Speciation of selenium in stream insects using X-ray absorption spectroscopy

Selenium contamination in the environment is a widespread problem affecting insects and other wildlife. Insects occupy a critical middle link and aid in trophic transfer of selenium in many terrestrial and freshwater food chains, but the mechanisms of selenium uptake through the food chain are poorly understood. In particular, biotransformation of selenium by insects into different chemical forms will greatly influence how toxic or benign the selenium is to that organism or to its predators. We have used X-ray absorption spectroscopy (XAS) to identify the chemical form of selenium in insects inhabiting selenium contaminated streams near Hinton, Alberta (Canada). Selenium K near-edge spectra indicate a variability of selenium speciation among the insects that included mayflies (Ephemeroptera), stoneflies (Plecoptera), caddisflies (Trichoptera), and craneflies (Diptera). Higher percentages of inorganic selenium were observed in primary consumers, detritivores, and filter feeders than in predatory insects. Among the organic forms of selenium, organic selenides constituted a major fraction in most organisms. A species modeled as trimethylselenonium was observed during the pupal stage of caddisflies. These results provide insights into how the insects cope with their toxic cargo, including how the selenium is biotransformed into less toxic forms and how it can be eliminated from the insects. More broadly, this study demonstrates the strengths of XAS to probe the effects of heavy elements at trace levels in insects from the field.     

荧光分光光度法测定蔬菜中Vc含量

Vc经活性炭处理后,可氧化为顺式脱氢型,此化合物的α-酮基与邻苯二胺反应形成喹喔啉,在激发波长351nm,发射波长432nm处测定其荧光强度。采用外标法(标准曲线),所作标准曲线相关系数为0.9993,相对标准偏差小于0.86%,回收率在97%～99.2%之间,此法精确度好、回收率高,适合于蔬菜中微量Vc的含量测定。     

分子荧光光谱技术在食品安全中的应用

食品安全事故经常发生,要求人们研发快速检测技术。分子荧光光谱技术是近年来发展起来的一类新型的分析检测技术,具有分析时间短、样品预处理少、非破坏性、无污染及成本低等特点,在食品安全检测领域得到广泛应用。从分子荧光光谱原理入手,概述了分子荧光光谱技术在控制食品质量、鉴别食品真伪、分析食品种类、追溯产品来源、检测药物残留等领域中的应用,旨在为推动分子荧光光谱技术的发展、完善食品安全检测技术体系提供参考。     

前表面荧光法在牛奶美拉德反应检测中的应用

在热处理中,牛奶中的乳蛋白容易与乳糖发生美拉德反应,使牛奶的色泽、风味、营养等发生变化。与传统化学检测法相比,前表面荧光法具有快速灵敏、前处理简便等优点。为了评估前表面荧光法在检测牛奶美拉德反应程度上的准确性和适用性,本文对比了不同热处理下牛奶的美拉德反应的荧光图谱和美拉德产物的含量,分析了指标间的相关性。并以前表面荧光法和羟甲基糠醛含量建立模型对商业乳品进行预测,结果良好,为荧光检测的工业应用提供理论依据。结果显示,前表面荧光法可应用于牛奶前中期美拉德产物的无损检测。     

Utilization of front-face fluorescence spectroscopy for analysis of process cheese functionality

The purpose of this study was to evaluate the feasibility of front-face fluorescence spectroscopy (FFFS) to predict the meltability of process cheese spreads or products. Twenty-seven commercial samples from 3 manufacturers were used in this study. Each sample was analyzed using dynamic stress rheometry, which was used to calculate the meltability index (temperature at tandelta = 1). Additionally, fluorescence spectra of tryptophan (excitation: 290 nm; emission: 305 to 400 nm) were collected on each sample at 20 degrees C using a front-face accessory. Fluorescence spectrum for each sample consisted of an average of 36 scans (6 scans performed on 6 replicates). The spectral data set consisted of normalized and mean-centered spectra from all the samples. Multivariate statistical analysis was used to correlate spectral data with cheese meltability index as measured by dynamic stress rheometry. A prediction model was developed using partial least square regression and was calibrated using a cross-validation method. A correlation coefficient of 0.93 was obtained between fluorescence spectra and cheese meltability. The regions 335 to 350 nm and 385 to 400 nm had the highest correlation to cheese meltability. A negative correlation between the peak height of tryptophan (335 to 350 nm) and cheese meltability index was observed. This correlation may be due to presence of tryptophan residues in a more hydrophobic environment in stronger emulsions as compared with a more polar environment in weak emulsions. These results indicate that the melt properties of process cheese spreads or products are related to molecular structure that can be measured using FFFS. Hence, FFFS can be used as an analysis technique to predict process cheese meltability.     

荧光光谱法测定食品中二丁基羟基甲苯

目的建立食品中二丁基羟基甲苯(BHT)荧光光谱测定法。方法在KMn O4溶液(p H=2.5)中,温度为75℃的水浴锅中加热50 min后,BHT的氧化产物在λex/λem=292/342 nm处发射强荧光,用荧光光度计测定。结果BHT在1.32~11.01 mg/L范围内,其氧化产物的荧光强度与BHT浓度呈良好的线性关系,相关系数r=0.992,方法检出限为0.01 mg/L,精密度为2.1%。结论该方法有较高灵敏度和较好精密度,可用于食品中BHT的检测。     

荧光共振能量转移技术在食品分析检测中的应用

荧光共振能量转移技术(fluorescence resonance energy transfer,FRET)是一种均相分析检测技术,具有灵敏度高、选择性好、操作简单方便等优点,广泛应用于食品安全检测领域。本文主要综述了荧光共振能量转移的基本原理,对荧光共振能量转移在食品中各种安全危害因子包括真菌毒素、抗生素、重金属等分析检测中的应用进行了概述,最后对其未来的发展方向进行了展望。     

Application of fluorescence spectroscopy for monitoring changes in nonfat dry milk during storage

The objective of this study was to determine if fluorescence spectroscopy could be used to characterize the biochemical characteristics of nonfat dry milk (NDM) caused by manufacturing and storage conditions. Nine low-heat NDM samples were collected from 3 manufacturers and stored at 4 temperatures (4, 22, 35, and 50°C) for 8 wk. The spectra of Maillard products, tryptophan, and riboflavin were recorded and analyzed with principal components analysis. Colorimetric indices L*, a*, and b* were also determined. The before-storage NDM samples collected from each manufacturer had different fluorescent characteristics. Inconsistency was observed for the NDM samples collected from 1 manufacturer, whereas the samples from the other 2 manufacturers displayed consistent fluorescence characteristics. Biochemical reactions, such as Maillard reaction, modification of the tryptophan environment, and degradation of riboflavin occurred during the manufacturing process. For each of the data collections, discrimination of the NDM samples stored at 50°C from the samples stored at 4, 22, and 35°C was observed in the similarity maps. The factor loadings of the first 2 principal components for the fluorescence spectra of the samples before storage were similar to the principal components analysis results of the samples during storage. It appears that similar factors are responsible for the variation in the samples before storage and their changes during storage. Additionally, storage of the samples at 50°C accelerated these reactions. The results demonstrate that front-face fluorescence spectroscopy, coupled with multivariate statistical methods, can be utilized as an analytical technique to monitor variation in NDM samples from different manufacturers and changes during storage.     

Positive effects of wastewater ozonation displayed by in situ bioassays in the receiving stream

Tertiary treatment methods, like ozonation, are currently under discussion to improve removal efficiencies of micropollutants by municipal wastewater treatment plants (WWTPs). In order to assess the effects of a full-scale wastewater ozonation at WWTP Wu?eri, Switzerland, on the receiving stream, a total of seven in situ bioassays with Gammarus fossarum that lasted 7-days were conducted during an overall period of 33 months. Caged gammarids were exposed between 150 m up- and 400 m downstream of a WWTP effluent before, during and following the operation of the full-scale wastewater ozonation. During the release of nonozone treated wastewater, gammarid feeding was significantly reduced by up to 90% 50 and 150 m downstream of the WWTP effluent. In contrast, during the operation period of the ozonation, no significant alterations in feeding were observed downstream. The results of these bioassays were incorporated into a mathematical simulation of the release of nonozone treated wastewater in a Central European region, suggesting a 40% reduction in leaf litter breakdown and hence in energy provision for the remaining aquatic food web downstream of WWTP effluents, while the release of ozone treated wastewater did not affect this important ecosystem function.     

壳聚糖改性絮凝剂在染料废水处理中的应用

采用壳聚糖与有机单体丙烯酰胺接枝共聚制备絮凝剂,并用此絮凝剂对活性染料废水进行混凝处理.考查了无机絮凝剂、有机絮凝剂、废水pH值等因素对处理效果的影响.实验结果表明,在pH值5～9,PAC用量500 mg/L,壳聚糖改性絮凝剂用量6 mg/L时,染料废水的脱色率可达95%以上,COD去除率高于74%.壳聚糖改性絮凝剂处理活性染料废水时,具有原料来源丰富、用量小、使用条件温和、成本较低、絮凝效果显著等优点.     

Evaluation of near-infrared reflectance spectroscopy for predicting stover quality trait in semi-exotic populations of maize

Near-infrared reflectance spectroscopy (NIRS) analysis was investigated as a means of predicting quality parameters in semi-exotic maize stover. These parameters included crude protein (CP), neutral detergent fibre, acid detergent fibre and in vitro dry matter digestibility (IVDMD). Samples of semi-exotic maize stover were collected during three growing seasons (1989, 1990, 1991) from three locations in Catalonia, Spain. Calibration equations were obtained by multiple linear regression of conventional laboratory values on NIRS data from 84 samples and verified with 20 additional samples. Separate NIRS calibration were developed also within year (1989 and 1990, respectively). A Bran + Luebbe InfraAnalyzer model 450 was used for the study. In the multi-year calibration the coefficients of squared multiple correlation (R²) ranged from 0–81 for IVDMD to 0–92 for CP and the standard errors of calibration (SEC) ranged from 0–35 for CP to 1–46 for IVDMD. The study showed that NIRS analysis can be used to evaluate the quality of semi-exotic maize in breeding programmes.     

Near infrared reflectance spectroscopy for predicting intake of digestible organic matter by cattle

The near infrared reflectance spectra of 15 forages and the first and second derivatives of those spectra were examined for variations that would relate to measures of forage quality and animal performance. Strong relationships between second derivative values and protein, NDF, ADF, and digestible DM were found at wavelengths reported previously as well as at other wavelengths. Error mean squares for simple regressions were similar to those previously reported for multiple wavelength regressions. The more important measures of forage quality, digestible organic matter intake and average daily body weight gain, were each highly correlated with second derivative values at 1696 and 2298 nm (r greater than /.91/). Second derivatives at 1696 and 2298 nm were also correlated (r greater than /.95/) with ADF and protein, respectively. The evidence suggests a biological basis for the estimation of digestible organic matter intake from near infrared reflectance spectroscopy spectra.     

Near-infrared reflectance spectroscopy for predicting chemical, instrumental and sensory quality of beef

The aim of this study was to assess near-infrared reflectance (NIR) spectroscopy as a tool for determining sensory and texture characteristics of beef. Chemical, instrumental, texture and sensory characteristics were predicted by near-infrared reflectance spectroscopy carried out on longissimus dorsi muscle samples from 190 young bulls. The use of first derivative gave best predictions together with NIR spectra, except for myoglobin and water holding capacity, which had an R(2) of prediction of 0.91 and 0.82, respectively, using visible and NIR spectra. Tenderness was the best-predicted variable (R(2)=0.98) demonstrating the potential of NIR spectroscopy in the prediction of sensory variables. Chemical composition variables and Warner-Bratzler shear force were predicted with an R(2) of prediction of around 0.7, but protein was not predicted with accuracy.     

The characterization of soybean varieties by fluorescence spectroscopy

Fluorescence spectroscopy was used to differentiate between β‐conglycinin (βC) and glycinin (G) fractions that were isolated from four food grade soybean varieties (Glycine max var. K1430, Hutcheson, K93‐90‐29, and KS4997) grown in the same location. The protein fractions were discriminated by using spectroscopic tryptophan fluorescence emission and synchronous scanning techniques that took advantage of the sensitivity of the chromophore to changes in the protein environment. The relative intensities of the βC and glycinin fluorescence ranged from 1.00 to 1.30 and 1.00 to 1.31 respectively. The intensities of the βC and glycinin synchronous fluorescence ranged from 1.00 to 1.45 and 1.00 to 1.30 respectively. The spectroscopic method proved to be an effective technique to differentiate between different soybean varieties.     

基于荧光法的牛奶中单诺沙星的快速检测

采用荧光法结合化学计量学来建立牛奶中单诺沙星(DANO)残留的快速检测方法 先利用加标法制备含有不同浓度的DANO(0～56μg/L)的全脂奶作为校正集,除蛋白后经扫描得到荧光光谱,利用化学计量学技术对其进行主成分分析(PCA)并建立偏最小二乘法(PLS)和判别分析(PLSDA)模型.采用加入不同浓度DANO的4种品牌的超高温杀菌和巴氏杀菌牛奶作为预测集,验证了两种模型的准确性.实验结果表明,定性模型可以准确地将阴性与阳性样品区分,定量模型预测出的样品回收率在88％ ～ 114.4％,预测误差在可接受范围内.     

The use of near infrared reflectance spectroscopy for predicting the quality of grass silage

Near infrared reflectance spectroscopy, using a fixed-filter instrument fitted with 19 filters, was evaluated for the prediction of crude protein and in-vitro dry matter digestibility in commercial farm grass silage. Crude protein (6.5–17.6%) was estimated with acceptable accuracy (standard error of prediction=0.63%) using a six-wavelength calibration, but in-vitro dry matter digestibility (40.7–69.9%) was not predicted with sufficient accuracy (standard error of prediction=2.96%) by this technique.     

Validation of milk mid-infrared spectroscopy for predicting the metabolic status of lactating dairy cows in Australia

Increased concentrations of some serum biomarkers are known to be associated with impaired health of dairy cows. Therefore, being able to predict these biomarkers, especially in the early stage of lactation, would enable preventive management decision. Some health biomarkers may also be used as phenotypes for genetic improvement for improved animal health. In this study, we validated the accuracy and robustness of models for predicting serum concentrations of β-hydroxybutyrate (BHB), fatty acids, and urea nitrogen, using milk mid-infrared (MIR) spectroscopy. The data included 3,262 blood samples of 3,027 lactating Holstein-Friesian cows from 19 dairy herds in Southeastern Australia, collected in the period from July 2017 to April 2020. The models were developed using partial least squares regression and were validated using 10-fold random cross-validation, herd-year by herd-year external validation, and year by year validation. The coefficients of determination (R²) for prediction of serum BHB, fatty acids, and urea obtained through random cross-validation were 0.60, 0.42, and 0.87, respectively. For the herd-year by herd-year external validation, the prediction accuracies held up comparatively well, with R² values of 0.49, 0.33, and 0.67 for of serum BHB, fatty acids, and urea, respectively. When the models were developed using data from a single year to predict data collected in future years, the R² remained comparable, however, the root mean squared errors increased substantially (4–10 times larger than compared with that of herd-year by herd-year external validation) which could be due to machine differences in spectral response, the change in spectral response of individual machines over time, or other differences associated with farm management between seasons. In conclusion, the mid-infrared equations for predicting serum BHB, fatty acids, and urea have been validated. The prediction equations could be used to help farmers detect cows with metabolic disorders in early lactation in addition to generating novel phenotypes for genetic improvement purposes.     

Visible-near infrared spectroscopy sensor for predicting curd and whey composition during cheese processing

The potential of visible-near infrared spectra, obtained using a light backscatter sensor, in conjunction with chemometrics, to predict curd moisture and whey fat content in a cheese vat was examined. A three-factor (renneting temperature, calcium chloride, cutting time), central composite design was carried out in triplicate. Spectra (300–1,100 nm) of the product in the cheese vat were captured during syneresis using a prototype light backscatter sensor. Stirring followed upon cutting the gel, and samples of curd and whey were removed at 10 min intervals and analyzed for curd moisture and whey fat content. Spectral data were used to develop models for predicting curd moisture and whey fat contents using partial least squares regression. Subjecting the spectral data set to Jack-knifing improved the accuracy of the models. The whey fat models (R = 0.91, 0.95) and curd moisture model (R = 0.86, 0.89) provided good and approximate predictions, respectively. Visible-near infrared spectroscopy was found to have potential for the prediction of important syneresis indices in stirred cheese vats.