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Hand-sewn anastomosis and stapled anastomosis are the 2 main types of gastrojejunal anastomotic methods in pancreaticoduodenectomy. There is ongoing debate regarding the most effective anastomotic method for reducing delayed gastric emptying after pancreaticoduodenectomy. This study aims to identify factors that influence delayed gastric emptying after pancreaticoduodenectomy and assess the impact of different anastomotic methods on delayed gastric emptying. The study included 1,077 patients who had undergone either hand-sewn anastomosis (n = 734) or stapled anastomosis (n = 343) during pancreaticoduodenectomy between December 2016 and November 2021 at our department. We retrospectively analyzed the clinical data, and a 1:1 propensity score matching was performed to balance confounding variables. After propensity score matching, 320 patients were included in each group. Compared with the stapled anastomosis group, the hand-sewn anastomosis group had a significantly lower incidence of delayed gastric emptying (28 [8.8%] vs 55 [17.2%], P =.001) and upper gastrointestinal tract bleeding (6 [1.9%] vs 17 [5.3%], P =.02). Additionally, the hand-sewn anastomosis group had a significantly reduced postoperative length of stay and lower hospitalization expenses. However, the hand-sewn anastomosis group had a significantly longer operative time, which was consistent with the analysis before propensity score matching. Logistic regression analysis showed that stapled anastomosis, intra-abdominal infection, and clinically relevant postoperative pancreatic fistula were independent prognostic factors for delayed gastric emptying. Hand-sewn anastomosis was associated with a lower incidence rate of clinically relevant delayed gastric emptying after pancreaticoduodenectomy. Stapled anastomosis, intra-abdominal infection, and clinically relevant postoperative pancreatic fistula could increase the incidence of postoperative clinically relevant delayed gastric emptying. Hand-sewn anastomosis should be considered by surgeons to reduce the occurrence of postoperative delayed gastric emptying and improve patient outcomes. [ABSTRACT FROM AUTHOR]

Highlights • Raman technologies in the area of horticultural product evaluation are reviewed. • Raman principles, techniques, instruments, and data analysis methods are presented. • Applications for quality and safety of horticultural products are discussed. Abstract This paper gives an overview of Raman technology for inspecting quality and safety of horticultural products. Emphasis is put on introduction and demonstration of Raman spectroscopy and imaging techniques for practical uses to assess the horticultural products. Raman scattering principles are presented first, followed by introduction and comparison to Raman measurement techniques, such as backscattering Raman spectroscopy, transmission Raman spectroscopy, spatially offset Raman spectroscopy, Raman chemical imaging, surface-enhanced Raman spectroscopy, etc. Raman measurement instruments, including excitation sources, wavelength separation devices, detectors, commercial integrated and custom-developed systems, and system calibration methods, are discussed and compared. Raman data analysis methods, such as data preprocessing, spectral mixture analysis, and quantitative analysis, are presented with examples for analyzing Raman spectral and image data of selected horticultural products including tomato and carrot. Raman spectroscopy and imaging applications for quality and safety evaluation of the horticultural products are also reviewed. [ABSTRACT FROM AUTHOR]

Abstract The oxidation kinetics of uranium surfaces modified by pulsed laser nitriding in air at temperatures of 420, 440, 450 and 460 K has been investigated. X-ray diffraction (XRD), Auger electron spectroscopy (AES) and scanning electron microscopy (SEM) were used to characterize the structure, morphology and composition of the samples. The nitrided uranium was consisted of three parts: an outer thin uranium oxide (UO 2) layer in contact with air, an inner oxygen diffusion layer at the interface, which was formed by the diffusion of oxygen into the uranium mononitride (UN) and the quantity of oxygen descended gradually as the modified layer thickening, and an underlying UN layer mixed with metallic uranium. Oxide thickness measurements via in situ XRD indicate that a linear oxidation kinetics for the nitrided uranium was observed at 460 K. At temperature range 420–450 K, the oxidation kinetics can clearly be subdivided into two stages: a non-linear curve, initial region of slow oxide-film growth, which is followed by a much faster growth stage of a linear curve. The transformation critical thickness was about 300 nm. The average activation energy of oxidation was estimated to be 118.8 kJ/mol and 89.5 kJ/mol, when the oxide-film for new growth was below and above the critical thickness, respectively. Highlights • Oxidation kinetics of uranium surfaces modified by pulsed laser nitriding in air was investigated. • The oxidation kinetics can clearly be subdivided into two different stages: a non-linear curve and a linear curve. • The activation energies calculated for the oxide growth are Q non-linear = 118.8 kJ/mol and Q linear = 89.5 kJ/mol. [ABSTRACT FROM AUTHOR]

Despite its biochemical importance, a complete Raman analysis of arachidonic acid (AA, 20:4n-6) has never been reported. Gradient temperature Raman spectroscopy (GTRS) applies the temperature gradients utilized in differential scanning calorimetry (DSC) to Raman spectroscopy, providing a straightforward technique to identify molecular rearrangements that occur near and at phase transitions. Herein we utilize the GTRS technique for AA and 1 -18:0, 2 -20:4n-6 phosphatidyl choline (AAPC) from cryogenic to mammalian body temperatures. 20 Mb three-dimensional data arrays with 0.2 °C increments and first/second derivatives allowed complete assignment of solid, liquid and transition state vibrational modes. The AA DSC shows a large exothermic peak at −60 °C indicating crystallization or a similar major structural change. No exothermic peak of this magnitude was observed in six other unsaturated lipids (DHA, n-3DPA, n-6DPA, LA, ALA, OA). Melting in AA occurs over a large range: (−60 to −35 °C): very large frequency offsets and intensity changes correlate with premelting initiating circa −60 °C, followed by melting (−37 °C). Novel, unique 3D structures for both molecules reveal that AA is not symmetric as a free fatty acid, and it changes significantly when in the sn-2 phospholipid position. Further, different CH and CH 2 sites are unequally elastic and nonequivalent. [ABSTRACT FROM AUTHOR]

Subsurface inspection of food and agricultural products is challenging for optical-based sensing techniques due to complex interactions between light and heterogeneous or layered samples. In this study, a method for subsurface food inspection was presented based on a newly developed line-scan spatially offset Raman spectroscopy (SORS) technique. A 785 nm point laser was used as a Raman excitation source. The line-shape SORS data from the sample was collected in a wavenumber range of 0–2815 cm −1 using a detection module consisting of an imaging spectrograph and a CCD camera. Two layered samples, one by placing a 1 mm thick plastic sheet cut from original container on top of cane sugar and the other by placing a 5 mm thick carrot slice on top of melamine powder, were created to test the subsurface food inspection method. For each sample, a whole set of SORS data was acquired using one CCD exposure in an offset range of 0–36 mm (two sides of the incident laser point) with a spatial interval of 0.07 mm. Raman spectra from the cane sugar under the plastic sheet and the melamine powder under the carrot slice were successfully resolved using self-modeling mixture analysis (SMA) algorithms, demonstrating the potential of the technique for authenticating foods and ingredients through packaging and evaluating internal food safety and quality attributes. The line-scan SORS measurement technique provides a rapid and nondestructive method for subsurface inspection of food safety and quality. [ABSTRACT FROM AUTHOR]

Both surface and subsurface food inspection is important since interesting safety and quality attributes can be at different sample locations. This paper presents a multipurpose line-scan Raman platform for food safety and quality research, which can be configured for Raman chemical imaging (RCI) mode for surface inspection and spatially offset Raman spectroscopy (SORS) mode for subsurface inspection. In the RCI mode, macro-scale imaging was achieved using a 785 nm line laser up to 24 cm long with a push-broom method. In the SORS mode, a 785 nm point laser was used and a complete set of SORS data was collected in an offset range of 0–36 mm with a spatial interval of 0.07 mm using one CCD exposure. The RCI and SORS modes share a common detection module including a dispersive imaging spectrograph and a CCD camera, covering a Raman shift range from −674 to 2865 cm −1 . A pork shoulder and an orange carrot were used to test large-field-of-view (230 mm wide) and high-spatial-resolution (0.07 mm/pixel) settings of the RCI mode for food surface evaluation. Fluorescence-corrected images at selected Raman peak wavenumbers were used to view Raman-active analytes on the whole sample surfaces (e.g., fat on the pork shoulder and carotenoids over the carrot cross section). Also, three layered samples, which were created by placing carrot slices with thicknesses of 2, 5, and 8 mm on top of melamine powder, were used to test the SORS mode for subsurface food evaluation. Raman spectra from carrot and melamine were successfully resolved for all three layered samples using self-modeling mixture analysis. The line-scan Raman imaging and spectroscopy platform provides a new tool for surface and subsurface inspection for food safety and quality. [ABSTRACT FROM AUTHOR]

Highlights: [•] Nondestructive inspection can be implemented for high speeds and product volumes. [•] Food inspection applications can include external and internal attributes of food. [•] Automated online imaging has great potential for the food processing industry. [Copyright &y& Elsevier]

Abstract: The potential of Raman chemical imaging for simultaneously detecting multiple adulterants in milk powder was investigated. Potential chemical adulterants, including ammonium sulphate, dicyandiamide, melamine, and urea, were mixed together into skim dry milk in the concentration range of 0.1–5.0% for each adulterant. Using a 785-nm laser, a Raman imaging system acquired hyperspectral images in the wavenumber range of 102–2538cm−1 for a 25×25mm2 area of each mixture sample, with a spatial resolution of 0.25mm. Self-modelling mixture analysis (SMA) was used to extract pure component spectra, by which the four types of the adulterants were identified at all concentration levels based on their spectral information divergence values to the reference spectra. Raman chemical images were created using the contribution images from SMA, and their use to effectively visualise identification and spatial distribution of the multiple adulterant particles in the dry milk was demonstrated. [Copyright &y& Elsevier]

Abstract: This research explored the use of spatially offset Raman spectroscopy (SORS) for nondestructive evaluation of internal maturity of tomatoes. A Raman system using a 785-nm laser was developed to collect spatially offset spectra in the wavenumber range of 200–2500cm−1. The SORS measurements were conducted using a source-detector distance ranging from 0 to 5mm with a step size of 0.2mm. One hundred and sixty tomatoes at seven ripeness stages (i.e., immature green, mature green, breaker, turning, pink, light red, and red) were tested. The feasibility of the SORS for subsurface detection was examined by using a Teflon slab placed under outer pericarp slices of 5-mm and 10-mm thicknesses cut from green and red tomatoes. Raman signals from the outer pericarp layer and the Teflon layer were effectively separated by self-modeling mixture analysis of the offset spectra after fluorescence correction. Three Raman peaks due to carotenoids inside the tomatoes started showing at the mature green stage. Two peaks appeared consistently at 1001 and 1151cm−1, and the third peak was gradually shifted from 1525cm−1 (lutein at mature green stage) to 1513cm−1 (lycopene at red stage) owing to the loss of lutein and β-carotene and the accumulation of lycopene during tomato ripening. The Raman peak changes were evaluated by spectral information divergence (SID) with pure lycopene as the reference. The SID values decreased as the tomatoes ripened, and thus these values can be used to evaluate the internal ripeness of tomatoes. [Copyright &y& Elsevier]

Abstract: Inspection of citrus canker is crucial due to its fast spread, high damage potential, and massive impact on export and domestic trade. This research was aimed to develop a prototype for real-time citrus canker detection. An inspection module was developed on a one-line commercial fruit sorting machine. Twenty tungsten halogen spotlights coupled with an aluminum dome painted with white diffuse paint provided reflectance illumination to the fruits in the detection chamber. The camera unit was a two-band spectral imaging system, which mainly consisted of a beamsplitter, two bandpass filters with central wavelengths at 730 and 830nm, and two identical monochrome cameras. Using an exposure time of 10ms, the imaging system can capture narrowband images without blurring from samples moving at a speed of 5 fruits/s. Spatial resolution of the acquired images was 2.3pixels/mm. Real-time image processing and classification algorithms were developed based on a two-band ratio approach (i.e., R830/R730). The system was tested using 360 grapefruits with normal surface, canker lesions, and other peel diseases and defects. The overall classification accuracy was 95.3%, demonstrating that the methodology as well as the hardware and the software are effective and suitable for real-time citrus canker detection. Greasy spot, melanose, and sooty mold could generate false positive errors for the fruits without canker. The current system setup was limited to a single perspective view of the fruits. Future work will be conducted with an emphasis on whole surface inspection of each fruit. [Copyright &y& Elsevier]

Abstract: Lycopene is a major carotenoid in tomatoes and detecting changes in its content can be used to monitor the ripening of tomatoes. Raman chemical imaging is a new technique that shows promise for mapping constituents of interest in complex food matrices. In this study, a benchtop point-scan Raman chemical imaging system was developed to detect and visualize internal lycopene distribution during postharvest ripening of tomatoes. Tomato samples at different ripeness stages (i.e., green, breaker, turning, pink, light red, and red) were selected and cut open for imaging. Hyperspectral Raman images were acquired from fruit cross-sections in the wavenumber range of 200–2500cm−1 with a spatial resolution of 1mm. A polynomial curve-fitting method was used to correct for the underlying fluorescence background in the original spectra. A hyperspectral image classification method was developed based on spectral information divergence to identify lycopene in the tomato cross-sections. Raman chemical images were created to visualize the spatial distribution of the lycopene for different ripeness stages. The system was also configured to test the feasibility of utilizing spatially offset Raman spectroscopy (SORS) technique for subsurface detection of a Teflon slab placed under samples of outer pericarp cut in 5-mm and 10-mm thick slices from green and breaker tomatoes. The results showed that the Raman spectrum of Teflon can be extracted from the SORS measurements of the pericarps placed over the Teflon, demonstrating the potential of the future development of a Raman-based nondestructive approach for subsurface detection of lycopene as an indicator of tomato maturity. [Copyright &y& Elsevier]

Abstract: Objective: To investigate the clinical characteristics, diagnosis and surgical treatment of intravenous leiomyomatosis (IVL), and outline the differences between Chinese and overseas cases. Methods: Clinical data of two IVL cases, treated in our hospital, were analyzed retrospectively and the related literature was also reviewed. The data of preoperative diagnostic rate, surgical procedures, and postoperative recurrence between patients in China and other countries were compared. Results: The first stage operation was performed successfully in 2 patients. However, they refused subsequent therapies, including a second stage operation to excise the remnants of the tumor, uterus, bilateral oviducts and ovaries, and anti-estrogen therapy. Both suffered from IVL recurrence, one at 6-month and the other at 9-month, and died at 16-month and 12-month respectively after the first stage surgery. Worldwide reports of 110 IVL cases were reviewed, which included 28 cases in China and 82 cases in other countries. In the majority of the Chinese patients, tumors only extended into the right atrium rather than the right ventricle (RA 22 cases vs RV 4 cases). However, among the overseas patients, the rate of extension into the right atrium was similar to that of extension into the right ventricle (RA 41 cases vs RV 38 cases). The rate of hysterectomies was not significantly different between Chinese and overseas patients (67.86% vs 55.9%, P=0.278). The rate of correct preoperative diagnosis in the Chinese patients was significantly lower than that in the overseas patients (32.14% vs 80%, P=0.000002), as well as the rate of complete excision of the tumor (22.7% vs 75.5%, P=0.000001). The proportion of patients who undergoing a single-stage or a two-stage operation was similar in Chinese and overseas patients. The recurrence rate was significantly higher in the Chinese patients than in the overseas patients (36.8% vs 9.1%, P=0.0055), and the patients with tumor recurrence were partial tumor excision patients. Conclusion: The possibility of IVL should be considered if echocardiography in female patients demonstrates a tumor in the right heart and a mass in the inferior vena cava (IVC). Further imaging should be performed to confirm the diagnosis. The correct diagnosis and accurate preoperative delineation of tumor extension are essential for an optimal surgical outcome. The key point in IVL treatment is the complete excision of tumors (single-stage or two-stage surgical procedure). [Copyright &y& Elsevier]

Abstract: Citrus canker is one of the most devastating diseases that threaten marketability of citrus crops. This research was aimed to develop a hyperspectral imaging approach for detecting canker lesions on citrus fruit. A hyperspectral imaging system was developed for acquiring reflectance images from citrus samples in the spectral region from 450 to 930nm. Ruby Red grapefruits with cankerous, normal and other common peel diseases including greasy spot, insect damage, melanose, scab, and wind scar were tested. Spectral information divergence (SID) classification method, which was based on quantifying the spectral similarities by using a predetermined canker reference spectrum, was performed on the hyperspectral images of the grapefruits for differentiating canker from normal fruit peels and other citrus surface conditions. The overall classification accuracy was 96.2% using an optimized SID threshold value of 0.008, which was determined under the condition that the errors of false negative and false positive were weighted equally. Considering the high economic impact of missing a cankerous fruit, zero false negative error was achieved by using a threshold value of 0.009, under which the classification accuracy was 95.2%. This research demonstrated that hyperspectral imaging technique coupled with the SID based image classification method could be used for discriminating citrus canker from other confounding diseases. [Copyright &y& Elsevier]

This paper reports on the measurement of the optical properties of fresh fruits and vegetables over the visible and short-wave near-infrared region (500–1000nm) using a spatially resolved steady-state diffuse reflectance technique. A hyperspectral imaging system in line scan mode was used to acquire spatially resolved diffuse reflectance images from the samples of apple (three varieties), peach, pear, kiwifruit, plum, cucumber, zucchini squash, and tomato (at three ripeness stages) over the spectral range of 500–1000nm. The absorption and reduced scattering coefficients of the samples were determined from the spatially resolved scattering profiles using inverse algorithms for a diffusion theory model. Spectra of the absorption coefficient were featured by major pigments (chlorophyll, anthocyanin, and carotenoid) and water in the samples, whereas spectra of the reduced scattering coefficient generally decreased with the increase of wavelength. Values of the absorption and reduced scattering coefficients varied greatly among the test samples. Large differences in the absorption spectra were observed for the tomatoes of three ripeness stages (green, pink, and red), and their ripeness was correctly classified using the ratio of the absorption coefficient at 675nm (for chlorophyll) to that at 535nm (for anthocyanin). Values of the reduced scattering coefficient positively correlated with the firmness of tomatoes at individual wavelengths of 500–1000nm, with the maximum correlation of 0.66 being obtained at 790nm. Light penetration depths, defined as the depths at which the incident light was reduced by 99%, were estimated to be between 0.97 and 6.52cm for the fruit and vegetable samples over the wavelength range of 500–1000nm; they were influenced by major pigments in the plant tissue. The spatially resolved steady-state diffuse reflectance technique provides a convenient and efficient means for measuring the optical properties of turbid food and agricultural products. [Copyright &y& Elsevier]

Substitution of high-priced fish species with inexpensive alternatives and mislabeling frozen-thawed fish fillets as fresh are two important fraudulent practices of concern in the seafood industry. This study aimed to develop multimode hyperspectral imaging techniques to detect substitution and mislabeling of fish fillets. Line-scan hyperspectral images were acquired from fish fillets in four modes, including reflectance in visible and near-infrared (VNIR) region, fluorescence by 365 nm UV excitation, reflectance in short-wave infrared (SWIR) region, and Raman by 785 nm laser excitation. Fish fillets of six species (i.e., red snapper, vermilion snapper, Malabar snapper, summer flounder, white bass, and tilapia) were used for species differentiation and frozen-thawed red snapper fillets were used for freshness evaluation. All fillet samples were DNA tested to authenticate the species. A total of 24 machine learning classifiers in six categories (i.e., decision trees, discriminant analysis, Naive Bayes classifiers, support vector machines, k-nearest neighbor classifiers, and ensemble classifiers) were used for fish species and freshness classifications using four types of spectral data in three different datasets (i.e., full spectra, first ten components of principal component analysis, and bands selected by sequential feature selection method). The highest accuracies were achieved at 100% using full VNIR reflectance spectra for the species classification and 99.9% using full SWIR reflectance spectra for the freshness classification. The VNIR reflectance mode gave the overall best performance for both species and freshness inspection, and it will be further investigated as a rapid technique for detection of fish fillet substitution and mislabeling. • Multimode hyperspectral imaging techniques were used to authenticate fish fillets. • Different fish species and freshness showed differences in four types of spectra. • Fish species and freshness can be classified using spectral machine learning methods. • Visible-near-infrared reflectance can be used to develop a low-cost detection device. [ABSTRACT FROM AUTHOR]

Raman imaging can analyze biological materials by generating detailed chemical images. Over the past decade, significant advancements in Raman imaging and data analysis techniques have overcome problems such as long data acquisition and analysis times and poor sensitivity. In this review article, Raman spectroscopy and imaging are introduced and the corresponding computational methods for image data analysis are discussed. We provide an overview of the applications of this method in areas such as food, pharmaceutical, and biomedical sectors, with emphasis on recent developments that have helped industrialize its applications in various sectors. Finally, the current limitations and trends for future Raman imaging are outlined and discussed with a view toward new research practices for applying this technique more efficiently and adaptably in numerous sectors. [ABSTRACT FROM AUTHOR]

[Display omitted] • Angiogenesis impairment caused by GBHs is related to mitochondrial dysfunction. • GBHs have negative impact on placental function. • Maternal GBHs exposure during pregnancy impairs postnatal progeny health. • Betaine protects placenta and postnatal progeny against GBHs-induced damage. • The limit level of glyphosate residue by governments needs to be reappraised. Glyphosate-based herbicides (GBHs) are the most widely used pesticide worldwide and can provoke placental injury. However, whether and how GBHs damage angiogenesis in the placenta is not yet known. This work evaluated the safety of glyphosate on pregnant sows based on the limit level by governments and investigated the effects and mechanism of Low-GBHs (20 mg/kg) and High-GBHs (100 mg/kg) exposure on placental angiogenesis. Results showed that gestational exposure to GBHs decreased placental vessel density and cell multiplication by interfering with the expression of VEGFA, PLGF, VEGFr2 and Hand2 (indicators of angiogenesis), which may be in relation to oxidative stress-induced disorders of mitochondrial fission and fusion as well as the impaired function of the mitochondrial respiratory chain. Additionally, GBHs destroyed barrier function and nutrient transport in the placenta, and was accompanied by jejunum oxidative stress in newborn piglets. However, GBHs exposure had no significant differences on sow reproductive performance. As a natural antioxidant, betaine treatment protected placenta and newborn piglets against GBHs-induced damage. In conclusion, GBHs impaired placental angiogenesis and function and further damaged the health of postnatal progeny, these effects may be linked to mitochondrial dysfunction. Betaine treatment following glyphosate exposure provided modest relief. [ABSTRACT FROM AUTHOR]

[Display omitted] • Phospholipids containing sn1 saturated and sn2 polyunsaturated fatty acids are the most common in biological membranes. • 1- 18:0, 2- 20:4n-6; 1- 18:0 2- 22:6n-3; 1- 18:0, 2- 18:0 neat/molecularly hydrated were analyzed with gradient temperature Raman. • Phase transitions and numerous spectral differences resulting from hydration and double bonds were observed. • Molecular models showed minimal water makes large structural changes; hydrated 1- 18:0 2- 22:6n-3 is strikingly compact. Mixed chain phospholipids containing a saturated fatty acid at sn 1 and a polyunsaturated fatty acid in sn 2 are common in the specialized biological membranes prevalent in neural, retinal and organ tissues. Particularly important are mixed lipids containing palmitic or stearic acid and arachidonic or docosahexaenoic acid. Gradient temperature Raman spectroscopy (GTRS) applies the temperature gradients utilized in differential scanning calorimetry to Raman spectroscopy, providing a straightforward technique to identify molecular rearrangements and phase transitions. Herein we utilize GTRS for 1- 18:0, 2 -20:4n-6 PC; 1- 18:0 2- 22:6n-3 PC; and 1 -18:0, 2 -18:0 PC from −80 to 50 °C temperatures. 20 Mb three-dimensional data arrays with 0.2 °C increments and first/second derivatives allowed detailed vibrational mode assignment and analysis. Samples were analyzed neat and with molecular hydration. Previously reported phase transitions for hydrated 18:0−20:4PC and 18:0−22:6PC and numerous spectral differences resulting from hydration and the double bond structure were clearly observed. Molecular models showed that the addition of minimal water molecules results in significant structural differences compared to the neat molecules; 18:0−22:6PC is strikingly compact with water when viewed from the hydrophilic end. This precise Raman data cannot be observed in typically utilized fully hydrated vesicle samples, however the improved GTRS will allow for more precise analysis in fully hydrated vesicles because the underlying modes in the unavoidably broadened spectra can be identified. [ABSTRACT FROM AUTHOR]

Packaged food safety has gained increasing attention worldwide. Existing analytical methods pose difficulties in accurately measuring food quality without destroying the packaging. In this study, a nondestructive detection method for packaged food was proposed based on the generalized Gaussian model for Raman scattering images. The Raman peaks of the scattering image were extracted, and the attenuation information of the peaks far from the laser point were imported into the established generalized Gaussian model. Analysis of the histogram of residual distribution revealed that the difference in residual distribution was enhanced, and an appropriate threshold was selected to separate the Raman baseline correction spectrum of the internal materials. Food-grade polyethylene sheets with thicknesses of 1, 2, and 3 mm were used as packaging materials for comparison experiments. The proposed model can accurately separate the Raman peak of the subsurface material when 1 mm-thick polyethylene was used as the packaging. Food-grade plastic sheets of polyethylene, polypropylene and high-density polyethylene were covered with pure substances such as melamine, sodium nitrite, and maleic anhydride. This model was considered suitable for most food-grade plastic packaging, and the subsurface materials did not influence the separation effect. Finally, evaluation of premium white granulated sugar demonstrated that the model effectively separated the Raman peak produced by packaged food and detected the packaged food without conferring damage. • This method can be applied to nondestructive testing with packaged foods. • Generalized Gaussian model separated food and package Raman peaks. • Two-layer sample experiments verified that this method is effective. • Analyzed the scope of application by changing the sample materials. [ABSTRACT FROM AUTHOR]

Total volatile basic nitrogen (TVB-N) content is an important index used to evaluate the freshness of pork. In this paper, a strategy for measurement of TVB-N content in pork through hyperspectral imaging (HSI) (400–1000 nm) was developed. Firstly, image textural features based on Gabor filter and spectral features were obtained from the hyperspectral image after determining the region of interest. Then, nine feature wavelengths were selected using partial least-squares projection algorithm. And, major components were obtained from the 2D principal component analysis (2DPCA). Finally, a calibration model was established based on major components using least-squares support vector machine to predict TVB-N values. The results of two methods for data fusion, which are 2DPCA and principal component analysis (PCA), are compared. The correlation coefficients of prediction ( R P ) and root-mean-square errors of prediction (RMSEP) obtained through 2DPCA were 0.955 and 1.86 mg/100 g respectively, which was superior to the results based on PCA ( R P = 0.944, RMSEP = 2.07 mg/100 g). Compared to PCA, the residual prediction deviations (RPD) based on 2DPCA was raised from 3.01 to 3.35. Results demonstrated that the proposed model based on 2DPCA exhibited potential for nondestructive detection of TVB-N content in pork. [ABSTRACT FROM AUTHOR]

Docosahexaenoic acid (DHA, 22:6n-3) is exclusively utilized in fast signal processing tissues such as retinal, neural and cardiac. N-3 docosapentaenoic acid (n-3DPA, 22:5n-3), with just one less double bond, is also found in the marine food chain yet cannot substitute for DHA. Gradient temperature Raman spectroscopy (GTRS) applies the temperature gradients utilized in differential scanning calorimetry (DSC) to Raman spectroscopy, providing a straightforward technique to identify molecular rearrangements that occur near and at phase transitions. Herein we apply GTRS and both conventional and modulated DSC to n-3DPA and DHA from −100 to 20 °C. Three-dimensional data arrays with 0.2 °C increments and first derivatives allowed complete assignment of solid, liquid and transition state vibrational modes. Melting temperatures n-3DPA (−45 °C) and DHA (−46 °C) are similar and show evidence for solid-state phase transitions not seen in n-6DPA (−27 °C melt). The C6H2 site is an elastic marker for temperature perturbation of all three lipids, each of which has a distinct three dimensional structure. N-3 DPA shows the spectroscopic signature of saturated fatty acids from C1 to C6. DHA does not have three aliphatic carbons in sequence; n-6DPA does but they occur at the methyl end, and do not yield the characteristic signal. DHA appears to have uniform twisting from C6H2 to C12H2 to C18H2 whereas n-6DPA bends from C12 to C18, centered at C15H2. For n-3DPA, twisting is centered at C6H2 adjacent to the C2-C3-C4-C5 aliphatic moiety. These molecular sites are the most elastic in the solid phase and during premelting. [ABSTRACT FROM AUTHOR]

One of the great unanswered questions with respect to biological science in general is the absolute necessity of docosahexaenoic acid (DHA, 22:6n-3) in fast signal processing tissues. N-6 docosapentaenoic acid (n-6DPA, 22:5n-6), with just one less double bond, group, is fairly abundant in terrestrial food chains yet cannot substitute for DHA. Gradient temperature Raman spectroscopy (GTRS) applies the temperature gradients utilized in differential scanning calorimetry (DSC) to Raman spectroscopy, providing a straightforward technique to identify molecular rearrangements that occur near and at phase transitions. Herein we apply GTRS and DSC to n-6DPA and DHA from −100 to 20 °C. 20 Mb three-dimensional data arrays with 0.2 °C increments and first/second derivatives allowed complete assignment of solid, liquid and transition state vibrational modes, including low intensity/frequency vibrations that cannot be readily analyzed with conventional Raman. N-6DPA and DHA show significant spectral changes with premelting (−33 and −60 °C, respectively) and melting (−27 and −44 °C, respectively). The CH2 (HC CH) CH2 moieties are not identical in the second half of the DHA and DPA structures. DPA has bending (1450 cm −1 ) over almost the entire temperature range. In contrast, DHA contains major CH 2 twisting (1265 cm −1 ) with no noticeable CH 2 bending, consistent with a flat helical structure with a small pitch. Further modeling of neuronal membrane phospholipids must take into account torsion present in the DHA structure, which essential in determining whether the lipid chain is configured more parallel or perpendicular to the hydrophilic head group. [ABSTRACT FROM AUTHOR]

Since 2008, the detection of the adulterant melamine (2,4,6-triamino-1,3,5-triazine) in food products has become the subject of research due to several food safety scares. Near-infrared (NIR) hyperspectral imaging offers great potential for food safety and quality research because it combines the features of vibrational spectroscopy and digital imaging. In this study, NIR hyperspectral imaging was investigated for quantitative evaluation of melamine particles in nonfat and whole milk powders. Melamine was mixed into milk powders in a concentration range of 0.02–1.00% (w/w). A NIR hyperspectral imaging system was used to acquire images (938–1654 nm) of melamine powder, whole milk powder, nonfat milk powder, and mixtures of melamine and each of the milk powders. Two optimal bands (1447 nm and 1466 nm) were selected by a linear correlation algorithm with pure milk and pure melamine. Band ratio (B 1447/1466 ) images coupled with a single threshold were used to create resultant images to visualize identification and distribution of the melamine adulterant particles in milk powders. The identification results were verified by spectral feature comparison between separated mean spectra of melamine pixels and milk pixels. Linear correlations (r) were found between the number of pixels identified as containing melamine and melamine concentration in nonfat milk and whole milk powders, which were 0.980 and 0.970 or higher, respectively. The study demonstrated that the combination of NIR hyperspectral imaging and simple band ratioing was promising for rapid quantitative analysis of melamine in milk powders. [ABSTRACT FROM AUTHOR]

The objectives of this study were to investigate the feasibility of hyperspectral scattering imaging to predict the bacterial contamination in meat nondestructively, and propose an optimal approach for detecting low levels of total viable count (TVC) contamination in beef. Fresh beef samples were obtained from a commercial slaughtering plant, and stored at 4 °C for 0–12 days. The visible/near-infrared (VIS/NIR) hyperspectral images in the backscattering mode were acquired from 3–5 beef samples on each day of the experiment, in parallel with microbiological analysis to enumerate the TVC population. Lorentzian function was used to resolve the light scattering information within the hyperspectral image and consequently Lorentzian parameters, which represented different hyperspectral scattering characteristics were extracted. In this study, not only the individual Lorentzian parameters but also the parameter combinations were used to establish the multivariate statistical models for predicting beef TVC, based on the modeling methods of principal component regression (PCR), partial least squares regression (PLSR), and back propagation neural network (BPNN), respectively. The models established using individual Lorentzian parameters did not perform well in predicting low levels of TVC contamination in beef, and the best prediction result could only achieved with the correlation coefficient of prediction set ( R P ) and root mean squared error of prediction set (RMSEP) of 0.81 and 1.27 log CFU/g, respectively. Based on the parameter combinations, the best modeling results were achieved with R P and RMSEP of 0.86 and 0.93 log CFU/g, 0.87 and 0.79 log CFU/g, 0.90 and 0.88 log CFU/g by PCR, PLSR, and BPNN methods, respectively, which confirmed the superiority of the parameter combination method. The results of this study demonstrated for the first time that hyperspectral scattering imaging combined with Lorentzian function and the proposed parameter combination method could be used to detect low levels of bacterial contamination in beef nondestructively. [ABSTRACT FROM AUTHOR]

Aflatoxins, commonly found in corn and corn-derived products, can cause severe illness in animals and humans if consumed in significant amounts. Early detection is critical to preventing illness, but the most sensitive and effective of commonly used screening tools for aflatoxins are expensive and cumbersome methods based on chromatography or imunoassays that require technical expertise to perform. Multiple hyperspectral imaging techniques, including reflectance in the visible and near-infrared (VNIR) region and short-wave infrared (SWIR) region, fluorescence by 365 nm ultraviolet (UV) excitation, and Raman by 785 nm laser excitation, were used for detection of aflatoxin in ground maize. Four classification models based on linear discriminant analysis (LDA), linear support vector machines (LSVM), quadratic discriminant analysis (QDA), and quadratic support vector machines (QSVM) algorithms were developed for classification with each hyperspectral imaging mode. The multivariate classification models in combination with different preprocessing methods were applied for screening of maize samples naturally contaminated with aflatoxin. The classification accuracies for fluorescence with QSVM, VNIR with QSVM, SWIR with LSVM, and Raman with LSVM were 95.7%, 82.6%, 95.7%, and 87.0%, respectively, with no false-negative error at the cutoff of 10 μg/kg. The SWIR and fluorescence models showed slightly higher performance accuracies, suggesting that they may be more effective and efficient analytical tools for aflatoxin analysis in maize compared to conventional wet-chemical methods. These methods show promise as inexpensive, and easy-to-use screening tools for food safety, to rapidly detect aflatoxins in maize or other food ingredients intended for animal or human consumption. • Comparison of reflectance, fluorescence, and Raman imaging for aflatoxin in maize • Machine learning algorithms for analysis of hyperspectral images of ground maize • Higher classification accuracies from fluorescence and SWIR reflectance imaging • Easy-to-use screening tools to rapidly detect aflatoxin contamination for food safety [ABSTRACT FROM AUTHOR]

Highlights: [•] Hyperspectral near-infrared imaging to detect low-concentration melamine in dry milk. [•] Visualization of melamine at 200ppm in milk powder without sample pretreatment. [•] Potential detection technique to screen food ingredients for multiple adulterants. [Copyright &y& Elsevier]

Highlights: [•] Optical instrument was developed for pesticide residue detection in apple surface. [•] Hardware and software system was self developed as prototype instrument. [•] The instrument can detect chlorpyrifos pesticide in apple surface nondestructively. [•] 6.69mg/kg of pesticide residue in apple surface is detectable by the instrument. [•] The system can detect the pesticide residue in apple surface within 4s. [ABSTRACT FROM AUTHOR]

Prawns are highly popular with consumers but present many technical difficulties for the evaluation of their internal quality when intact (in-shell prawns). This study proposed a nondestructive method to assess the internal quality of intact prawns (Fenneropenaeus chinensis) using spatially offset Raman spectroscopy (SORS) technique combined with data modeling analysis. This technique holds promise due to the capability of SORS to obtain chemical information nondestructively from below the surface of a sample material. Raman scattering image data for 100 fresh prawns (approximately 15 g each) were collected using a line-scan Raman imaging system over the course of seven days with 24 h measurement intervals. Measurement anomalies due to physical prawn irregularities were eliminated using a peak identification method. Twenty feature bands selected by Random Forest (RF) method were input to Partial Least Squares Regression (PLSR), Support Vector Regression (SVR), and Extremely Randomized Tree (ET) models to predict the freshness of prawns during the storage time. The prediction model based on SORS enhanced data and combining RF feature band selection with SVR demonstrated the best performance, with RMSEP, R2, and RPD values of 0.71, 0.88, and 2.63, respectively. This rapid and nondestructive method for quality evaluation may be feasible as a practical means of assessing internal quality of materials that demonstrate surface interference, such as in-shell prawns. • This method can be applied to nondestructive testing with intact prawns. • Spatially offset Raman spectroscopy technique enhanced internal signal. • Feature bands were extracted by Random Forest model. • Verified the effectiveness of this method by multi-model comparison. [ABSTRACT FROM AUTHOR]

Abstract: MDM2 is a phosphoprotein that interacts with P53 and inhibits its activity. Recently, a T/G substitution (SNP309) in the promoter of MDM2 was identified and has been demonstrated to be associated with an increased MDM2 expression and a significantly earlier age of onset of several tumors, including breast cancer. To test the hypothesis that this functional variant in the MDM2 promoter is associated with risk of breast cancer, we conducted a molecular epidemiological study of 366 breast cancer cases (BC), 263 patients with benign breast diseases (BBD) and 605 cancer-free controls in China, in which we genotyped this T/G variant and another common insertion/deletion polymorphism (Del1518) in the MDM2 promoter and evaluated the associations between these two polymorphisms and breast cancer risk. We found that the variant allele frequencies of these two polymorphisms were not statistically different between the cases and controls (SNP309G: 0.500, 0.542, and 0.506 in BC, BBD, and controls, respectively, and Del1518−: 0.296, 0.308, and 0.297 in BC, BBD, and controls, respectively). Logistic regression analyses revealed that the variant genotypes of both MDM2 SNP309 and Del1518 polymorphisms were not significantly associated with risk of breast cancer (adjusted OR, 1.03; 95% CI, 0.74–1.42 for SNP309 TG and GG; and adjusted OR, 1.09; 95% CI, 0.83–1.43 for Del1518 +/− and −/−). These findings suggest that these two MDM2 promoter variants may not play a major role in the etiology of breast cancer. [Copyright &y& Elsevier]

Serum vascular endothelial growth factor (VEGF) and endostatin levels were detected in 59 patients with breast cancer before surgery and at 3 weeks after surgery. Pre-operatively, their levels were significantly elevated and correlated with each other. Post-operatively, VEGF level decreased significantly and endostatin remained at a high level. Patients with both normalized VEGF and elevated endostatin following surgery had a lower risk of relapse than patients whose VEGF failed to normalize. Univariate and multivariate analyses showed a correlation between elevated VEGF level and short free-relapse survival. These findings suggest a new angiogenesis balance is formed in the patients after surgery and such a resultant balance may be beneficial for the prognosis of breast cancer, which deserves more extensive study. [Copyright &y& Elsevier]

This paper investigated a usage of multispectral imaging system based on single shot method for detecting the foreign matter (FM) in the pickled and dried mustard (PDM) on a moving conveyor belt. Multispectral images of PDM and FM in a quiescent state and the PDM mixed with FM in a moving state were respectively obtained using the multispectral imaging system with a spectral range from 676 to 952 nm and spatial resolution of 409 × 216 pixels. Pure pixel data of PDM and FM were extracted from multispectral images of the PDM and the FM in a quiescent state. For the pixel-level classification, the support vector machine (SVM) and the back propagation neural network (BPNN) were applied to develop models to classify FM and PDM on the full bands, respectively. The classification accuracy and the mean prediction time of SVM model were 98.23% and 6.8s; the classification accuracy and the mean prediction time of BPNN model were 98.07% and 0.04s. The BPNN model was selected as the optimal model considering the classification accuracy and prediction time synthetically. Using the optimal model to detect FM in the PDM during the moving process, the identification accuracy of FM was 97.9%. The results demonstrated that multispectral imaging system could be used for the online detection of foreign matter in the pickled and dried mustard. • SVM and BPNN models are used to classify PDM and FM at the pixel level. • Based on the optimal model, the FM in PDM are detected during the moving process. • The model performance is evaluated using images of the PDM mixed with FM. • The proposed method exhibits good results in detecting the FM in PDM. [ABSTRACT FROM AUTHOR]

• This method exhibits a good result of quality prediction of dried carrot slices. • A new multispectral image system is proposed for quality detection of carrot slices. • This method can detect the quality of dried carrots quickly and non destructively. Carrot has high nutritional value and health-promoting effects and is popular among consumers. Real-time quality detection of dried carrot slices allows producers to adjust the process parameters of the drying device in time, thereby ensuring the final product quality and realizing energy conservation. Traditional methods of detecting moisture content and shrinkage ratio usually require a long measurement time, which is difficult to meet the needs of practical application. This investigated a rapid method based on a novel multispectral imaging system for acquiring multispectral images of samples in 25 wavebands over the spectral region between 675 and 975 nm at one time to detect moisture content and shrinkage ratio of dried carrot slices. The multispectral images of 600 carrot slice samples, which were dried at different times, were acquired using the multispectral imaging system. After extracting the spectral and GLCM features of the samples, prediction models were developed based on partial-least squares regression (PLSR) and least squares-support vector machines (LS-SVM) by using different feature combinations. Compared with PLSR models, LS-SVM models achieved better detection accuracy for moisture content and shrinkage ratio. The LS-SVM model obtained the following best results: coefficient of determination in prediction (Rp) = 0.942, root mean square error of prediction (RMSEP) = 0.0808%, and residual predictive deviation (RPD) = 2.636 for shrinkage ratio as well as Rp = 0.953, RMSEP = 0.0902%, and RPD = 3.271 for moisture content under static condition (without movement). The detection accuracy decreased with increasing movement speed of the test sample. When the movement speed of the sample was lower than 30 mm/s, the moisture content detected achieved satisfactory accuracy, with Rp = 0.941, RMSEP = 0.0981%, and RPD = 3.001. The novel multispectral imaging system shows potential for real-time detection of moisture and shrinkage of products during drying. [ABSTRACT FROM AUTHOR]

• IR and Raman spectra were acquired from turmeric-adulterant samples. • Vibration modes were assigned and interpreted for turmeric-adulterant samples. • False positive detection of adulterants was observed in binary Raman images. • DD-SIMCA models were developed using IR spectra to authenticate yellow turmeric samples. • IR and Raman spectra can provide a more complete diagnostic fingerprint of samples. Deliberate chemical contamination of food powders has become a major food safety concern worldwide. This study used Raman imaging and FT-IR spectroscopy to detect Sudan Red and white turmeric adulteration in turmeric powder. While Sudan Red Raman spectral peaks were identifiable in turmeric-Sudan Red samples, Sudan Red false positive detection was observed in binary Raman images, limiting effective quantitative detection. In addition, white turmeric Raman spectral peaks were unidentifiable in turmeric-white turmeric mixtures. However, IR spectra of turmeric-Sudan Red and turmeric-white turmeric samples provided discrete identifier peaks for both the adulterants. Partial least squares regression models were developed using IR spectra for each mixture type. The models estimated Sudan Red and white turmeric concentrations with correlation coefficients of 0.97 and 0.95, respectively. Priority should be given to developing an IR imaging system and incorporating it with Raman system to simultaneously measure of food samples for detection of adulterants. [ABSTRACT FROM AUTHOR]

Fish products are important foodstuffs for most consumers worldwide. However, fish bones are considered as a serious hazard in fish products, and new detection techniques are increasingly needed to effectively detect fish bones. For this reason, a new method of fish-bone detection based on Raman hyperspectral imaging technology was developed to improve the detection ratio and realize automatic detection. This study describes the proposed method and the corresponding validation experiments with grass carp fillets. The differences in Raman spectra between fish bone and fish meat were investigated, and the optimal band information was selected using a fuzzy-rough set model based on the thermal-charge algorithm (FRSTCA). Then the support vector data description (SVDD) classification model was established for the selected band information (961 and 965 cm−1) to realize the automatic identification of fish bones. Finally, the composition of each pixel in the Raman hyperspectral image of the fillet sample was classified and judged by the established detection model, the fish bone position and a fish bone distribution image were finally obtained. Experiments on 191 fish bones from 22 grass carp fillets showed that our method can effectively detect fish bones with a depth of up to 2.5 mm and yielded a detection performance of 90.5%. The proposed method may open new possibilities in the field of automated fish-bone detection in grass carp and other similar fish and for the further automatic detection of other foreign bodies such as fish bone in the future. • The Raman imaging technology was firstly used in automated fish-bone detection. • Wavenumbers 961 and 965 cm−1 were selected to distinguish fish bone from meat. • This method can detect fish bones with a depth of 2.5 mm under the current system. • Yielded a detection performance of 90.5% by support vector data description model. [ABSTRACT FROM AUTHOR]