近红外漫反射无损检测梨果可溶性固形物的研究

应用近红外漫反射无损检测梨果可溶性固形物。通过自行设计的NIR光谱系统测定了240个梨果样品的SSC。180个梨果样品用来建模,其余60个用来验证模型的性能。采集完整梨果的近红外漫反射光谱（350～1 800 nm）,光谱经移动窗口平滑处理、一阶微分和二阶微分预处理后,再分别采用多元线性回归、主成分回归和偏最小二乘法,建立梨果可溶性固形物的定量预测数学模型。结果表明：采用一阶微分结合偏最小二乘法所建模型的预测效果较好,可溶性固形物定量预测数学模型的相关系数为0.928 5,均方根误差为0.436 4。近红外漫反射光谱作为一种无损的检测方法,可用于评价梨果的可溶性固形物。     

蓝莓可溶性固形物、总酸近红外无损检测模型的建立

建立了近红外漫反射光谱技术检测蓝莓可溶性固形物、总酸的数学模型,并对其进行评价。实验比较了在近红外全波长范围400~2 500 nm内,不同的光谱预处理方法对模型的影响。结果表明利用偏最小二乘法(PLS)、一阶导数(D1Log(1/R))和加权多元离散校正处理(WMSC)建立的可溶性固形物含量(SSC)定标模型预测结果相对较好。其预测相关系数Rp2为0.8518,预测标准误差(SEP)为0.351,相对分析误差(RPD)为2.05。总酸的最佳模型处理条件为改进偏最小二乘法(MPLS)、二阶导数(D2Log(1/R))和WMSC,其Rp2为0.8776,SEP为0.042,RPD为2.10。由此确定近红外漫反射技术可用于蓝莓可溶性固形物、总酸含量的快速无损检测。     

近红外漫反射光谱预测久保桃查溶性固形物初步实验研究

以150个久保桃果实为标准样品,20个果实为验证样品,研究近红外光谱漫反射技术预测久保桃内部可溶性固形物含量的方法.实验结果表明,一阶微分处理的光谱和化学值采用改进偏最小二乘法建立的预测模型具有较高的相关性,预测久保桃样品的可溶性固形物含量范围为10.2～13.2°Brix,其平均值为12.0°Brix,实测值与预测值偏差(bias)为-0.381,标准预测误差(SEP)为0.427,相关系数为0.701.预测结果表明,采用600～1848nm近红外漫反射光谱无损检测久保桃可溶性固形物是可行的.     

䥺Symbol`@@基于近红外光谱漫透射技术的苹果可溶性固形物含量在线检测

为研究苹果的内部品质,提高检测的速度和稳定性,将近红外光谱漫透射技术应用于在线检测研究,并采取偏最小二乘回归(PLSR)算法结合不同光谱预处理方法建立苹果内部的可溶性固形物含量(SSC)的定量模型。结果表明:采用一阶微分结合多元散射校正(MSC)预处理后的模型最稳定,校正集和预测集的标准差分别为0.17和0.39,校正集的相关系数也达到0.988 3。试验结果说明近红外光谱漫透射技术能够快速、无损地检测出苹果的可溶性固形物含量。     

基于近红外光谱漫透射技术的苹果可溶性固形物含量在线检测

为研究苹果的内部品质,提高检测的速度和稳定性,将近红外光谱漫透射技术应用于在线检测研究,并采取偏最小二乘回归(PLSR)算法结合不同光谱预处理方法建立苹果内部的可溶性固形物含量(SSC)的定量模型。结果表明:采用一阶微分结合多元散射校正(MSC)预处理后的模型最稳定,校正集和预测集的标准差分别为0.17和0.39,校正集的相关系数也达到0.988 3。试验结果说明近红外光谱漫透射技术能够快速、无损地检测出苹果的可溶性固形物含量。     

冰糖橙可溶性固形物和pH值近红外光谱检测

研究利用近红外漫反射无损检测冰糖橙可溶性固形物含量和p H值的方法。以45个麻阳冰糖橙为标准样本,采集350 nm~1 800 nm范围的近红外光光谱,光谱采用9点滑动窗口平滑处理、一阶微分和多元散射校正分别进行预处理,然后采用偏最小二乘算法(PLS)、主成分回归算法(PCR)、多元线性回归算法(MLR)3种数学校正方法分别建立预测模型。经比较,采用一阶微分的PLS模型预测性能最好。     

近红外光谱检测猕猴桃可溶性固形物和pH

研究了利用近红外漫反射无损检测海沃德猕猴桃可溶性固形物含量和pH的方法。以45个湘西海沃德猕猴桃为标准样本,采集1 000~1 800 nm范围的近红外光光谱,光谱采用9点滑动窗口平滑处理、一阶微分和多元散射校正分别进行预处理,然后采用偏最小二乘算法(PLS)、主成分回归算法(PCR)和多元线性回归算法(MLR)分别建立预测模型。经比较,采用一阶微分的PLS模型预测性能最好。     

基于近红外光谱技术检测蓝莓可溶性固形物含量

采用近红外漫反射光谱技术对辽宁丹东蓝莓基地的六个蓝莓品种(埃利奥特、达柔、爱国者、北蓝、杜克、蓝丰)进行光谱分析,快速无损测定蓝莓可溶性固形物含量,利用一阶导数进行光谱预处理,主成分分析(PCA)和偏最小二乘法(PLS)建立蓝莓可溶性固形物预测模型。结果表明,所建模型的相关系数(Corr.Coeff.)为0.91518、校正集标准偏差(RMSEC)为0.801、预测集标准偏差(RMSEP)为1.06。该方法快速、准确、无损,能准确地预测蓝莓中可溶性固形物含量。     

磨盘柿可溶性固形物的可见/近红外漫反射光谱无损检测

研究可见/近红外漫反射光谱技术快速检测磨盘柿可溶性固形物的方法。在可见/近红外光谱区域(570～1848nm),对比分析不同数学建模算法、不同导数处理方法和不同散射及标准化处理的果实可溶性固形物定标模型。结果表明：应用改进偏最小二乘回归算法、一阶导处理和去散射处理所建果实可溶性固形物定标模型的预测性能较优,其定标交互验证相关系数(Rcv)和预测相关系数(Rp2)分别为0.8076和0.8085,定标交互验证均方根误差(RMSECV)和预测均方根误差(RMSEP)分别为0.4546°Brix和0.4482°Brix。这表明,可见/近红外漫反射技术对磨盘柿可溶性固形物的快速无损检测具有可行性。     

基于Android平台微型近红外光谱仪的开发与应用

在Android平台上对C11708MA微型近红外光谱仪进行系统开发,实现光谱仪控制、样品指标测量、调用模型文件并显示样品可溶性固形物的预测结果等功能。利用近红外漫反射无损检测技术对镇江句容果园水蜜桃样品的可溶性固形物含量进行相关研究,运用化学计量学方法建立了水蜜桃可溶性固形物含量的近红外模型,并对模型的性能进行了评价。结果表明,采用偏最小二乘法(PLS)建立模型,光谱预处理的最佳条件为:移动窗口平滑(MAF)和Savitzky-Golay一阶导数。所建模型的校正相关系数(R_c)和预测相关系数(R_p)分别为0.931 1和0.880 2,校正标准偏差(RMSEC)和预测标准偏差(RMSEP)分别为0.441 0和0.531 0。开发的App程序运行稳定,预测结果准确,可应用于水蜜桃内部品质可溶性固形物含量的快速、无损、活体检测。     

四个品种赣南脐橙果皮精油提取及挥发性成分分析

以四个品种赣南脐橙(纽荷尔、朋娜、华盛顿、奈维林娜)为原料,通过检测其可溶性糖、可滴定酸、可溶性固形物含量与固酸比,确定了四个品种果实的成熟度,并利用水蒸气蒸馏法提取果皮精油,采用气相色谱-质谱联用仪对挥发性成分进行研究,比较四个品种在精油得率和挥发性成分及相对含量上的差异。结果表明:四个品种脐橙的固酸比均大于或等于20.0,均已达到成熟状态;各脐橙果皮精油得率为:纽荷尔(1.05%)＞奈维林娜(0.94%)＞华盛顿(0.91%)＞朋娜(0.75%);样品中共鉴定出21种挥发性成分,包括13种烯烃类、3种醇类和5种醛类,烯烃类化合物是其主要挥发性成分。其中,纽荷尔脐橙果皮中鉴定出11种,d-柠檬烯(92.962%)、月桂烯(2.851%)和罗勒烯(1.039%)为其主要香气成分;朋娜脐橙果皮中鉴定出13种,d-柠檬烯(92.328%)、月桂烯(2.700%)和3-亚甲基-6-(1-甲基乙基)环己烯(1.020%)为其主要香气成分;华盛顿脐橙果皮中鉴定出14种,d-柠檬烯(92.322%)和β-蒎烯(2.653%)为其主要香气成分;奈维林娜脐橙果皮中鉴定出11种,月桂烯(47.036%)、2-蒎烯(15.313%)、3-亚甲基-6-(1-甲基乙基)环己烯(11.593%)为其主要香气成分。本研究结果为赣南脐橙品种精油的开发利用提供参考。     

黄龙病对纽荷尔脐橙品质的影响

以纽荷尔脐橙为原料,通过对外观品质、理化品质、活性成分和精油成分的比较来研究黄龙病对脐橙果实品质的影响。结果表明：脐橙感染黄龙病后,果实质量降低,果皮难以转色;以可溶性糖、可溶性固形物质量分数为代表的果实成熟度指标均明显降低,果实食用品质下降明显;果皮、果肉中橙皮苷的含量均大幅度升高,精油挥发性成分的种类增加90.90%。脐橙果感染黄龙病后,食用品质严重下降,难以达到鲜食的要求;然而其橙皮苷、纤维、精油等功效成分的含量增多,如考虑将其用于副产物的提取,将利于资源的合理利用。本研究旨在为感染黄龙病脐橙果的综合利用提供理论参考。     

Application of NIRS for Nondestructive Measurement of Quality Parameters in Intact Oranges During On-Tree Ripening and at Harvest

External and internal quality parameters were measured in oranges (Citrus sinensis (L.) Osbeck cv. “Powell Summer Navel”) during on-tree ripening and at harvest using near-infrared reflectance (NIR) spectroscopy. The performance of two NIRS instruments was evaluated: a handheld microelectromechanical system spectrophotometer working in the 1,600- to 2,400-nm range, and a diode array visible–NIR spectrophotometer working in the 380- to 1,700-nm range. Spectra and analytical data were used to construct MPLS prediction models for quantifying weight, size (equatorial and axial diameters), color (L*, a*, b*, C*, h*, and color index), texture (firmness and maximum penetration force), yield (pericarp thickness, juice weight, and juice content), and chemical parameters (soluble solids content, pH, titratable acidity, and maturity index). Both instruments yielded promising results for on-tree and at-harvest quality measurements, but models constructed using the diode array instrument provided greater predictive capacity, particularly for fruit size (equatorial and axial diameters) and total soluble solids content. Subsequent evaluation of the LOCAL algorithm revealed that it increased the predictive capacity of models constructed for all the main parameters tested. These results confirm that noninvasive NIRS technology can be used to simultaneously evaluate external and internal quality parameters in intact oranges both during on-tree ripening and at harvest, thus making it easier for farmers to monitor the ripening process and also to optimize harvest timing in order to meet the demands of the citrus-fruit industry.     

5种市售脐橙果实香气成分的主成分分析

研究5种市售脐橙的香气成分,并探索将脐橙香气成分作为风味评价指标的可能性。采用固相微萃取和气相色谱-质谱联用技术测定5种市售脐橙果实的香气成分,并用主成分分析法对脐橙果实的香气成分进行分析。结果表明：5种市售脐橙的香气成分存在较大差异,从中检出65种香气成分,主要是单萜、倍半萜、醛类、酮类、醇类和酯类,第一主成分、第二主成分分别指向单萜、烯萜类氧化衍生物。这些香气成分的差异,形成脐橙各自的风味特征,脐橙香气成分的主成分分析可以作为脐橙香气品质潜在的评价方法。     

Quality evaluation of frozen guava and yellow passion fruit pulps by NIR spectroscopy and chemometrics

The present study investigated the application of near infrared spectroscopy as a green, quick, and efficient alternative to analytical methods currently used to evaluate the quality (moisture, total sugars, acidity, soluble solids, pH and ascorbic acid) of frozen guava and passion fruit pulps. Fifty samples were analyzed by near infrared spectroscopy (NIR) and reference methods. Partial least square regression (PLSR) was used to develop calibration models to relate the NIR spectra and the reference values. Reference methods indicated adulteration by water addition in 58% of guava pulp samples and 44% of yellow passion fruit pulp samples. The PLS models produced lower values of root mean squares error of calibration (RMSEC), root mean squares error of prediction (RMSEP), and coefficient of determination above 0.7. Moisture and total sugars presented the best calibration models (RMSEP of 0.240 and 0.269, respectively, for guava pulp; RMSEP of 0.401 and 0.413, respectively, for passion fruit pulp) which enables the application of these models to determine adulteration in guava and yellow passion fruit pulp by water or sugar addition. The models constructed for calibration of quality parameters of frozen fruit pulps in this study indicate that NIR spectroscopy coupled with the multivariate calibration technique could be applied to determine the quality of guava and yellow passion fruit pulp.     

Nondestructive estimation of maturity and textural properties on tomato ‘Momotaro’ by near infrared spectroscopy

Near infrared spectroscopy offers the possibility to classify and predict the internal quality of fruits and vegetables. The objective of this study was to evaluate the ability of near infrared spectroscopy to classify the maturity level and to predict textural properties of tomatoes variety “Momotaro”. Principal component analysis (PCA) and Soft independent modeling of class analogy (SIMCA) were used to distinguish among different maturities (mature green, pink and red). Partial least squares (PLS) regression was used to estimate textural properties, alcohol insoluble solids and soluble solids content of the tomatoes. The PCA calibration model with mean normalization pretreatment spectra of mature green tomatoes, gave the highest distinguishability (96.85%). It could classify 100.00% of red and pink tomatoes. The SIMCA model could not give better accuracy in maturity classification than individual PCA models. Among the textural parameters measured, the bioyield force from the puncture test with the near infrared (NIR) spectra (between 1100 and 1800 nm) pretreated by multiplicative scatter correction (MSC) had the highest correlation coefficient between NIR predicted and reference values (r = 0.95) and lowest standard error of prediction (SEP = 0.35 N) and bias of 0.19 N. The ratio of standard deviation of reference data of prediction set to standard error of prediction (RPD) was 2.71. In the case of Momotaro tomato, NIR spectroscopy by using PLS regression could not predict alcohol insoluble solids in fresh weight accurately but could predict soluble solids content well with r of 0.80, SEP of 0.210 %Brix and bias of 0.022 %Brix.     

一种基于近红外光谱快速鉴别染色橙的新方法

本文应用近红外光谱仪(NIRS)测定染色橙样品的光谱数据,采用多种方式对光谱数据进行预处理,用主成分分析法(PCA)对不同染色橙样品进行聚类分析并获得染色橙的近红外光谱数据的主成分,在此基础上建立了偏最小二乘(PLS)回归模型,并根据均方根校准误差(RMSEC)和相关系数(R2)对模型性能进行评价。结果表明,主成分分析可以快速鉴别染色橙样品,模型识别率达到94%。将主成分分析(PCA)与偏最小二乘(PLS)相结合建立的回归模型,均方根校准误差(RMSEC)为0.26,决定系数R2为0.96,模型效果较好。表明利用近红外光谱鉴别染色橙是可行的,这为染色橙的鉴别提供了一种快速无损的新方法。     

Improvement of Near-Infrared Spectral Calibration Models for Brix Prediction in ‘Gannan’ Navel Oranges by a Portable Near-Infrared Device

A portable near-infrared (NIR) device was developed to nondestructively predict Brix value in intact ‘Gannan’ navel oranges. This research focused on developing calibration models which were less disturbed by the challenges of portable applications. The spectra of 150 samples were collected in the wavelength range of 820–950 nm. Wavelet transformed (WT) was applied to compress the raw data for improving the optimization efficiency. Classical linear partial least squares regression and nonlinear least squares support vector regression (LSSVR) were applied to building calibration models. By comparison, both prediction precision and optimization efficiency of the compressed regression models were improved. The LSSVR models outperformed the PLS models with higher accuracy and lower error. LSSVR combined with WT compression (WT–LSSVR) produced the best correlation coefficient value (r) and the root mean squared error of prediction of 0.918 and 0.321 ^oBrix. Based on these results, WT–LSSVR is to be a promising method to improve precision and optimization efficiency of NIR spectral calibration models for Brix prediction in ‘Gannan’ navel oranges by the portable near-infrared device.     

Effect of canning and storage on the chemical composition and organoleptic quality of juices of different varieties of oranges grown in Lebanon

Juice from five different varieties of oranges grown in Lebanon was canned according to commercial practices and stored at room temperature. At weekly intervals for seven weeks, chemical analyses for ascorbic acid, total acidity, total soluble solids, nitrogen, ash, total lipids, total solids, essential oils and flavonoids were performed on each sample. The fresh juice from the Blood and Washington Navel varieties compared favourably in chemical composition with a concentrated frozen product from the U.S.A.; the juice from Blood withstood canning and storage better than all other varieties tested. In all samples, there was a significant decrease in the levels of ascorbic acid and of essential oils during storage. Statistical analysis of organoleptic evaluations showed that, in general, blends of two or three different varieties were preferred to the juice from a single variety.     

Change in Rind, Flesh, and Juice Color of Blood Oranges Stored in Air Supplemented with Ethylene or in Oxygen-Enriched Atmospheres

Ruby, Tarocco, and Sanguinello blood oranges were stored 4 wk at 15°C in flowing air, 20 ppm ethylene in air, 40% O₂+ 60% N₂, or 80% O₂+ 20% N₂, followed by storage in air. Ethylene caused rind color of Ruby and Tarocco oranges to become deeper orange while 80% O₂ caused rind of Ruby and Sanguinello oranges to be paler orange than when stored in other atmospheres. Ethylene deepened red color of the flesh and juice of Ruby and Tarocco oranges, but high O₂ more intensely deepened the red color of flesh and juice of all three cultivars. Total soluble solids content, total acidity, or pH of the juice was not affected. Fruit stored in the ethylene atmosphere developed off-flavor.