Search Results (19)

In this study, we demonstrate the reflectance spectrum of one-dimensional photonic crystals comprising two different types of metamaterials. In this regard, the designed structure can act as a simple and efficient detector for fat concentrations in milk samples. Here, the hyperbolic and gyroidal metamaterials represent the two types of metamaterials that are stacked together to construct the candidate structure; meanwhile, the designed 1D PCs can be simply configured as [G(ED)^m]^S. Here, G refers to the gyroidal metamaterial layers in which Ag is designed in a gyroidal configuration form inside a hosting medium of TiO₂. In contrast, (ED) defines a single unit cell of the hyperbolic metamaterials in which two layers of porous SiC (E) and Ag (D) are combined together. It is worth noting that our theoretical and simulation methodology is essentially based on the effective medium theory, characteristic matrix method, Drude model, Bruggeman’s approximation, and Sellmeier formula. Accordingly, the numerical findings demonstrate the emergence of three resonant peaks at a specified wavelength between 0.8 μm and 3.5 μm. In this context, the first peak located at 1.025 μm represents the optimal one regarding the detection of fat concentrations in milk samples due to its low reflectivity and narrow full bandwidth. Accordingly, the candidate detector could provide a relatively high sensitivity of 3864 nm/RIU based on the optimal values of the different parameters. Finally, we believe that the proposed sensor may be more efficient compared to other counterparts in monitoring different concentrations of liquid, similar to fats in milk. Full article

Fourier Transform Mid-Infrared Spectroscopy (FT-MIRS) can be used for quantitative detection of milk components. Here, milk samples of 458 Chinese Holstein cows from 11 provinces in China were collected and we established a total of 22 quantitative prediction models in milk fatty acids by FT-MIRS. The coefficient of determination of the validation set ranged from 0.59 (C18:0) to 0.76 (C4:0). The models were adopted to predict the milk fatty acids from 2138 cows and a new high-throughput computing software HiBLUP was employed to construct a multi-trait model to estimate and analyze genetic parameters in dairy cows. Finally, genome-wide association analysis was performed and seven novel SNPs significantly associated with fatty acid content were selected, investigated, and verified with the FarmCPU method, which stands for “Fixed and random model Circulating Probability Unification”. The findings of this study lay a foundation and offer technical support for the study of fatty acid trait breeding and the screening and grouping of characteristic dairy cows in China with rich, high-quality fatty acids. It is hoped that in the future, the method established in this study will be able to screen milk sources rich in high-quality fatty acids. Full article

The detection of the amount of aflatoxin M1 (AFM1) in milk is crucial for food safety. Here, we utilize a fiber optic (FO) localized surface plasmon resonance (LSPR) biosensor by constructing gold nanoparticle (AuNP) multimers, in which the nanogaps amplified the LSPR signal by the hot spot effect, and achieved a highly sensitive detection of f AFM1. Through the optimization of parameter conditions for the fabrication of the sensor and detection system, a high performance result from the FO LSPR biosensor was obtained, and the method for AFM1 detection was established, with a wide detection range of 0.05–100 ng/mL and a low limit of detection (LOD) of 0.04 ng/mL, and it has been successfully validated with the actual sample milk. Therefore, it is a good strategy to fabricate highly sensitive FO LSPR sensors for detecting AFM1 by constructing AuNP multimers, and this approach is suitable for developing other biosensors. Full article

Accurately measuring leaf chlorophyll content (LCC) is crucial for monitoring maize growth. This study aims to rapidly and non-destructively estimate the maize LCC during four critical growth stages and investigate the ability of phenological parameters (PPs) to estimate the LCC. First, four spectra were obtained by spectral denoising followed by spectral transformation. Next, sensitive bands (R_λ), spectral indices (SIs), and PPs were extracted from all four spectra at each growth stage. Then, univariate models were constructed to determine their potential for independent LCC estimation. The multivariate regression models for the LCC (LCC-MR) were built based on SIs, SIs + R_λ, and SIs + R_λ + PPs after feature variable selection. The results indicate that our machine-learning-based LCC-MR models demonstrated high overall accuracy. Notably, 83.33% and 58.33% of these models showed improved accuracy when the R_λ and PPs were successively introduced to the SIs. Additionally, the model accuracies of the milk-ripe and tasseling stages outperformed those of the flare–opening and jointing stages under identical conditions. The optimal model was created using XGBoost, incorporating the SI, R_λ, and PP variables at the R3 stage. These findings will provide guidance and support for maize growth monitoring and management. Full article

Milk and dairy products are included in the list of the Food Security Doctrine and are of paramount importance in the diet of the human population. At the same time, the presence of many macro- and microcomponents in milk, as available sources of carbon and energy, as well as the high activity of water, cause the rapid development of native and pathogen microorganisms in it. The goal of the work was to assess the possibility of using an array of gas chemical sensors based on piezoquartz microbalances with polycomposite coatings to assess the microbiological indicators of milk quality and to compare the microflora of milk samples. Piezosensors with polycomposite coatings with high sensitivity to volatile compounds were obtained. The gas phase of raw milk was analyzed using the sensors; in parallel, the physicochemical and microbiological parameters were determined for these samples, and species identification of the microorganisms was carried out for the isolated microorganisms in milk. The most informative output data of the sensor array for the assessment of microbiological indicators were established. Regression models were constructed to predict the quantity of microorganisms in milk samples based on the informative sensors’ data with an error of no more than 17%. The limit of determination of QMAFAnM in milk was 243 ± 174 CFU/cm³. Ways to improve the accuracy and specificity of the determination of microorganisms in milk samples were proposed. Full article

The aim of this study was to construct an enhanced selection index using the genomic and economic parameters of new health disorders and current production and functional traits. Genomic evaluation for the incidence of clinical mastitis (CM), three claw disease traits, retained placenta (RET), metritis (MET), and cystic ovaries (CYS) was performed using linear animal models based on producer-recorded data. Good correlations among the health disorders were found, and their heritability estimates did not exceed 7%. Economic weights (EWs) for the health disorders were EUR −132.10 for CM, EUR −128.87 for overall claw diseases, EUR −52.10 for RET, EUR −80.48 for MET, and EUR −16.16 for CYS. These EWs indicate changes in the present value of the annual profit per cow when increasing the incidence of the traits by one case per cow year. Selection using the enhanced index resulted in favourable responses for most of the new health disorders (e.g., −0.001 and −0.006 cases of RET and MET per cow year, respectively), and also in the current breeding objective traits (+49 kg of milk, −0.02% of calf losses). An index contribution of 7% for the new health disorders was assessed as acceptable for the breeders. Full article

A meta-analysis was conducted with an aim to quantify the beneficial effects of nine different dietary rumen modulating strategies which includes: the use of plant-based bioactive compounds (saponin, tannins, oils, and ether extract), feed additives (nitrate, biochar, seaweed, and 3-nitroxy propanol), and diet manipulation (concentrate feeding) on rumen fermentation, enteric methane (CH₄) production (g/day), CH₄ yield (g/kg dry matter intake) and CH₄ emission intensity (g/kg meat or milk), and production performance parameters (the average daily gain, milk yield and milk quality) of ruminant livestock. The dataset was constructed by compiling global data from 110 refereed publications on in vivo studies conducted in ruminants from 2005 to 2023 and anlayzed using a meta-analytical approach.. Of these dietary rumen manipulation strategies, saponin and biochar reduced CH₄ production on average by 21%. Equally, CH₄ yield was reduced by 15% on average in response to nitrate, oils, and 3-nitroxy propanol (3-NOP). In dairy ruminants, nitrate, oils, and 3-NOP reduced the intensity of CH₄ emission (CH₄ in g/kg milk) on average by 28.7%. Tannins and 3-NOP increased on average ruminal propionate and butyrate while reducing the acetate:propionate (A:P) ratio by 12%, 13.5% and 13%, respectively. Oils increased propionate by 2% while reducing butyrate and the A:P ratio by 2.9% and 3.8%, respectively. Use of 3-NOP increased the production of milk fat (g/kg DMI) by 15% whereas oils improved the yield of milk fat and protein (kg/d) by 16% and 20%, respectively. On the other hand, concentrate feeding improved dry matter intake and milk yield (g/kg DMI) by 23.4% and 19%, respectively. However, feed efficiency was not affected by any of the dietary rumen modulating strategies. Generally, the use of nitrate, saponin, oils, biochar and 3-NOP were effective as CH₄ mitigating strategies, and specifically oils and 3-NOP provided a co-benefit of improving production parameters in ruminant livestock. Equally concentrate feeding improved production parameters in ruminant livestock without any significant effect on enteric methane emission. Therefore, it is advisable to refine further these strategies through life cycle assessment or modelling approaches to accurately capture their influence on farm-scale production, profitability and net greenhouse gas emissions. The adoption of the most viable, region-specific strategies should be based on factors such as the availability and cost of the strategy in the region, the specific goals to be achieved, and the cost–benefit ratio associated with implementing these strategies in ruminant livestock production systems. Full article

Milk is an important and necessary food product for reducing morbidity in the human body. There are numerous misconceptions around milk and dairy products in this regard. At the same time, one of the most time-consuming indicators of raw milk comprises its microbiological parameters. The purpose of this research is to study the gas phase of raw milk samples, using piezoelectric sensors with polycomposite coatings, to predict its physicochemical or microbiological properties. The sorption of volatile compounds onto the coatings based on chitosan–micellar-casein concentrate with polymeric sorbents was studied. This array was employed to analyze the gas phase over raw milk samples. It evaluated the physicochemical indicators of milk (the contents of fat, protein, and solid substances; the acidity) and the microbiological indicators (the total microbial count; the presence of mold, yeasts, or pathogenic microorganisms). The influence of several factors on the composition of volatile compounds in milk was evaluated using the output data of the sensors. These are the injector or frontal mode of inputting the gas phase into the detection cell, the processing of milk samples via ultrasound and microwave radiation, and the introduction of glucose and hydrogen peroxide additives into samples. Statistically significant correlations have been established between the sensor output data and the physicochemical or microbiological indicators of raw milk samples. The regression model was constructed using partial least squares regression to predict the total microbial count of milk based on the output data of piezoelectric sensors with composite coatings, with an appropriate error. Full article

Milk is one of the preferred beverages in modern healthy diets, and its freshness is of great significance for product sales and applications. By combining the two-dimensional (2D) correlation spectroscopy technique and chemometrics, a new method based on visible/near-infrared (Vis/NIR) spectroscopy was proposed to discriminate the freshness of milk. To clarify the relationship be-tween the freshness of milk and the spectra, the changes in the physicochemical indicators of milk during storage were analyzed as well as the Vis/NIR spectra and the 2D-Vis/NIR correlation spectra. The threshold-value method, linear discriminant analysis (LDA) method, and support vector machine (SVM) method were used to construct the discriminant models of milk freshness, and the parameters of the SVM-based models were optimized by the grid search method and particle swarm optimization algorithm. The results showed that with the prolongation of storage time, the absorbance of the Vis/NIR spectra of milk gradually increased, and the intensity of autocorrelation peaks and cross peaks in synchronous 2D-Vis/NIR spectra also increased significantly. Compared with the SVM-based models using Vis/NIR spectra, the SVM-based model using 2D-Vis/NIR spectra had a >15% higher prediction accuracy. Under the same conditions, the prediction performances of the SVM-based models were better than those of the threshold-value-based or LDA-based models. In addition, the accuracy rate of the SVM-based model using the synchronous 2D-Vis/NIR autocorrelation spectra was >97%. This work indicates that the 2D-Vis/NIR correlation spectra coupled with chemometrics is a great pattern to rapidly discriminate the freshness of milk, which provides technical support for improving the evaluation system of milk quality and maintaining the safety of milk product quality. Full article

The major focus of this study was determining the effectiveness of new construction specifications regarding the method of cement grout injection for the jet grouting system (high-pressure injection stirring method), with the objective of developing a sustainable ground improvement method. The recent innovative jet grouting techniques allow for improvement at middle pressure, but the mud discharge amount is drastically increased. This produces a serious environmental and financial burden during the disposal of mud discharge. This study attempts to develop a sustainable jet grouting method. The simulation model was prepared by the 3D AutoCAD software, and the analysis was conducted using the moving particle semi-implicit method (MPS method). The study focused on the changes that occurred in the mixing ratio of cement slurry and soil due to the changes made in cement milk spraying during the construction phase and compared it with the traditional method of cement milk spraying. All other construction parameters were kept the same for both cases, and the comparison result shows that the modified construction specification provides a denser and larger improved soil body than the traditional method. Furthermore, the density of the number of particles was determined at the upper, middle, and lower portions of the improved body for comparison. Full article

A compact laser scatterometric device for determining the fat percentage of milk filling a cylindrical tube has been designed. The device operates by detecting the angular distribution of the scattered radiation of a semiconductor laser using an axial array of photodiodes. We have experimentally found that the light-scattering indicatrix in cow milk has a monotonous dependence on milk fat content. The intensity at side- or forward-scattering angles normalized to the backscattering intensity proves to be a reliable, informative parameter. A polynomial approximation for the calibration curve of fat percentage versus normalized scattering intensity is constructed to enable fat content measurements in the fairly wide range of ~0.01–10%. Furthermore, the intensity at forward scattering angles responds to the presence of large-scale particles in milk. The device was tested in a laminar flow regime at milk flow rates up to 100 mL/s. Full article

The construction of novel fluorescent nanozymes is highly desirable for providing new strategies for nanozyme-based sensing systems. Herein, a novel ratiometric fluorescence sensing platform was constructed based on carbon dots (CDs) as both luminophores and nanozymes, which could realize the sensitive detection of hydrogen peroxide (H₂O₂). CDs with peroxidase-mimicking activity were prepared with a one-step hydrothermal method using L-histidine as an inexpensive precursor. CDs had bright blue fluorescence. Due to the pseudo-peroxidase activity, CDs catalyzed the oxidation of o-phenylenediamine (OPD) with H₂O₂ to generate 2,3-diaminophenolazine (DAP). The fluorescence resonance energy transfer (FRET) between CDs and DAP resulted in a decrease in the fluorescence of CDs and an increase in the fluorescence of DAP, leading to a ratiometric fluorescence system. The free radical trapping experiment was used to investigate the reactive oxygen radicals (ROS) in the catalytic process of CD nanozymes. The enzymatic parameters of CD nanozymes, including the Michaelis constant (K_m) and the maximum initial reaction velocities (V_max), were investigated. A good affinity for both OPD and H₂O₂ substrates was proven. Based on the FRET between CDs and OPD, a ratiometric fluorescence analysis of H₂O₂ was achieved and results ranged from 1 to 20 μM and 20 to 200 μM with a low limit of detection (LOD, 0.42 μM). The detection of H₂O₂ in milk was also achieved. Full article

The aims of the study were: (i) to compare survival curves for cows culled for different reasons over three successive lactations using the Kaplan–Meier estimator; (ii) to determine the effects of breeding documentation parameters on cow survival; (iii) to investigate the similarity between culling categories. The survival times for a subset of 347,939 Holstein-Friesian cows culled between 2017 and 2018 in Poland were expressed in months from calving to culling or the end of lactation. The survival tables were constructed for each culling category and lactation number. The survival curves were also compared. The main culling categories were reproductive disorders—40%, udder diseases—13 to 15%, and locomotor system diseases—above 10%. The survival curves for cows from individual culling categories had similar shapes. A low probability of survival curves for metabolic and digestive system diseases and respiratory diseases was observed in each of the three lactations. The contagious disease category was almost non-existent in the first lactation. The greatest influence on the relative culling risk was exerted by age at first calving, lactation length, calving interval, production subindex, breeding value for longevity, temperament, and average daily milk yield. A more accurate method of determining culling reasons would be required. Full article

The aim of this article is to show the relationship between external thermal conditions and the quality of the indoor environment on a dairy farm during the summer. The measurements were carried out on a large dairy farm of Holstein cattle situated in the Czech Republic. The research included the measurement of the cowshed for 440 lactating cows, a milking parlor, a maternity cowshed, a cowshed for dry cows, 69 individual calf hutches, and three outdoor group shelters for calves. The results of the registration measurements of the thermal state parameters outside and inside the buildings were analyzed. The critical and dangerous situations were especially regarding the calves. The highest temperature in the calf hutches was 48 °C with the value of THI_max = 90.1, while in the calf group shelters it was 46.9 °C with the value of THI_max = 89.4. The research results showed that not only the critical values of temperature and the temperature–humidity index that affect the housed animals are important but also the duration for which the animals are exposed to heat stress. The massive masonry constructions of the milking parlor and also of the cowshed for dry cows dampened the temperature rise in these barns, with good values for the attenuation coefficient. Full article

Particle deposition on the surface of a drying chamber is the main drawback in the spray drying process, reducing product recovery and affecting the quality of the product. In view of this, the potential application of chemical surface modification to produce a hydrophobic surface that reduces the powder adhesion (biofouling) on the wall of the drying chamber is investigated in this study. A hydrophobic polydimethylsiloxane (PDMS) solution was used in the vertical dipping method at room temperature to determine the optimum coating parameters on borosilicate glass and stainless steel substrates, which were used to mimic the wall surface of the drying chamber, to achieve highly hydrophobic surfaces. A single-factor experiment was used to define the range of the PDMS concentration and treatment duration using the Response Surface Methodology (RSM). The Central Composite Rotatable Design (CCRD) was used to study the effects of the concentration of the PDMS solution (X₁, %) and the treatment duration (X₂, h) on the contact angle of the substrates (°), which reflected the hydrophobicity of the surface. A three-dimensional response surface was constructed to examine the influence of the PDMS concentration and treatment duration on contact angle readings, which serve as an indicator of the surface’s hydrophobic characteristics. Based on the optimisation study, the PDMS coating for the borosilicate glass achieved an optimum contact angle of 99.33° through the combination of a PDMS concentration of X₁ = 1% (w/v) and treatment time of X₂ = 4.94 h, while the PDMS coating for the stainless steel substrate achieved an optimum contact angle of 98.31° with a PDMS concentration of X₁ = 1% (w/v) and treatment time of X₂ = 1 h. Additionally, the infrared spectra identified several new peaks that appeared on the PDMS-treated surfaces, which represented the presence of Si-O-Si, Si-CH₃, CH₂, and CH₃ functional groups for the substrates coated with PDMS. Furthermore, the surface morphology analysis using the Field Emission Scanning Electron Microscopy (FESEM) showed the presence of significant roughness and a uniform nanostructure on the surface of the PDMS-treated substrates, which indicates the reduction in wettability and the potential effect of unwanted biofouling on the spray drying chamber. The application of PDMS and PTFE on the optimally coated substrates successfully reduced the amount of full cream milk particles that adhered to the surface. The low surface energy of the treated surface (19–27 mJ/m²) and the slightly higher surface tension of the full cream milk (54–59 mJ/m²) resulted in a high contact angle (102–103°) and reduced the adhesion work on the treated substrates (41–46 mJ/m²) as compared to the native substrates. Full article