特征参数与脐橙内部品质参数之间的关系并检验。结果:建立了超声波衰减系数(Attenuation coefficient,A)与脐橙可溶性固形物(Total soluble solid,TSS)之间的拟合方程:TSS=2.512A3-11.78A2+23.03A-2.805,R2=0.9982,RSME=0.1377,预测相对误差σ<5%;超声波衰减系数与脐橙总酸(Total acid,TA)之间的拟合方程:TA=-0.5219A3+2.073A2-2.724A+1.716,R2=0.9735,RSME=0.0131,预测相对误差σ<5%。结论:超声波衰减系数对脐橙内部品质的变化敏感,超声波无损检测技术用于脐橙内部品质检测是可行的。 相似文献
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研究贮藏期间损伤猕猴桃内部品质与其近红外漫反射光谱之间的关系。利用近红外光谱(12000~4000cm-1)技术和多元线性回归(multiple linear regression,MLR)、主成分回归(principal component regression,PCR)和偏最小二乘法(partial least squares,PLS)3种校正方法分别对损伤华优猕猴桃在2℃条件下贮藏4周期间的可溶性固形物含量、pH值和硬度进行定量分析;并对比吸光度原始光谱、一阶微分和二阶微分3种不同预处理方法的PLS模型校正结果。结果表明:一阶微分预处理方法时,应用PLS建立的可溶性固形物含量、pH值和硬度校正模型的效果最佳;预测集样品预测值与测量值之间的相关系数分别为0.812、0.703、0.919,预测均方根误差分别为0.749、0.153、1.700。说明应用近红外漫反射技术检测贮藏期间损伤猕猴桃的内部品质是可行的。 相似文献
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目的:实现对鲜食玉米含水率的快速、准确预测。方法:采用高光谱技术对鲜食水果玉米进行光谱数据采集,比较了变量标准化算法(SNV)、附加散射校正算法(MSC)、卷积平滑(SG)、移动平均法(MA)等数据预处理方法对模型精度的影响,选取MSC进行预处理。基于MSC预处理数据选用连续投影算法(SPA)、竞争性自适应重加权算法(CARS)以及随机蛙跳法(RF)分别提取含水率的特征波长并建模分析。结果:MSC-CARS-PLS模型的含水率预测效果最好,预测集的决定系数(R2p)达到0.825 0,预测均方根误差(RMSEP)为0.006 0。结论:利用高光谱技术可实现对鲜食水果玉米含水率的快速无损检测。 相似文献
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生鲜紫薯花青素等多品质参数的可见-近红外快速无损检测 总被引:1,自引:0,他引:1
基于实验室自行搭建的可见-近红外光谱系统,以市售生鲜紫薯为研究对象,探讨其花青素、可溶性固形物(soluble solid contents,SSC)以及总糖(total sugars,TS)的同时快速无损检测方法。对紫薯原始光谱进行SG(Savitzky-Golay)平滑、标准正态变量变换以及一阶求导预处理,然后用偏最小二乘回归法进行建模分析。对于花青素和TS,经SG平滑结合一阶求导预处理的模型预测效果最佳;对于SSC,经SNV预处理的模型预测效果最好。针对紫薯各参数最佳预处理光谱采用竞争性自适应加权算法进行波长筛选,再次建立模型。花青素模型预测集的相关系数为0.942 1,预测均方根误差(root mean square error of prediction,RMSEP)为0.225?9?mg/g;SSC模型预测集相关系数为0.943?1,RMSEP为0.878?7?°Brix;TS模型预测集的相关系数为0.925?3,RMSEP为0.244?3%。结果显示,利用可见-近红外光谱可以实现对生鲜紫薯的花青素、SSC以及TS的同时快速无损检测,对生鲜紫薯品质的快速无损检测分选有着重要的实用意义。 相似文献
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利用高光谱技术研究柑橘不同部位的糖度预测模型,将花萼、果梗和赤道部位的高光谱信息分别建立与其对应部位糖度的预测模型,建立基于偏最小二乘(Least squares regression,PLSR)、主成分回归(Principal component regression,PCR)和多元线性回归(Stepwise multivariate linear regression,SMLR)预测模型,3种预测模型中PLSR模型检测效果最好,通过Norris derivative预处理方法对花萼光谱数据进行处理后,预测集相关系数r_(pre)=0.950,预测集均方根误差RMSEP=0.636°Brix。结果表明,采用柑橘不同部位的高光谱信息与对应糖度预测模型是可行的,花萼部位所建立模型的效果优于果梗、赤道部位,因此花萼部位可作为优先选择的光谱检测部位,这对于指导实际检测分级生产中柑橘的摆放位置具有重要意义;采用PLSR方法建立柑橘花萼、果梗和赤道部位的高光谱信息与平均糖度的预测模型时,花萼部位模型效果最好,预测集相关系数r_(pre)=0.913,预测集均方根误差RMSEP=0.621°Brix,建模效果相较于对应部位光谱与糖度模型差,因此,采用柑橘全部果肉的平均糖度与采集部位光谱建立糖度预测模型具有一定的局限性。 相似文献
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近红外无损检测寒富苹果可溶性固形物含量(TSS) 总被引:1,自引:1,他引:1
应用波长为643.26~985.11 nm的Purespect近红外透射光谱仪,分析了储藏时间对吸光度的影响。对不同储藏期寒富苹果的校正集样品进行了各自建模和共同建模,并研究了模型的差异性。结果表明:建立的共同模型预测结果较好,模型的相关系数(RC)为0.948,校正均方根误差(RMSEC)为0.468,预测均方根误差(RMSEP)为0.456,偏差(Bias)为0.027。该模型扩大了校正集样品化学成分含量的范围,提高了模型的适用范围,能满足实际生产要求。 相似文献
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Sara Ricardo-Rodrigues Marta Laranjo Ana Cristina Agulheiro-Santos 《Journal of the science of food and agriculture》2023,103(2):463-478
Sweet cherry (Prunus avium L.) is a highly valued fruit, whose quality can be evaluated using several objective methodologies, such as calibre, colour, texture, soluble solids content (SSC), titratable acidity (TA), as well as maturity indexes. Functional and nutritional compounds are also frequently determined, in response to consumer demand. The aim of the present review is to clarify and establish quality evaluation parameters and methodologies for the whole cherry supply chain, in order to promote easy and faithful communication among all stakeholders. The use of near-infrared spectroscopy (NIRS) as a non-destructive and expeditious method for assessing some quality parameters is discussed. In this review, the results of a wide survey to assess the most common methodologies for cherry quality evaluation, carried out among cherry researchers and producers within the framework of the COST Action FA1104 ‘Sustainable production of high-quality cherries for the European market’, are also reported. The standardisation of quality evaluation parameters is expected to contribute to the preservation and shelf-life extension of sweet cherries, and the valorisation of the whole supply chain. For future studies on sweet cherry, we put forward a proposal regarding both sample size and the tests chosen to evaluate each parameter. © 2022 Society of Chemical Industry. 相似文献
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柑橘浮皮果和可溶性固形物是评价柑橘品质的重要指标,在运动速度5个/s、积分时间100ms条件下,采集350~1 150nm范围内的柑橘光谱,探讨在同一条生产线上同时在线检测浮皮果与可溶性固形物的可行性,同时探索柑橘正常果,轻度、重度浮皮果的光谱响应特征,建立柑橘浮皮果与正常果的定性判别模型,并对比分析两种判别模型,同时还建立柑橘可溶性固形物的定量检测模型,最终实现了柑橘浮皮果与可溶性固形物同时在线检测。采用未参与建模的35个样品对模型在线分选的准确性进行评价,其中柑橘浮皮果都被正确的推入预设的浮皮果出口,正确判别率为100%,而可溶性固形物正确分级率为97%。研究可为柑橘在线分选提供分选策略与理论依据。 相似文献
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The relationships between the nondestructive visible and near-infrared (Vis-NIR) measurements and the internal quality indices of pear fruit were established, and the potential of Vis-NIR spectrometry technique was investigated for its ability to nondestructively measure soluble solids content (SSC) and firmness of intact pear fruit. Intact pear fruit were measured by diffuse reflectance Vis-NIR in 350–1800 nm range. In this study, calibration models relating Vis-NIR spectra to SSC and firmness were developed based on multi-linear regression (MLR), principal component regression (PCR) and partial least squares regression (PLSR) with respect to the logarithms of the reflectance reciprocal log(1/R), its first derivative D1 log(1/R) and second derivative D2 log(1/R). The best combination, based on the robust models and the prediction results, was PLSR method with respect to log(1/R) at equatorial position of pear fruit. The PLSR models for prediction samples resulted correlation coefficient (rp) of 0.912 and 0.854, and root mean standard error of prediction (RMSEP) of 0.662°Brix and 1.232 N for SSC and firmness, respectively. The results indicate that Vis-NIR spectrometry technique could provide an accurate, reliable and nondestructive method for assessing the internal quality indices of intact pear fruit. 相似文献
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Pavel A. Solovyev Carsten Fauhl-Hassek Janet Riedl Susanne Esslinger Luana Bontempo Federica Camin 《Comprehensive Reviews in Food Science and Food Safety》2021,20(2):2040-2062
Wine authentication is vital in identifying malpractice and fraud, and various physical and chemical analytical techniques have been employed for this purpose. Besides wet chemistry, these include chromatography, isotopic ratio mass spectrometry, optical spectroscopy, and nuclear magnetic resonance (NMR) spectroscopy, which have been applied in recent years in combination with chemometric approaches. For many years, 2H NMR spectroscopy was the method of choice and achieved official recognition in the detection of sugar addition to grape products. Recently, 1H NMR spectroscopy, a simpler and faster method (in terms of sample preparation), has gathered more and more attention in wine analysis, even if it still lacks official recognition. This technique makes targeted quantitative determination of wine ingredients and nontargeted detection of the metabolomic fingerprint of a wine sample possible. This review summarizes the possibilities and limitations of 1H NMR spectroscopy in analytical wine authentication, by reviewing its applications as reported in the literature. Examples of commercial and open-source solutions combining NMR spectroscopy and chemometrics are also examined herein, together with its opportunities of becoming an official method. 相似文献