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Bimetallic Core Shelled Nanoparticles (Au@AgNPs) for Rapid Detection of Thiram and Dicyandiamide Contaminants in Liquid Milk Using SERS
摘要： Existing methods for contaminants detection in liquid milk are complex, requires chemicals and time-consuming experimental procedure. In this study, SERS based on bimetallic core shelled nanoparticles was employed for simultaneous and fast detection of thiram and dicyandiamide (DCD) in the milk. Spectra ranging from 400 to 1700 cm-1 were selected to examine thiram (0.5, 1, 2, 5 and 10 ppm) and DCD (20, 40, 80,160 and 320 ppm), by employing 28 nm gold cores and silver-shell thickness of 8 nm. A strong peak at 1379 cm-1 was ascribed to thiram with LOD of 0.21 ppm and R2 of 0.9896, whereas a band at 929 cm-1 was associated with DCD, delivering LOD of 14.88 ppm and R2 of 0.9956. The proposed method could achieve results within 34 min and this ecofriendly method can be further employed for simultaneous and rapid screening of other accidental contaminants in milk.
关键词： SERS,dicyandiamide,milk adulteration,thiram
更新于2025-09-23 15:19:57
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Online Milk Quality Assessment during Milking Using Near-infrared Spectroscopic Sensing System
摘要： In recent times, there has been an urgent requirement for a technique that can be used by dairy farmers to assess the quality of milk of an individual cow during milking. A near-infrared (NIR) spectroscopic sensing system was designed on an experimental basis for the online assessment of the three major milk constituents (fat, protein, and lactose), solids not fat (SNF), milk urea nitrogen (MUN), and somatic cell count (SCC). This system was used to obtain the NIR spectra of non-homogenized milk during milking over a wavelength range of 700 to 1,050 nm. Calibration models for predicting three major milk constituents, SNF, MUN and SCC of non-homogenized milk were developed, and the precision and accuracy of the models were validated. The coefficients of determination, standard errors of prediction, and bias values showed high levels of precision and accuracy for the prediction of the considered parameters. The results indicated that the developed NIR spectroscopic sensing system can be used to assess milk quality in real-time during milking. This system can provide dairy farmers with information concerning milk quality and physiological condition of each cow, and can therefore optimize dairy farm management.
关键词： calibration models,milk constituents,somatic cell count,solids not fat,milk urea nitrogen
更新于2025-09-19 17:13:59
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Detection of Chlortetracycline Hydrochloride in Milk with Solid SERS Substrate Based on Self-assembled Gold Nanobipyramids
摘要： In this paper, a high-yield, monodisperse Au nanobipyramids (Au NBs) sol was prepared by seed-mediated method, and gold nanoparticles were assembled on the surface of the silicon wafer by self-assembly technology to obtain a solid SERS substrate. Scanning electron microscopy (SEM) showed that the average length of Au NBs was 34.31 nm, and the analysis enhancement factor (AEF) was approximately 7.3×105 with rhodamine 6G (R6G) as a probe. SERS detection of chlortetracycline hydrochloride (CCH) in milk was performed utilizing the prepared Au NBs substrate, and the limit of detection was 0.01 mg/mL. In the range of 0.01~1 mg/mL, the mass concentration of CCH and SERS signal intensity satisfied the linear relationship of y=258.467x+150.501 and the value of correlation coefficient was 0.9785. In addition, the recovery of spiked samples fluctuated between 96.80% to 111.38%. These results proved that the method is simple and fast, and it is promising to be applied to the field detection of antibiotics in milk.
关键词： chlortetracycline hydrochloride,milk,self-assembly,Surface enhanced Raman spectroscopy,Au nanobipyramids
更新于2025-09-19 17:13:59
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Robust Fourier transformed infrared spectroscopy coupled with multivariate methods for detection and quantification of urea adulteration in fresh milk samples
摘要： Urea is added as an adulterant to give milk whiteness and increase its consistency for improving the solid not fat percentage, but the excessive amount of urea in milk causes overburden and kidney damages. Here, an innovative sensitive methodology based on near‐infrared spectroscopy coupled with multivariate analysis has been proposed for the robust detection and quantification of urea adulteration in fresh milk samples. In this study, 162 fresh milk samples were used, those consisting 20 nonadulterated samples (without urea) and 142 with urea adulterant. Eight different percentage levels of urea adulterant, that is, 0.10%, 0.30%, 0.50%, 0.70%, 0.90%, 1.10%, 1.30%, and 1.70%, were prepared, each of them prepared in triplicates. A Frontier NIR spectrophotometer (BSEN60825‐1:2007) by Perkin Elmer was used for scanning the absorption of each sample in the wavenumber range of 10,000–4,000 cm-1, using 0.2 mm path length CaF2 sealed cell at resolution of 2 cm-1. Principal components analysis (PCA), partial least‐squares discriminant analysis (PLS‐DA), and partial least‐squares regressions (PLSR) methods were applied for the multivariate analysis of the NIR spectral data collected. PCA was used to reduce the dimensionality of the spectral data and to explore the similarities and differences among the fresh milk samples and the adulterated ones. PLS‐DA also showed the discrimination between the nonadulterated and adulterated milk samples. The R‐square and root mean square error (RMSE) values obtained for the PLS‐DA model were 0.9680 and 0.08%, respectively. Furthermore, PLSR model was also built using the training set of NIR spectral data to make a regression model. For this PLSR model, leave‐one‐out cross‐validation procedure was used as an internal cross‐validation criteria and the R‐square and the root mean square error (RMSE) values for the PLSR model were found as 0.9800 and 0.56%, respectively. The PLSR model was then externally validated using a test set. The root means square error of prediction (RMSEP) obtained was 0.48%. The present proposed study was intended to contribute toward the development of a robust, sensitive, and reproducible method to detect and determine the urea adulterant concentration in fresh milk samples.
关键词： urea,principal components analysis,partial least‐squares regressions,milk adulteration,NIR spectroscopy,partial least‐squares discriminant analysis
更新于2025-09-19 17:13:59
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SERS detection of sodium thiocyanate and benzoic acid preservatives in liquid milk using cysteamine functionalized core-shelled nanoparticles
摘要： A cysteamine functionalized core shelled nanoparticles (Au@Ag-CysNPs) was presented for simultaneous and rapid detection of sodium thiocyanate (STC) and benzoic acid (BA) preservatives in liquid milk using surface-enhanced Raman spectroscopy (SERS) technique. A spectrum covering 350-2350 cm-1 region was selected to detect STC with concentrations ranging from 0.5 to 10 mg/L and BA with concentrations ranging from 15 to 240 mg/L in milk samples. Characterization of nanoparticles using high-resolution TEM confirmed that the successful synthesis of Au@AgNPs with core (gold) size of 28 nm and shell (silver) thickness of about 5 nm was grafted with 120 μL of 0.1 nM cysteamine hydrochloride. Results showed that Au@Ag-CysNPs could be used to detect STC up to 0.03 mg/L with a limit of quantification (LOQ) of 0.039 mg/L and a coefficient of determination (R2) of 0.9833 in the milk sample. For detecting BA, it could be screened up to 9.8 mg/L with LOQ of 10.2 mg/L and R2 of 0.9903. The proposed substrate was also highly sensitive and the employed method involved only minor sample pretreatment steps. It is thus hoped that the new substrate could be used in the screening of prohibited chemicals in complex food matrices in future studies.
关键词： SERS,milk adulteration,sodium thiocyanate,nanoparticles,benzoic acid
更新于2025-09-16 10:30:52
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Crowdfunding preferences for a sustainable milk product with integrated photovoltaic water pumping system in China
摘要： This paper studies the role of potential investors in financing renewable energy systems—specifically, relating to crowdfunding as a financing mechanism, with the enhancement of internet and social-media tools. The research question in this study is whether crowdfunding with a novel socio-technical product reward program attracts potential customers to a more sustainable milk product with a specific integrated photovoltaic water pumping (PVWP) system. The particular case study we empirically investigated is product reward crowdfunding in dairy milk production in China. The milk production chain was supplied by PVWP system integration, which generated solar energy both for feed production for dairy cows and for the operation of dairy farms. 48 semi-structured in-depth interviews were conducted between the research team and customers in order to perform qualitative analyses of the determinants of customers’ milk purchase behaviors. In addition, 357 online surveys were collected for quantitative analysis. Binary and ordered probit regressions were employed to use survey date to systematically estimate purchase intention and willingness-to-pay for sustainable milk. Customer behaviors, environmental consciousness, and individual socio-demographic factors were investigated as potential explanatory variables. Over 82% of the survey participants showed intentions to purchase the sustainable milk with the PVWP system. In the survey and interview samples, results showed that milk quality, nutrition improvement, emissions reduction, and environmental benefits attributed to the integrated PVWP system were the major factors considered by interviewees who showed intentions to purchase the crowdfunded dairy milk. Regression model results suggested that potential customers with higher income levels, and those of parenting age, and those with young children or planning to have children, had a higher willingness-to-pay than other customers for the crowdfunded sustainable dairy milk. The familiarity with and popularity of online shopping and pre-sale purchases in China made customers more open to and proactive towards pre-pay and crowdfunding mechanisms. This article evaluated key factors which may influence potential customers for crowdfunding, and used a discrete choice model to estimate customers’ willingness-to-pay for reward-based projects. These results could help producers of sustainable milk products to identify potential target groups in China and estimate market demand. This exploratory study could provide a framework with both quantitative and qualitative assessment of crowdfunding for renewable energy systems in a national or international context.
关键词： Discrete choice model,Photovoltaic water pumping,Sustainable milk,Crowdfunding,Willingness-to-pay
更新于2025-09-16 10:30:52
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Quantitative SERS assay on a single chip enabled by electrochemically assisted regeneration: a method for detection of melamine in milk
摘要： Reusability of sensors is relevant when aiming to decrease variation between measurements, cost and time of analysis. We present an electrochemically assisted surface-enhanced Raman spectroscopy (SERS) platform with the capability to reverse the analyte-surface interaction, without damaging the SERS substrate, allowing for efficient sensor reuse. The platform was used in combination with a sample pre-treatment step, when detecting melamine from milk. We found that the electrochemically enhanced analyte-surface interaction results in significant improvement in detection sensitivity, with detection limits (0.01 ppm in PBS and 0.3 ppm in milk) below the maximum limit allowed in food samples. The reversibility of interaction enabled continuous measurement in aqueous solution and a complete quantitative assay on a single SERS substrate.
关键词： Reusability,Quantification,SERS,Reversibility,Melamine,Milk,Gold-capped (Au-capped) Si nanopillars,EC-SERS
更新于2025-09-16 10:30:52
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Purchase Intention for Crowd-funded Milk Products with Integrated Photovoltaic Water Pumping Systems in China
摘要： In comparison with current financing mechanisms for renewable energy systems, crowd-funding financing mechanism offers a new potential source of financing with recent use of social media. Crowd-funding financing mechanism can also increases the social supports for renewable energy systems as users and investors turn to be more actively engaged in energy systems. As a new potential source of financing, crowd-funding mechanism has different forms, including donation, lending, equity and product reward approaches. In this paper, discrete choice model was used to explore whether crowd-funding financing with a novel sociotechnical product reward practice, has the attractions for potential customers to pay for a more sustainable milk product with distributed photovoltaic (PV) system. We empirically investigated the reward-base crowd funding with the specific integrated photovoltaic water pumping (PVWP) system in dairy milk production in China. 48 in-depth interviews were adopted for qualitative analysis of determinants of customer milk purchase decision. The ordered probit regression was employed with 357 online surveys to systematically estimate the purchase intention for the online-crowd-funding sustainable milk. Customer behaviours, environmental consciousness, and the individual socio-demographic factors were tested as potential explanatory variables. In the survey and depth interview samples, we found interviewees as potential customers showed strong purchase intentions to the crowd funding dairy milk for noticing milk quality and nutritious improvement, emission reduction and environmental benefits by the integrated PVWP system. In our findings of the regression results, the females, customers with young children or planning to have children were found with higher willing to purchase than other customers for crowd funding the sustainable dairy milk. The familiarity and popularity with online shopping and pre-sale purchase in China made customers more open and active towards pre-pay and crowd-funding mechanism.
关键词： Binary probit regression,Dairy milk in China,Discrete choice model,Crowd-funding,Photovoltaic water pumping
更新于2025-09-12 10:27:22
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Circannual changes in major chemical composition of bulk dromedary camel milk as determined by FT-MIR spectroscopy, and factors of variation
摘要： We monitored the major chemical composition of bulk dromedary camel milk by FT-MIR spectroscopy over a 5-year period. The results highly correlated with those determined with reference methods (r > 0.985, p < 0.001). Production parameters showed significant (p < 0.001) seasonal and yearly changes. The overall mean fat, protein, lactose, solids-not-fat, and total solids concentrations of bulk dromedary camel milk were 2.87%, 2.94%, 4.15%, 8.00%, and 10.69%, respectively. Month of the year, year of the study, and level of production had a strong influence on bulk milk chemical composition and yield of milk components; however, the relative effect of season on composition was greater (proportion of variance app. 50%) compared to that of other factors of variation. The highest and lowest values were measured during winter and summer, respectively. Circannual variation in major milk components was associated with environmental conditions (photoperiod, temperature), whereas it was independent of nutritional factors.
关键词： Dromedary,Raw milk,Seasonal variation,Chemical composition,Camel
更新于2025-09-10 09:29:36
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Rapid and sensitive label-free determination of aflatoxin M1 levels in milk through a White Light Reflectance Spectroscopy immunosensor
摘要： Α miniaturized optical immunosensor based on White Light Reflectance Spectroscopy (WLRS) for the rapid and label-free detection of aflatoxin M1 (AFM1) in milk samples has been developed. WLRS sensing system consists of the measurement set-up and the biochip. The first encompasses the reflection probe, the light source and the spectrometer, while the latter is a Si chip with a SiO2 layer on top where an AFM1-bovine serum albumin conjugate has been immobilized. The assay was performed by running mixtures of rabbit polyclonal anti-AFM1 antibody with the calibrators or the samples, followed by reaction with biotinylated anti-rabbit IgG antibody and streptavidin. The assay cycle was completed in 25 min, the limit of detection was 6 pg/mL, and the linear working range extended from 0.012 to 2.0 ng/mL. The assay was repeatable (intra-and inter-assay coefficients of variation ranged from 2.1 to 6.3% and 3.5 to 8.2%, respectively) and accurate (percent recovery values ranged from 92.5 to 110%). AFM1 could be detected with the immunosensor developed in both processed and unprocessed milk of different animal species without any dilution. The excellent analytical characteristics and the small instrument size make the proposed sensor suitable for accurate low-cost AFM1 determination in milk samples at the point-of-need.
关键词： Aflatoxin M1,Immunosensor,Milk,White Light Reflectance Spectroscopy
更新于2025-09-10 09:29:36