COMPARATIVE CHARACTERISTICS OF COW AND GOAT MILK COMPONENT BY MIR-SPECTROSCOPY

На основе анализа компонентного состава молока проведено изучение белковой и жировой фракций, метаболитов веществ и соматических клеток для голштинизированных черно-пестрых коров и карачаевских коз в сравнительном аспекте. Молоко коров предназначалось для переработки, а молоко коз использовалось для выкармливания козлят. В этой связи представляет интерес использование экспресс-метода инфракрасной (ИК) спектроскопии для исследования точности прогностической модели анализа молока от разных видов животных, в частности, для определения в образцах содержания жирных кислот (ЖК). Скрининг молока по 25 показателям выполняли с помощью анализатора CombiFOSS 7 DSCC. Установлено, что в молоке коз было достоверно больше жира и белка, насыщенных ЖК (69,59% против 65,67% в коровьем) и более значимых для питания человека полиненасыщенных ЖК (4,05% против 3,66% у коров). Коэффициент детерминации показал высокую значимость совокупных факторов, включенных в GLM-уравнение, для массовой доли лактозы (23,9%), короткоцепочечных ЖК (28,1%), ацетона (24,3%), бетагидроксибутирата (37,9%), точки замерзания молока (46,0%) и мочевины (85,1%). Корреляции между компонентами имели биологическую направленность, характерную для процессов синтеза молока в организме жвачных животных. Проведенный комплексный анализ показал перспективность ИК-спектров для использования как в менеджменте стада коров и коз, так и в накоплении информации для изучения генетической детерминации процессов образования молока у сельскохозяйственных животных. The protein and fat fractions, metabolites and somatic cells count for Holsteinized Black-and-White cows and Karachai goats were studied by in a comparative aspect. The cows’ milk was intended for processing, and milk of goats was used to feed the goatlet. In this regard, to use the express method of infrared (MIR) spectroscopy to study the accuracy of the predictive model for analyzing milk from different animal species, in particular, to determine the content of fatty acids (FA) was interesting. Milk screening for 25 parameters was performed using a CombiFOSS 7 DSCC analyzer. It was found that under the same paratypical conditions, there was significantly more fat and protein in goat milk, however, in terms of lactose content, milk pH values were higher in cows’ milk. Goat milk has a higher content of saturated FAs (69.59% opp. 65.67% in cow milk) and polyunsaturated FAs that are more significant for human nutrition (4.05% opp. 3.66% in cows). The determination coefficient showed the high significance of the aggregate factors included in the GLM equation for the lactose percentage (23.9%), short-chain FA (28.1%), acetone (24.3%), betahydroxybutyrate (37.9%), milk freezing point (46.0%) and urea (85.1%). The correlations between components had a biological orientation that characterized for the milk synthesis processes into the body of ruminants. The analysis showed that MIR spectra are promising for use in the management of a herd of cows and goats, and in the information accumulation for studying the genetic determination of milk processes synthesis in animals.

A highly stable, nanotube-enhanced, CMOS-MEMS thermal emitter for mid-IR gas sensing

The gas sensor market is growing fast, driven by many socioeconomic and industrial factors. Mid-infrared (MIR) gas sensors offer excellent performance for an increasing number of sensing applications in healthcare, smart homes, and the automotive sector. Having access to low-cost, miniaturized, energy efficient light sources is of critical importance for the monolithic integration of MIR sensors. Here, we present an on-chip broadband thermal MIR source fabricated by combining a complementary metal oxide semiconductor (CMOS) micro-hotplate with a dielectric-encapsulated carbon nanotube (CNT) blackbody layer. The micro-hotplate was used during fabrication as a micro-reactor to facilitate high temperature (>700 $$^{\circ }$$ ∘ C) growth of the CNT layer and also for post-growth thermal annealing. We demonstrate, for the first time, stable extended operation in air of devices with a dielectric-encapsulated CNT layer at heater temperatures above 600 $$^{\circ }$$ ∘ C. The demonstrated devices exhibit almost unitary emissivity across the entire MIR spectrum, offering an ideal solution for low-cost, highly-integrated MIR spectroscopy for the Internet of Things.

The Storage Period Discrimination of Bolete Mushrooms Based on Deep Learning Methods Combined With Two-Dimensional Correlation Spectroscopy and Integrative Two-Dimensional Correlation Spectroscopy

Boletes are favored by consumers because of their delicious taste and high nutritional value. However, as the storage period increases, their fruiting bodies will grow microorganisms and produce substances harmful to the human body. Therefore, we need to identify the storage period of boletes to ensure their quality. In this article, two-dimensional correlation spectroscopy (2DCOS) images are directly used for deep learning modeling, and the complex spectral data analysis process is transformed into a simple digital image processing problem. We collected 2,018 samples of boletes. After laboratory cleaning, drying, grinding, and tablet compression, their Fourier transform mid-infrared (FT-MIR) spectroscopy data were obtained. Then, we acquired 18,162 spectral images belonging to nine datasets which are synchronous 2DCOS, asynchronous 2DCOS, and integrative 2DCOS (i2DCOS) spectra of 1,750–400, 1,450–1,000, and 1,150–1,000 cm–1 bands. For these data sets, we established nine deep residual convolutional neural network (ResNet) models to identify the storage period of boletes. The result shows that the accuracy with the train set, test set, and external validation set of the synchronous 2DCOS model on the 1,750–400-cm–1 band is 100%, and the loss value is close to zero, so this model is the best. The synchronous 2DCOS model on the 1,150–1,000-cm–1 band comes next, and these two models have high accuracy and generalization ability which can be used to identify the storage period of boletes. The results have certain practical application value and provide a scientific basis for the quality control and market management of bolete mushrooms. In conclusion, our method is novel and extends the application of deep learning in the food field. At the same time, it can be applied to other fields such as agriculture and herbal medicine.

Diamond-Coated Silicon ATR Elements for Process Analytics

Infrared attenuated total reflection (ATR) spectroscopy is a common laboratory technique for the analysis of highly absorbing liquids or solid samples. However, ATR spectroscopy is rarely found in industrial processes, where inline measurement, continuous operation, and minimal maintenance are important issues. Most materials for mid-infrared (MIR) spectroscopy and specifically for ATR elements do not have either high enough infrared transmission or sufficient mechanical and chemical stability to be exposed to process fluids, abrasive components, and aggressive cleaning agents. Sapphire is the usual choice for infrared wavelengths below 5 µm, and beyond that, only diamond is an established material. The use of diamond coatings on other ATR materials such as silicon will increase the stability of the sensor and will enable the use of larger ATR elements with increased sensitivity at lower cost for wavelengths above 5 µm. Theoretical and experimental investigations of the dependence of ATR absorbances on the incidence angle and thickness of nanocrystalline diamond (NCD) coatings on silicon were performed. By optimizing the coating thickness, a substantial amplification of the ATR absorbance can be achieved compared to an uncoated silicon element. Using a compact FTIR instrument, ATR spectra of water, acetonitrile, and propylene carbonate were measured with planar ATR elements made of coated and uncoated silicon. Compared to sapphire, the long wavelength extreme of the spectral range is extended to approximately 8 μm. With effectively nine ATR reflections, the sensitivity is expected to exceed the performance of typical diamond tip probes.

Age Discrimination of Chinese Baijiu Based on Midinfrared Spectroscopy and Chemometrics

Baijiu is a traditional and popular Chinese liquor which is affected by the storage time. The longer the storage time of Baijiu is, the better its quality is. In this paper, the raw and mellow Baijiu samples from different storage time are discriminated accurately throughout midinfrared (MIR) spectroscopy and chemometrics. Firstly, changing regularities of the substances in Chinese Baijiu are discussed by gas chromatography-mass spectrometry (GC-MS) during the aging process. Then, infrared spectrums of Baijiu samples are processed by smoothing, multivariate baseline correction, and the first and second derivative processing, but no significant variation can be observed. Next, the spectral date pretreatment methods are constructively introduced, and principal component analysis (PCA) and discriminant analysis (DA) are developed for data analyses. The results show that the accuracy rates of samples by the DA method in calibration and validation sets are 91.7% and 100%, respectively. Consequently, an identification model based on support vector machine (SVM) and PCA is established combined with the grid search strategy and cross-validation methods to discriminate the age of Chinese Baijiu validly, where 100% classification accuracy rate is obtained in both training and test sets.

Effect of Different Extraction Methods on the Quality and Biochemical Attributes of Pomegranate Juice and the Application of Fourier Transformed Infrared Spectroscopy in Discriminating Between Different Extraction Methods

This study investigated the effects of extraction methods on the physicochemical, phytochemical, and antioxidant properties of pomegranate juice (cv. Wonderful). In addition, the application of attenuated total reflectance Fourier transformed mid-infrared (ATR-FT-MIR) spectroscopy and chemometrics were explored in order to discriminate between different extraction methods. Juice variants evaluated included juice extracted without crushing the seeds (arils only) using a juice extractor (JE), juice extracted by crushing the seeds using a blender (arils plus seed) (JB), and juice extracted from half fruit using a commercial hand press juicer (CH). Juice extracted from CH had higher total soluble solid (TSS) content (18.20%), TSS/TA ratio (15.83), and color properties (a* = 32.67, b* = 11.80, C* = 34.77) compared with extraction methods JE and JB. The juice extracted from JB showed the highest titratable acidity (2.17%), cloudiness (0.43), and lowest pH value (2.69). The total phenolics and anthocyanin content in the investigated juice ranged from 1.87 to 3.04 g gallic acid equivalent (GAE)/L and 37.74–43.67 mg cyanidin 3-glucoside equivalent/L of crude juice, respectively. Juice extracted from JB and CH was significantly higher in phenolic and anthocyanin compared with JE. Orthogonal partial least squares discriminant analysis (OPLS-DA) and principal component analysis (PCA) were used for classification. Classification accuracy of 100% was achieved between the three methods. The S-line plot revealed that the corresponding wavelength bands within the following regions 1,090, 1,250, 1,750, and 3,200 cm−1 were responsible for discrimination between the different extraction methods. Our results suggest that the main contributor to the discrimination between extraction methods were TSS, TSS/TA, color attributes, and anthocyanin content. Overall, this study has demonstrated that ATR-FT-MIR spectroscopy provides a powerful way to discriminate between juice extraction methods.

A highly stable, nanotube-enhanced, CMOS-MEMS thermal emitter for mid-IR gas sensing

The gas sensor market is growing fast, driven by many socioeconomic and industrial factors. Mid-infrared (MIR) gas sensors offer excellent performance for an increasing number of sensing applications in healthcare, smart homes, and the automotive sector. Having access to low-cost, miniaturized, energy efficient light sources is of critical importance for the monolithic integration of MIR sensors. Here, we present an on-chip broadband thermal MIR source fabricated by combining a complementary metal oxide semiconductor (CMOS) micro-hotplate with a dielectric-encapsulated carbon nanotube (CNT) blackbody layer. The micro-hotplate was used during fabrication as a micro-reactor to facilitate high temperature (>700 • C) growth of the CNT layer and also for post-growth thermal annealing. We demonstrate, for the first time, stable extended operation in air of devices with a dielectric-encapsulated CNT layer at heater temperatures above 600 • C. The demonstrated devices exhibit almost unitary emissivity across the entire MIR spectrum, offering an ideal solution for low-cost, highly-integrated MIR spectroscopy for the Internet of Sensors.