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Journal of Food Measurement and Characterization
Journal Prestige (SJR): 0.369  Citation Impact (citeScore): 1 Number of Followers: 0  Hybrid journal (It can contain Open Access articles)ISSN (Print) 2193-4126 - ISSN (Online) 2193-4134 Published by Springer-Verlag  [2468 journals]
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- Sensor fusion techniques in deep learning for multimodal fruit and
vegetable quality assessment: A comprehensive review-
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Abstract: Abstract Fruit and vegetable quality assessment is a critical task in agricultural and food industries, impacting various stages from production to consumption. Leveraging deep learning methods, particularly through sensor fusion, offers promising avenues to enhance the accuracy and robustness of quality assessment systems by amalgamating information from diverse sensor modalities such as visual, spectral, and tactile. The review scrutinizes a plethora of sensor fusion strategies, encompassing early fusion, late fusion, and hybrid fusion approaches, each with its distinct advantages and limitations. Furthermore, it explores the utilization of various deep learning architectures, including convolutional neural networks (CNNs), recurrent neural networks (RNNs), and their combinations, tailored specifically for multimodal data fusion. Additionally, attention is paid to the challenges and considerations associated with sensor fusion in this domain, including data heterogeneity, synchronization, and feature alignment. Moreover, the review discusses the implications of dataset size, diversity, and annotation quality on the effectiveness of deep learning-based fusion models. Furthermore, it sheds light on the transferability of fusion models across different fruit and vegetable types and environmental conditions, highlighting the need for domain adaptation techniques. Moreover, the review delves into the real-world applications and commercial implementations of sensor fusion-based quality assessment systems, providing insights into their scalability, efficiency, and economic viability.
PubDate: 2024-08-08
DOI: 10.1007/s11694-024-02789-z
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- Utilization of retentates for white brined cheese production: comparative
evaluation of physico-chemical and sensory properties-
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Abstract: Abstract The aim of the present study is (1) to enhance the protein fraction in cheese milk through membrane filtration and consequently (2) to separate the majority of whey as ‘ideal whey’ prior to the production of white brined cheese, and (3) to explore the potential utilization of retentates in the production of white brined cheese. The chemical, physical, textural and sensory properties of cheeses produced from microfiltration (MF) retentates were characterized to investigate the effects of cross-flow MF on white brined cheese. Polyether sulfone (MP005) membranes featuring a pore diameter of 0.05 μm and polyvinylidene fluoride (MV020) membranes with a pore diameter of 0.20 μm were utilized. The assessed quality parameters of cheeses derived from polyethersulfone membrane (MP005) retentates were similar to the control (p > 0.05), whereas the cheese obtained from polyvinylidene fluoride membrane (MV020) retentates exhibited notable differences (p < 0.05) from the control. The traditional whey generated after cheese-making, which typically requires substantial on-site processing and/or treatment, was reduced by 3.5–6.7 times using the MP005 retentates. Simultaneously, 58–70% of the cheese milk (w/w) was separated as ideal whey before the cheese-making process. MF shows potential as an eco-friendly technology suitable for use in cheese production processes. The potential utilization of MP005 for enriching the protein content in cheese milk holds promise for white cheese production.
PubDate: 2024-08-07
DOI: 10.1007/s11694-024-02808-z
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- A hyperspectral imaging technique for rapid non-destructive detection of
soluble solid content and firmness of wolfberry-
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Abstract: Abstract Soluble solid content (SSC) and firmness are significant indexes to evaluate the quality of wolfberry. This study employed hyperspectral imaging (HSI) technology for the rapid detection and visualization of the distribution of SSC and firmness in mature wolfberries. The hyperspectral images of Ningqi 1 and Ningqi 7 were collected in the range of 400–1000 nm. The image segmentation method was used to determine the region of interest (ROI) of the wolfberry samples and extract the mean spectra, and the performance of the four preprocessing techniques was evaluated based on the partial least squares (PLSR) model, which concluded that the standard normal variable transformation (SNV) and multiple scattering correction (MSC) preprocessing methods were able to achieve the optimal results. Principal component analysis (PCA), successive projection algorithm (SPA), competitive adaptive reweighted sampling method (CARS) and their combination were used to select the characteristic wavelength, with CARS-SPA being more accurate. PLSR, support vector machine regression (SVR) and backpropagation genetic algorithm (BPNN-GA) models were used to predict the soluble solid content and firmness of wolfberry by full wavelength and characteristic wavelength, respectively. The optimal model for SSC and firmness of Ningqi 1 was identified as MSC-CARS-SPA-BPNN-GA, with Rp2 of 0.949 and 0.913, RMSEP of 0.365 and 0.524, and RPD of 4.104 and 3.422, respectively. For Ningqi 7, the optimal model was SNV-CARS-SPA-BPNN-GA, with Rp2 of 0.936 and 0.880, RMSEP of 0.364 and 0.537, and RPD of 3.860 and 2.706, respectively. Finally, these optimal models were utilized to visualize the distribution of SSC and firmness in the ROI. The findings underscore the rapid and precise nature of hyperspectral imaging in detecting the SSC and firmness of wolfberry, thereby establishing a technological and theoretical foundation for expedited wolfberry quality assessment.
PubDate: 2024-08-07
DOI: 10.1007/s11694-024-02775-5
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- Characterization of extruded whole grain cereals enriched with Indian
horse chestnut flour-
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Abstract: Abstract This study explores the development of a fibre-rich breakfast cereal utilizing Indian Horse Chestnut Flour (IHCF) combined with traditional whole grains, including whole wheat flour, barley flour, and corn flour. The research focuses on optimising key extrusion process variables—feed moisture content (10–18%), barrel temperature (70–150 °C), screw speed (290–380 rpm), and IHCF concentration (1.75–4.75%) to enhance the cereal’s quality attributes. Comprehensive measurements and analyses were conducted to determine the optimal conditions, focusing on water absorption capacity, bulk density, sectional expansion, water solubility index, porosity, rehydration ratio, hardness, and overall product acceptability. Extrudates rich in IHCF were also evaluated for rheological and Fourier Transform Infrared (FTIR) spectroscopy. Statistical analysis revealed significant impacts of these variables on the cereal’s physical properties. Under optimal conditions (12% feed moisture, 130 °C barrel temperature, 380 rpm screw speed, and 2.5% IHCF), the breakfast cereal exhibited superior expansion, porosity, and rehydration ratios, along with desirable hardness, achieving an overall acceptability score of 77.1. Further, an increase in feed moisture content corresponded with improved pasting properties in the optimized extruded flours. The rheological assessment indicated that the storage modulus (G′) of both extruded and native flours surpassed the loss modulus (G″), with samples at higher moisture content displaying the highest flow index but the lowest consistency coefficient. FTIR spectroscopy analysis underscored a reduction in peak intensity during extrusion, indicating notable structural modifications in the cereal constituents. This research presents significant advancements in the measurement and characterization of breakfast cereals, underscoring the potential of IHCF as a nutritious ingredient in the food industry.
PubDate: 2024-08-06
DOI: 10.1007/s11694-024-02753-x
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- Optimization of the acid extraction process of pectin from cassava cortex
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Abstract: Pectin is an additive generally extracted from citrous and apple peels, but an increasing demand has stimulated the search for new commercial sources of this product. The cassava cortex is rich in pectin and could be destined for reuse as a new source of this additive, since the disposal of cassava processing residues results in soil and water contamination. Thus, the aim of the present study was to extract pectin from cassava cortex. Initially the flour of this residue was obtained by convective drying and characterized, providing evidence for the possibility of extracting pectin. A central rotational composite design was used to define the best extraction condition based on yield, degree of exterification and galacturonic acid for two extracting solvents (citric and acetic acid) in response to the variables concentration, time and temperature. After extraction, the samples were submitted to convective drying to obtain pectin powders. The optimum condition for pectin extraction was obtained using the desirability function of the Statistica software with the degree of esterification as the priority variable, since the aim was to obtain quality pectin favorable for application. According to the results obtained, the optimized extraction conditions with citric acid were a concentration of 7%, temperature of 62 °C and time of 90 min. With acetic acid they were a concentration of 7%, temperature of 80 °C and process time of 90 min. Graphical abstract
PubDate: 2024-08-06
DOI: 10.1007/s11694-024-02713-5
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- Novel electrochemical sensor based on zirconium phosphate phosphidation
for detection of Asulam-
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Abstract: Abstract In this study, the phosphidation of zirconium phosphate nanoparticles (ZrP) was pursued to create zirconium phosphide on the surface of ZrP (ZrP@P) by the calcination process. The morphology and structure of prepared ZrP and ZrP@P were characterized by different methods including XPS, SEM, XRD, and FT-IR. Deposited nanocomposite on a glassy carbon electrode (ZrP@P/GCE) showed boosted electrochemical properties towards oxidation of Asulam investigated by cyclic and differential pulse voltammetry techniques. After optimizing the variables affecting the ZrP@P/GCE response, the Asulam quantification was tested, and the linear range of 5–45 µg/L and detection limit of 0.16 µg/L were obtained. The phosphidation process increased the surface-active points and the active surface area of the ZrP facilitating the interaction of Asulam molecules with the GCE surface modified with ZrP@P. The ZrP@P/GCE accurately quantified Asulam in real samples such as tomato, lettuce, and cucumber with obtained recovery values of 96–113% and RSD ≤ 4.4%. This sensor offers a simple, low-cost, and convenient method to detect Asulam.
PubDate: 2024-08-05
DOI: 10.1007/s11694-024-02788-0
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- Characterization of different hempseed fractions after dehulling and
defatting: chemical composition and functional properties-
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Abstract: Abstract Hemp is a highly sustainable crop that grows rapidly and can be cultivated in a variety of climates. Hempseeds either whole or dehulled are processed into hempseed oil, hempseed protein powder, and hempseed milk, among other food products. The by-products, such as hempseed cake, are also used in animal feed processing. The aim of this study was to examine the bioactive components and functional characteristics of whole hempseed (WHS), dehulled hempseed (DHS), defatted hempseed/hempseed cake (HSC), and hempseed oil. DHS and HSC exhibited reduced condensed tannins and saponins compared to WHS. The most important cannabinoid in hempseed, d9-THC, was highest in HSC (0.061 µg/mg), followed by WHS (0.37 µg/mg), and then DHS (0.25 µg/mg). UHPLC-ESI-QTOF-MS identified 45 compounds, predominantly polyphenols in hempseed. Moreover, GC–MS detected various unsaturated fatty acids in hempseed oil, mainly C-18. WHS demonstrated potent antioxidant properties, protecting C. elegans from glucose-induced reactive oxygen species. Hempseed oil exhibited weak scavenging potential against DPPH (26.39%) and ABTS (10.30%) and showed limited antimicrobial effects against growth of pathogenic bacteria. In vitro lipase inhibition values were highest in WHS (83.63%), followed by DHS (52.94%) and HSC (43.08%). Dehulled and defatted hempseed had alpha-glucosidase inhibition values of 67.55% and 51.49%, respectively, compared to WHS (82.18%). This study offers insights into hempseed's bioactive components and health properties, serving as a reference for understanding the impact of dehulling and defatting on industrial hempseed and its oil quality as emerging food materials.
PubDate: 2024-08-05
DOI: 10.1007/s11694-024-02771-9
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- Enhancing the solubility and stability of Dendrobium officinale flavonoids
through interaction with soybean peptides-
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Abstract: Abstract Flavonoids play a major role in promoting human health, yet their instability in solution greatly limits its industrial utilization. This study aimed to introduce soybean peptides (SP) to improve the stability and solubility of Dendrobium officinale flavonoids (DOFs), and to investigate the effects of their interaction, sterilization and storage. The results revealed that DOFs bind to SP through hydrogen bonding and steric effects, leading to changes in the structure, energy, and activity of DOFs, which resulted in enhanced stability and antioxidant capacity. The sedimentation rate and flavonoid content were measured to be 24.64 ± 0.55%, 3.83 ± 0.14 mg/mL, respectively, at the optimum mass ratio of DOFs and SP of 2:5. After thermal treatment, the flavonoid content and antioxidant activity of the complexes both dramatically enhanced. The optimum sterilization condition was 75 °C for 20 min, while the optimum range of temperatures for storage was 4 ~ 25 °C. These findings provide valuable insights for the processing, preservation and application of flavonoids in the future.
PubDate: 2024-08-05
DOI: 10.1007/s11694-024-02679-4
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- Innovative utilization of olive mill wastewater phenolics extracted by
lecithin: spray-dried powders in cake formulations-
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Abstract: In the present study, the olive mill wastewater (OMW) phenolics were extracted with soy lecithin using the cloud point extraction method, and this enriched lecithin (OMW-L) was converted into spray-dried powders using maltodextrin (MD) and whey protein concentrate to be utilized as a dry food ingredient in a cake premix. The inlet temperature of 170 °C and a 3 mL/min feed flow rate yielded the highest powder yield (70.88 ± 2.12%) with a moisture content of 3.78 ± 0.03% when the mass ratio of lecithin to MD was 1:3 (w:w). The hydroxytyrosol and tyrosol contents of the powder were 42.60 ± 4.51 mg/100 g and 15.48 ± 2.50 mg/100 g, respectively. Vanillic acid, caffeic acid, 3-hydroxybenzoic acid, catechin, and rutin were also identified in the powders. The spray-dried OMW-L powder with a higher loading of polyphenols was then used in a cake premix, replacing 1% and 3% of wheat flour. This substitution significantly reduced the K value of the cake batter, as determined by rheological analyses. The addition of spray-dried OMW-L powder to the cake samples, particularly at higher concentrations (3%), influenced both crust and crumb color, causing changes in L*, a*, and b* values. The hardness values of the cake samples did not alter when blank or OMW-enriched lecithin powders were added; rather, the hardness value was influenced by the powder content. Overall, this research offers a different perspective on the use of OMW phenolics in food applications, especially in ready-to-use blends, and demonstrates the effects of the obtained spray-dried lecithin powders on batter rheology and cake characteristics. Graphical abstract
PubDate: 2024-08-03
DOI: 10.1007/s11694-024-02780-8
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- Optimization of ultrasound-assisted extraction of bioactive compounds from
carob pulp using response surface methodology-
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Abstract: Carob plant extracts contain a variety of secondary metabolites (SM) with potential health benefits. Factors such as the extraction method and the geographical origin of the plant influence the extraction yield and quality of SM extracts. This study aims to increase the percentage of aqueous fraction in the solvent used to extract SM from carob pulp from distinct regions of Morocco (Ghafsai and Tainest). At the same time, it seeks to maximize the total phenolic content (TPC) in the extracts, minimize degradation, and preserve their integrity. A preliminary screening was conducted to assess the extraction efficiency of pure aqueous and organic solvents, revealing that water, methanol, and ethanol were the most effective solvents. The mixture response surface design methodology was then applied to investigate the synergistic effect of these solvents on the extraction of Total Phenolic Content (TPC). The results from the mixture design methodology (MDM) demonstrated that the optimal solvent system was a water/methanol/ethanol blend (50:30:20 v/v/v), yielding TPC concentrations of up to 55.47 ± 0.01 and 41.85 ± 0.04 mg GAE/g from carob samples collected in Ghafsai and Tainest, respectively. These extracts also exhibited notable IC50 values (DPPH: 328.18 ± 0.21 and 879.06 ± 0.15, ABTS: 65.71 ± 0.2 and 128.05 ± 0.17, FRAP: 328.18 ± 0.21 and 879.06 ± 0.15 µg/mL for Tainest and Ghafsai samples, respectively). This study underscores the synergistic effect of the solvent mixture on TPC extraction and the influence of interregional variation on SM contents. Overall, this study advocates for the promotion and increased utilization of water as a green solvent in SM extraction from plant material, aiming to mitigate toxicity and risks associated with high proportions of organic solvents used in the extraction process. Graphical abstract
PubDate: 2024-08-02
DOI: 10.1007/s11694-024-02776-4
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- Orally dissolving yoghurt strip: a new approach in delivery of probiotics
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Abstract: Abstract The study focused on developing functional yoghurt edible film oral strip encapsulating viable probiotics (Streptococcus thermophilus (S. thermophilus), Lactobacillus bulgaricus (L. bulgaricus), and Lactococcus lactis (L. lactis)) with pectin biopolymer. The oral strip was optimized with Central Composite Design using independent variables such as functional yoghurt powder (2.5% w/v–7.5% w/v), pectin (1.5% w/v–2.5% w/v), and glycerol (55% w/w–65% w/w). The optimum oral strip was prepared at 7.5% (w/v) yoghurt powder, 2.5% (w/v) pectin, and 57.18% (w/w) glycerol, respectively. The oral strip developed with S. thermophilus, L. bulgaricus, and L. lactis had viability of 8.57 ± 0.04, 8.35 ± 0.04 and 8.44 ± 0.04 (log CFU/strip). Antibacterial zone of inhibition against Klebsiella pneumoniae and Pseudomonas aeruginosa were 12.00 ± 1.00 mm and 11.67 ± 0.58 mm accordingly. Optimized oral strip had moisture content of 9.85 ± 0.25 (%), colour difference (∆E) of 48.19 ± 1.30, tensile strength of 2.82 ± 0.07 (MPa), elongation at break of 12.68 ± 0.45 (%) and Youngs modulus as of 0.22 ± 0.01, respectively. Additionally, scanning electron microscopy of oral strip showed well-incorporated yoghurt powder in the film matrix. In the present study, nutritional improvements were developed with acceptable functional properties and probiotic viability.
PubDate: 2024-08-02
DOI: 10.1007/s11694-024-02790-6
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- Recent progress in food quality control through flavor analysis using gas
chromatography–ion mobility spectrometry-
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Abstract: Abstract With the improvement of food safety requirements, rapid, nondestructive, accurate, and high-throughput determination of volatile ingredients plays an important role in the analysis area. Owing to the advantages of high separation efficiency, high sensitivity, no sample pretreatment requirement, and fast response, gas chromatography–ion mobility spectrometry (GC–IMS) is important in the nondestructive and rapid detection of volatile organic compounds in the fields of biology, pathology, and food science. In the end, current GC–IMS applications in food safety control and quality analysis are systematically reviewed based on developments in working principles, experimental processes, and methods in cheminformatics and bioinformatics. In addition, the latest developments and advances, practical challenges and limitations, and requirements for GC–IMS applications are also critically discussed, providing new insights into GC–IMS application in food science.
PubDate: 2024-08-02
DOI: 10.1007/s11694-024-02782-6
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- Breakage of packaged cookies due to fatigue failure from repetitive shock
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Abstract: The commercial value of cookies is easily lost when they break due to mechanical stress, such as shock, during distribution. Therefore, it is important to prevent shock by incorporating a cushioning design into cookie packaging. To optimize packaging, we must first understand the type of breakage caused by shock. During distribution, fatigue failure due to repetitive shocks might be the main factor involved in breakage of cookies because events related to shock stress usually occur more than once. Accordingly, we investigated the relationships between acceleration, shock frequency, and the occurrence of breakage in two types of packaged cookies (soft and hard). A drop test was performed at heights of 0.15–0.45 m. The results suggest that both types of cookies are broken by repetitive shocks, and the relationship between the number of shocks, acceleration (related to drop height), and the occurrence of breakage can be expressed as power approximation curves. Generally, the breakage of cookies due to mechanical stress is known to be a result of brittle fractures. However, our results suggest that the visible breakage of packaged cookies due to repetitive shock may be the result of fatigue failure. In addition, we propose a simple method that uses a small accelerometer to simulate breakage during transportation. The results of this study contribute to the development of new cushioning packaging designs to reduce the breakage of cookies during transportation. Graphical Schematic of the study
PubDate: 2024-08-01
DOI: 10.1007/s11694-024-02781-7
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- The physicochemical properties and antioxidant and bacteriostatic
activities of Auricularia auricula melanin modificated by Arginine-
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Abstract: Abstract Auricularia auricula melanin has a variety of biological activities, but its application is limited because melanin is not easily soluble in water and most organic solvents. In this study, Auricularia auricula melanin was modified using arginine and analyzed for its structure, physicochemical properties, as well as antioxidant and antibacterial activities. It was found that the water solubility of melanin modified by arginine was 11.6 mg/mL. Arg-melanin is stable under cold dark conditions. Structural analysis by UV, IR and NMR revealed that Auricularia auricula melanin was mainly eumelanin. Arg-melanin exhibited scavenging activities of 75.4%, 76.7%, and 77.6% against DPPH radicals, OH radicals, and O2−, respectively, which were 9.6%, 42.2%, and 31.2% higher than those of melanin. The MICs of melanin and Arg-melanin were 2.5 mg/mL and 1.5 mg/mL against S. aureus, and 3 mg/mL against E. coli. The MIC and MBC values were identical. As the concentration of melanin increased, the strain exhibited greater growth inhibition and more nucleic acid leakage. Arginine modification of melanin can improve its water solubility, and can enhance the antioxidant and bacteriostatic activity of melanin, which provides a theoretical basis for the application of melanin in the field of food and medicine.
PubDate: 2024-08-01
DOI: 10.1007/s11694-024-02739-9
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- Non-destructive predictions of sugar contents in litchis based on
near-infrared spectroscopy and stochastic configuration network-
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Abstract: Abstract To address the problem that the traditional detection method for litchi sugar content is time-consuming and laborious and will destroy the tested sample, this paper proposed a non-destructive detection method for litchi sugar content based on near-infrared spectroscopy (NIR) and artificial intelligence algorithm. Firstly, to remove noise and other interference, the preprocessing methods for spectral data are studied. Nine preprocessing methods, such as moving average smoothing (MA), standard normal variate transform (SNV), and multiplicative scatter correction (MSC), are adopted to preprocess the spectral data. Then, to reduce the input dimension of the model and overcome the interference of redundant bands, the feature extraction methods for spectral data are examined. Two feature extraction methods, including Monte-Carlo uninformative variable elimination (MCUVE) and competitive adaptive reweighted sampling (CARS), are utilized to extract the features of spectral data. Finally, partial least squares regression (PLSR) and stochastic configuration network (SCN) are adopted to establish the prediction model of litchi sugar content. The experimental results show that the SNV-CARS-SCN prediction model has the highest accuracy. The coefficient of determination ( \(R^2\) ), RMSE, and MAE of the training dataset are 0.9996, 0.1145, and 0.1154, respectively. \(R^2\) , RMSE, and MAE of the test dataset are 0.9740, 0.4962, and 0.3818, respectively. The NIR detection system and SCN prediction model designed in this paper are of great significance for the design of litchi automatic sorting system.
PubDate: 2024-08-01
DOI: 10.1007/s11694-024-02787-1
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- Methodology and optimization research for discrimination of different
brands of Baijiu based on multispectral techniques-
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Abstract: Abstract The accurate differentiation of Baijiu holds significant importance in the realm of food safety. Hence, a comprehensive dataset comprising UV, NIR, and three-dimensional fluorescence spectral information was collected from 17 representative Chinese Baijiu brands. By combining multispectral information with chemometrics, the different Baijiu brands were classified and identified. PCA was employed to extract characteristic variables from the high-dimensional UV and NIR spectral data, while PARAFAC decomposition was applied to the three-dimensional fluorescence spectral data to obtain concentration scores as characteristic variables. The dataset was balanced using the SMOTE algorithm, and subsequently, LDA, SVM, and BPNN classification models were constructed. Model evaluation was based on the accuracy, sensitivity, and specificity of the test set. The results demonstrated that the three models, in conjunction with chemometric methods, effectively distinguished between different Baijiu brands, boasting accuracy, sensitivity, and specificity rates exceeding 99%.
PubDate: 2024-08-01
DOI: 10.1007/s11694-024-02770-w
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- Hyperspectral image characterization and modeling for prediction of
ipomeamarone content in sweet potato-
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Abstract: Abstract In order to rapidly and accurately detect ipomeamarone using hyperspectral image technology sweet potato inoculated with Ceratocystis fimbriata (that can infect sweet potato with black spot disease, leading to the generation of ipomeamarone) was used as the research object, methods of hyperspectral characterization information extraction and robust model construction for ipomeamarone content were explored. After eliminating the effects of noisy signals and offsetting baseline, hyperspectral characterization information of ipomeamarone was extracted by the successive projection algorithm (SPA) and the competitive adaptive reweighted sampling algorithm (CARS), 26 and 48 optimal characteristic wavelengths were extracted, respectively; Based on the extracted characteristic wavelengths, back propagation neural network (BPNN), least squares support vector machine (LSSVM), radial basis function neural network(RBFNN), partial least squares regression(PLSR)and extreme learning machine (ELM) prediction models were established, respectively. The performance of prediction models was compared and the results showed that the LSSVM model based on characterization information extracted by CARS (CARS-LSSVM) was optimal, with a R2 of 0.968 and a RMSE of 0.2678. the content change and distribution of ipomeamarone in sweet potato samples were clearly illustrated in pseudo-color plots based on the prediction results of the CARS-LSSVM mode. Simultaneously electron microscope scanning (SEM) was performed for the sweet potato samples, the SEM results showed that the texture of sweet potato was varied with the development of black spot disease. The research provided a new method for the detection of ipomeamarone; and provided a basis for the early prevention and control of sweet potato black spot disease.
PubDate: 2024-08-01
DOI: 10.1007/s11694-024-02763-9
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- Preparation, characterization, antioxidant, and hypoglycemic activity of
polysaccharide nano-selenium from Fagopyrum tataricum-
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Abstract: Abstract To enhance the stability of nano-selenium, polysaccharide was employed as template to prepare polysaccharide nano-selenium, and its biological activity was studied. The Fagopyrum tataricum polysaccharide (FTP1, FTP2, FTP3, FTP4) was extracted using a water extraction-alcohol precipitation method, and Fagopyrum tataricum polysaccharide nano-selenium (FTP3-SeNPs) was synthesized via by HNO3-Na2SeO4 method, and its structure was characterized using ultraviolet–Vis (UV–Vis), fourier-transform infrared (FT-IR), X-ray diffraction (XRD), and scanning electron microscopy (SEM). Then, the antioxidant and hypoglycemic activities of FTP3-SeNPs in vitro were studied. According to the results of UV–Vis, FT-IR, XRD, and SEM, FTP3-SeNPs formed granular surface structure, altering the surface morphology of the polysaccharide while preserving its fundamental structure intact; the UV-Vis spectrum exhibited a novel absorption peak at approximately 290 nm, and an evident dispersion peak emerged within the XRD pattern at 20°~30°, indicating a pronounced interaction between FTP3 and SeNPs, leading to the formation of the FTP3-SeNPs complex. The average particle size of FTP3-SeNPs was 101.76 nm, significantly smaller than FTP3. The stability of FTP3-SeNPs was higher than FTP3, which was because the Zeta potential absolute value of FTP3-SeNPs was greater than FTP3. The highest scavenging activities of FTP3-SeNPs on DPPH, ·OH, and ABTS were 60.97%, 82.53%, and 79.11%, significantly higher than FTP3. The highest inhibitory activities of FTP3-SeNPs on α-glucosidase and α-amylase were 93.17 and 83.26%, significantly higher than FTP3. In conclusion, selenization modification could increase the antioxidant and hypoglycemic activity of polysaccharide from Fagopyrum tataricum.
PubDate: 2024-08-01
DOI: 10.1007/s11694-024-02778-2
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- Evaluation of the effect of a composite coating of chitosan-cress seed
gum, along with hydrolyzed protein from sesame meal (in free and
encapsulated forms), to increase the shelf life of ostrich fillets-
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Abstract: Abstract Hydrolyzed proteins have gained significant importance in the food industry due to their potential antioxidant and antimicrobial properties. They have been recognized for their ability to improve the shelf life and safety of food products. In this study, the researchers focused on incorporating hydrolyzed protein from sesame meal (SMPH) into a composite coating along with chitosan-cress seed gum (CH-CG). The aim was to investigate the effect of this composite coating, in both free and nanoparticle forms, on the shelf life of ostrich fillets during a 12-day refrigerated storage period. Initially, SMPH was produced using microbial alcalase protease enzymes, and its degree of hydrolysis and antioxidant properties were evaluated. Then, SMPH was encapsulated using liposomes. Six treatments were evaluated to examine the effect of CH-CG coating and SMPH, in both free and nanoparticle forms, on the extension of the shelf life of ostrich fillets: control, CH-CG, CH-CG + 0.5% SMPH, CH-CG + 1% SMPH, CH-CG + 0.5% nano SMPH (NSMPH), and CH-CG + 1% NSMPH. Chemical parameters (peroxide value, thiobarbituric acid, and nitrogenous volatile bases) and microbial parameters (total bacterial count and psychrotrophic bacteria count) were periodically analyzed. The results showed that SMPH with a hydrolysis time of 90 min and a molecular weight of 3 kD exhibited the highest protein content, degree of hydrolysis, and DPPH free radical scavenging activity (P < 0.05). The particle size of NSMPH was found to be 56.3 nm, the zeta potential was 38.1 mV, and the encapsulation efficiency was 75.95%. The chemical and microbial analyses indicated that the composite coating with SMPH led to a slower increase in oxidative and microbial indices compared to the control treatment, and NSMPH enhanced its antimicrobial and antioxidant properties. Among all the treatments, the CH-CG + 1% NSMPH treatment demonstrated the most favorable results among all the tested treatments. Therefore, this treatment has the potential to serve as a natural preservative option in the meat industry, offering improved preservation, reduced spoilage, and enhanced product quality and safety.
PubDate: 2024-07-30
DOI: 10.1007/s11694-024-02715-3
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- Mechanical behavior of impact damage on Aronia melanocarpa: an experiment
on pendulum method and hyperspectral imaging-
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Abstract: Abstract The mechanical damage to the Aronia melanocarpa caused by collisions during the mechanical harvesting process can reduce its storage time and market value. The study employs a pendulum impact test to analyze the impact behavior between A. melanocarpa fruits and impact surfaces. The impact surface material is steel plate, acrylic board, corrugated cardboard and pearl cotton plate. The tests were performed on a pendulum test platform, using a high-speed photography system to record the absorbed energy and contact area. The hyperspectral imaging technology is employed to detect fruits damage, and then the Support Vector Machine supervised learning algorithm was applied to classify its damaged regions. The degree of damage for A. melanocarpa is classified. The results indicate that the damage rate increases from 34.92% to 52.52%, and the absorbed energy increases from 2.1185 to 7.9009 mJ, with the pendulum height increases from 200 to 650mm, when the impact surface material is steel plate and the moisture content of the samples was 82%. With the increase of absorbed energy and damage rate, the results show that pendulum height, impact face material, and fruit moisture content have effects on the spectral reflectance of the samples. The impact surface material has the greatest influence on the damage rate, followed by the pendulum height, and the smallest is the water content. Furthermore, the results reveal that a strong linear correlation between contact area and damage rate, as well as absorption energy. The study provides a theoretical basis for the identification and classification of A. melanocarpa damage, as well as the optimization of design parameters for its mechanical harvesting.
PubDate: 2024-07-30
DOI: 10.1007/s11694-024-02773-7
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