Policosanol content and composition in perilla seeds

Policosanols, long-chain alcohols, have many beneficial physiological activities. Contents and compositions in perilla seeds (Perilla frutescens) produced in Korea and China were determined. Waxy materials were extracted from perilla seeds using hot hexane. Yield of the waxy materials from perilla seeds was 72.1 mg/100 g of dry weight. Contents and compositions of the waxy materials and policosanols were identified and quantified by TLC, HPLC, and GC. Major components of the waxy materials from Korean and Chinese perilla seeds were policosanols (25.5 and 34.8%, respectively), hydrocarbons (18.8 and 10.5%), wax esters, steryl esters and aldehydes (53.0 and 49.8%), acids (1.7 and 2.1%), and triacylglycerols (1.0 and 2.9%), determined by HPLC. For comparison, waxy materials of sesame seeds were also analyzed. Yield of the waxy materials from sesame seeds were 8.6 mg/100 g. Less than 5% policosanols were detected in the waxy materials extracted from sesame seeds produced in Korea and China. Wax esters or steryl esters accounted for 93-95% of the sesame waxy materials. Policosanols in the perilla seeds were composed of 67-68% octacosanol, 16-17% hexacosanol, 6-9% triacontanol, and others.     

近红外光谱分析法测定菜籽油中芥酸的含量

采用多通道PDA型近红外光谱仪,应用偏最小二乘法建立了菜籽油中芥酸含量与近红外透射光谱的校正模型,讨论多项式求导及平滑的窗口宽度和相关系数法筛选有效波长对校正模型的影响,并对10个预测集样品利用预测相关系数R_p和预测均方根误差RMSEP指标进行了预测精度分析,结果发现：在使用全谱数据进行偏最小二乘回归建模时,一阶7点求导及平滑的预处理方法结果最佳,此时建模效果为：R_p=0.739,RMSEP=1.659;在此基础上通过相关系数法筛选波长后的建模效果为：R_p=0.958,RMSEP=0.963。后者R_p提高29%,RMSEP减少42%。由此可得出多项式求导及平滑法和相关系数法相结合对校正模型稳健性,预测精度都有较大提高的结论。研究证明：多通道近红外光谱仪快速测测菜籽油中芥酸含量的方法是可行的。     

Nondestructive determination of total soluble solid content and firmness in plums using near-infrared reflectance spectroscopy

The fruit industry requires rapid, economical, and nondestructive methods for classifying fruit by internal quality, which can be built into the processing line. Total soluble solid content and firmness are the two indicators of plum internal quality that most affect consumer acceptance. These parameters are routinely evaluated using methods which involve destruction of the fruit; as a result, only control batches can be analyzed. The development of nondestructive analytical methods would enable the quality control of individual fruits. Near-IR spectroscopy (NIRS) was used to assess total soluble solid content (SSC, degrees Brix) and firmness (N) in intact plums. A total of 720 plums (Prunus salicina L. cv. 'African Pride', 'Black Diamond', 'Fortune', 'Laetitia', 'Larry Anne', 'Late Royal', 'Prime Time', 'Sapphire', and 'Songold') were used to obtain calibration models based on reference data and near-IR spectral data. Standard errors of cross-validation (SECV) and coefficients of determination for cross-validation (r(2)) were (0.77 degrees Brix; 0.83) for total soluble solids content and (2.54 N; 0.52) for firmness. Results suggest that NIRS technology enables fruit to be classified in terms of total soluble solid content and firmness, thus allowing increased sampling of each production batch and ensuring a given quality with greater precision and accuracy.     

Nondestructive determination of lignans and lignan glycosides in sesame seeds by near infrared reflectance spectroscopy

Sesame (Sesamum indicum L.) contains abundant lignans including lipid-soluble lignans (sesamin and sesamolin) and water-soluble lignan glycosides (sesaminol triglucoside and sesaminol diglucoside) related to antioxidative activity. In this study, near infrared reflectance spectroscopy (NIRS) was used to develop a rapid and nondestructive method for the determination of lignan contents on intact sesame seeds. Ninety-three intact seeds were scanned in the reflectance mode of a scanning monochromator. This scanning procedure did not require the pulverization of samples, allowing each analysis to be completed within minutes. Reference values for lignan contents were obtained by high-performance liquid chromatography analysis. Calibration equations for lignans (sesamin and sesamolin) and lignan glycosides (sesaminol triglucoside and sesaminol diglucoside) contents were developed using modified partial least squares regression with internal cross-validation (n = 63). The equations obtained had low standard errors of cross-validation and moderate R2 (coefficient of determination in calibration). The prediction of an external validation set (n = 30) showed significant correlation between reference values and NIRS predicted values based on the SEP (standard error of prediction), bias, and r2 (coefficient of determination in prediction). The models developed in this study had relatively higher values (more than 2.0) of SD/SEP(C) for all lignans and lignan glycosides except for sesaminol diglucoside, which had a minor amount, indicating good correlation between the reference and the NIRS estimate. The results showed that NIRS, a nondestructive screening method, could be used to rapidly determine lignan and lignan glycoside contents in the breeding programs for high quality sesame.     

可见/近红外光谱结合遗传算法无损检测牛肉pH值

为了实现牛肉在整个货架期内(4℃环境)pH值的无损快速检测,该文采用可见/近红外光谱技术并结合遗传算法(GA,genetic algorithm),搭建了可见/近红外光谱检测系统,采集储藏在4℃下1～18d的120个牛肉样品400～1700nm范围的光谱,用不同预处理方法处理,并分别建立全波段光谱和经过遗传算法提取有效光谱的预测牛肉pH值的多元线性回归(MLR,multiple linear regression)模型、偏最小二乘回归(PLSR,partial least-squares regression)模型和最小二乘支持向量机(LS-SVM,least square-support vector machine)模型。结果表明,多元散射校正(MSC,multiplicatives catter correction)结合Savitzky-Golay(SG)平滑为最佳预处理方法,遗传算法提取光谱后所建模型的预测精度均高于全波段光谱所建模型,其中LS-SVM为最佳预测模型,其预测相关系数和标准差分别为0.935和0.111,相比全波段LS-SVM模型预测,精度得到了提高。研究表明可见/近红外光谱技术结合遗传算法所建LS-SVM预测模型能够实现4℃下牛肉整个货架期内pH值的无损快速检测。该研究为进一步开发实用的牛肉pH值无损快速检测设备提供依据。     

Assessment of oil content and fatty acid composition variability in two economically important Hibiscus species

The Hibiscus genus encompasses more than 300 species, but kenaf (Hibiscus cannabinus L.) and roselle (Hibiscus sabdariffa L.) are the two most economically important species within the genus. Seeds from these two Hibiscus species contain a relatively high amount of oil with two unusual fatty acids: dihydrosterculic and vernolic acids. The fatty acid composition in the oil can directly affect oil quality and its utilization. However, the variability in oil content and fatty acid composition for these two species is unclear. For these two species, 329 available accessions were acquired from the USDA germplasm collection. Their oil content and fatty acid composition were determined by nuclear magnetic resonance (NMR) and gas chromatography (GC), respectively. Using NMR and GC analyses, we found that Hibiscus seeds on average contained 18% oil and seed oil was composed of six major fatty acids (each >1%) and seven minor fatty acids (each <1%). Hibiscus cannabinus seeds contained significantly higher amounts of oil (18.14%), palmitic (20.75%), oleic (28.91%), vernolic acids (VA, 4.16%), and significantly lower amounts of stearic (3.96%), linoleic (39.49%), and dihydrosterculic acids (DHSA, 1.08%) than H. sabdariffa seeds (17.35%, 18.52%, 25.16%, 3.52%, 4.31%, 44.72%, and 1.57%, respectively). For edible oils, a higher oleic/linoleic (O/L) ratio and lower level of DHSA are preferred, and for industrial oils a high level of VA is preferred. Our results indicate that seeds from H. cannabinus may be of higher quality than H. sabdariffa seeds for these reasons. Significant variability in oil content and major fatty acids was also detected within both species. The variability in oil content and fatty acid composition revealed from this study will be useful for exploring seed utilization and developing new cultivars in these Hibiscus species.     

基于近红外分析技术检测大豆脂肪酸含量的研究

为探索近红外光谱技术在大豆脂肪酸测试中的应用,寻找一种快速的检测方法。以黑龙江省各地的25份大豆品种为材料,采用Perten8620型近红外光谱仪对搜集到的样品进行扫描并得到光谱数据,采用多元线性回归(MLR)和偏最小二乘法(PLS)对试验数据进行了多元统计分析。结果表明：在1700～2300 nm范围内检测大豆脂肪酸含量是可靠的,并且PLS模型的性能优于MLR模型。该文还对近红外仪中的滤光片组合作了初步探讨,表明不同的滤光片组合对测量精度有一定影响。     

Genotypic variation in fatty acid content of blackcurrant seeds.

The fatty acid composition and total fatty acid content of seeds from 36 blackcurrant genotypes developed at the Scottish Crop Research Institute were examined. A rapid small-scale procedure, involving homogenization of seeds in toluene followed by sodium methoxide transesterification and gas chromatography, was used. There was considerable variation between genotypes. The gamma-linolenic acid content generally varied from 11 to 19% of the total fatty acids, but three genotypes had higher values of 22-24%, levels previously not reported for blackcurrant seed and similar to those for borage seed. Other nutritionally important fatty acids, stearidonic acid and alpha-linolenic acid, varied from 2 to 4% and 10-19%, respectively. The mean total fatty acid contents ranged from 14 to 23% of the seed, but repeatability was poor. The results are discussed. Blackcurrant seeds are mainly byproducts from juice production, and the study shows the potential for developing blackcurrant genotypes with optimal added value.     

Rapid determination of the main organic acid composition of raw Japanese apricot fruit juices using near-infrared spectroscopy

The potential of near-infrared (NIR) spectroscopy to rapidly determine citric and malic acid contents of raw Japanese apricot (Japanese "ume", also known as the Japanese plum) fruit juice was investigated. In total, 314 raw juice samples with different organic acid compositions were collected over a long growth period, and spectra (1100-1850 nm) of these samples were acquired using an NIR spectrophotometer with a 1-mm path length. Calibrations were performed using a partial least-squares regression method based on a calibration sample set (211 samples), while validations were performed based on a validation sample set (103 samples). The results revealed good agreement between NIR spectroscopy and capillary electrophoresis, including the correlation coefficient (r2), standard error of prediction (SEP), and bias; no statistically (p = 0.05) significant differences were found for these parameters. Moreover, standard deviation ratios of reference data in the validation sample set to the SEP were higher than 3, indicating that NIR spectroscopy may represent an acceptable method for quantitative evaluation of citric and malic acids in raw Japanese apricot fruit juice.     

Quantification of fatty acids in forages by near-infrared reflectance spectroscopy

Near-infrared reflectance spectroscopy (NIRS) was evaluated as a possible alternative to gas chromatography (GC) for the quantitative analysis of fatty acids in forages. Herbage samples from 11 greenhouse-grown forage species (grasses, legumes, and forbs) were collected at three stages of growth. Samples were freeze-dried, ground, and analyzed by GC and NIRS techniques. Half of the 195 samples were used to develop an NIRS calibration file for each of eight fatty acids, with the remaining half used as a validation data set. Spectral data, collected over a wavelength range of 1100-2498 nm, were regressed against GC data to develop calibration equations for lauric (C12:0), myristic (C14:0), palmitic (C16:0), stearic (C18:0), palmitoleic (C16:1), oleic (C18:1), linoleic (C18:2), and alpha-linolenic (C18:3) acids. Calibration equations had high coefficients of determination for calibration (0.93-0.99) and cross-validation (0.89-0.98), and standard errors of calibration and cross-validation were < 20% of the respective means. Simple linear regressions of NIRS results against GC data for the validation data set had r2 values ranging from 0.86 to 0.97. Regression slopes for C12:0, C14:0, C16:0, C18:0, C16:1, C18:2, and C18:3 were not significantly different (P = 0.05) from 1.0. The regression slope for C18:1 was 1.1. The ratio of standard error of prediction to standard deviation was > 3.0 for all fatty acids except C12:0 (2.6) and C14:0 (2.9). Validation statistics indicate that NIRS has high prediction ability for fatty acids in forages. Calibration equations developed using data for all plant materials accurately predicted concentrations of C16:0, C18:2, and C18:3 in individual plant species. Accuracy of prediction was less, but acceptable, for fatty acids (C12:0, C14:0, C18:0, C16:1, and C18:1) that were less prevalent.     

Analysis of fiber content in flax stems by near-infrared spectroscopy

The conventional means of measuring the fiber content of flax is time-consuming and laborious, and the results obtained vary with the analysis technique used. The plant tissues must first be "retted", a process by which the fibers are separated from the rest of the stem, either by indigenous organisms in the soil when the stems are left in the field or by water (anerobic bacteria) or enzymatic retting. The fiber content is then determined by mechanical or manual separation. In this study, fiber content of flax stems was measured rapidly and objectively by near-infrared spectroscopy (NIRS) using whole pieces of stem in a large cell, in reflectance mode. Compared to the conventional method, the standard error of performance of the NIRS method was between 0.96 and 1.45% (dry matter basis), depending on the model and data processing used. NIRS calibrations were generated by hand separation of fiber from water-retted specimens. The water retting procedure takes several days to complete and requires considerable trained labor to complete the hand separation step. The NIRS procedure was conducted on pieces of stem to simulate measurement in the field.     

分提橄榄油中主要脂肪酸成分傅里叶变换红外光谱法测量（英）

为了测量从橄榄油中分提的高、低熔点油脂的脂肪酸成分,在4 000～600 cm-1 的范围测量了31个含有不同脂肪酸成分植物油的傅里叶变换红外光谱,用于建立偏最小二乘（PLS）回归分析校正模型。在油脂的傅里叶变换红外光谱变量和脂肪酸组成变量之间建立了交叉验证的PLS校正模型。为了校正油酸和亚油酸含量,在4?000～600 cm-1 的频率范围,经平滑,二阶导数,规范化处理的红外光谱获得了最好的交叉验证校正模型和最佳的预测结果。PLS校正模型预测结果表明,与高熔点橄榄油（油酸,72.29%,亚油酸,9.98%）相比,低熔点橄榄油含有较高的油酸含量和亚油酸含量（油酸,77.46%,亚油酸,12.51%）,预测的结果与气相色谱测量的结果有很好的一致性。建立的PLS校正模型预测橄榄油的不饱和脂肪酸含量具有较好的相关性。该研究为分提油脂质量的判别评价提供了便捷的方法。     

Method for determining frying oil degradation by near-infrared spectroscopy

A rapid near-infrared (NIR) spectroscopic method for measuring degradation products in frying oils, including total polar materials (TPMs) and free fatty acids (FFAs), has been developed. Calibration models were developed using both forward stepwise multiple linear regression (FSMLR) and partial least-squares (PLS) regression techniques and then tested with two independent sets of validation samples. Derivative treatments had limited usefulness, especially in the longer (1100-2500 nm) wavelength region. When using a wavelength region of 700-1100 nm, PLS models gave improved results compared to FSMLR models. The best correlations (r) between the NIR and wet chemical methods for TPM and FFA were 0.983 and 0.943, respectively. In the longer wavelength region (1100-2500 nm), FSMLR models were as good or better than PLS models. The best correlations for TPM and FFA obtained in this region were 0.999 and 0.983, respectively.     

Characterization of sphingolipids from sunflower seeds with altered fatty acid composition

Sphingolipids are a group of lipids that are derived from long-chain 1,3-dihydroxy-2-amino bases and that are involved in important processes in plants. Long-chain bases are usually found bound to long-chain fatty acids forming ceramides, the lipophilic moiety of the most common sphingolipid classes found in plant tissues: glucosyl-ceramides and glucosyl inositol phosphoryl-ceramides (GIPCs). The developing sunflower seed kernel is a tissue rich in sphingolipids, although, importantly, its glycerolipid composition can vary if some steps of the fatty acid synthesis are altered. Here, the sphingolipid composition of the seed from different sunflower mutants with altered fatty acid compositions was studied. The long-chain base composition and content were analyzed, and it was found to be similar in all of the mutants studied. The sphingolipid species were also determined by mass spectrometry, and some differences were found in highly saturated sunflower mutants, which contained higher levels of GIPC, ceramides, and hydroxyl-ceramides.     

Comparison of diffuse reflectance fourier transform mid-infrared and near-infrared spectroscopy with grating-based near-infrared for the determination of fatty acids in forages

Diffuse reflectance Fourier transform mid infrared (FTMIR) and near-infrared spectroscopy (FTNIR) were compared to scanning monochromator-grating-based near-infrared spectroscopy (SMNIR), for their ability to quantify fatty acids (FA) in forages. A total of 182 samples from thirteen different forage cultivars and three different harvest times were analyzed. Three calibration analyses were conducted for lauric (C12:0), myristic (C14:0), palmitic (C16:0), stearic (C18:0), palmitoleic (C16:1), oleic (C18:1), linoleic (C18:2), and alpha-linolenic (C18:3) acids. When all samples were used in a one-out partial least squares (PLS) calibration, the average R (2) were FTNIR (0.95) > SMNIR (0.94) > FTMIR (0.91). Constituents C18:2 and C16:0 had among the highest R (2) regardless of the spectroscopic method used. The FTNIR did better for C12:0, C14:0, and C18:3. The SMNIR did better for C16:0, C16:1, C18:0, C18:1, and C18:2. A second set of calibrations developed with half of the samples as the calibration set and the rest as the validation set showed that all the methods produce acceptable calibrations, with calibration R (2) above 0.9 for most constituents. However, the SMNIR had a better average calibration relative error than the FTNIR, which was slightly better than the FTMIR. A third set of calibration equations developed using 100 random PLS runs with the 182 samples split randomly also shows that the three spectral methods are satisfactory for predicting FA. It is not clear whether any of the spectral methods is distinctly better than another. Calibration R (2) and validation R (2) were higher for most FA with the SMNIR than the FTMIR and FTNIR.     

牛肉质构特性的近红外光谱无损检测

为了建立基于近红外光谱技术的牛肉质构特性快速检测方法,该试验采集了202个新鲜牛肉样品在800～2500 nm波长范围内的漫反射光谱,测定了牛肉的硬度、弹性、咀嚼性和黏附性,经小波消噪后,分别采用平滑、一阶微分、二阶微分等6种方法预处理,建立了牛肉质构特性的偏最小二乘回归模型,并用最优模型进行预测。结果表明：经小波消噪后采用二阶微分预处理方法建立的牛肉硬度、弹性、咀嚼性的检测模型效果最好,其校正集相关系数 r 均在0.9以上,校正集均方根误差（root means square error of calibration,RMSEC）分别为6.247 N、0.760 mm、14.954 mJ,预测集相关系数均在0.664以上,预测集均方根误差（root means square error of prediction,RMSEP）分别为8.887 N、0.951 mm、22.117 mJ,相对预测误差（ratio of prediction to deviation,RPD）值分别为2.43、1.88、2.32,预测精度较高,能够有效地预测牛肉的硬度、咀嚼性,可以检测精度要求不高的牛肉弹性;试验所建立的牛肉黏附性检测模型的预测性能不是很理想,虽然其校正集和预测集相关系数较高（分别为0.720、0.694）,RMSEC 和 RESEP 均较小（分别为0.302、0.243 N·mm）,但其 RPD 值小于1.5,模型预测精度较差,不可以用于预测未知样品的黏附性,此方法还需进一步研究。研究结果为牛肉质构特性的快速无损评价提供了理论依据。     

可见/近红外光谱技术无损检测果实坚实度的研究

该研究的目的是建立可见/近红外光谱与梨果实坚实度之间的数学模型,评价可见/近红外光谱技术无损测量梨果实坚实度的应用价值。在可见/近红外光谱区域(350～1800 nm),试验对比分析了不同测量部位、不同光谱预处理方法和不同校正建模算法的梨果实坚实度校正模型。结果表明：赤道部位吸光度一阶微分光谱的偏最小二乘回归所建梨果实坚实度校正模型的预测性能较优,其校正和预测相关系数分别为0.8779和0.8087,校正和预测均方误差分别为1.0804 N和1.4455 N。研究表明：可见/近红外光谱技术无损检测梨果实坚实度是可行的。     

Determination of chemical composition of commercial honey by near-infrared spectroscopy.

The feasibility of using near-infrared spectroscopy to determine chemical composition of commercial honey was examined. The influences of various sample presentation methods and regression models on the performance of calibration equations were also studied. Transmittance spectra with 1 mm optical path length produced the best calibration for all constituents examined. The regression model of modified partial least squares (mPLS) was selected for the calibration of all honey constituents except moisture, for which the optimal calibration was developed with PLS. Validation of the established calibration equations with independent samples showed that the spectroscopic technique could accurately determine the contents of moisture, fructose, glucose, sucrose, and maltose with squared correlation coefficients (R(2)) of 1.0, 0.97, 0.91, 0.86, and 0.93 between the predicted values and the reference values. The prediction accuracy for free acid, lactone, and hydroxymethylfurfural (HMF) contents in honey was poor and unreliable. The study indicates that near-infrared spectroscopy can be used for rapid determination of major components in commercial honey.     

Screening of the entire USDA castor germplasm collection for oil content and fatty acid composition for optimum biodiesel production

Castor has tremendous potential as a feedstock for biodiesel production. The oil content and fatty acid composition in castor seed are important factors determining the price for production and affecting the key fuel properties of biodiesel. There are 1033 available castor accessions collected or donated from 48 countries worldwide in the USDA germplasm collection. The entire castor collection was screened for oil content and fatty acid composition by nuclear magnetic resonance (NMR) and gas chromatography (GC), respectively. Castor seeds on the average contain 48.2% oil with significant variability ranging from 37.2 to 60.6%. Methyl esters were prepared from castor seed by alkaline transmethylation. GC analysis of methyl esters confirmed that castor oil was composed primarily of eight fatty acids: 1.48% palmitic (C16:0), 1.58% stearic (C18:0), 4.41% oleic (C18:1), 6.42% linoleic (C18:2), 0.68% linolenic (C18:3), 0.45% gadoleic (C20:1), 84.51% ricinoleic (C18:1-1OH), and 0.47% dihydroxystearic (C18:0-2OH) acids. Significant variability in fatty acid composition was detected among castor accessions. Ricinoleic acid (RA) was positively correlated with dihydroxystearic acid (DHSA) but highly negatively correlated with the five other fatty acids except linolenic acid. The results for oil content and fatty acid composition obtained from this study will be useful for end-users to explore castor germplasm for biodiesel production.     

Prediction chemical composition and alveograph parameters on wheat by near-infrared transmittance spectroscopy

Moisture, protein, wet gluten, dry gluten, and alveograph parameters (W, P, and P/L) of whole wheat grown in different countries around the world were analyzed using near infrared (NIR) transmittance spectroscopy. Modified partial least squares on NIR spectra (850-1048.2 nm) were developed for each constituent or physical property. The best models were obtained for protein, moisture, wet gluten, and dry gluten with r(2) = 0.99, 0.99, 0.95, and 0.96, respectively. Initial alveograph NIR models proposed for all wheat samples did not perform well. However, when wheat samples were divided in two groups depending on W (deformation energy) values, NIR models were highly improved, showing enough prediction accuracy for screening wheat at the receiving stage at mills or elevators.