bluuebunny/crossref_metadata_2025 huggingface dataset:
An Auxiliary Passive Circuit and Control Design for Wireless Power Transfer Systems in DC Microgrids with Zero Voltage Switching and Accurate Output Regulations
Authors: Xiong Hu , Xiang Bin , Mao Yuan
Published: January 2023

This paper presents an auxiliary passive circuit and control design for wireless power transfer (WPT) systems in DC microgrids to achieve optimal power transfer efficiency while maintain accurate output voltage regulation. An auxiliary inductance is added at the transmitter resonator to form a current sink to ensure zero voltage switching (ZVS) of the primary-side full-bridge inverter with even extremely light load conditions. Moreover, an adaptive proportional–integral (PI) controller is adopted to track the output voltage references by regulating the phase shift angle of the phase shift control for the full-bridge inverter. The coefficients of the adaptive PI controller are determined by the inductance of the auxiliary inductance. Both simulation and experimental results validated the effectiveness of the proposed circuit and control design in achieving optimal efficiency and output voltage regulation for WPT systems in DC microgrids with source and load variations.
Review of Urban Drinking Water Contamination Source Identification Methods
Authors: Gong Jinyu , Guo Xing , Yan Xuesong , Hu Chengyu
Published: January 2023

When drinking water flows into the water distribution network from a reservoir, it is exposed to the risk of accidental or deliberate contamination. Serious drinking water pollution events can endanger public health, bring about economic losses, and be detrimental to social stability. Therefore, it is obviously crucial to research the water contamination source identification problem, for which scholars have made considerable efforts and achieved many advances. This paper provides a comprehensive review of this problem. Firstly, some basic theoretical knowledge of the problem is introduced, including the water distribution network, sensor system, and simulation model. Then, this paper puts forward a new classification method to classify water contamination source identification methods into three categories according to the algorithms or methods used: solutions with traditional methods, heuristic methods, and machine learning methods. This paper focuses on the new approaches proposed in the past 5 years and summarizes their main work and technical challenges. Lastly, this paper suggests the future development directions of this problem.
Decarbonization Prospects for the European Pulp and Paper Industry: Different Development Pathways and Needed Actions
Authors: Lipiäinen Satu , Apajalahti Eeva-Lotta , Vakkilainen Esa
Published: January 2023

The pulp and paper industry (PPI) has several opportunities to contribute to meeting prevailing climate targets. It can cut its own CO2 emissions, which currently account for 2% of global industrial fossil CO2 emissions, and it has an opportunity to produce renewable energy, fuels, and materials for other sectors. The purpose of this study is to improve understanding of the decarbonization prospects of the PPI. The study provides insights on the magnitude of needed annual renewal rates for several possible net-zero target years of industrial fossil CO2 emissions in the PPI and discusses decarbonization opportunities, namely, energy and material efficiency improvement, fuel switching, electrification, renewable energy production, carbon capture, and new products. The effects of climate policies on the decarbonization opportunities are critically evaluated to provide an overview of the current and future business environment of the European PPI. The focus is on Europe, but other regions are analyzed briefly to widen the view. The analysis shows that there are no major technical barriers to the fossil-free operation of the PPI, but the sector renovates slowly, and many new opportunities are not implemented on a large scale due to immature technology, poor economic feasibility, or unclear political environment.
Impact of Hot Arid Climate on Optimal Placement of Electric Vehicle Charging Stations
Authors: El Hafdaoui Hamza , El Alaoui Hamza , Mahidat Salma , El Harmouzi Zakaria , Khallaayoun Ahmed
Published: January 2023

Electric vehicles (EVs) are becoming more commonplace as they cut down on both fossil fuel use and pollution caused by the transportation sector. However, there are a number of major issues that have arisen as a result of the rapid expansion of electric vehicles, including an inadequate number of charging stations, uneven distribution, and excessive cost. The purpose of this study is to enable EV drivers to find charging stations within optimal distances while also taking into account economic, practical, geographical, and atmospheric considerations. This paper uses the Fez-Meknes region in Morocco as a case study to investigate potential solutions to the issues raised above. The scorching, arid climate of the region could be a deterrent to the widespread use of electric vehicles there. This article first attempts to construct a model of an EV battery on MATLAB/Simulink in order to create battery autonomy of the most widely used EV car in Morocco, taking into account weather, driving style, infrastructure, and traffic. Secondly, collected data from the region and simulation results were then employed to visualize the impact of ambient temperature on EV charging station location planning, and a genetic algorithm-based model for optimizing the placement of charging stations was developed in this research. With this method, EV charging station locations were initially generated under the influence of gas station locations, population and parking areas, and traffic, and eventually through mutation, the generated initial placements were optimized within the bounds of optimal cost, road width, power availability, and autonomy range and influence. The results are displayed to readers in a node-link network to help visually represent the impact of ambient temperatures on EV charging station location optimization and then are displayed in interactive GIS maps. Finally, conclusions and research prospects were provided.
Electric Vehicle Charging Station Based on Photovoltaic Energy with or without the Support of a Fuel Cell–Electrolyzer Unit
Authors: Enescu Florentina Magda , Birleanu Fernando Georgel , Raboaca Maria Simona , Raceanu Mircea , Bizon Nicu , Thounthong Phatiphat
Published: January 2023

The transport sector generates more than 35% of total CO2 emissions. Electric vehicles are the future of transportation systems, and the demand for electric vehicles has grown considerably in the last few years due to government support. Companies worldwide are investing heavily in electric car charging stations based on renewable energy. This research study presents a complete design (including an appropriate energy management strategy) for a photovoltaic energy-based electric vehicle charging station (EVCS) with or without the support of a fuel cell and electrolyzer system. The parameters considered for designing the necessary capacity of the battery pack to support the required load are relative to the location-specific solar radiation (using RETScreen® Clean Energy Management Software, Version 9.0, Government of Canada, Toronto, Canada), the efficiency of the solar panel, the used strategy, etc. The battery capacity in the EVCS design based on a power-following strategy is about 20 times smaller than that resulting in the reference design. Additionally, the cost for an EVCS design based on a power-following strategy is almost half that resulting in the reference design. An analysis of the power-following strategy was carried out according to three EVCS operating scenarios.
Idiopathic Short Stature: What to Expect from Genomic Investigations
Authors: Andrade Nathalia Liberatoscioli Menezes , Cellin Laurana Polli , Rezende Raissa Carneiro , Vasques Gabriela Andrade , Jorge Alexander Augusto Lima
Published: January 2023

Short stature is a common concern for physicians caring for children. In traditional investigations, about 70% of children are healthy, without producing clinical and laboratory findings that justify their growth disorder, being classified as having constitutional short stature or idiopathic short stature (ISS). In such scenarios, the genetic approach has emerged as a great potential method to understand ISS. Over the last 30 years, several genes have been identified as being responsible for isolated short stature, with almost all of them being inherited in an autosomal-dominant pattern. Most of these defects are in genes related to the growth plate, followed by genes related to the growth hormone (GH)–insulin-like growth factor 1 (IGF1) axis and RAS-MAPK pathway. These patients usually do not have a specific phenotype, which hinders the use of a candidate gene approach. Through multigene sequencing analyses, it has been possible to provide an answer for short stature in 10–30% of these cases, with great impacts on treatment and follow-up, allowing the application of the concept of precision medicine in patients with ISS. This review highlights the historic aspects and provides an update on the monogenic causes of idiopathic short stature and suggests what to expect from genomic investigations in this field.
Drought Changes the Trade-Off Strategy of Root and Arbuscular Mycorrhizal Fungi Growth in a Subtropical Chinese Fir Plantation
Authors: Dong Jie , Jiang Yongmeng , Lyu Maokui , Cao Cong , Li Xiaojie , Xiong Xiaoling , Lin Weisheng , Yang Zhijie , Chen Guangshui , Yang Yusheng , Xie Jinsheng
Published: January 2023

As a consequence of changing global rainfall patterns, frequent extreme droughts will significantly affect plant growth and ecosystem functions. Fine roots and arbuscular mycorrhizal fungi (AMF) both facilitate Chinese fir nutrient uptake. However, how the growth of fine roots and AMF is regulated for the Chinese fir under drought conditions is unclear. This study used a precipitation reduction treatment (−50% throughfall) to study the seasonal effects of drought on a subtropical Chinese fir plantation. The effects measured included the fine root production, root diameter, specific root length, specific surface area, root tissue density, mycorrhizal hyphal density, spore number, mycorrhizal infection rate and total glomalin. Drought had no significant effect on Chinese fir fine root production but decreased the diameter and tissue density of primary and secondary roots while increasing the specific surface area of secondary roots. Additionally, drought significantly decreased the arbuscular mycorrhizal infection rate and significantly increased hyphal density. The results showed that drought caused the decrease in root diameter, which decreased the surface area available for AMF infection and led to the increase in mycorrhizal hyphal density. Redundancy analyses showed that soil-dissolved organic carbon and nitrogen were the key factors affecting AMF. Our results show that drought could enhance the cooperative strategy of nutrient and moisture absorption by roots and mycorrhizae of the Chinese fir, improving the resistance of Chinese fir growth to drought.
Developing and Comparing Individual Tree Growth Models of Major Coniferous Species in South Korea Based on Stem Analysis Data
Authors: Seo Yeongwan , Lee Daesung , Choi Jungkee
Published: January 2023

Tree growth in Korean red pine (Pinus densiflora, hereafter Pd), Korean white pine (Pinus koraiensis, hereafter Pk), and Japanese larch (Larix kaempferi, hereafter Lk) was modeled using Logistic, Korf, Gompertz, Chapman-Richards, and Weibull equations and stem analysis data from sample trees: 38 trees for Pd, 46 trees for Pk, and 45 trees for Lk. The models were fitted to the total increment of tree size variables, diameter at breast height (DBH), height, basal area, and stem volume, as a function of age. After selecting the best-fit growth function, the current annual increment (CAI) and mean annual increment (MAI) were compared for each variable by species. The optimal growth functions were Chapman-Richards for DBH and stem volume, Korf for height, and Gompertz for basal area. The parameter estimates in the final models were all significant (p < 0.01) with best-fit statistics and unbiased residual plots. When plotted with observed values, the growth patterns of each variable were represented properly. The predicted growth curves over age were concave with respect to the Y-axis in DBH and height but lightly convex in basal area, and explicitly convex in stem volume, whereas an asymptote of sigmoid curve in stem volume was not apparent until 100 years. Age with the maximum MAI among variables was arranged similarly to CAI; the age with maximum MAI was earliest for DBH and latest for volume. The maximum growth was achieved earliest in Lk, followed by Pk and Pd. The developed models were able to predict tree size variables and serve as a reference to understand growth characteristics by species.
Improved Soil Organic Carbon Prediction in a Forest Area by Near-Infrared Spectroscopy: Spiking of a Soil Spectral Library
Authors: Long Miao , Yue Tianxiang , Xu Zhe , Guo Jiaxin , Luo Jie , Guo Xi , Zhao Xiaomin
Published: January 2023

The rapid quantitative assessment of soil organic carbon (SOC) is essential for understanding SOC dynamics and developing management strategies in forest ecosystems. Compared with traditional laboratory methods, visible and near-infrared spectroscopy is an efficient and inexpensive technique widely used to predict SOC content. Herein, we compared three different spiking strategies. That is, a large-scale global soil spectral library (global-SSL; 3122 samples) was used as the basis for predicting SOC content in a small-scale local soil spectral library (local-SSL; 89 samples) in Wugong Mountain, Jiangxi Province, China. Partial least squares regression models using global-SSL ‘spiking’ with local samples did not necessarily achieve more accurate predictions than models using local-SSL. Using the developed strategy, a calibration set can be established by selecting the top N spectral samples from global-SSL with high similarity to each local sample, together with the ‘spiking’ set from local-SSL. It is possible to individually improve the prediction results based on local samples (R2 = 0.90, RMSE = 7.19, RPD = 3.38) and still allow for quantitative prediction from fewer local calibration samples (R2 = 0.83, RMSE = 8.71, RPD = 2.68). The developed method is cost-effective and accurate for local-scale SOC assessment in target forest areas using a large soil spectral library.
Thermal Comfort and Human Responses according to Tree Density in Forest Environments during and after Physical Activities in the Summer
Authors: Kim Juhyeon , Song Injoon , Kim Choyun , Gho Hyejung , An Siok , Song Doyun , Joung Dawou , Kang Shinkwang , Yi Yunjeong , Park Bum-Jin , Song Chorong
Published: January 2023

This study aimed to comprehensively investigate the thermal comfort and physiological and psychological effects according to tree density in forest environments during rest and during and after physical activities in the summer. Participants consisted of 18 male university students (average age: 24.0 ± 1.6 years old), and a within-subjects experimental design was used. Participants sat on a chair for 5 min to rest, performed a step-box exercise for 8 min, and then sat on the chair again, and rested for 10 min in a forest with high tree density (85.6%) and one with low tree density (12.2% as a control). Thermal comfort (predicted mean vote; PMV and percentage of dissatisfied; PPD) and physiological and psychological responses were measured. We investigated and analyzed the changes in “rest”, “during exercise”, and “after exercise”. As a result, a forest with high tree density showed a statistically significant decrease in PMV and PPD values; an increase in parasympathetic nervous activity; a decrease in respiratory rate, systolic blood pressure, and pulse rate; an improvement in mood state; an increase in comfortable, relaxed, and natural feelings; and more of an increase in personal thermal sensation during the recovery period after physical activities than in a forest with low tree density. In conclusion, a forest with high tree density during recovery after physical activities in the summer has higher thermal comfort and physiological and psychological relaxation effects on humans, as compared to one with low tree density.
Effect of Aspergillus niger Fermentation on the Metabolites in Corn Stalks
Authors: Fan Zhen , Chen Tianming , Cai Guolin , Huang Xiaoyu , Zhong Suchuan , Li Xiaoming , Zhang Enping
Published: January 2023

Fermentation has been considered as an effective means to improve the feed nutrient digestibility of corn stalks, and it is beneficial to animal growth performance and health. The beneficial functions of fermented corn stalks are related to the variety of metabolites produced through fermentation, but the nature of these components is still unclear. In this study, gas chromatography–mass spectrometry, combined with principal component analysis and partial least squares discriminant analysis, was used to explore the differential metabolites of corn stalks before and after Aspergillus niger fermentation. A total of 32 potential characteristic compounds were obtained, mainly including sugar and glycoside derivatives, organic acids and their derivatives, alcohol compounds, benzene and its substituted derivatives, amino acids, phenolic compounds, and flavonoids. Compared with the metabolites in corn straw before fermentation, the relative content of D-threitol, mannitol-1-phosphate, coniferin, citrazinic, oxoglutaric acid, chenodeoxycholic acid, naproxen, 5-aminovaleric acid, vanillin, catechin, and UDP-glucuronic acid was significantly increased, and the relative content of N-acetylgalactosamine, heneicosanoic acid, chlorogenic acid, and adenosine was significantly decreased. Kyoto Encyclopedia of Genes and Genomes pathway analysis showed that 20 metabolic pathways corresponded to the differential characteristic metabolites. The results of this study will provide theoretical support for the quality evaluation of fermented corn stalks and high-value product development in the future.
Product Evaluation Prediction Model Based on Multi-Level Deep Feature Fusion
Authors: Zhou Qingyan , Li Hao , Zhang Youhua , Zheng Junhong
Published: January 2023

Traditional product evaluation research is to collect data through questionnaires or interviews to optimize product design, but the whole process takes a long time to deploy and cannot fully reflect the market situation. Aiming at this problem, we propose a product evaluation prediction model based on multi-level deep feature fusion of online reviews. It mines product satisfaction from the massive reviews published by users on e-commerce websites, and uses this model to analyze the relationship between design attributes and customer satisfaction, design products based on customer satisfaction. Our proposed model can be divided into the following four parts: First, the DSCNN (Depthwise Separable Convolutions) layer and pooling layer are used to combine extracting shallow features from the primordial data. Secondly, CBAM (Convolutional Block Attention Module) is used to realize the dimension separation of features, enhance the expressive ability of key features in the two dimensions of space and channel, and suppress the influence of redundant information. Thirdly, BiLSTM (Bidirectional Long Short-Term Memory) is used to overcome the complexity and nonlinearity of product evaluation prediction, output the predicted result through the fully connected layer. Finally, using the global optimization capability of the genetic algorithm, the hyperparameter optimization of the model constructed above is carried out. The final forecasting model consists of a series of decision rules that avoid model redundancy and achieve the best forecasting effect. It has been verified that the method proposed in this paper is better than the above-mentioned models in five evaluation indicators such as MSE, MAE, RMSE, MAPE and SMAPE, compared with Support Vector Regression (SVR), DSCNN, BiLSTM and DSCNN-BiLSTM. By predicting customer emotional satisfaction, it can provide accurate decision-making suggestions for enterprises to design new products.
Post-Fire Natural Regeneration Trends in Bolivia: 2001–2021
Authors: Maillard Oswaldo
Published: January 2023

In the last 21 years, Bolivia has recorded a series of thousands of wildfires that impacted an area of 24 million hectares, mainly in the departments of Beni and Santa Cruz. In this sense, identifying trends in the increase of natural vegetation after wildfires is a fundamental step in implementing strategies and public policies to ensure ecosystem recovery. The main objective of this study was to evaluate the spatial trends of the increase and decrease in vegetation affected by wildfires for the whole of Bolivia, for the period 2001–2021, using non-parametric tests, through the analysis of Normalized Difference Vegetation Index (NDVI) remote sensing products. The results indicated that 53.6% of the area showed an increasing trend (p < 0.05) and 15.9% of the area showed a decreasing trend (p < 0.05). In terms of land cover type, forests were proportionally represented by 18.1% of the areas that showed an increasing trend (p < 0.05) and 3.0% of the forests showed a decreasing trend (p < 0.05). In contrast, non-forested areas showed an increasing trend of 35.5% and 12.9% showed a decreasing trend (p < 0.05). It can be concluded that there is a continuous regeneration process throughout the country.
Geospatial Wildfire Risk Assessment from Social, Infrastructural and Environmental Perspectives: A Case Study in Queensland Australia
Authors: Shafapourtehrany Mahyat
Published: January 2023

Although it is hard to predict wildfires, risky areas can be systematically assessed and managed. Some of the factors for decision-making are hazard, vulnerability, and risk maps, which are the end product of wildfire mapping. This study deals with wildfire risk analysis in Queensland, Australia. A review of the previous studies focusing on each aspect has been done and used with wildfire records from 2011 to 2019 in Queensland, Australia, to compile the required input models to detect risky wildfire regions. Machine learning (ML) methods of Decision Tree (DT) and Support Vector Machine (SVM) were used to perform hazard assessment. The reason was to select the most accurate outcomes for the rest of the analysis. Among accuracy assessment techniques, the Area Under Curvature (AUC) method was used to evaluate the hazard maps. Prediction rates of 89.21% and 83.78% were obtained for DT and SVM, respectively. The DT prediction value showed that the DT-hazard map was more accurate than the SVM-hazard map. Vulnerability analysis was implemented by assigning weights to each factor according to the literature. Lastly, in order to create the wildfire risk map, the hazard and vulnerability indices were combined. The risk map showed that particularly dense urbanization regions are under future wildfire risk. To perform preliminary land use planning, this output can be used by local governmental authorities.
A Common Anaesthetic, MS-222, Alters Measurements Made Using High-Resolution Respirometry in the Three-Spined Stickleback (Gasterosteus aculeatus)
Authors: Barnes Megan , Ebanks Brad , MacColl Andrew , Chakrabarti Lisa
Published: January 2023

Submersion in the anaesthetic MS-222 is a well-established and effective method used during the euthanasia of fish, but the consequences of treatment with this anaesthetic for mitochondrial respiration are yet to be established. This is important to evaluate, as an increasing amount of research is conducting high-resolution respirometry to measure respiration across multiple species of fish, including looking at thermal sensitivity and mitochondrial responses to the warmer temperatures faced with climate change. Analysis often occurs after euthanasia with MS-222 without knowledge of how MS-222 itself affects any measured parameters of mitochondrial respiration, leaving potential for a misinterpretation of results. Here, high-resolution respirometry was conducted to explore how MS-222 affects oxidative phosphorylation in the brain and skeletal muscle of the three-spined stickleback, Gasterosteus aculeatus, which is a model species in evolutionary ecology. In the brain, differences in respiration were observed between three-spined sticklebacks euthanised with MS-222 and those where no anaesthetic was implemented. No differences between treatments were observed in the skeletal muscle, although variation between individuals was high and oxygen flux was lower than in the brain. Overall, this study highlights the need for a consistent method of euthanasia when conducting high-resolution respirometry in fish, as MS-222 may alter measures of oxidative phosphorylation.
Numerical Simulation of Carbon Dioxide–Nitrogen Mixture Dissolution in Water-Saturated Porous Media: Considering Cross-Diffusion Effects
Authors: Mahmoodpour Saeed , Singh Mrityunjay , Mahyapour Ramin , Omrani Sina , Sass Ingo
Published: January 2023

The possibility of impure carbon dioxide (CO2) sequestration can reduce the cost of these projects and facilitate their widespread adoption. Despite this, there are a limited number of studies that address impure CO2 sequestration aspects. In this study, we examine the convection–diffusion process of the CO2–nitrogen (N2) mixture dissolution in water-saturated porous media through numerical simulations. Cross-diffusion values, as the missing parameters in previous studies, are considered here to see the impact of N2 impurity on dissolution trapping in more realistic conditions. Homogeneous porous media are used to examine this impact without side effects from the heterogeneity, and then simulations are extended to heterogeneous porous media, which are a good representative of the real fields. Heterogeneity in the permeability field is generated with sequential Gaussian simulation. Using the averaged dissolved CO2 and dissolution fluxes for each case, we could determine the onset of different dissolution regimes and behaviors of dissolution fluxes in CO2–N2 mixture dissolution processes. The results show that there is a notable difference between the pure cases and impure cases. Additionally, a failure to recognize the changes in the diffusion matrix and cross-diffusion effects can result in significant errors in the dissolution process. At lower temperatures, the N2 impurity decreases the amount and flux of CO2 dissolution; however, at higher temperatures, sequestrating the CO2–N2 mixture would be a more reasonable choice due to enhancing the dissolution behavior and lowering the project costs. The results of the heterogeneous cases indicate that heterogeneity, in most cases, reduces the averaged dissolved CO2, and dissolution flux and impedes the onset of convection. We believe that the results of this study set a basis for future studies regarding the CO2–N2 mixture sequestration in saline aquifers.
Trade for Food Security: The Stability of Global Agricultural Trade Networks
Authors: Wang Xiang , Ma Libang , Yan Simin , Chen Xianfei , Growe Anna
Published: January 2023

Global food production is facing increasing uncertainties under climate change and the coronavirus pandemic, provoking challenges and severe concerns to national food security. The role of global agricultural trade in bridging the imbalance between food supply and demand has come to the fore. However, the impact of multifaceted and dynamic factors, such as trade policies, national relations, and epidemics, on the stability of the agricultural trade network (ATN) needs to be better addressed. Quantitatively, this study estimated grouping characteristics and network stability by analyzing the changing global ATN from 1986 to 2018. We found that the evolution of global agricultural trade communities has gone through four stages: the dominance of the US–Asian community, the rise of the European–African community, the formation of tri-pillar communities, and the development of a multipolar community with a more complex structure. Despite witnessing a progressive increase in the nodal stability of the global ATN during the decades, particular gaps can still be found in stability across countries. Specifically, the European community achieved stability of 0.49 and its trade relations were effectively secured. Meanwhile, the remaining leading communities’ stability shows a stable and upward trend, albeit with more significant challenges in trade relations among some of them. Therefore, how to guarantee the stability of trade relations and strengthen the global ATN to resist external shocks has become an essential question to safeguard global food security.
Role of Stingray (Himantura signifier) Non-Protein Nitrogenous Fraction on the Oxidative Stability of Lipid and Myoglobin
Authors: Panpipat Worawan , Limsuwanmanee Jutaporn , Cheong Ling-Zhi , Chaijan Manat
Published: January 2023

Non-protein nitrogen (NPN) is abundant in stingray (Himantura signifier) muscle, which also has in vitro antioxidant activity. In this study, NPN from stingray muscle was further investigated for its antioxidant properties in lecithin liposome and oxymyoglobin model systems to validate its protective impact against lipid and myoglobin oxidations during storage for 120 min at various temperatures (4, 25, and 60 °C). NPN solution (10 ppm nitrogen) was added to the lecithin liposome system at different concentrations (0, 0.5, 1, 5, and 10% (v/v)) to investigate its effects on lipid stability by measuring the conjugated diene (CD), peroxide value (PV), and thiobarbituric acid reactive substances (TBARS) contents. In the oxymyoglobin system, NPN solution (10 ppm nitrogen) was also added at different concentrations (0, 0.5, 1, 5, and 10% (v/v)) to the oxymyoglobin solution in order to examine its effect on the stability of myoglobin by determining the contents of oxymyoglobin, metmyoglobin, and protein carbonyl. According to the findings, in all NPN concentrations, the system incubated at 4 °C had the lowest levels of lipid oxidation as measured by CD, PV, and TBARS values, and the lowest levels of myoglobin oxidation. At all incubating temperatures, the oxymyoglobin and lipid oxidation of all model systems tended to rise with the lengthening of the incubation duration. With the addition of 5% NPN, however, the lowest CD, PV, TBARS, oxymyoglobin oxidation, metmyoglobin formation, and protein carbonyl content were all observable, and the remarkable result was discovered during incubation at 4 °C. The results indicate that stingray NPN, especially at 5%, can be used to delay lipid and myoglobin oxidation, particularly at 4 °C. In order to prolong the shelf life of products with dark-fleshed fish and red meat, stingray NPN might be used as an alternative antioxidant to delay the oxidation of lipid and myoglobin during cold chain storage.
Microbial Decontamination of Red Wine by Pulsed Electric Fields (PEF) after Alcoholic and Malolactic Fermentation: Effect on Saccharomyces cerevisiae, Oenococcus oeni, and Oenological Parameters during Storage
Authors: Delso Carlota , Berzosa Alejandro , Sanz Jorge , Álvarez Ignacio , Raso Javier
Published: January 2023

New techniques are required to replace the use of sulfur dioxide (SO2) or of sterilizing filtration in wineries, due to those methods’ drawbacks. Pulsed electric fields (PEF) is a technology capable of inactivating microorganisms at low temperatures in a continuous flow with no detrimental effect on food properties. In the present study, PEF technology was evaluated for purposes of microbial decontamination of red wines after alcoholic and malolactic fermentation, respectively. PEF combined with SO2 was evaluated in terms of microbial stability and physicochemical parameters over a period of four months. Furthermore, the effect of PEF on the sensory properties of red wine was compared with the sterilizing filtration method. Results showed that up to 4.0 Log10 cycles of S. cerevisiae and O. oeni could be eradicated by PEF and sublethal damages and a synergetic effect with SO2 were also observed, respectively. After 4 months, wine treated by PEF after alcoholic fermentation was free of viable yeasts; and less than 100 CFU/mL of O. oeni cells were viable in PEF-treated wine added with 20 ppm of SO2 after malolactic fermentation. No detrimental qualities were found, neither in terms of oenological parameters, nor in the sensory parameters of wines subjected to PEF after storage time.
Antitumor Effects of Poplar Propolis on DLBCL SU-DHL-2 Cells
Authors: Liu Xiaoqing , Tian Yuanyuan , Yang Ao , Zhang Chuang , Miao Xiaoqing , Yang Wenchao
Published: January 2023

Propolis is resinous natural product produced by Western honeybees using beeswax and plant and bud exudates, which has a wide range of biological activities, including antioxidation, antibacterial, anti-inflammation, immune regulation, antitumor, and so on. Diffuse large B-cell lymphoma (DLBCL) is an aggressive cancer, and accounts for about 30% of all lymphomas. The effect of poplar propolis on DLBCL has not been reported. The IC50 of propolis on the proliferation of DLBCL SU-DHL-2 cell line and its proteins and gene expressions were detected by CCK-8 kit, label-free proteomic, and RT-PCR. The results showed that the IC50 of propolis at the 5 × l05/mL cell for 24 h was 5.729 μg/mL. Label-free-based proteomics analysis showed that there were 115 differentially expressed proteins (61 up-regulated and 54 down-regulated proteins) between IC50 dose-treated and solvent control groups. There were 32.47% differential proteins located in the nucleus, 20.78% in the cytoplasm, and 14.29% in mitochondria. The most significant different pathway (p = 0.0016) of protein enrichment was ferroptosis (including glutamate–cysteine ligase regulatory subunit, ferritin, and heme oxygenase). The relative expression trend of 17 of the total 22 genes selected according to proteomics results was in line with their encoded protein. The highest protein–protein interaction was serine/threonine-protein kinase PLK, which interacted with 16 differential proteins. In conclusion, poplar propolis inhibited SU-DHL-2 cells via ferroptosis pathway, accelerating cell death and down-regulated serine/threonine-protein kinase PLK1, affecting apoptosis of cell. This result provides a theoretical basis for the treatment of DLBCL using propolis.
Dietary Effect of Brevibacillus laterosporus S62-9 on Chicken Meat Quality, Amino Acid Profile, and Volatile Compounds
Authors: Liu Xiangfei , Ma Aijin , Zhi Tongxin , Hong Dan , Chen Zhou , Li Siting , Jia Yingmin
Published: January 2023

Probiotics are being used in diets to improve the quality of chicken meat. The aim of the study was to investigate the effects of dietary supplementation with Brevibacillus laterosporus S62-9 microbial agent on the meat quality, amino acids, and volatile compounds of chicken. The experiment was carried out with 160 1-day-old Arbor Acres male broiler chickens, rearing for 42 d. The chickens were randomly divided into two groups of 8 replicates each, with 10 chickens in each group. No supplement was added to the basal diet in the control group and Brevibacillus laterosporus S62-9 microbial agent was added to the diet of the experimental group. At the end of the experiment, the meat quality, meat chemical composition, amino acid composition, and volatile compounds of chicken were determined. The results showed that pH (p < 0.05), pressing loss (p < 0.05), cooking loss (p < 0.05), and shear force (p < 0.01) were notably decreased, the percentage of breast meat (p < 0.01), protein content (p < 0.05) were visibly increased, and remarkable changes were observed in the amino acid composition (change in seven amino acids) and volatile compounds profile (an increase of about 20-fold in the contents of 1-octen-3-ol and hexanal). In summary, it was found that Brevibacillus laterosporus S62-9 microbial agent can be used as a novel and effective feed supplement to improve the nutritional quality and flavor characteristics of broilers.
Widely Targeted Metabolomics Was Used to Reveal the Differences between Non-Volatile Compounds in Different Wines and Their Associations with Sensory Properties
Authors: Cao Weiyu , Shu Nan , Wen Jinli , Yang Yiming , Wang Yanli , Lu Wenpeng
Published: January 2023

In this study, metabolites from six varieties of wines, including ‘Haasan’ (A1), ‘Zuoshaner’ (A2), ‘Beibinghong’ (A3), ‘Shuanghong’ (A4), ‘Zijingganlu’ (A5), and ‘Cabernet Sauvignon’ (A6), were identified and quantified using widely targeted metabolomics analysis techniques. Based on the test results, 1172 metabolites were detected and classified into 18 categories. These include 62 amino acids, 178 alkaloids, 189 flavonoids, 106 phenols, 148 terpenoids, etc. Comparing the differential metabolites between the comparison groups of each variety, differences between varieties based on P-values and VIP values were shown. Among these differential metabolites, Trimethoprim and Crotonoside were screened out as core differential metabolites. Multiple comparisons also screened the biomarkers for each species. We used widely targeted metabolomics to reveal the differences between non-volatile compounds in different wines and their associations with sensory properties. We also used the simultaneous weighted gene co-expression network analysis (WGCNA) to correlate metabolites with sensory traits, including color difference values and taste characteristics. Two of the six key modules were screened by WGCNA for relevance to sensory traits (brown module and turquoise module). This study provides a high-throughput method for linking compounds to various sensory characteristics of food, opening up new avenues for explaining differences in different varieties of wine.
Optimization of Enzyme-Assisted Mechanical Extraction Process of Hodgsonia heteroclita Oilseeds and Physical, Chemical, and Nutritional Properties of the Oils
Authors: Piseskul Jirachaya , Suttisansanee Uthaiwan , Chupeerach Chaowanee , Khemthong Chanakan , Thangsiri Sirinapa , Temviriyanukul Piya , Sahasakul Yuraporn , Santivarangkna Chalat , Chamchan Rungrat , Aursalung Amornrat , On–nom Nattira
Published: January 2023

Hodgsonia heteroclita subsp. Indochinensis W.J.de Wlide & Duyfjes (or Making in Thai) is a neglected and underutilized crop (NUC) with high fat containing nuts. In this study, the enzyme-assisted mechanical extraction of H. heteroclita seed oil was investigated using response surface methodology (RSM) to predict the optimal fat extraction conditions. The most efficient enzyme used in the experiment was a mixture of Flavourzyme® and Viscozyme® (1:1, w/w). The predicted maximum oil yield was 46.44%, using the following extraction conditions: 2.98% (w/w) enzyme loading, 48 °C incubation temperature and 76 min of incubation time. H. heteroclita seed oil obtained from heat and enzymatic pretreatments exhibited the highest lightness and viscosity. The chemical properties of this seed oil, including water and volatile compounds (≤0.2% w/w), acid value (≤4.0 mg KOH/g), peroxide value (≤15 mEq of active oxygen/kg) and soap content (≤0.005% w/w), were within the acceptable levels specified by the Codex Alimentarius (2019). H. heteroclita seed oil obtained from heat and enzymatic pretreatments contained the highest content of δ-tocopherol (88.29 mg/100 g) and omega-6 fatty acids (48.19 g/100 g). This study is the first to report on the enzyme-assisted mechanical extraction of H. heteroclita oilseeds as a promising plant material for vegetable oil production.
Botanical Origin of Galician Bee Pollen (Northwest Spain) for the Characterization of Phenolic Content and Antioxidant Activity
Authors: Rojo Sergio , Escuredo Olga , Rodríguez-Flores María Shantal , Seijo María Carmen
Published: January 2023

Bee pollen is considered a natural product, relevant for its nutritional and antioxidant properties. Its composition varies widely depending on its botanical and geographical origins. In this study, the botanical characteristics of 31 bee pollen samples from Galicia (Northwest Spain) were analyzed; samples have not been studied until now from this geographical area. The study focused on the evaluation of the influence of plant origin on total phenol and flavonoid contents and antioxidant activity measured by radical scavenging methods. The multivariate statistical treatment showed the contribution of certain pollen types in the extract of bee pollen as to phenols, flavonoids and antioxidant capacity. Specifically, the bee pollen samples with higher presence of Castanea, Erica, Lythrum and Campanula type indicated higher total phenol and flavonoid contents and antioxidant activities according to the principal component analysis. On the contrary, Plantago and Taraxacum officinale type contributed a lower content of these compounds and radical scavenging activity. The cluster analysis classified the bee pollen samples into three groups with significant differences (p > 0.05) for the main pollen types, total phenol and flavonoid contents and antioxidant capacities. These results demonstrate the richness and botanical diversity in the pollen spectrum of bee pollen and enhance the possible beneficial nutraceutical properties of this beekeeping product.
Non-Destructive Discrimination of Sunflower Seeds with Different Internal Mildew Grades by Fusion of Near-Infrared Diffuse Reflectance and Transmittance Spectra Combined with 1D-CNN
Authors: Liu Jie , Fan Shuang , Cheng Weimin , Yang Yang , Li Xiaohong , Wang Qi , Liu Binmei , Xu Zhuopin , Wu Yuejin
Published: January 2023

Internally mildewed sunflower seeds, which cannot be recognized and discarded based on their appearance, pose a serious risk to human health. Thus, there is a need for a rapid non-destructive mildew grade discrimination method. Currently, few reports are available regarding this process. In this study, a method based on the combination of the near-infrared diffuse reflectance and near-infrared diffuse transmission (NIRr-NIRt) fusion spectra and a one-dimension convolutional neural network (1D-CNN) is proposed. The NIRr-NIRt fusion spectra can provide more complementary and comprehensive information, and therefore better discrimination accuracy, than a single spectrum. The first derivative (FD) preprocessing method could further improve the discrimination effect. By comparison against three conventional machine learning algorithms (artificial neural network (ANN), support vector machine (SVM), and K-nearest neighbor (KNN)), the 1D-CNN model based on the fusion spectra was found to perform the best. The mean prediction accuracy was 2.01%, 5.97%, and 10.55% higher than that of the ANN, SVM, and KNN models, respectively. These results indicate that the CNN model was able to precisely classify the mildew grades with a prediction accuracy of 97.60% and 94.04% for the training and test set, respectively. Thus, this study provides a non-destructive and rapid method for classifying the mildew grade of sunflower seeds with the potential to be applied in the quality control of sunflower seeds.
Techno-Functional Properties of Corn Flour with Cowpea (Vigna unguilata) Powders Obtained by Extrusion
Authors: Sotelo-Díaz Luz Indira , Igual Marta , Martínez-Monzó Javier , García-Segovia Purificación
Published: January 2023

Legumes are a good source of vegetal protein that improves diets worldwide. Cowpea has been used as fortification agents in some traditional corn foods in developing countries such as Colombia. The work aimed to evaluate the physicochemical properties of extruded mixtures of corn and cowpea flours to assess the use of these mixes as vegetable protein ingredients. Corn flour was mixed with 15, 30, and 50% of cowpea flour and extruded for this proposal. After extrusion, mixtures were ground to produce a powder. Techno-functional properties of powders as water content, hygroscopicity, water absorption, fat absorption, water solubility index, swelling index, bulk density, Hausner ratio, Carr index, and porosity were evaluated in the mixtures, extrudates, and obtained powders to assess the effect of the addition of cowpea on these properties. Results showed that processing powder obtained by extrusion and drying could be used as a powder to regenerate with water as a source of protein. Moreover, storing processing samples in sections (pellet format) is convenient to avoid wetting since this format is less hygroscopic and the same mass occupies less storage volume than powders.
Shelf-Life Performance of Fish Feed Supplemented with Bioactive Extracts from Fermented Olive Mill and Winery By-Products
Authors: Filipe Diogo , Gonçalves Margarida , Fernandes Helena , Oliva-Teles Aires , Peres Helena , Belo Isabel , Salgado José Manuel
Published: January 2023

Fortifying fish feeds with bioactive compounds, such as enzymes and antioxidants, has been an adopted strategy to improve feed nutritional quality and sustainability. However, feed additives can lose activity/effectiveness during pelleting and storage processes. This work aimed to monitor functional activity stability in feeds supplemented with a bioactive extract, including cellulases, xylanases, and antioxidants. This bioactive extract (FBE) was produced by Aspergillus ibericus under solid-state fermentation of olive mill and winery by-products. Two isoproteic and isolipidic diets were formulated and unsupplemented or supplemented with lyophilized FBE (0.26% w/w). Both diets were stored at room temperature (RT) or 4 °C for 4 months. Results showed that feed storage at 4 °C enhanced the stability of the enzymes and cellulase was more stable than xylanase. Compared to RT, storage at 4 °C increased cellulase and xylanase half-life by circa 60 and 14%. Dietary FBE supplementation increased antioxidant activity and storage at 4 °C reduced antioxidant activity loss, while in the unsupplemented diet, antioxidant activity decreased to the same level in both storage temperatures. Dietary supplementation with FBE reduced lipid peroxidation by 17 and 19.5% when stored at 4 °C or RT, respectively. The present study is a step toward improving the storage conditions of diets formulated with bioactive compounds.
Formulation of a Synergistic Enzyme Cocktail for Controlled Degradation of Sorghum Grain Pericarp
Authors: Sruthi N. U. , Rao Pavuluri Srinivasa , Bennett Sarita Jane , Bhattarai Rewati Raman
Published: January 2023

Sorghum is one of the major grains produced worldwide for food and fodder, owing to its nutritional profile advantages. However, the utilisation of whole grain sorghum as an ingredient in conventional food formulations is limited due to its poor digestibility, which requires the removal of the outer fibrous layers. Grain breakage and loss of essential nutrients also disadvantage traditional milling practices. Using carbohydrate degrading enzymes to hydrolyse the grain pericarp is a novel approach to biopolishing, where selective degradation of the pericarp layers occurs without adversely affecting the nutrient profile. A collective synergism of enzymes has been proven to cause effective hydrolysis compared to individual enzymes due to the complex presence of non-starch polysaccharides in the grain’s outer layers, which comprise a variety of sugars that show specific degradation with respect to each enzyme. The present study aimed to formulate such an enzyme cocktail with xylanase, cellulase, and pectinase in different proportions for hydrolysing sorghum grain pericarp by determining the yield of specific sugars in the pericarp extract after a certain period of incubation. The results showed that the xylanase enzyme has a major effect on the grain bran composition compared to cellulase and pectinase; however, a synergistic mixture yielded more hydrolysed sugars and anti-nutrients in the extract compared to each of the enzymes individually. The results were confirmed by morphological and crystallinity studies of the soaked grain. Compared to conventional water-soaked samples, grains soaked in a cocktail with 66.7% xylanase, 16.7% cellulase, and 16.7% pectinase had visibly thinner and more degraded fibre layers.