Simple and sensitive determination of Cr (III), Cu (II) and Pb (II) in tea infusions using AgNPs-modified resin combined with laser-induced breakdown spectroscopy.

The detection of heavy metals in tea infusions is important because of the potential health risks associated with their consumption. Existing highly sensitive detection methods pose challenges because they are complicated and time-consuming. In this study, we developed an innovative and simple method using Ag nanoparticles-modified resin (AgNPs-MR) for pre-enrichment prior to laser-induced breakdown spectroscopy for the simultaneous analysis of Cr (III), Cu (II), and Pb (II) in tea infusions. Signal enhancement using AgNPs-MR resulted in amplification with limits of detection of 0.22 µg L-1 for Cr (III), 0.33 µg L-1 for Cu (II), and 1.25 µg L-1 for Pb (II). Quantitative analyses of these ions in infusions of black tea from various brands yielded recoveries ranging from 83.3% to 114.5%. This method is effective as a direct and highly sensitive technique for precisely quantifying trace concentrations of heavy metals in tea infusions.

Rapid identification of artificial fragrant rice based on volatile organic compounds: From PTR-MS to FTIR.

The volatile organic compounds (VOCs) released from foods can reflect their internal properties. Artificial fragrant rice (AFR) is a fraudulent food product in which the flavor of low-quality rice is artificially enhanced by addition of essence. In this study, proton-transfer reaction mass spectrometry, long optical path gas phase FTIR spectroscopy and fiber optic evanescent wave were used to analyze the characteristic mass-charge ratios signal and infrared fingerprint signal of four essence which may be used to make AFR, and the prepared AFR samples with different essence levels (0.001 %-0.3 %) were used to verify the detection performance of the detection methods. The results show that the three detection methods effectively identified AFR containing the minimum recommended dose of essence (≥0.1 %, w/w). The above detection methods can provide detection results in real time without complex sample pretreatment and provide options as rapid screening methods for food regulatory authorities to identify AFR.

Detecting volatile compounds in food by open-path Fourier-transform infrared spectroscopy.

We previously found that the brand of a food and spoilage of the food can be identified from the infrared spectra of the volatile compounds released. However, this required pumping the volatile compounds into a gas cell, meaning measurements over large areas could not be made. Gas components can be quantified from a distance of a few metres or kilometres by open-path Fourier-transform infrared spectroscopy (FTIR), and the spatial distributions of gas clouds can even be determined using open-path FTIR and an imaging detection method. In the study described here, we used open-path FTIR to remotely detect volatile compounds in food. Active and passive methods were used to obtain infrared spectra of volatile compounds released from spirits, vinegars, and grapes from a distance of 5 m. The absorption characteristics of ethanol, esters, and unknown volatile compounds were clearly found in the spectra. The brands of the spirits and degree to which the grapes had spoiled were identified by compensating for ethanol in the atmosphere and chemometrics. The results indicate that open-path FTIR can be used to remotely detect volatile compounds released by food and may be able to be used to identify spoiling food in large food warehouses.

Detecting and Mapping Harmful Chemicals in Fruit and Vegetables Using Nanoparticle-Enhanced Laser-Induced Breakdown Spectroscopy.

Residues of harmful chemicals in fruit and vegetables pose risks to human health. Ordinary laser-induced breakdown spectroscopy (LIBS) techniques are unsatisfactory for detecting harmful chemicals in fruit and vegetables. In this study, we applied metal nanoparticles to fruit and vegetables samples to improve the ability of LIBS to detect trace pesticide and heavy metal residues in the samples. The nanoparticle-enhanced LIBS technique gave pesticide residue detection limits for fruit and vegetables two orders of magnitude lower than achieved using standard LIBS and heavy metal detection limits markedly better than achieved using standard LIBS. We used the nanoparticle-enhanced LIBS technique to study the distributions of harmful chemicals in vegetable leaves. We found that heavy metals are distributed unevenly in edible plant leaves, the heavy metal concentrations being higher in the veins than in the mesophyll.

Compensation method for the influence of angle of view on animal temperature measurement using thermal imaging camera combined with depth image.

In the study, we proposed an animal surface temperature measurement method based on Kinect sensor and infrared thermal imager to facilitate the screening of animals with febrile diseases. Due to random motion and small surface temperature variation of animals, the influence of the angle of view on temperature measurement is significant. The method proposed in the present study could compensate the temperature measurement error caused by the angle of view. Firstly, we analyzed the relationship between measured temperature and angle of view and established the mathematical model for compensating the influence of the angle of view with the correlation coefficient above 0.99. Secondly, the fusion method of depth and infrared thermal images was established for synchronous image capture with Kinect sensor and infrared thermal imager and the angle of view of each pixel was calculated. According to experimental results, without compensation treatment, the temperature image measured in the angle of view of 74° to 76° showed the difference of more than 2°C compared with that measured in the angle of view of 0°. However, after compensation treatment, the temperature difference range was only 0.03-1.2°C. This method is applicable for real-time compensation of errors caused by the angle of view during the temperature measurement process with the infrared thermal imager.

An instantaneous approach for determining the infrared emissivity of swine surface and the influencing factors.

Infrared thermal imaging technology has been widely employed in temperature measurements of human and animals and its accuracy relies on the determination process of the emissivity of the target to a large extent. However, common used methods were unable to determine the emissivity of the surface of living animals and thus lower the accuracy. In this paper, we suggested a new approach to acquire the infrared emissivity of living swine in real time. In the approach, the surface temperature of swine and reference body were measured to compute the emissivity and the measurement process was completed in a non-contact and non-invasive manner. We changed the surface reflection energy of animals and reference body by changing the ambient radiant energy and obtain the surface emissivity in real time without confirming the actual temperature of animal surface. In this way, the infrared emissivity of the animal surface can be determined instantaneously and without knowing the real temperature. Both swine specimen and a living swine were used in this study. Using this method, we measured the emissivity of different body sites of the swine. The results showed that the emissivity values at different body sites show the significant differences. The emissivity values at trotter and eye were respectively 0.895 and 0.930 and the emissivity on swine surface varied from 0.945 to 0.978. More important, the distribution of the infrared emissivity on a living swine was explored and the detailed differences of the emissivity on a swine surface can be cleanly seen. Furthermore, we studied the influencing factors on the emissivity of animal surface, through measuring the emissivity distribution on swine surface when pig specimens were sprayed with water on the surface or heated using this method. This study is of great significance for the accurate measurement of swine surface temperature.

[Research on Grape Deterioration Process via Volatiles -Using Long Optical-Path Infrared Spectroscopy and Simplified E-Nose].

Grapes vaporize volatiles in specific compositions and concentrations during deterioration processes. Our previous study demonstrated that it is possible to analyze grapes spoilage stages by using the infrared spectra of their volatiles. However, only the spectral characteristics of alcohol, ethyl acetate and carbon dioxide were observed in the experiment because of the low concentration of the volatiles. In this paper, the sensitivity of the spectrometry system was enhanced by increasing the optical-path with multi-reflecting mirrors. We used the new spectrometry system to study the details of the infrared spectra of the volatiles from grapes during spoilage, and observed the spectral characteristics of several kinds of ethanol, esters, aldehyde and ethylene. The concentrations of some components in the volatiles changes with storage time, which can be a biomarker to represent the spoilage stages of grapes. Chemometrics were used to analyze the spectral bands of ethanol and esters, demonstrating there are obvious differences between fresh and decayed grapes. Furthermore, we developed a simplified E-nose system comprised by sensor array, based on the results of spectral analysis. The classification and discrimination of grape spoilage were tested with E-nose. This was a further study of the previous publication and had given a more precise observation of the infrared spectral characteristics of the volatiles from decayed grapes. This study provided a basis for developing real-time monitoring techniques of fruits deterioration.

[Application of Fourier transform infrared spectroscopy in identification of wine spoilage].

In the present work, fresh and spoiled wine samples from three wines produced by different companies were studied u- sing Fourier transform infrared (FTIR) spectroscopy. We analyzed the physicochemical property change in the process of spoil- age, and then, gave out the attribution of some main FTIR absorption peaks. A novel determination method was explored based on the comparisons of some absorbance ratios at different wavebands although the absorbance ratios in this method were relative. Through the compare of the wine spectra before and after spoiled, the authors found that they were informative at the bands of 3,020~2,790, 1,760~1,620 and 1,550~800 cm(-1). In order to find the relation between these informative spectral bands and the wine deterioration and achieve the discriminant analysis, chemometrics methods were introduced. Principal compounds analysis (PCA) and soft independent modeling of class analogy (SIMCA) were used for classifying different-quality wines. And partial least squares discriminant analysis (PLS-DA) was applied to identify spoiled wines and good wines. Results showed that FTIR technique combined with chemometrics methods could effectively distinguish spoiled wines from fresh samples. The effect of classification at the wave band of 1 550-800 cm(-1) was the best. The recognition rate of SIMCA and PLSDA were respectively 94% and 100%. This study demonstrates that Fourier transform infrared spectroscopy is an effective tool for monitoring red wine's spoilage and provides theoretical support for developing early-warning equipments.

Analyzing strawberry spoilage via its volatile compounds using longpath Fourier transform infrared spectroscopy.

The volatile compounds from fruits vary based on the spoilage stage. We used FTIR spectroscopy to analyze and to attempt to identify the spoilage process of strawberries. To enhance the sensitivity of the measuring system, we increased the optical pathlength by using multi-reflecting mirrors. The volatile compounds that were vaporized from strawberries in different spoilage stages were tested. We analyzed the spectra and found that the concentrations of esters, alcohols, ethylene, and similar compounds changed with deterioration. The change patterns of the infrared spectra for the volatiles were further examined using 2D correlation spectroscopy. We analyzed the spectral data using PCA and were able to distinguish the fresh, slightly spoiled strawberries from the seriously spoiled strawberries. This study demonstrates that FTIR is an effective tool for monitoring strawberry spoilage and for providing status alerts.

[Pretreatment method of near-infrared diffuse reflection spectra used for sugar content prediction of pears].

The content of sugar is an important quality index for pears. However, the traditional sugar measurement methods are time-consuming and destructive. In the present study, the authors measured the sugar content of pears using visible and near infrared diffuse reflection spectroscopy. The pretreatment methods of multiplicative scatter correction (MSC), baseline correction, standard normal variate (SNV) transformation, and moving average algorithms were used on the original absorbance spectrum. Results indicate that the absorbance spectra after pretreatment are better than the original absorbance spectra for prediction. Partial least squares (PLS) regression was also used on the original absorbance spectrum and the absorbance spectrum after moving average and baseline correction. It follows that the forecast accuracy of the absorbance spectra after moving average is higher than that of the original absorbance spectra. The models gave good predictions of the sugar content of pears, with corresponding r values of 0.990 8, and standard errors of predictions of 0.019 0.

[Determination of potassium in farmland soil using laser-induced breakdown spectroscopy].

The real-time measurement of potassium in farmland soil has great importance. A method to determine the potassium content in farmland soil based on laser-induced breakdown spectroscopy (LIBS) was studied using a LIBS equipment consisting of a 1,064 nm laser generator and a high resolution spectrometer. The farmland soil samples with potassium content in the range of 8.74-34.56 g.kg-1 were analyzed. The 766.49 nm was chosen as the analysis line, by comparing the potassium atom characteristic lines of 404.40, 404.72, 766.49 and 769.90 nm. The errors of characteristic line strength caused by the laser stability and random noise was analyzed. The silicon, which is nearly constant in farmland soil, was chosen as the standard element, and a calibration model between the ratio of potassium to silicon (K/Si) and the potassium content was established. The linear fitting degree of the calibration curve was 0.935, and the relative standard deviation of the calibration model for prediction set samples was 9.26%.

[Laser-induced fluorescence spectroscopy characterization of farmland soil moisture content].

Online measurement of soil moisture is significant for agricultural production. The abundance and deficiency of leaf water shortage has been able to effect measured by fluorescence, but the research of correlation between soil moisture and laser-induced fluorescence spectroscopy has not been carried out yet. In this paper, the relationship between laser-induced plant chlorophyll fluorescence and soil moisture was studied. In the experiment with rice as the research object, the chlorophyll fluorescence induced by a 450 nm LED light source was measured by a Y-shaped fiber probe, and the soil moisture was obtained by TDR sensors. The changes in the peak intensity near 743 nm of chlorophyll fluorescence under continuous water stress and intermittent water stress were studied. The result showed that the intensity decreased with the soil moisture content. Finally, the model between the soil water content and the intensity of chlorophyll fluorescence under continuous water stress was created by using Lorentzian equation, and the coefficient of determination (R2) of the model was high. The result indicated that the method mentioned in paper can be applied to measure soil moisture in agricultural production.