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Abstract The levels, transfer factors and health risks of selected metals were investigated in paddy soil-rice systems of industrial and township areas from subtropical China. The mean concentrations of cadmium (Cd), lead (Pb), arsenic (As) and mercury (Hg) in paddy soils were 1.08, 52.8, 19.5 and 0.20 mg·kg−1 (dry weight), respectively. The concentrations of Cd from ca. 99% of the soil samples and 68.9% of the rice grain samples in the study region were above the allowable limits according to the current standards. The concentrations of Cd and Pb in paddy soil from industrial areas were significantly higher than those from township and clean areas, however, these situations did not happen for Cd and Pb concentrations in rice grains. The mean of transfer factors of Cd was 0.742, which was the highest of all selected metals. The soil pH and transfer factors of Cd were analyzed separately in groups of 0.1 pH unit interval. Piecewise means of the log Cd transfer factors kept around −0.10 between soil pH 4.3 and 6.3, whereas linearly decreased by a factor of 1.80 with the increase of soil pH from 6.4 to 7.7. The high hazard index values and cancer risk values were found in our study area, indicating a high non-carcinogenic and carcinogenic health risk from consumption of rice grains. Highlights • Metal contents in paddy soils were followed the order: Pb > As > Cd > Hg. • 68.9% of rice grains exceeded the maximum permissible Cd concentration. • Cadmium had a high mobility from paddy soils to rice grains. • The mean hazard index values varied greatly from 1.34 to 5.99 for human. • The total cancer risk values for adults varied greatly from 0.019 to 0.088. [ABSTRACT FROM AUTHOR]

Abstract: The feasibility of using hyperspectral imaging technology combined with wavelet transform and multiway partial least squares (N‐PLS) algorithm to predict the total viable count (TVC) of spiced beef during storage was investigated. The mean spectral data were extracted from the hyperspectral images and further decomposed in nine levels by daubechies8 (db8) wavelet function to obtain an approximation coefficient (A9) and nine detail coefficients (D1–D9). Selecting wavelet coefficients to compose different three‐dimension matrixes, further integrating N‐PLS algorithm to establish the predictive models for detecting TVC in spiced beef. The experimental results show that the N‐PLS model with D4, D5, D6, D7 coefficient (also named D4,5,6,7‐N‐PLS) exhibit an excellent prediction capability for TVC of spiced beef sample with a higher determination coefficients in prediction ( R p 2) of 0.934 and lower root mean squared errors estimated by prediction of 0.755 than other N‐PLS models, raw spectra PLS model, and Unfold‐PLS models. Therefore, the established model using three‐dimension data array and N‐PLS algorithm has great potential in the TVC value detection of spiced beef and other meat productions. Practical applications: Spiced beef is one of the most popular meat products in China owing to its good taste, low fat, and high protein. Unfortunately, the spiced beef during storage is just a suitable habitat for many pathogens and spoilage microbes to colonize. Thus, it is necessary to monitor the microbiological contamination to guarantee the sanitary quality of meat productions. The total viable count (TVC) of bacteria was considered as a key indicator for the freshness evaluation of meat productions, Traditional techniques for determination of TVC are laborious, time consuming, and unsuitable for modern meat industrial processing and production technologies. Therefore, this study attempted to use hyperspectral imaging technology combined with wavelet transform and multiway partial least squares (N‐PLS) algorithm to predict the TVC of spiced beef during storage. The proposed method is helpful for most consumers to judge easily the freshness state of meat productions and further purchase them. [ABSTRACT FROM AUTHOR]

This study explored the feasibility of rapid detection of biogenic amines (BAs) in cooked beef during the storage process using hyperspectral imaging technique combined with sparse representation (SR) algorithm. The hyperspectral images of samples were collected in the two spectral ranges of 400–1000 nm and 1000–1800 nm, separately. The spectral data were reduced dimensionality by SR and principal component analysis (PCA) algorithms, and then integrated the least square support vector machine (LS-SVM) to build the SR-LS-SVM and PC-LS-SVM models for the prediction of BAs values in cooked beef. The results showed that the SR-LS-SVM model exhibited the best predictive ability with determination coefficients R P 2 ) of 0.943 and root mean square errors (RMSEP) of 1.206 in the range of 400–1000 nm of prediction set. The SR and PCA algorithms were further combined to establish the best SR-PC-LS-SVM model for BAs prediction, which had high R P 2 of 0.969 and low RMSEP of 1.039 in the region of 400–1000 nm. The visual map of the BAs was generated using the best SR-PC-LS-SVM model with imaging process algorithms, which could be used to observe the changes of BAs in cooked beef more intuitively. The study demonstrated that hyperspectral imaging technique combined with sparse representation were able to detect effectively the BAs values in cooked beef during storage and the built SR-PC-LS-SVM model had a potential for rapid and accurate determination of freshness indexes in other meat and meat products. [ABSTRACT FROM AUTHOR]

The aim of this study was to measure the improvement in mapping accuracy of spatial distribution of Cd in soils by using geostatistical methods combined with auxiliary factors, especially qualitative variables. Significant correlations between Cd content and correlation environment variables that are easy to obtain (such as topographic factors, distance to residential area, land use types and soil types) were analyzed systematically and quantitatively. Based on 398 samples collected from a Cd contaminated area (Hunan Province, China), we estimated the spatial distribution of Cd in soils by using spatial interpolation models, including ordinary kriging (OK), and regression kriging (RK) with each auxiliary variable, all quantitative variables (RKWQ) and all auxiliary variables (RKWA). Results showed that mapping with RK was more consistent with the sampling data of the spatial distribution of Cd in the study area than mapping with OK. The performance indicators (smaller mean error, mean absolute error, root mean squared error values and higher relative improvement of RK than OK) indicated that the introduction of auxiliary variables can improve the prediction accuracy of Cd in soils for which the spatial structure could not be well captured by point-based observation (nugget to sill ratio = 0.76) and strong relationships existed between variables to be predicted and auxiliary variables. The comparison of RKWA with RKWQ further indicated that the introduction of qualitative variables improved the prediction accuracy, and even weakened the effects of quantitative factors. Furthermore, the significantly different relative improvement with similar R 2 and varying spatial dependence showed that a reasonable choice of auxiliary variables and analysis of spatial structure of regression residuals are equally important to ensure accurate predictions. [ABSTRACT FROM AUTHOR]

Heavy metal concentrations of As, Cd, Cu, Hg, Ni, Pb, and Zn were investigated for 107 soil samples collected from crop land, orchard land, greenhouse land, and wood land in the peri-urban area of Beijing, China. The mean concentrations of As, Cd, Cu, Hg, Ni, Pb, and Zn in all soil samples were 8.40, 0.20, 24.7, 0.08, 25.0, 23.0, and 77.1 mg/kg, dw, respectively. Among the four land use types, the Cd concentration in greenhouse land was significantly higher than the other three kinds of land uses (p< .05), and Cu and Zn concentrations in greenhouse land were significantly higher than in crop land and wood land (p< .05). Based on principal component analysis, elevated Cu, Zn, and Cd concentrations in greenhouse land might have originated from high application rates of manure and fertilizer. According to an ecological risk analysis, the four land use types can be ranked in the following order: greenhouse land > orchard land > crop land > wood land. However, the degree of non-cancer risk for both adults and children in different land uses decreased in the order of greenhouse land > orchard land > wood land > crop land. [ABSTRACT FROM PUBLISHER]

A fast and novel analytical method was developed for the determination of trace levels of sulfonylurea herbicides in water and soil samples. Graphene was used as a sorbent for extraction, and ultra high performance liquid chromatography with tandem mass spectrometry was used for quantification. Five sulfonylurea herbicides were preconcentrated from water samples using a graphene-loaded packed cartridge, while extraction from soil samples was performed in a single step using graphene-supported matrix solid-phase dispersion. Under the optimized conditions, the calibration plots were linear in the range between 5 and 1000 ng/L for water samples, and between 1 and 200 ng/g for soil samples. All correlation coefficients ( R) were >0.99. The limits of detection for water and soil samples were 0.28-0.53 ng/L and 0.08-0.26 ng/g, respectively. This method was successfully applied to the analysis of spiked samples of environmental water and soil, with recoveries ranging from 84.2-109.3 and 86.12-103.2%, respectively, all with relative standard deviations of <10%. [ABSTRACT FROM AUTHOR]

Abstract: An extensive survey was conducted in this study to determine the spatial distribution and possible sources of heavy metals in the agricultural soils in Shunyi, a representative agricultural suburb in Beijing, China. A total of 412 surface soil samples were collected at a density of one sample per km2, and concentrations of As, Cd, Cu, Hg, Pb and Zn were analyzed. The mean values of the heavy metals were 7.85±2.13, 0.136±0.061, 22.4±6.31, 0.073±0.049, 20.4±5.2, and 69.8±16.5mgkg−1 for As, Cd, Cu, Hg, Pb, and Zn, respectively, slightly higher than their background values of Beijing topsoil with the exception of Pb, but lower than the guideline values of Chinese Environmental Quality Standard for Soils. Multivariate and geostatistical analyses suggested that soil contamination of Cd, Cu and Zn was mainly derived from agricultural practices. Whereas, As and Pb were due mainly to soil parent materials, and Hg was caused by the atmospheric deposits from Beijing City. The identification of heavy metal sources in agricultural soils is a basis for undertaking appropriate action to protect soil quality. [Copyright &y& Elsevier]

Abstract: Time effect on the fractionation of Cu, Zn, Pb, and Cd in three typical Chinese soils was investigated. A total of 500 mg kg−1 of Cu, Zn, Pb and 2.5 mg kg−1 of Cd were added to soils as nitrates. Metals in the incubated soils were fractionated termly from 3 h to 8 weeks by the sequential extraction procedure, in which the metal fractions were experimentally defined as exchangeable, carbonate-, Fe–Mn oxide-, organic matter-bound and residual fractions. Results showed that the changes of Cu, Pb and Zn in fraction distribution were biphasic by an initial rapid step followed by a slow one. Metals in exchangeable fraction were increased in the first 3 h, and then decreased, such decreases could be simulated by a diffusion equation and the decrease rate followed the order Pb>Cu>Zn≫Cd. Metals bound to Fe–Mn oxides and organic matter increased consistently in the 8-week incubation. There were almost no changes for the metals in the residual fraction. After 3-h incubation most of Cd added to soils presented in the exchangeable fraction. The content of Cd in each fraction changed slightly in the 8-week incubation. Soil pH played an important role in metal fraction distribution patterns. Jiangxi soil, with low soil pH, tended to keep more metals added in exchangeable fraction and the changes of metals in each fraction were not as remarkable as in other two soils. High organic matter content resulted in the increased organic matter-bound fraction. [Copyright &y& Elsevier]

A single microwave extraction procedure was conducted to investigate the bioavailability of rare earth elements (REEs) by using different extractants of 0.05 M EDTA, 0.10 M CH3COOH, 0.10 M HCl, and 0.05 M CaCl2. The experimental conditions of heating time and microwave power were optimized. A microwave power of 60% and extraction time of 30 min were adopted. Compared to the conventional single extraction schemes reported in the literature, the recommended technique shortened the operational time, simplified the experimental task, improved the precision, and obtained consistent results with those obtained by using the conventional methods. In addition, the suggested microwave extraction method has been successfully used to evaluate the bioavailability of REEs in soils. Soil samples collected from 15 sites in China were extracted by four different extractants with microwave ancillary. Extractable REEs from soils were well correlated with REEs contents in shoots of wheat (Troticum aestivum L.) under the greenhouse conditions. The correlation coefficients were 0.6514–0.8996, 0.4522–0.7783, 0.6506–0.8671, 0.4869–0.7014 between the extractable REEs in soils and their concentrations in wheat shoots for the extractants of CaCl2, EDTA, CH3COOH and HCl, respectively. [Copyright &y& Elsevier]

Biodegradable plastics promise eco-friendliness, yet their transformation into microplastics (bio-MPs) raises environmental alarms. However, how those bio-MPs affect the greenhouse gases (GHGs) and volatile organic compounds (VOCs) in soil ecosystems remains largely unexplored. Here, we investigated the effects of diverse bio-MPs (PBAT, PBS, and PLA) on GHGs and VOCs emission in typical paddy or upland soils. We monitored the carbon dioxide (CO 2) and methane (CH 4) fluxes in-situ using the self-developed portable optical gas sensor and analyzed VOC profiles using a proton-transfer reaction mass spectrometer (PTR-MS). Our study has revealed that, despite their biodegradable nature, bio-MPs do not always promote soil GHG emissions as previously thought. Specifically, PBAT and PLA significantly increased CO 2 and CH 4 emissions up to 1.9–7.5 and 115.9–178.5 fold, respectively, compared to the control group. While PBS exhibited the opposite trend, causing a decrease of up to 39.9% for CO 2 and up to 39.9% for CH 4. In addition, different types of bio-MPs triggered distinct soil VOC emission patterns. According to the Mann-Whitney U-test and Partial Least Squares Discriminant Analysis (PLS-DA), a recognizable VOC pattern associated with different bio-MPs was revealed. This study claims the necessity of considering polymer-specific responses when assessing the environmental impact of Bio-MPs, and providing insights into their implications for climate change. [Display omitted] • Effects of bio-MPs on soil GHG fluxes and VOC emissions in both paddy and upland soils were explored. • Different bio-MPs, despite being biodegradable, had varying effects on soil GHG emissions. • PBAT and PLA increased GHG fluxes in paddy or upland soils, whereas PBS exhibited the opposite trend. • Bio-MPs triggered characteristic VOC emission pattern in the soil, offering a potential tracking method. [ABSTRACT FROM AUTHOR]

AbstractLimitations in instrument resolution mean that soil samples analysis using energy-dispersive X-ray fluorescence (EDXRF) often produced overlapping spectral peaks of heavy metals with similar energies. This overlapping of spectral peaks posed a significant problem in the quantitative analysis of heavy metals in soil samples. Therefore, it was necessary to decompose the overlapping peaks. In this paper, a new method for decomposing overlapping peaks was presented in the context of Gaussian Mixture Model (GMM) parameter estimation, combining the k-means algorithm and the African Vulture Optimization Algorithm (AVOA). The data acquired from EDXRF instruments were preprocessed before being input to the k-means algorithm, which produces the output used to initialize the parameters of the GMM. Subsequently, AVOA was employed to optimize the GMM parameters based on a fitness function derived from the data. Ultimately, the optimized GMM parameters obtained through the AVOA process yield the optimal solution for the decomposition of overlapping peaks. This approach effectively addressed the challenge of peak overlap in the determination of heavy metals in soil by EDXRF. Soil samples were obtained from national standard samples, peach gardens, and vegetable-growing regions. The results showed that the maximum absolute errors for the peak channel and peak area were 1.46% and 6.37%, respectively. A comparison of the proposed model with others models indicated that the k-means-GMM-AVOA model exhibits the best performance in terms of speed, accuracy, and stability. [ABSTRACT FROM AUTHOR]

A novel adsorbent is described for magnetic solid-phase extraction (MSPE) of the aflatoxins AFB1 and AFB2 (AFBs). Magnetic agarose microspheres (MAMs) were functionalized with an aptamer to bind the AFBs which then were quantified by HPLC and on-line post-column photochemical derivatization with fluorescence detection. Streptavidin-conjugated MAMs were synthesized first by a highly reproducible strategy. They possess strong magnetism and high surface area. The MAMs were characterized by transmission electron microscopy, scanning electron microscopy, optical microscopy, laser diffraction particle size analyzer, Fourier transform infrared spectrometry, vibrating sample magnetometry and laser scanning confocal microscopy. Then, the AFB-aptamers were immobilized on MAMs through biotin-streptavidin interaction. Finally, the MSPE is performed by suspending the aptamer-modified MAMs in the sample. They are then collected by an external magnetic field and the AFBs are eluted with methanol/buffer (20:80). Several parameters affecting the coupling, capturing and eluting efficiency were optimized. Under the optimized conditions, the method is fast, has good linearity, high selectivity, and sensitivity. The LODs are 25 pg·mL−1 for AFB1 and 10 pg·mL−1 for AFB2. The binding capacity is 350 ± 8 ng·g−1 for AFB1 and 384 ± 8 ng·g−1 for AFB2, and the precision of the assay is <8%. The method was successfully applied to the analysis of AFBs in spiked maize samples.Schematic of novel aptamer functionalized magnetic agarose microspheres (Apt-MAM) as magnetic adsorbents for simultaneous and specific affinity capture of aflatoxins B1 and B2 (AFBs). [ABSTRACT FROM AUTHOR]

We have developed an aptamer affinity column (AAC) for the purification and enrichment of trace aflatoxin B1 (AFB1) and aflatoxin B2 (AFB2) in genuine agro-products through the covalent conjugation of amino modified aptamer and NHS-activated Sepharose. The coupling and working conditions found to be suitable for this AFB-AAC were examined in regard to coupling time (2 min), loading volume (30 mL), and the methanol concentration (< 10%) used in the loading step. The performance of AFB-AAC was then further evaluated in terms of capacity (329.1 ± 13.7 ng for AFB1 and 162.5 ± 8.9 ng for AFB2), selectivity (excellent), reusability (twenty-three times for AFB1 and twelve times for AFB2), and repeatability (92.7% ± 2.9% for AFB1 and 71.5% ± 3.4% for AFB2). Furthermore, the AAC clean-up combined with HPLC-FLD demonstrated excellent linearity over a wide range, good sensitivity with an LOD of 50 pg mL−1 for AFB1 and 15 pg mL−1 for AFB2, and acceptable recovery with different spiking levels in different matrices. Finally, the AAC was successfully applied to analyte AFB1 and AFB2 in four types of agro-products as well as a maize flour reference material, and the results were found to be in accordance with those of commercial IACs. This study provides a reference for the analysis of other trace analytes by merely changing the corresponding aptamer and represents a strong contender for immune affinity columns. [ABSTRACT FROM AUTHOR]

The feasibility of combining spectral and textural information from hyperspectral imaging to predict the moisture content and storage time of cooked beef was explored. A total of 10 optimal wavelengths were selected for the moisture content and storage time by conducting variable combination population analysis (VCPA). Principal component analysis was employed to reduce the number of dimensions of hyperspectral images, while a discrete cosine transform was applied to the first three principal component images to extract 30 textural features. A back-propagation artificial neural network (BP-ANN) model and partial least-squares regression model were developed to predict the moisture content and storage time from spectra, textural data, and their combination. The fused BP-ANN model provided satisfactory results with R p 2 of 0.977, and RMSEP of 0.9151 for the prediction of moisture content; these results were superior to those obtained with spectral or textual information alone. Combined with the storage time, the distribution map of the moisture content of cooked beef was visualized using the best fused BP-ANN model with imaging process method. The results reveal that the combination of spectral and textural information of hyperspectral imaging coupled with the BP-ANN algorithm has strong potential for the prediction and visualization of the moisture content of cooked beef at different storage times. [ABSTRACT FROM AUTHOR]

A fast and reliable ultra-high performance liquid chromatography–tandem mass spectrometry method was developed for the determination of aflatoxins B1, B2, G1, and G2in cereal. The analytes were extracted by accelerated solvent extraction with methanol/water (80:20). A polymeric solid-phase extraction column was used for sample preparation. Under optimum conditions, the analyte recoveries for samples spiked at different concentration levels in rice and maize ranged from 71.2 to 94.0%, with relative standard deviations less than 16.4%. Limits of detection (signal-to-noise ratio, 3:1) for the aflatoxins ranged from 0.25 to 0.93 ng/g. The developed method was applied to the determination of aflatoxins in ten rice and maize samples. One maize sample tested positive with an aflatoxin B1concentration of 2.7 ng/g. [ABSTRACT FROM PUBLISHER]

Abstract: Plant foliar uptake and translocation is an important pathway for the migration of radiocesium to the human diet. This study reports the effects of accompanying anions ( , , , and I-) on cesium retention and translocation. An experiment to simulate cesium retention and translocation was conducted in a greenhouse by applying droplets of stable cesium solutions to the upper surface of four soybean [Glycine max (L.) Merr.] trifoliate leaves. The average percentages of cesium retention with the accompanying anions , , , and I- on the leaves were 7.2, 21.5, 49.3, and 10.2%, respectively. Retention values of the four treatments were stable during the 3-day exposure period, indicating that cesium could be absorbed and penetrate the cuticle quickly once it was dissolved. Scanning electron microscopy coupled with energy dispersive X-ray microanalysis showed that particles containing cesium remained on the leaf surfaces after washing. Also, nano-sized particles containing cesium were observed inside the leaf tissues. Cesium concentrations in the uncontaminated leaves, pods, stems, and roots increased during the study period indicating cesium redistribution from the contaminated leaves. [Copyright &y& Elsevier]

Microplastics (MPs) are ubiquitous contaminants that have become an emerging pollutant of concern, potentially threatening human health and ecosystem environments. Although current detection methods can accurately identify various types of MPs, it remains necessary to develop non-destructive and rapid methods to meet growing demands for detection. Herein, we combine a hyperspectral unmixing method and machine learning to analyse Raman imaging data of environmental MPs. Five MPs types including poly(butylene adipate-co-terephthalate) (PBAT), poly(butylene succinate) (PBS), p -polyethylene (PE), polystyrene (PS) and polypropylene (PP) were visualized and identified. Individual or mixed pure or aged MPs along with environmental samples were analysed by Raman imaging. Alternating volume maximization (AVmax) combined with unconstrained least squares (UCLS) method estimated end members and abundance maps of each of the MPs in the samples. Pearson correlation coefficients (r) were used as the evaluation index; the results showed that there is a high similarity between the raw spectra and the average spectra calculated by AVmax. This indicates that Raman imaging based on machine learning and hyperspectral unmixing is a novel imaging analysis method that can directly identify and visualize MPs in the environment. [Display omitted] • Fast identification of environmental MPs based on novel AVmax-UCLS Raman imaging. • AVmax-UCLS has high recognition rate for target particles in complex background. • AVmax-UCLS applied directly on environmental samples without complex pre-processing. • Efficient method for MPs monitoring in aquatic and terrestrial environment. [ABSTRACT FROM AUTHOR]

Polycyclic musks (PCMs) have recently received growing attention as emerging contaminants because of their bioaccumulation and potential ecotoxicological effects. Herein, an effective method for the determination of five PCMs in aqueous samples is presented. Reduced graphene oxide-derivatized silica (rGO@silica) particles were prepared from graphene oxide and aminosilica microparticles and characterized by scanning electron microscopy, Fourier transform infrared spectroscopy, and X-ray photoelectron spectroscopy. PCMs were preconcentrated using rGO@silica as the solid-phase extraction sorbent and quantified by gas chromatography–tandem mass spectrometry. Several experimental parameters, such as eluent, elution volume, sorbent amount, pH, and sample volume were optimized. The correlation coefficient (R) ranged from 0.9958 to 0.9992, while the limits of detection and quantitation for the five PCMs were 0.3–0.8 ng/L and 1.1–2.1 ng/L, respectively. Satisfactory recoveries were obtained for tap water (86.6–105.9%) and river water samples (82.9–107.1%), with relative standard deviations <10% under optimal conditions. The developed method was applied to analyze PCMs in tap and river water samples from Beijing, China. Galaxolide (HHCB) and tonalide (AHTN) were the main PCM components detected in one river water sample at concentrations of 18.7 for HHCB, and 11.7 ng/L for AHTN. [ABSTRACT FROM AUTHOR]

The occurrence, speciation and transport of heavy metals in 9 coastal rivers from watershed of Laizhou Bay were investigated. The largest dissolved concentrations of Cd, Cu and Zn in water were 6.26, 2755.00, 2076.00 μg/L, respectively, much higher than several drinking water guidelines. The greatest concentrations of Cu, Zn, Cr, Ni, Pb and Cd in sediments were 1462, 1602, 196, 67.2, 63.5 and 1.41 mg/kg, dw, respectively. Correlation and principal component analysis was also conducted to determine the extent between the concentrations of metals in water and sediment, as well as relevant parameters. Throughout the river stretch, most of Cr Zn, Cr, Ni and Pb bound to residual fraction, however, Cd was preferentially bound to the exchangeable phase. Among the 9 rivers, Yellow river account for 72.5%, 67.5%, 55.4%, 59.4%, 79.4% and 85.5% for Cr, Ni, Cu, Zn. Cd and Pb, respectively. The combined potential ecological risk indexes were used to evaluate potential risks. The majority of sampling sites from watershed of Laizhou Bay have moderate ecological risk from metals. The government should pay more attention to the ecological risk of river ecosystem which flow to Laizhou Bay. [ABSTRACT FROM AUTHOR]

Douchi is a fermented soybean food, which is popular in China. Composition and angiotensin I-converting enzyme-inhibitory activity of Douchi fermented withMucor wutungkiaowere studied in this work. The results showed that the nutritional potency of protein, fat, and soluble polysaccharide was improved in Douchi fermentation. The angiotensin I-converting enzyme-inhibitory activity of Douchi that ripening for 2 weeks showed the highest angiotensin I-converting enzyme-inhibitory activity. Then this sample was purified with Sephadex G-25 gel chromatography, and the amino acids and angiotensin I-converting enzyme-inhibitory activity of the purified fractions were studied. The results suggested that hydrophobic amino acids were assumed to cause the main increase of the angiotensin I-converting enzyme-inhibitory activity in Douchi. [ABSTRACT FROM PUBLISHER]

The increased use of plastic film in greenhouse vegetable production (GVP) could result in phthalate ester (PAE) contamination in vegetables. However, limited information is currently available on their occurrence and associated potential risks in GVP systems. The present study documents the occurrence and composition of 15 PAEs in soil, plastic film, and vegetable samples from eight large-scale GVP bases in Beijing, China. Results showed that PAEs are ubiquitous contaminants in these GVP bases. Total PAE concentrations ranged from 0.14 to 2.13 mg/kg (mean 0.99 mg/kg) in soils and from 0.15 to 6.94 mg/kg (mean 1.49 mg/kg) in vegetables. Di (2-ethylhexyl) phthalate, di- n -butyl phthalate, and diisobutyl phthalate were the most abundant components, which accounted for > 90% of the total PAEs. This investigation also indicated that the widespread application of plastic film in GVP systems may be the primary source of these PAEs. The non-cancer and carcinogenic risks of target PAEs were estimated based on the exposures of vegetable intake. The hazard quotients of PAE in all vegetable samples were lower than 1 and the carcinogenic risks were also at acceptable levels for consumers. The data in this study can provide valuable information to understand the status of potential pollutants, specifically PAEs, in GVP systems. [ABSTRACT FROM AUTHOR]

The occurrence of 15 antibiotics in soil and manure samples from 11 large-scale greenhouse vegetable production (GVP) bases in Beijing, China was investigated. Results showed that the greenhouse soils were ubiquitously contaminated with antibiotics, and that antibiotic concentrations were significantly higher in greenhouses than in open field soils. The mean concentrations of four antibiotic classes decreased in the following order: tetracyclines (102 μg/kg) > quinolones (86 μg/kg) > sulfonamides (1.1 μg/kg) > macrolides (0.62 μg/kg). This investigation also indicated that fertilization with manure and especially animal feces might be the primary source of antibiotics. A risk assessment based on the calculated risk quotients (RQs) demonstrated that oxytetracycline, chlortetracycline, norfloxacin, ciprofloxacin and enrofloxacin could pose a high risk to soil organisms. These results suggested that the ecological effects of antibiotic contamination in GVP bases and their potential adverse risks on human health need to be given special attention. [ABSTRACT FROM AUTHOR]

We describe a fast and sensitive method for the detection of aflatoxin B2 (AFB2) that is based on the addition of AFB2-sensitive aptamers to a colloidal solution of gold nanoparticles (AuNPs). Subsequent addition of AFB2 and NaCl to the solution causes a color change from wine-red to blue-purple. Best results are obtained at a pH value of 7.0, a 10 mM aptamer concentration, and a 2 M concentration of NaCl. The method has a linear dynamic range that extends from 0.025 to 10 ng∙mL of AFB2, and the detection limit is 25 pg∙mL. The method is simple, fast, highly sensitive, and enables both visual and microplate readout. [Figure not available: see fulltext.] [ABSTRACT FROM AUTHOR]

Fast and accurate acquisition of the outline of rural buildings on remote sensing images is an efficient method to monitor illegal rural buildings. The traditional object detection method produces useless background information when detecting rural buildings; the semantic segmentation method cannot accurately segment the contours between buildings; the instance segmentation method cannot obtain regular building contours. The rotated object detection methods can effectively solve the problem that the traditional artificial intelligence method cannot accurately extract the outline of buildings. However, the rotated object detection methods are easy to lose location information of small objects in advanced feature maps and are sensitive to noise. To resolve these problems, this paper proposes a two-stage rotated object detection network for rural buildings (TRDet) by using a deep feature fusion network (DFF-Net) and a pixel attention module (PAM). Specifically, TRDet first fuses low-level location and high-level semantic information through the DFF-Net and then reduces the interference of noise information to the network through the PAM. The experimental results show that the mean average precession (mAP), precision, recall rate, and F1 score of the proposed TRDet are 83.57%, 91.11%, 86.5%, and 88.74%, respectively, which outperform the R2CNN model by 15%, 15.54%, 4.01%, and 9.87%. The results demonstrate that the TRDet can achieve better detection in small rural buildings and dense rural buildings. [ABSTRACT FROM AUTHOR]

Abstract: A hydroponic experiment was conducted to investigate the debrominated, hydroxylated and methoxylated metabolism of polybrominated diphenyl ethers (PBDEs, BDE-15, -28 and -47) in maize. A total of six debrominated metabolites (de-PBDEs), seven hydroxylated PBDEs (OH-PBDEs, including two unidentified OH-di-PBDEs and one unidentified OH-tri-PBDE) and four methoxylated PBDEs (MeO-PBDEs) were determined in the exposed plants. The metabolic products were detected in maize only after 12h of exposure to the PBDEs. However, the concentration of each type of the metabolites (de-PBDEs, OH-PBDEs or MeO-PBDEs) decreased at the later exposure time, possibly due to further metabolism. The removal of a bromine atom or the introduction of a hydroxyl/methoxy group was easier at the ortho-positions on the biphenyl structure than at the para-positions. Concentration ratios of the total debrominated, hydroxylated or methoxylated metabolites to the parent congener (BDE-28 or -47) generally followed the order of leaves>stems≫roots, and MeO-PBDEs>de-PBDEs≫OH-PBDEs. These results suggest that metabolism occurred preferentially in leaves and stems than in roots. Less transformation and shorter elimination half-life of OH-PBDEs would contribute to the lower concentrations of OH-PBDEs than of de-PBDEs or MeO-PBDEs in maize. [Copyright &y& Elsevier]

• Estimating soil metal elements through data fusion of NIR, MIR, and XRF. • Fusion models with feature bands performed better than full spectral data. • SPA showed the best performance in combination with the XRF-MIR model. • XRF-MIR improved the accuracy of As, Cr, Cu, Ni, and Zn. • Monitoring polluted soils in an accurate, fast and cheap way. This paper aims to investigate the feasibility combination of X-ray fluorescence (XRF), near-infrared (NIR), and mid-infrared (MIR) sensors for the detection of seven key monitoring elements in the soil. Two strategies for data fusion were adopted: (i) the XRF characteristic bands were fused with all spectral data of NIR and MIR separately, and (ii) the XRF characteristic bands were fused with the characteristic bands of NIR and MIR, respectively. Also, different feature extraction methods were compared. The best feature extraction methods for XRF-NIR and XRF-MIR models were principal component analysis (PCA) and successive projections algorithm (SPA). The modeling results showed that strategy (ii) showed better performance, and the XRF-MIR model provided more accurate results than the XRF-NIR model. Both XRF-MIR and XRF-NIR methods improved the accuracy of As, Cr, Cu, Ni, and Zn. The XRF-MIR obtained the best predictions, and the determination coefficients (R2) were 0.93, 0.98, 0.98, 0.95, and 0.98. For Pb and Cd, the measurement could be obtained by XRF alone, and the corresponding R2 were both 0.98. The results confirmed that sensor fusion can effectively improve the accuracy of the spectrometer in detecting metal elements in the soil. [ABSTRACT FROM AUTHOR]

• Lactoferrin is widely used in healthcare and the food industry. • Aptamers as solid-phase extraction recognition elements. • Coupling an amino-modified aptamer with NHS-activated Sepharose. • An aptamer affinity column for purification and enrichment of lactoferrin in milk. As an active glycoprotein with high nutritional value, lactoferrin is widely used in food and medical treatment. Therefore, it is very important to establish an accurate and efficient detection method for lactoferrin. At present, the detection of lactoferrin in milk faces many challenges, such as low separation degree and poor parallelism. To address this issue, we developed an aptamer affinity column (AAC) for purification and enrichment of lactoferrin in milk. The column was prepared by covalent conjugation of an amino-modified aptamer with NHS-activated Sepharose. The washing buffer type (0.01 mol/L phosphate buffer) and volume (10 mL) and the sodium chloride concentration (1 mol/L) in the elution buffer were optimized for the AAC method. The performance of the AAC was then evaluated in terms of the column capacity, specificity, stability, and reusability. The column capacity was 500 ± 13.7 μg and the column could be reused up to ten times with a large loss in performance. The AAC method combined with high-performance liquid chromatography gave excellent linearity over a wide range, good sensitivity with a limit of detection of 3 μg/mL, and acceptable recoveries for different concentrations of lactoferrin spiked in real raw milk samples from cattle. Finally, the AAC was successfully applied to analyze lactoferrin in milk. This method could be applied to routine analysis of samples for lactoferrin in testing laboratories and dairy factories. [ABSTRACT FROM AUTHOR]

The spread of pharmaceutically active chemicals (PACs), such as antibiotics and estrogenic hormones from animal manures can pose threats to the ecologic environment. In this work, animal manure samples were collected from 71 concentrated animal feedlots in Northern China and investigated for 24 antibiotics and 4 estrogenic hormones. Results showed that these micropollutants were ubiquitous in manures with the concentration ranges of undetectable (ND)–543,445 μg/kg (mean: 44,568 μg/kg) for antibiotics and ND–249.8 μg/kg (mean: 24.78 μg/kg) for estrogens. There was a significant variation in the amounts of PACs in different animal manures. The amounts of antibiotics in manures had following order: swine (83,177 μg/kg) >chicken (52,932 μg/kg) >beef (37,120 μg/kg) >dairy (305 μg/kg), while the estrogens in dairy (mean: 39.27 μg/kg) and chicken manures (mean: 40.08 μg/kg) were higher than those in beef (2.7 μg/kg) and swine manures (1.8 μg/kg). Based on the estimated farmland application rate of manure, antibiotics and estrogens may cause high ecological risks to terrestrial organisms according to the risk quotient evaluation. Estrogens could pose a relatively higher risk than antibiotics. The toxicological effects of antibiotics and estrogens to the terrestrial environment should receive more intensive study. • Antibiotics and estrogens were ubiquitous in CAFO manures in China. • Significant variation in antibiotics and estrogen amounts were detected between animal groups. • Several antibiotics and estrogens are possible environmental risk factors. [ABSTRACT FROM AUTHOR]