Nondestructive Estimation of Fat Constituents of Sesame (Sesamum indicum L.) Seeds by Near‐Infrared Reflectance Spectroscopy

A rapid and efficient method for oil constituent estimation in intact sesame seeds was developed through near‐infrared reflectance spectroscopy (NIRS) and was used to evaluate a sesame germplasm collection conserved in China. A total of 342 samples were scanned by reflectance NIR in a range of 950–1650 nm, and the reference values for oil content and fatty acid (FA) profiles were measured by Soxhlet and gas chromatograph methods. Useful chemometric models were developed using partial least squares regression with full cross‐validation. The equations had low standard errors of cross‐validation, and high coefficient of determination of cross‐validation (R_c²) values (>0.8) except for stearic acid (0.794). In external validation, r² values of oil and FA composition equations ranged from 0.815 (arachidonic acid) to 0.877 (linoleic acid). The relative predictive determinant (RPD_v) values for all equations were more than 2.0. The whole‐seed NIR spectroscopy equations for oil content and FA profiles can be used for sesame seed quality rapid evaluation. The background information of the 4399 germplasm resources and accessions with high linoleic acid content identified in this study should be useful for developing new sesame cultivars with desirable FA compositions in future breeding programs.     

Evaluation of benchtop versus portable near-infrared spectroscopic method combined with multivariate approaches for the fast and simultaneous quantitative analysis of main sugars in syrup formulations

In this work a total of 116 syrup samples was investigated in order to establish predictive models for glucose, fructose and sucrose of sufficient accuracy based on partial least squares regression. The samples are divided into two main groups a) standard syrups b) reformulated syrups. The latter products can be distinguished via the very low amount of glucose and sucrose and a high amount of fructose which makes them suitable for special nutrition. Near-infrared spectroscopy was applied together with Multivariate Analysis to develop a new method for quality control of syrups. Comparison between a portable spectrometer and the benchtop device showed that the reduced wavelength range and reduced resolution of the portable device is sufficient to receive calibrations with R² ≥ 0.96 for standard syrups with comparable SEP values of 1.30 g/100 g vs. 1.19 g/100 g, 0.94 g/100 g vs. 0.99 g/100 g and 2.04 g/100 g vs. 2.46 g/100 g for glucose, fructose and sucrose respectively using the handheld device. The SEP values led to high RPD values of 5.56 vs. 5.26, 4.30 vs. 4.72, 5.06 vs. 4.20 for fructose, glucose and sucrose respectively. The R² values for reformulated syrups were 0.94 with a SEP of 1.04 g/100 g and a RPD value of 2.58 for the portable spectrometer and 0.92 with a SEP of 0.92 g/100 g and a resulting RPD value of 2.84 for the benchtop spectrometer. The method is suitable to be implemented for quality control in the producing industry as well as in grocery stores.     

A passenger reduces sleepy driver's activation in the right prefrontal cortex: A laboratory study using near-infrared spectroscopy

The present study aimed to examine how a passenger affects the sleepiness effect (awake vs. sleepy) on an individual's prefrontal activation during a simulated driving-game task using a wireless portable near-infrared spectroscopy (NIRS) device. Participants drove from start to goal along default routes either solely (no-passenger group) or with a friend sitting beside him/her as a passenger (with-passenger group). Sleepiness level was assessed by a five-item scale questionnaire. In the no-passenger group, there were no performance and activation differences between the sleepy and awake participants. In the with-passenger group, by contrast, the sleepy participants showed more errors and lower activations in their right prefrontal cortex than the awake participants. These results suggest that a passenger has little effect on awake participants, but may weaken the sleepy participants’ vigilance and/or their cognitive abilities of action control. Practically, the present study demonstrates that NIRS may provide us a new possibility to monitor and examine the driver's mental states in the brain.     

Prediction of fatty acids content in pig adipose tissue by near infrared spectroscopy: At-line versus in-situ analysis

A handheld micro-electro-mechanical system (MEMS) based spectrometer working in the near infrared region (NIR) (1600–2400 nm) was evaluated for in-situ and non-destructive prediction of main fatty acids in Iberian pig (IP) carcasses. 110 IP carcasses were measured. Performance of the instrument was compared with at-line high-resolution NIRS monochromators working in two analysis modes: melted fat samples (transflectance cups) and intact adipose tissues (interactance fiber optic). Standard Error of Prediction (SEP) values obtained on the MEMS-NIRS device were: 0.68% (stearic), 1.30% (oleic), 0.55% (linoleic) and 1% (palmitic), explaining a variability of 83%, 84%, 81% and 78%, respectively. As expected, this represented a loss of predictive capability in comparison to at-line models, even with the same spectral characteristics as on the handheld device. However, the estimated total errors were at the same level for gas chromatography and NIRS analysis. This indicates that the MEMS-NIRS in-situ analysis of each individual carcass provides a cost-effective and real-time quality control system with suitable accuracy.     

Climate driven release of carbon and mercury from permafrost mires increases mercury loading to sub-arctic lakes

In sub-arctic and arctic regions mercury is an element of concern for both wildlife and humans. Over thousands of years large amounts of atmospherically deposited mercury, both from natural and anthropogenic sources, have been sequestered together with carbon in northern peatlands. Many of these peatlands are currently underlain by permafrost, which controls mire stability and hydrology. With the ongoing climate change there is concern that permafrost thawing will turn large areas of these northern peatlands from carbon/mercury-sinks into much wetter carbon/mercury-sources. Here we can show that such a change in mire structure in the sub-arctic Stordalen mire in northern Sweden actually is responsible for an increased export of mercury to the adjacent lake Inre Harrsjön. We also show that sediment mercury accumulation rates during a warm period in the pre-industrial past were higher than in the 1970s when atmospheric input peaked, indicating that in areas with permafrost, climate can have an effect on mercury loading to lakes as large as anthropogenic emissions. Thawing of permafrost and the subsequent export of carbon is a widespread phenomenon, and the projection is that it will increase even more in the near future. Together with our observations from Stordalen, this makes northern peatlands into a substantial source of mercury, at risk of being released into sensitive arctic freshwater and marine systems.     

The application of near-infrared (NIR) and Raman spectroscopy to detect adulteration of oil used in animal feed production

Basic vegetable blends (BVB’s) and soya oils, used in the animal feed industry, are sometimes adulterated with transformer and mineral oil as a means of illegally increasing profit. A set of BVB’s and soya oil samples adulterated with transformer oil and mineral oil were characterised using both NIRS and Raman spectroscopy. Applying chemometrics to the NIRS and Raman spectral data, very good calibration and prediction statistics were obtained for transformer and mineral oils. Using NIRS, R² values greater than 0.99 were obtained with corresponding values for root mean squared error of calibration and prediction (<0.57 and <0.55, respectively). Using Raman, R² values greater than 0.97 were obtained with the root mean squared error of calibration (<2.01) and prediction (<1.92) calculated. Furthermore, using a qualitative approach it was possible, using PCA, to discriminate between 100% soya and BVB. This study demonstrates that both NIRS and Raman technology can be successfully applied as rapid screening techniques for the detection of oil adulteration and fraud in the food and feed industry.     

基于近红外光谱技术与BP-ANN算法的豆粕品质快速检测

应用近红外漫反射光谱技术结合误差反向传递人工神经网络(BP-ANN)算法,建立豆粕品质(包括水分、粗蛋白、残油)的定量分析模型。将豆粕漫反射吸收光谱数据进行SNV、DT、SG求导、SG平滑和均值中心化处理,然后采用偏最小二乘方法(PLS)降维获取主成分,并优化选择合适的隐含层节点数、隐含层和输出层转化函数,建立校正模型,并用验证样品对校正模型进行验证。结果显示,BP-ANN法建立的水分、粗蛋白和残油的预测相关系数(R)分别为0.981、0.988、0.982,预测标准偏差(SEP)分别为0.120、0.216、0.036,均优于PLS建模方法结果,且满足传统分析方法的重复性要求,表明BP-ANN方法可用于生产过程豆粕品质的快速监控。     

Identification of cattle, llama and horse meat by near infrared reflectance or transflectance spectroscopy

Visible and near infrared reflectance spectroscopy (VIS-NIRS) was used to discriminate meat and meat juices from three livestock species. In a first trial, samples of Longissimus lumborum muscle, corresponding to beef (31) llamas (21) and horses (27), were homogenised and their spectra collected in reflectance (NIRSystems 6500 scanning monochromator, in the range of 400-2500 nm). In the second trial, samples of meat juice (same muscle) from the same species (20 beef, 19 llama and 19 horse) were scanned in folded transmission (transflectance). Discriminating models (PLS regression) were developed against “dummy” variables, testing different mathematical treatments of the spectra. Best models indentified the species of almost all samples by their meat (reflectance) or meat juice (transflectance) spectra. A few (three of beef and one of llama, for meat samples; one of beef and one of horse, for juice samples) were classified as uncertain. It is concluded that NIRS is an effective tool to recognise meat and meat juice from beef, llama and horses.     

Quality assessment of tomato landraces and virus-resistant breeding lines: quick estimation by near infrared reflectance spectroscopy

BACKGROUND: Several tomato landraces are very popular in south‐eastern Spain for their organoleptic fruit quality, but these cultivars are highly susceptible to several viruses. A breeding programme is being carried out for the introduction of virus resistances into these landraces. In the last steps of our breeding programme a high number of breeding lines must be evaluated for agronomic and organoleptic quality parameters. Near infrared reflectance spectroscopy (NIRS) technology shows considerable promise and is ideally suited to the requirements of breeders. RESULTS: Significant differences between a set of 35 tomato breeding lines, seven landraces and one commercial hybrid were observed for quality and mineral content parameters, suggesting that there are considerable levels of genetic diversity between the cultivar groups studied. Using NIRS on dry samples of tomato constitutes a feasible technique to estimate the content of several minerals (C, N, P, K, Ca, Na, Mn, Mg and Cu) according to the coefficient of determination for calibration (R² > 0.90). NIRS estimations of soluble solids content and titratable acidity obtained were considered useful only for general screening purposes. CONCLUSIONS: NIRS technology may be a useful tool in the selection of lines coming out of tomato breeding programs, allowing a quick estimation of mineral content. However, the estimation of soluble solids content and titratable acidity by NIRS must be improved. Copyright © 2011 Society of Chemical Industry