不同挥发性物质对桃果实品质及抗氧化活性影响的多变量分析

采用单因素方差分析、主成分分析、相关性分析、偏最小二乘回归分析、通径分析5种数据分析方法考察1-甲基环丙烯(1-MCP)、二氧化氯、百里酚和乙醇处理对桃果实品质及抗氧化活性的作用效果。结果表明：乙醇处理可显著抑制常温贮藏4d后桃果实侵染性病害的发生,其他处理与空白对照无显著性差异;1- MCP 处理延缓了桃果皮b*值的升高,乙醇处理提高果皮L*值的同时降低了果皮a*值;与空白对照相比,乙醇、1-MCP及二氧化氯处理对总黄酮含量、总抗氧化能力、清除DPPH自由基能力、清除·OH能力4个指标的影响较为显著。结合相关性分析与回归分析可知,腐烂率仅与可溶性固形物含量(SSC)呈显著负相关;对果皮L*值、果皮a*值、果皮b*值的直接效应最为强烈的参数分别是总黄酮含量、清除DPPH自由基能力、SSC;总酚含量与清除DPPH自由基能力具有显著正相关性;总黄酮含量与总抗氧化能力、清除DPPH自由基及·OH能力也存在显著或极显著相关性效应。     

基于LF-NMR弛豫特性的煎炸油总极性化合物含量定量建模方法

将低场核磁共振（low field nuclear magnetic resonance,LF-NMR）分析技术应用于煎炸油脂总极性化合物（total polar compounds,TPC）含量的预测。采用柱层析方法测定油脂样品的TPC含量作为测定值,采集油脂样品的LF-NMR弛豫特性（峰起始时间T21、T22、T23相应的峰面积比例S21、S22、S23、单组分弛豫时间T2W）,分别利用向后筛选多元回归分析、主成分回归分析和偏最小二乘回归分析建立LF-NMR弛豫特性与TPC含量的回归方程,比较3 种模型的校正集和预测集的决定系数与均方根误差,最终确定最优模型为偏最小二乘回归模型。应用此模型预测预测集样品TPC含量,决定系数R2可达0.928,预测集均方根误差为0.568%,模型稳定。     

Rapid Fruit Extracts Antioxidant Capacity Determination by Fourier Transform Infrared Spectroscopy

ABSTRACT: The antioxidant content of fruits have made them a desirable component of the human diet. Several wet chemistry techniques, including the oxygen radical absorbance capacity (ORAC_FL) assay, have been reported for measuring the antioxidant activities of fruit. In this study, we investigated the use of Fourier transform infrared spectroscopy (FTIR) to measure fruit antioxidant activity. Flavonoid-rich extracts from 5 blueberry, 5 grape, and 6 blackberry genotypes were obtained by methanol-water-formic acid (60:37:3, v/v/v) solvent. The total antioxidant capacities of the fruit extracts were determined by the ORAC_FL assay, and the FTIR spectra of the fruit extracts were collected. Partial least squares (PLS) regressions with cross-validation was conducted on 128 spectra of extracts and their corresponding ORAC_FL values to obtain a calibration model for predicting the antioxidant activity of the extracts. Spectra from an additional 16 extracts were used as an external validation set for the model. A good calibration model ( R ²= 0.97) for antioxidant activity was obtained with satisfactory predictive ability (root mean standard error [RMSE] = 5.35) using the spectral region 2000/cm to 900/cm. Cross-validation procedures indicated good correlations ( R ²= 0.94) between ORAC_FL assay values and FTIR estimates. The ratio of the standard deviation of the data to the standard error of validation (RPD) values were above 5.0 for blueberry, grapes, and the combined extracts in the external validation set indicating that the calibration model was suitable for quantifying fruit extracts antioxidant activities. This study shows that an FTIR technique would be suitable for rapidly measuring fruit extract antioxidant activity.     

Multiproduct,Multicomponent and Multivariate Calibration: a Case Study by Using Vis-NIR Spectroscopy

Vitamin C and total acidity were determined in industrialized fruit nectar and soy juices through visible-near infrared (Vis-NIR) spectroscopy and multiproduct, multicomponent, and multivariate calibration, based on partial least squares (PLS2) regression. Since samples with different types, flavors, and sugar content (light or not) were together in the model construction, the samples present higher heterogeneity and it was necessary to optimize the calibration and validation sets by outlier elimination based on leverage and unmodelled residuals in spectral data. The model was developed and validated by the evaluation of the parameters of merit such as accuracy, analytical sensitivity, adjust, linearity, residual prediction deviation, limits of detection, and quantification. The results achieved indicates that the multiproduct, multicomponent, and multivariate calibration model developed from Vis-NIR spectroscopy and PLS2 regression can be used in the industrial routine analysis as an alternative to titration reference methods that are time- and reagent-consuming methods, making the methodology extremely attractive from the industrial point of view.     

Determination of Antioxidant Activity and Polyphenols Content in Chips by Raman and IR Spectroscopy

The application of vibrational spectroscopy for the determination of total polyphenols content, antioxidant activity, colour parameters, and fat level in chips originated from yellow-, red- and purple-fleshed potato varieties is reported. Raman, infrared (IR) and near-infrared (NIR) spectra of the laboratory-prepared chips were collected. Combining spectral data with the results of reference analyses, partial least squares regression models were built. To characterise and compare the elaborated models, the relative standard errors of prediction were calculated for calibration and validation sets. In the case of total phenolics quantification by Raman/IR/NIR techniques, these errors (%) amounted to 4.0/7.0/7.1 and 6.4/8.5/8.4 for calibration and validation samples, respectively, whereas they were 4.9/7.7/4.8 and 6.6/8.3/6.8 for antioxidant activity. The obtained results demonstrate that both infrared and Raman spectroscopy can effectively replace commonly used extraction methods. It follows that Raman spectroscopy has the highest potential to be adopted for the online potato-derived product analysis.     

近红外光谱定性定量检测牛肉汉堡饼中猪肉掺假

利用近红外光谱技术结合化学计量学方法,对不同肥肉占比的解冻牛肉汉堡饼中的猪肉掺假进行定性判别建模,并建立猪肉掺假比例的定量检测模型。结果表明：对不同掺假比例样品的判别,应用偏最小二乘判别分析方法效果优于主成分分析-支持向量机方法,最优模型校正集和验证集判别正确率均为100%。应用偏最小二乘方回归法定量检测不同肥瘦比解冻牛肉汉堡饼中的猪肉掺假比例,模型校正集和验证集的相关系数Rc和Rp、验证集均方根误差分别为0.968 9、0.861 1、7.221%。因此,应用近红外光谱技术可以实现对不同肥肉占比的解冻牛肉汉堡饼中的猪肉掺假进行定性判别和定量检测。     

Discrimination of citrus fruits using FT-IR fingerprinting by quantitative prediction of bioactive compounds

High throughput screening of citrus samples containing elevated concentrations of total carotenoids, flavonoids, and phenolic compounds was accomplished using ultraviolet–visible spectroscopy and Fourier transform infrared (FT-IR) spectroscopy, combined with multivariate analysis. Principal component analysis and partial least squares discriminant analysis using FT-IR spectra were able to differentiate seven citrus fruit groups into three distinct clusters corresponding to their taxonomic relationship. Quantitative prediction modeling of total carotenoids, flavonoids, and phenolic compounds in citrus fruit was established using a partial least squares regression algorithm from the FT-IR spectra. The regression coefficients (R ²) of predicted and estimated values of total carotenoids, flavonoids, and phenolic compounds were all 0.99. The results indicated that accurate quantitative predictions of total carotenoids, flavonoids, and phenolic compounds were possible from citrus fruit FT-IR spectra, and that the resulting quantitative prediction model might be useful as a rapid selection tool for citrus fruits containing elevated carotenoids, flavonoids, and phenolic compounds.     

Rapid Analysis of Glucose,Fructose, Sucrose,and Maltose in Honeys from Different Geographic Regions using Fourier Transform Infrared Spectroscopy and Multivariate Analysis

ABSTRACT: Quantitative analysis of glucose, fructose, sucrose, and maltose in different geographic origin honey samples in the world using the Fourier transform infrared (FTIR) spectroscopy and chemometrics such as partial least squares (PLS) and principal component regression was studied. The calibration series consisted of 45 standard mixtures, which were made up of glucose, fructose, sucrose, and maltose. There were distinct peak variations of all sugar mixtures in the spectral “fingerprint” region between 1500 and 800 cm⁻¹. The calibration model was successfully validated using 7 synthetic blend sets of sugars. The PLS 2nd-derivative model showed the highest degree of prediction accuracy with a highest R² value of 0.999. Along with the canonical variate analysis, the calibration model further validated by high-performance liquid chromatography measurements for commercial honey samples demonstrates that FTIR can qualitatively and quantitatively determine the presence of glucose, fructose, sucrose, and maltose in multiple regional honey samples.     

A sensometric approach to cod-quality measurement

The quality index method was used for describing the sensory quality of thawed whole cod and raw fillet and the quality of boiled fillet was assessed by profiling analysis. These data were compared to the water holding capacity of the minced cod by principal component analysis (PCA) and partial least squares regression. The sensory data and the water holding capacity were correlated to an extent that made possible the prediction of high and low values of water holding capacity. Multivariate methods were also used for extracting some information about the assessor variability. This was done by determining the ability of the assessors to predict the water holding capacity through partial least squares regression and by examining the distances between PCA-models of profiling data from the single assessors.     

Quantitative bioactive compounds assessment and their relative contribution to the antioxidant capacity of commercial orange juices

Dietary recommendations for healthy eating include the consumption of fruit juices whose health effects are ascribed, in part, to carotenoids, phenolic compounds and vitamin C. These bioactive compounds have been implicated in the reduction of degenerative human diseases, mainly due to their antioxidant potential. Orange juice is characterized by substantial accumulation (apart from ascorbic acid) of flavonoids and carotenoids. Commercial orange juice is the main human dietary source of antioxidant compounds in developed countries. The qualitative and quantitative determination of carotenoid, flavonoid and vitamin C content of Spanish commercial orange juices was achieved by high‐performance liquid chromatography. The health‐related properties of bioactive compounds contained in orange juice are based on their antioxidant activity. The antioxidant capacity of these juices was assessed by 2,2‐diphenyl‐1‐picrylhydrazyl stable radical scavenging and was compared with a freshly squeezed orange juice. In addition, the relative contribution of the different bioactive compounds to the antioxidant activity of orange juices was calculated. Total vitamin C was found to be the major contributor to the antioxidant potential of the orange juices studied, followed by flavonoid and carotenoid compounds. Ascorbic acid, total vitamin C and β‐cryptoxanthin content correlated positively with the free‐radical scavenging parameters. No significant differences, in terms of antioxidant capacity, were found between commercial traditional pasteurized orange juices and freshly squeezed orange juice. Copyright © 2003 Society of Chemical Industry     

Quantification of aspartame in commercial sweeteners by FT-Raman spectroscopy

Efficient methods are proposed herein for the quantification of aspartame in commercial sweeteners. These methods are based on a treatment of Raman data with partial least squares (PLS), principal component regression (PCR) and counter-propagation artificial neural networks (CP-ANN) methods. For the three chemometric techniques used, the relative standard errors of prediction (RSEP) calculated for calibration and validation data sets were on the order of 1.8–2.2%. Four commercial preparations containing between 17% and 36% of aspartame by weight were evaluated by applying the developed models. Concentrations found from the Raman data analysis agree perfectly with the results of the UV–Vis reference analysis, with the recoveries in the 98.7–100.8%, 98.6–101.1% and 97.8–102.2% ranges for the PLS, PCR and CP-ANN models, respectively. The proposed procedures can be used for routine quality control during the production of commercial aspartame sweeteners.     

Characterization of Conventional,Biodynamic, and Organic Purple Grape Juices by Chemical Markers,Antioxidant Capacity,and Instrumental Taste Profile

The objectives of this study were to characterize organic, biodynamic, and conventional purple grape juices (n = 31) produced in Europe based on instrumental taste profile, antioxidant activity, and some chemical markers and to propose a multivariate statistical model to analyze their quality and try to classify the samples from the 3 different crop systems. Results were subjected to ANOVA, correlation, and regression analysis, principal component analysis (PCA), hierarchical cluster analysis (HCA), soft independent modeling of class analogy (SIMCA), and partial least‐squares discriminant analysis (PLSDA). No statistical significant differences (P > 0.05) were observed among juices from the 3 crop systems. Using PCA and HCA, no clear separation among crop systems was observed, corroborating the ANOVA data. However, PCA showed that the producing region highly affects the chemical composition, electronic tongue parameters, and bioactivity of grape juices. In this sense, when organic and biodynamic were grouped as “nonconventional” juices, SIMCA model was able to discriminate 12 out of 13 organic/biodynamic juices and 17 out of 18 conventional juices, presenting an efficiency of 93.5%, while 11 out of 13 non‐conventional and 100% conventional grape juices were correctly classified using PLSDA. The use of electronic tongue and the determination of antioxidant properties and major phenolic compounds have shown to be a quick and accurate analytical approach to assess the quality of grape juices.     

PSO-LSSVM用于近红外光谱预测混合制浆材Klason木质素含量

为优化混合制浆材中Klason木质素含量的近红外分析模型,收集了5种常见制浆材的82个原木样品,将样品粉碎预处理后在便捷式近红外光谱仪上采集其近红外光谱信号,对原始光谱数据进行多元散射校正(MSC)预处理,利用粒子群寻优(PSO)算法对最小二乘支持向量机(LSSVM)算法中的参数进行优化,然后利用最优参数建立混合制浆材Klason木质素的LSSVM定量分析模型。将结果与偏最小二乘(PLS)和主成分降维后的BP神经网络(PCA-BPNN)算法进行比较。结果表明,PCA-BPNN和PSO-LSSVM模型均优于PLS模型,且PSO-LSSVM模型预测结果最优,预测结果的相关系数(Rv)最大为0.9857;预测标准差(RMSEP)为0.7498%,比PLS模型和PCA-BPNN模型分别降低了0.2767%和0.1455%;相对标准偏差(RPD)最大为5.6174,比PLS模型和PCA-BPNN模型分别提高了1.5144和0.9138;真实值与预测值间的绝对偏差(AD)范围最小,为0.0065%~1.8449%。     

近红外光谱技术快速测定鹅肉新鲜度

目的：应用近红外光谱技术快速检测鹅肉的新鲜度,评价指标包括总挥发性盐基氮和pH值。方法：采集完整冷鲜鹅肉的近红外光谱（950～1 650 nm）,光谱经多种校正预处理后,采用偏最小二乘法建立鹅肉新鲜度的定量预测数学模型。结果：对于这2 种指标均采用标准常态变量结合偏最小二乘法所建立模型的预测效果最好,总挥发性盐基氮和pH值定量校正数学模型的模型决定系数分别为0.727、0.991,内部交互验证均方根误差分别为3.666、0.028。用此模型对预测集20 个样品进行预测,预测值与实测值的相关系数分别达到0.976、0.705,预测值平均偏差分别为－0.240、－0.024,预测值和实测值之间没有显著性差异（P＞0.05）。结论：近红外光谱作为一种无损快速的检测方法,可用于评价鹅肉新鲜度。     

Fourier Transform Infrared Spectroscopy for Antioxidant Capacity Determination in Colored Glutinous Rice

The determination of total phenolic content and antioxidant capacity of 48 colored rice varieties and two white rice varieties from Thailand by Fourier transform infrared (FT-IR) spectroscopy (400–4,000 cm^?1) was performed to explore the possibility of using FT-IR as an effective alternative technique for such determination. The peak at 1,635 cm^?1 resulted from the ring C-C stretch of phenyl was clearly observed. The levels of phenolic content in rice samples as indicated with infrared spectrum were consistent with the results from chemical assays. Dark glutinous rice had the highest level of antioxidant capacity and phytochemicals followed by red rice, brown rice, and white rice. The hierarchical cluster analysis based on selected principal components from principal component analysis model was performed to produce dendrograms which discriminated rice varieties according to their color well. The partial least squares regression models were constructed, and validated models were used to predict total antioxidant capacity and total phenolic content of the rice varieties. Satisfactory precision of prediction was achieved. With technical advantages that FT-IR offers especially when large number of samples are to be analyzed, FT-IR spectral features with chemometrics are suggested to be applicable for quantification and prediction of antioxidant capacity and phenolic compound content of colored rice.     

多元校正分析在微量金属元素检测中的应用

对多元校正分析法在微量金属元素检测中的应用作一概述,内容涉及多元线性回归、主成分分析、偏最小二乘法、人工神经网络、小波分析等方法及上述方法的一些结合运用,并对今后的发展方向加以展望。     

Determination of total phenolic content and antioxidant capacity of onion (Allium cepa) and shallot (Allium oschaninii) using infrared spectroscopy

Total phenolic content (TPC) and total antioxidant capacity (TAC) of four onion varieties (red, white, yellow and sweet) and shallot from selected locations (Washington, Idaho, Oregon, Texas and Georgia) were determined using Fourier transform infrared (FT-IR) spectroscopy (4000–400 cm⁻¹). The Folin–Ciocalteu (F–C) assay was used to quantify TPC and three assays were used to determine TAC, including 2,2-diphenyl-picrylhydrazyl (DPPH) assay, Trolox equivalent antioxidant capacity (TEAC) assay and ferric reducing antioxidant power (FRAP) assay. Partial least squares regression (PLSR) with cross-validation (leave-one-out) was conducted on onion and shallot extracts (n = 200) and their corresponding F–C, DPPH, TEAC and FRAP values were employed to obtain four independent calibration models for predicting TPC and TAC for the extracts. Spectra from an extra 19 independent extracts were used as an external validation set for prediction. A correlation of r > 0.95 was obtained between FT-IR predicted and reference values (by F–C, DPPH, TEAC and FRAP assay) with standard errors of calibration (SEC) and standard errors of cross-validation (SECV) less than 2.85, 0.35 and 0.45 μmol Trolox/g FW of extracts for TEAC, FRAP and DPPH assay, respectively; and 0.36 mg gallic acid/g FW of extracts for the F–C assay. In addition, cluster analysis (principal component analysis (PCA)) and discriminant function analysis (DFA) could differentiate varieties of onions and shallot based upon infrared spectral features. Loading plots for the various chemometrics models indicated that hydroxyl and phenolic functional groups were most closely correlated with antioxidant capacity. The use of mid-infrared spectroscopy to predict the total antioxidant capacity of vegetables provides a rapid and precise alternative to traditional wet chemistry analysis.     

甘薯水分和还原糖协同向量NIR快速检测方法

利用近红外光谱技术建立新鲜甘薯水分和还原糖含量的预测模型,实现快速检测与分析,为甘薯品质分析和种质资源筛选提供便捷。选用不同品系甘薯样品146份,109份作为校正样品,37份作为验证样品。运用不同光谱预处理方法、协同区间偏最小二乘最优波长选择法以及主成分回归和偏最小二乘法建立甘薯水分和还原糖模型。结果显示,所建甘薯水分(还原糖)最优模型的决定系数、预测均方根误差和标准差比率分别为0.974(0.885),1.154(0.270)和6.334(3.148)。表明2种模型具有较好的检测性能,近红外光谱模型的预测值与其相应的化学值有较好的相关性,适用于大批量甘薯选育时水分和还原糖含量的快速检测。     

Rapid Determination of Antioxidant Compounds and Antioxidant Activity of Sudanese Karkade (<Emphasis Type="Italic">Hibiscus sabdariffa</Emphasis> L.) Using Near Infrared Spectroscopy

The extraction conditions applied in destructive analysis of Hibiscus sabdariffa L. (Hs) matrices before the measurement of antioxidant compounds may reduce their activities during isolation and purification due to decomposition. Hence, near infrared spectroscopic system was applied to determine these compounds. The calibration models developed by using partial least squares regression (PLSR) with 48 Hs samples and 24 unknown samples were used to confirm the robustness of the developed model. The results of calibration models effectively allowed the determination of the concentrations of total phenol content (TPC), total flavonoid content (TFC), total antioxidant content (TAC), ferric reducing antioxidant power (FRAP), and 1,1-diphenyl-2-picrylhydrazyl (DPPH) with high correlation coefficients (0.85–0.91) and small standard error of cross-validation (RMSECV) ranged from 0.08 to 0.33. The prediction capacity (RPD) for TPC, TFC, TAC, FRAP, and DPPH ranged from 3.30 to 8.25, thus demonstrating that the near infrared spectroscopic (NIRS) equations developed were applicable to unknown samples. This study demonstrates that NIRS can be considered as a fast tool for the nondestructive determination of antioxidant compounds (phenolics and flavonoids) and antioxidant activity of the Hs.     

基于近红外光谱对牛奶中掺杂尿素的判别分析

采集40个合格的纯牛奶样品,并配制含有尿素为1～20g/L的40个牛奶样品,研究掺杂尿素牛奶的二维相关近红外特性,在此基础上选择波数4200～4800cm-1为建模区间,采用偏最小二乘法建立定性、定量模型。结果指出通过判别偏最小二乘法可以实现纯牛奶及掺杂尿素牛奶的定性鉴别,判别正确率为100%;掺杂牛奶校正集相关系数R为0.999,交叉验证均方差为0.242,对未知样品集预测相关系数R达到0.999,预测标准偏差为0.57,这表明所建模型具有较好的预测效果。