Search Results (38)

Starch is a natural polymer. It is also an important food nutrient. Studies related to starch content testing can provide basic data for starch intake assessments and correlation studies. Meanwhile, data on the starch content in food are important for guiding the population to have a reasonable diet. Starch content directly affects the nutritional value, consumption quality, and processing quality of food. This paper summarized the common starch content detection techniques in food in the past five years, such as titration, spectrophotometry, near-infrared spectroscopy, and other methods. The principles, advantages, and disadvantages of these starch content detection techniques were described and discussed. Their problems in real sample detection (e.g., time-consuming, cumbersome operation, over-reliance on modeling algorithms, etc.) were analyzed. Challenges and future trends are also presented with the expectation of providing useful references for future research and practical applications. This paper provides a direction and research basis for the development of starch content detection techniques for food. It also provides value to related work in starch research. Full article

The use of living Arthrospira platensis (A. platensis) cultures emerges as a promising green solution for the bioremediation of water contaminated by toxic metal waste. The scope of the present study is to evaluate the microalga’s potential in heavy metal remediation, in the case of multi-metal-treated (multi-MT) systems. For this reason, A. platensis cultures were exposed to mono- and multi-metal solutions of Cu, Cd, Ni, Pb, and Zn, and their metal adsorption ability was investigated. The heavy metal removal efficiency of A. platensis cultures was evaluated using atomic absorption spectroscopy (AAS). Additionally, the cultures were examined using Fourier transform infrared (FTIR) spectroscopy, Near-Infrared (NIR) Spectroscopy, UV-Vis spectrophotometry, and optical microscopy, together with pH and electrical conductivity (EC) measurements to evaluate the quality of the cultures and the changes induced by heavy metal stress. The results showed that metal removal is still efficient in multi-MT cultures. In particular, Cu, Cd, Pb, and Zn removal of multi-MT cultures is elevated or relative to the respective removal of the mono-metal-treated (mono-MT) cultures, showing a synergistic or cooperative interaction between the metals, while the removal of Ni of multi-MT cultures decreased compared to Ni of mono-MT cultures, showing an antagonistic interaction to the other metals. The study shows that A. platensis is considered an effective microalga toward the bioremediation of multi-metal polluted cultures. Full article

Reducing energy consumption in buildings is critical to reducing CO₂ emissions and mitigating global warming. Studies have shown that heating and cooling loads account for more than 40% of building energy consumption, and thermochromic glass (TCG) with dynamically adjustable solar transmittance is an excellent way to reduce this load. Although a large number of studies have tested the spectral parameters of TCG in totally transparent and totally turbid states, the impact of dynamic changes in optical properties on the simulation accuracy of building energy consumption has been neglected. In this study, a method is proposed for a hydrogel-type TCG to dynamically test its spectral parameters based on spectrophotometry. The method uses a spectrophotometer and a PID heater to achieve the dynamic optical parameter testing of TCGs at different temperatures. In this paper, the transmission and reflection spectra of the two TCGs at 20~25 °C, 30~35 °C, 40 °C, 45 °C, 50 °C, and 55 °C were obtained, and the regression segmentation functions of visible transmittance and solar transmittance were established. The R² of the function model is 0.99. In addition, the test results show that the thermochromic glass selected in this paper can selectively transmit different wavelengths of light, and its transmission mainly occurs in the visible and near-infrared wavelengths from 320 to 1420 nm, while the transmission rate of other wavelengths is very low. As the temperature increases, the visible, solar, and ultraviolet transmittances decrease at a similar rate. In addition, the higher the temperature acting on the thermochromic (TC) layer, the greater its haze. Full article

The online detection of fertilizer solution information is a crucial link in the implementation of intelligent and precise variable fertilization techniques. However, achieving simultaneous rapid online detection of multiple fertilizer components is still challenging. Therefore, a rapid detection method based on spectrophotometry for qualitative and quantitative identification of four fertilizers (typical N, P, and K fertilizers: KNO₃, (NH₄)₂SO₄, KH₂PO₄, and K₂SO₄) was proposed in this work. Full-scan absorption spectra of fertilizer solutions at varying concentrations were obtained using a UV–visible/near-infrared spectrophotometer. By assessing the linear fit between fertilizer concentration and absorbance at each wavelength within the characteristic band, the characteristic wavelengths for KNO₃, (NH₄)₂SO₄, KH₂PO₄, and K₂SO₄ were identified as 214 nm, 410 nm, 712 nm, and 1708 nm, respectively. The identification method of fertilizer type and the prediction model of concentration were constructed based on characteristic wavelength and the Lambert–Beer law. Based on the above analysis, a four-channel photoelectric sensor was designed with four LEDs emitting wavelengths closely matched to characteristic wavelengths for fertilizer detection. A detection strategy of “qualitative analysis followed by quantitative detection” was proposed to realize the online detection of four fertilizer types and their concentrations. Evaluation of the sensor’s performance showed its high stability, with an accuracy of 81.5% in recognizing fertilizer types. Furthermore, the relative error of the sensor detection was substantially less than ±15% for the fertilizer concentrations not exceeding 80 mg/L. These results confirm the capability of the sensor to meet the practical requirements for online detection of four fertilizer types and concentrations in the field of agricultural engineering. Full article

Cefdinir (CEF) is a semi-synthetic third-generation broad-spectrum oral cephalosporin that exhibits poor solubility at lower pH values. Considering this, pH-modulated CEF solid dispersions (ASDs) were produced by solvent evaporation method employing various hydrophilic carriers and alkalizers. Among different carriers, ASDs produced using PEG 6000 with meglumine as alkalizer were found to significantly increase (p < 0.005) the drug solubility (4.50 ± 0.32 mg/mL) in pH 1.2. Fourier transform infrared spectrophotometry confirmed chemical integrity of CEF while differential scanning calorimetry (DSC) and X-ray diffractometry (XRD) indicated CEF was reduced to an amorphous state in ASD8. Antimicrobial assay performed by well diffusion method against Staphylococcus aureus (MTCC96) and Escherichia coli (MTCC118) demonstrated significantly superior (p < 0.001) efficacy of CEFSD compared to CEF. The porous orodispersible tablets (ODTs) of ASD8 (batch F5) were developed by incorporating ammonium bicarbonate as a subliming agent by direct compression, followed by vacuum drying displayed quick disintegration (27.11 ± 1.96 s) that met compendial norms and near-complete dissolution (93.85 ± 1.27%) in 30 min. The ODTs of ASD8 appear to be a promising platform to mitigate the pH-dependent solubility and dissolution issues associated with CEF in challenging physiological pH conditions prevalent in stomach. Thus, ODTs of ASD8 are likely to effectively manage various infections and avoid development of drug-resistant strains, thereby improving the curing rates. Full article

Accurate and rapid determination of moisture content is essential in crop production and decision-making for irrigation. Near-infrared (NIR) spectroscopy has been shown to be a promising method for determining moisture content in various agricultural products, including herbs and vegetables. This study tested the hypothesis that NIR spectroscopy is effective in accurately measuring the moisture content of Genovese basil (Ocimum basilicum L.), with the objective of developing a respective calibration model. Spectral data were obtained from a total of 120 basil leaf samples over a period of six days. These included freshly harvested and detached leaves, as well as those left in ambient air for 1–6 days. Five spectra were taken from each leaf using a handheld NIR spectrophotometer, which covers the first and second overtones of the NIR spectral region: 950–1650 nm. After the spectral acquisition, the leaves were weighed for fresh mass and then put in an oven for 72 h at 80 °C to determine the dry weight and calculate the reference moisture content. The calibration model was developed using multivariate analysis in MATLAB, including preprocessing and regression modeling. The data obtained from 75% of the samples were used for model training and 25% for validation. The final model demonstrates strong performance metrics. The root mean square error of calibration (RMSEC) is 2.9908, the root mean square error of cross-validation (RMSECV) is 3.2368, and the root mean square error of prediction (RMSEP) reaches 2.4675. The coefficients of determination for calibration (R²C) and cross-validation (R²CV) are consistent, with values of 0.829 and 0.80, respectively. The model’s predictive ability is indicated by a coefficient of determination for prediction (R²P) of 0.86. The range error ratio (RER) stands at 11.045—highlighting its predictive performance. Our investigation, using handheld NIR spectrophotometry, confirms NIR’s usefulness in basil moisture determination. The rapid determination offers valuable insights for irrigation and crop management. Full article

This study investigates the pH values and optical characteristics of Dual Rinse HEDP, either independently or combined with sodium hypochlorite (NaOCl), and compares them to other irrigants used in endodontics. The solutions used in this study were commercially acquired and prepared, followed by pH measurements using a pH meter and spectral analysis using UV/Vis spectrophotometry in specified wavelengths of the ultraviolet (UV) C (190–280 nm), UVB (281–315 nm), UVA (316–400 nm), visible light (VL) (401–780 nm), and near-infrared (NIR) spectra (781–1100 nm). The pH analysis revealed alkaline values for NaOCl, EDTA, Dual Rinse HEDP, and the HEDP + NaOCl combination, an acidic value for citric acid, and nearly neutral values for chlorhexidine and distilled water. Spectral analysis revealed the notable absorption characteristics of endodontic irrigants. In the UV range, all solutions exhibited higher absorption values to water (p < 0.05), with Dual Rinse HEDP resembling EDTA and citric acid, and HEDP + NaOCl resembling NaOCl. The NIR region highlights absorption peaks around 975 nm for all solutions, including NaOCl and Dual Rinse HEDP + NaOCl, suggesting potential applications in laser-activated irrigation. This study provides comprehensive insights into the pH and optical features of endodontic irrigants, emphasizing their potential roles in enhancing disinfection strategies and optimizing laser-activated irrigation protocols. Full article

This paper reports the development of a near-infrared spectroscopy (NIRS) calibration procedure for the determination of sodium and potassium content in cured ham samples. Sliced samples of hams treated with different salts in different percentages were included in the study. Calibration models developed using partial least squares regression were cross-validated and predictive models were tested using the samples of cured ham with low sodium content. The results showed that the developed NIRS procedure is capable of directly measuring the potassium content of packaged dry-cured ham slices with low sodium content with a fitting accuracy of 91.44%, and that it can indirectly determine the sodium content by applying a correction factor to the values obtained for potassium. The prediction error between the calculated and actual sodium values determined using inductively coupled plasma atomic emission spectrophotometry (ICP-AES) was 0.004%, and this confirms that the NIRS procedure is a viable option for the determination of sodium and potassium content in this type of sample. Full article

Wheat is the most important raw material for bakery industries. Real-time grain quality assessment could increase bakery product quality and baking efficiency. The quality assessment of wheat grains can be conducted using modern and non-invasive techniques based on near-infrared spectrophotometry (NIRS) methods for the assessment of gluten content (WetGL), protein content, Zeleny index (ZelenyIdx), grain humidity (Ur), etc. The topic covered in the study is of current interest, is a part of sustainable research, and involves aspects of food quality, one of the concerns addressed by the University of Oradea’s Department of Food Engineering. The present study was carried out in 2020 on eleven wheat lots from Romania and Hungary. Following the NIRS analyses, the results show varied quality for the Romanian and Hungarians wheat lots. The Romanian variety Crisana recorded the highest values for quality parameters, being similar to the Hungarian variety Bekes from Hajdu Bihar County. The statistical analysis was carried out using multivariate analysis (multivariate analysis of variance (MANOVA), canonical variate analysis (CVA) and hierarchical cluster analysis (HCA)), which highlighted which of the batches of wheat grains can be mixed to obtain a raw material of high quality for the bakery industry. Full article

In Lebanon, olive oil is an integral part of its history and culinary traditions. However, the quality of this product, originating from different growing regions of the country, is rarely addressed. The objectives of this study were to compare the fatty acids and phenolic profiles of virgin olive oils produced from two local and eight European varieties, and to use these profiles as a tool for their characterization. Seventy-six samples were collected from two olive-growing regions of Lebanon and at two harvesting times. Fatty acid composition was determined by gas chromatography with a flame ionization detector, total phenols was determined by spectrophotometry and individual phenols by high performance liquid chromatography with diode array detector. All samples were also analyzed using near infrared spectroscopy. The experimental data were collected in numerical matrices and treated by chemometric methods. The results showed the significant effect of the geographical origin, the olive variety and the harvesting time on the ripening and industrial yield of the olives and on the major fatty acids and phenols of olive oil. Moreover, the used chemometric methods allowed the discrimination of European olive varieties based on their high contents of oleic acid, oleacein and oleocanthal. Full article

Scutellaria multicaulis is a medicinal plant indigenous to Iran, Afghanistan, and Pakistan. It has been widely used as a prominent herb in traditional medicine for thousands of years. This plant is reported to contain baicalein, wogonin, and chrysin flavonoids, which are a significant group of chemical ingredients which can cure different diseases, such as breast cancer. S. multicaulis leaf extract was used for the bioreduction of silver nanoparticles (SmL-Ag-NPs), and their phytochemical contents and antioxidant, antibacterial, anti-proliferative, and apoptotic activity were evaluated. Optimal physicochemical properties of SmL-Ag-NPs were obtained by mixing 5% of leaf extract and 2 mM of aqueous AgNO₃ solution and confirmed by characterization studies including UV–visible spectrophotometry, Field Emission Scanning Electron Microscope (FE-SEM), Energy Dispersive X-ray (EDX), Dynamic Light Scattering (DLS), zeta potential, Thermogravimetric analysis (TGA), Surface-enhanced Raman spectroscopy (SERS), X-ray crystallography (XRD), and Fourier transform infrared (FTIR) Spectroscopy. SmL-Ag-NPs exhibited a higher content of total phenol and total flavonoid and potential antioxidant activity. SmL-Ag-NPs also demonstrated dose-dependent cytotoxicity against MDA-MB231 cell multiplication with an IC₅₀ value of 37.62 μg/mL through inducing cell apoptosis. Results show that SmL-Ag-NPs is effective at inhibiting the proliferation of MDA-MB231 cells compared to tamoxifen. This demonstrates that SmL-Ag-NPs could be a bio-friendly and safe strategy to develop new cancer therapies with a reduction in the adverse effects of chemotherapy in the near future. Full article

This research used tomato waste as a substrate (fuel) in Single Chamber-Microbial Fuel Cells (scMFC) on a small scale. The electrochemical properties were monitored, the functional groups of the substrate were analyzed by Fourier Transform Infrared Spectrophotometry (FTIR) and a microbiological analysis was performed on the electrodes in order to identify the microorganisms responsible for the electrochemical process. The results show voltage peaks and an electrical current of 3.647 ± 0.157 mA and 0.957 ± 0.246 V. A pH of 5.32 ± 0.26 was measured in the substrate with an electrical current conductivity of 148,701 ± 5849 mS/cm and an internal resistance (R_int) of 77. 517 ± 8.541 Ω. The maximum power density (PD) displayed was 264.72 ± 3.54 mW/cm² at a current density (CD) of 4.388 A/cm². On the other hand, the FTIR spectrum showed a more intense decrease in its peaks, with the compound belonging to the phenolic groups being the most affected at 3361 cm⁻¹. The micrographs show the formation of a porous biofilm where molecular identification allowed the identification of two bacteria (Proteus vulgaris and Proteus vulgaris) and a yeast (Yarrowia lipolytica) with 100% identity. The data found show the potential of this waste as a source of fuel for the generation of an electric current in a sustainable and environmentally friendly way, generating in the near future a mechanism for the reuse of waste in a beneficial way for farmers, communities and agro-industrial companies. Full article

Near-infrared spectrophotometry and partial least squares regression (PLSR) were evaluated to create a pleasantly simple yet effective approach for measuring HNO₃ concentration with varying temperature levels. A training set, which covered HNO₃ concentrations (0.1–8 M) and temperature (10–40 °C), was selected using a D-optimal design to minimize the number of samples required in the calibration set for PLSR analysis. The top D-optimal-selected PLSR models had root mean squared error of prediction values of 1.4% for HNO₃ and 4.0% for temperature. The PLSR models built from spectra collected on static samples were validated against flow tests including HNO₃ concentration and temperature gradients to test abnormal conditions (e.g., bubbles) and the model performance between sample points in the factor space. Based on cross-validation and prediction modeling statistics, the designed near-infrared absorption approach can provide remote, quantitative analysis of HNO₃ concentration and temperature for production-oriented applications in facilities where laser safety challenges would inhibit the implementation of other optical techniques (e.g., Raman spectroscopy) and in which space, time, and/or resources are constrained. The experimental design approach effectively minimized the number of samples in the training set and maintained or improved PLSR model performance, which makes the described chemometric approach more amenable to nuclear field applications. Full article

To improve beef quality, a selection of specific breeds for crossbreeding, genotyping, and selection of specific candidate genes in breeding animals can be some of the solutions. The objective of this study was to determine the effects of FASN, SCD, and GH genes on carcass fatness and fatty acid (FA) composition of intramuscular lipids of crossbred Holstein × beef breeds (Simmental, Belgian Blue, Limousin, and Piemontese). The allelic and genotypic distribution of polymorphisms in the FASN, SCD, and GH genes was studied in 80 crossbreed animals. Genomic DNA was isolated from musculus longissimus dorsi, whose chemical composition was determined by near infrared transmittance spectrophotometry, while the fatty acid composition was determined by gas chromatography. DNA polymorphism was analyzed by restriction fragment length polymorphism analysis. The FASN (g. 17924A>G) polymorphism was significantly associated with C19:1 n-9 and C24:1 n-9, whereas GH (g.2141C>G) was significantly associated with C16:0 and C20:1 n-9. The SCD (g.8586C>T) polymorphism was significantly associated with C16:0, C18:0, C20:0, C14:1 n-5, C16:1, C18:1, C18:2 n-6, C18:3 n-3, C20:2 n-6, and C20:4 n-6, and analyzed the sum and ratios of fatty acids. Sex had significant effect on carcass fatness and fatty acid composition. This study provided useful results for the above candidate genes and their association with some FA, supporting their influence as genes associated with fats and fatty acid composition in beef meat. Full article

The contamination of agricultural products, such as vegetables, by pesticide residues has received considerable attention worldwide. Pesticide residue on vegetables constitutes a potential risk to human health. In this study, we combined near infrared (NIR) spectroscopy with machine learning algorithms, including partial least-squares discrimination analysis (PLS-DA), support vector machine (SVM), artificial neural network (ANN), and principal component artificial neural network (PC-ANN), to identify pesticide residue (chlorpyrifos) on bok choi. The experimental set comprised 120 bok choi samples obtained from two small greenhouses that were cultivated separately. We performed pesticide and pesticide-free treatments with 60 samples in each group. The vegetables for pesticide treatment were fortified with 2 mL/L of chlorpyrifos 40% EC residue. We connected a commercial portable NIR spectrometer with a wavelength range of 908–1676 nm to a small single-board computer. We analyzed the pesticide residue on bok choi using UV spectrophotometry. The most accurate model correctly classified 100% of the samples used in the calibration set in terms of the content of chlorpyrifos residue on samples using SVM and PC-ANN with raw data spectra. Thus, we tested the model using an unknown dataset of 40 samples to verify the robustness of the model, which produced a satisfactory F1-score (100%). We concluded that the proposed portable NIR spectrometer coupled with machine learning approaches (PLS-DA, SVM, and PC-ANN) is appropriate for the detection of chlorpyrifos residue on bok choi. Full article