Product Quality Characteristics Research Articles

Development of Plantain and Cocoyam Bread and Assessment of Its Nutritional Value to the Elderly

Cakes were produced from the substitution levels of cocoyam and plantain Nour blends (0-100% and 0-70%), respectively and enriched with 0-30% levels of Bambara groundnut protein concentrate (BGPC) Quality characteristics of the resultant product were analysed to ascertain its sensory. physical and chemical properties Acceptable cakes were produced from 70% wheat flour, 20% plantain flour and 10% BGPC with regards to colour which compared favourably with sample A (100% WF) except F and G samples which differs significantly with other samples The texture of the cakes was also acceptable but F and G samples (6.5 and 6.4), respectively shows significant difference (p <0.05) compared to others. The taste and overall acceptability were not significantly different it all levels of BGPC enrichment compared to sample A. There was no significant difference (p > 0:05) in all the samples in terms of the height except sample B with the value of 2.5cm. Highest weight of 194 2g was observed for sample B which was significantly different (p<0.05) compared to other samples Increase in BGPC further improved the volume and specific volume of the cake to 524cm3 and 3. 19cm3/100g (sample G), respectively A reduction in the values of carbohydrate, moisture and energy content of the cakes were observed at increased levels of protein concentrate Protein content of the cakes was observed to improve progressively at increasing levels of enrichment and showed significant differences up to sample D (10.4%) while the highest protein value was reported at sample G (13.2%) with 30% protein concentrate. This confirms that the developed cakes have a better nutritional value than the control and could be used to combat protein energy malnutrition.

Application of whey protein microparticulates in the production of ice cream and other dairy products

The aim of this paper is to systemize data on the use of whey protein microparticulates (WPMP) in production of ice cream and other dairy products. Information about the essence of the microparticulation process and methods for WPMP production is given. Data on the composition and physico-chemical properties of liquid and dry WPMP are presented. An effect of sizes of WPMP particles on quality characteristics of products made with their use is described. The majority of the analyzed studies indicate that the diameter of particles is 1.0–2.5 µm. However, contradictory data were obtained for this indicator — if the results of all studies are taken into consideration, a size of conglomerates can be 0.5 to 12 µm. These sizes are comparable with parameters of fat globules, which allow receptors of the human oral cavity to perceive them identically. Due to this, WPMP can be used as an imitator of milk fat. It is noted that the microparticulation process enables producing WPMP with targeted functional properties, namely, with particular characteristics by indicators “solubility”, “water holding capacity”, “gel formation”, “emulsifying and foam forming properties”. Information about the specific features of using and dosing WPMP in fermented milk products, such yogurt, kefir, curd cheese and cheese, is given. A special attention is paid to the results of the investigation of using WPMP in ice cream. It is noted that most often scientists used WPMP to make up for the sensation of fatness in defatted and nonfat dairy products. The ability of WPMP to increase the biological value of food products is highlighted. It has been concluded that WPMP enables formation of soft and elastic structure in low-fat dairy products, intensification of milky color and restriction of ice crystal growth in frozen desserts by binding and equally distributing moisture. The data were obtained about the clinical investigation of an effect of ice cream with WPMP on the health of children and adults. The negative effect of WPMP on the indicators of clinical analyses of humans and their health was not revealed.

Assessing the Physicochemical Characteristics: A Comparative Analysis of Various Drying Methods in Osmotic Treated Fruit Slices

Background: Due to their high perishability, we cannot store fruits in their fresh form for long. The different drying techniques have affected the physical and nutritional qualities of the dried fruit pieces. Adoption of osmotic dehydration will help to protect and improve the quality characteristics of the final products. Methods: Selected fruit slices, viz., apple, pineapple, guava, mango and banana, were subjected to sugar osmosis (60°Bx for up to 48 hours), followed by drying in different drying methods, viz., open sun (ODT), solar tunnel (SDT) and hot air drying (CDT) and the physical and chemical characteristics of the end products were analysed. Result: The osmosis process improved the total soluble solids content, while CDT and SDT improved both the rehydration of the dried fruit slices and the percentage of weight loss. The desirable physical attributes of the dried products significantly varied among the different drying methods and within the fruit slices. The CDT-dried samples had better nutritional properties in terms of total phenol content and antioxidant activity than did the other drying methods and fresh samples, except for vitamin C content, which was greater in fresh fruit slices. The results recommended using CDT techniques in osmosis-treated fruit slices, which could improve fruit's physical and nutritional properties and be useful as good functional foods for a long time.

FORECASTING AND OPTIMIZATION OF CATALYTIC CRACKING UNIT OPERATION UNDER CONDITIONS OF FUZZY INFORMATION

This paper discusses the application of nonlinear regression to forecast and optimize the operation of catalytic cracking units under conditions of fuzzy information. Catalytic cracking is a crucial process in oil refining that produces high-quality gasoline and other light hydrocarbon products. However, the complexity of the process and the uncertainty of initial data complicate the modeling and optimization of plant operations. To address this issue, a nonlinear regression method is proposed that accommodates the fuzziness of input and output parameters described by linguistic variables. The methodology includes the collection and formalization of expert knowledge, the construction of fuzzy models, and their integration into the process control system. Forecasting is performed by creating regression models that describe the relationships between operational parameters and product quality characteristics. The paper presents a procedure for developing and applying nonlinear regression models, describes algorithms for synthesizing linguistic models, and provides examples of their use to optimize the operation of catalytic cracking units. The modeling results demonstrate the high adequacy and accuracy of the proposed method, as well as its advantages over traditional approaches in conditions of uncertainty and data scarcity. The scientific novelty of the research lies in the development and testing of advanced nonlinear regression models adapted for analyzing and optimizing catalytic cracking processes based on fuzzy data. These methods take into account the specificity and uncertainty of process data, improving the accuracy and reliability of forecasts, which facilitates more effective management of production processes in the petrochemical industry. The main reason for conducting this study is the need to improve the control of oil refining processes, particularly catalytic cracking, which plays an important role in producing high-quality gasoline. The complexity of this process and the presence of fuzzy information caused by fuzzy initial data require the development of new modeling and optimization methods. Existing traditional models based on deterministic methods are often insufficient under uncertainty. This leads to a decrease in the accuracy of process control, which can negatively affect the quality of the final product and production efficiency. The use of nonlinear regression in combination with fuzzy logic is a more flexible and adaptive approach that allows you to take into account the fuzziness and uncertainty of data and use expert knowledge to build models that match the actual operating conditions of the units. Thus, this study aims to solve the key problems associated with data uncertainty and the complexity of the catalytic cracking process, which will improve the accuracy of forecasting and optimization of the units. The main contribution is creating a model that uses nonlinear regression methods in combination with fuzzy logic. This allows uncertainty in input data (such as reactor temperature or pressure) to be effectively considered and processed to improve gasoline and other product yield forecasts. It is shown that using nonlinear regression combined with fuzzy logic significantly improves the management of technological processes, increases the output and quality of products, and reduces production costs. The conclusion of the paper discusses the prospects for further development of the methodology and its application to solve similar tasks in other areas of chemical technology.

Change in the qualitative composition of non-metallic mineral raw materials as a result of blasting operations

Purpose. The research purpose is to study the change in the qualitative composition of granite before and after blasting operations to determine its compliance with the criteria of marketable products. Methods. X-ray phase and X-ray structural research methods are used to study changes in the mineral composition of granites before and after blasting operations. To separate magnetic and non-magnetic fractions of the selected granite samples, a three-roller RST magnetic separator is used. X-ray phase research is conducted using a DRON-3 diffractometer. Additionally, an analysis of the unit cell dimensions of the quartz crystal lattice was conducted, and the dislocation density along the corresponding crystallographic planes was studied. Findings. It has been determined that after blasting operations, granite mass is redistributed from coarse fractions of 1-20 mm to small fractions of 0-1 mm with an increase in the latter by 4.2%. It has been found that the biotite content decrea-ses naturally and consistently, and the quartz content increases correspondingly in products in the following series: magnetic separator drum (90%, 2%) → lower roller (72%, 14%) → upper roller (55%, 31%) → non-magnetic product (48%, 34%) before blasting operations. Therefore, despite significant differences in the magnetic favorability of these two mineral phases, they are present in all magnetic separation products (with the exception of quartz in the non-magnetic product): magnetic separator drum → lower roller → upper roller. Originality. It has been established that along the crystallographic directions 101 and 211, the maximum gradient of dislocation density increase in the quartz crystal lattice in granite samples before blasting operations is observed during the transition from the lower roller product to the upper roller product, amounting to 1.55·1010 and 6.63·1010 cm-2, respectively. After blasting operations, in granite samples along the same directions, the maximum gradient of dislocation density increase is observed between the upper roller product and the non-magnetic product, amounting to 3.01·1010 and 4.67·1010cm-2. As a result of the thermodynamic impact of blasting operations, the weighted average dislocation density value along crystallographic planes 101 and 211 in the quartz crystal lattice increases by 47.21 and 25.72%, respectively. Practical implications. Understanding the quality characteristics of marketable products after blasting operations will contribute to optimizing the stages of further processing of non-metallic mineral raw materials (two-, three- or four-stage crushing) and expanding the scope of granite applications. This increases its competitiveness in the building materials market by reducing the costs for additional processing with a reduction in the labor intensity of the process.

Extrusion-Cooking Aspects and Physical Characteristics of Snacks Pellets with Addition of Selected Plant Pomace

The article presents the possibilities of using by-products from the agri-food industry in the form of fruit and vegetable pomace as a supplementary ingredient to extruded food products in the form of snack pellets. In the recipe based on potato starch, pomace from apples, chokeberries, pumpkin, nigella seed and flaxseed were added in amounts of 10%, 20% and 30%. The prepared raw material blends were processed using a single-screw extruder-cooker with a plastification system L/D = 20 and variable screw speed. The aim of the research was to determine the effect of pomace addition on the extrusion-cooking process, i.e., efficiency and energy consumption, as well as on selected physical properties of the obtained food pellets, such as expansion index, bulk density and durability. The addition of selected pomace influenced the extrusion-cooking process and the physical properties of the extrudates. A percentage contribution ranging from 10 to 20% can optimize the extrusion-cooking process and improve the quality characteristics of the final product, while simultaneously utilizing by-products from the agri-food industry and reducing their negative environmental impact.

The Effect of Product Quality, Brand Image, and Customer Satisfaction On Customer Loyalty (As Study On Ultra Milk Consumers In Jakarta)

In today's increasingly competitive business environment, building and maintaining customer loyalty has become a key determining factor in an organization's success and profitability. Customer loyalty generates recurring revenue through repeat purchases and serves as a brand advocate, driving organic growth by attracting new customers. However, cultivating customer loyalty requires a strategic and holistic approach, which includes product quality, brand image, and customer satisfaction. This research empirically explores the impact of product quality characteristics, brand image, and customer satisfaction on Ultra Milk customer loyalty in the Jakarta area. This study uses a quantitative approach to determine the causal relationship between these factors. The data was collected by distributing questionnaires to 100 active Ultra Milk consumers in Jakarta. SPSS 29 software is used for data analysis, specifically multiple linear regression. The findings of this study aim to contribute to a theoretical understanding of the factors that affect consumer loyalty in the dairy industry. Practically, the findings of this study are expected to be the foundation for Ultra Milk companies to develop more effective marketing strategies to increase and maintain customer loyalty. The recommendations given will focus mainly on statistically significant variables in influencing customer loyalty.

Impact of mixing and shaking on mRNA-LNP drug product quality characteristics

Since the COVID-19 pandemic, the interest in RNA-lipid nanoparticle (LNP) based drug products has increased drastically. While one RNA-LNP drug product, Onpattro, was already on the market in 2018, high volume manufacturing was only initiated end of 2020 with the approval of the mRNA-LNP vaccines, Comirnaty and Spikevax. As such, deep product knowledge for RNA-LNPs is continuously increasing. In this article the effect of large-scale mixing and lab-scale shaking on mRNA-LNP drug product quality characteristics is investigated. It is shown that mixing and shaking can have a profound impact on both LNP size distribution and mRNA encapsulation, suggesting a direct correlation between both quality characteristics, and further supported by a proposed underlying mechanism. An in-depth investigation of different drug product (DP) presentations reveals a consistent effect of headspace volume and LNP content on the shaking stress sensitivity. Results reported in this study are of utter importance for both small- and large-scale manufacturers but also for care givers and patients using these products.

Occurrence and distribution of phytic acid and its degradation products in soybeans in China: Analytical challenges

Phytic acid (IP6) and its degradation products lower myo-inositol phosphates exert different impacts on nutrient bioavailability and product quality characteristics. However, information regarding the occurrence of IP6 and its degradation products is scarce. In this work, simultaneous determination of IP6 and its degradation products in soybeans was developed, with emphasis on analysis by UPLC-MS/MS and a BEH Amide column both with hybrid surface technology. The retention and analyte/metal surface interactions issues were effectively addressed without ion-pairing reagents addition or derivatization. This method was applied to analyze soybeans from China. Total contents were 0.44–13.2 mg/g, and IP6 and its degradation product myo-inositol pentakisphosphate (IP5) were the predominant analytes, accounting for over 99%. Accession type significantly affected IP5 content, and landraces had significantly higher IP5 than cultivars. Geographically, the lowest IP6 was concentrated in the Huanghuaihai region. Significant correlations existed between IP6 and longitude, altitude, and annual cumulative sunshine hours. This study provides comprehensive insights into the IP6 and its degradation product profile in soybeans, which will benefit breeding soybeans based on specific requirements.

ANALYSIS OF THE GENETIC STRUCTURE OF THE POLISH BEEF BREED BY MOLECULAR MARKERS OF MEAT QUALITY INDICATORS PRODUCTIVITY

The results of determining the genotypes of Polish beef breed animals based on polymorphism of the thyroglobulin (TG 5) and calpain (CAPN1 530) genes are given. The PCR-PDRF method was used for the analysis. Based on the obtained data, the specifics of the genetic structure of the studied population were established based on the distribution of frequencies of alleles and genotypes. For the thyroglobulin gene, animals with the homozygous SS genotype had a quantitative advantage, which led to a high concentration of the C allele (0.775). For the calpain gene, a high frequency of the desired G allele was found in the studied group of animals (0.539). Based on the results of the analysis, the prospects of the researched group of animals of the Polish meat breed were determined for establishing an associative relationship of various allelic variants of the thyroglobulin and calpain genes with the parameters of the quality characteristics of the final product – marbling and tenderness of meat.

Environmental Facility of Food Products as a Factor of Market Positioning

The purpose of the article is to analyze the reactions of consumers to the quality characteristics of food products, in particular related to the level of their environmental friendliness, in order to develop proposals for improving the communication programs of manufacturers of these products in Ukraine. The authors describe the reactions of consumers to the qualitative characteristics of food products based on the results of a sociological study. 1269 people participated in the study, including 539 (42.5%) men and 730 (57.5%) women. The distribution of respondents by age is as follows: from 18 to 20 years old - 68 people or 5.4%; from 21 to 30 years old - 367 people or 28.9%; from 31 to 40 years old - 705 people or 55.5%; over 40 years old – 129 people or 10.2%. The age structure of respondents shows that about 90% of respondents belong to generations Y and Z, according to the well-known American classification. The intensifying competition among food manufacturers in Ukraine requires them to improve their own communication programs and positioning strategies by identifying significant emotional and functional attributes of the specified products. The conducted sociological study of the purchasing behavior of consumers on the food market in Ukraine contributes to the solution of this problem. The authors identified a number of factors influencing the formation of stereotypes of food quality perception. Indicators of environmental friendliness and safety for human health turned out to be the most important attributes in market positioning. The results of the study serve as a methodological basis for improving the communication programs of food manufacturers, contribute to the development of healthy competition among them. The findings of this study can be considered important as a guide for future research.

Optimizing Lactic Acid Bacteria Proportions in Sourdough to Enhance Antifungal Activity and Quality of Partially and Fully Baked Bread.

The organic acids produced by lactic acid bacteria (LAB) during the fermentation of sourdoughs have the ability to reduce the growth of different molds. However, this ability depends on the LAB used. For this reason, in this study, the proportions of different LAB were optimized to obtain aqueous extracts (AEs) from sourdough to reduce fungal growth in vitro, control the acetic acid concentration, and obtain a specific lactic to acetic acid ratio. In addition, the optimized mixtures were used to formulate partially baked bread (PBB) and evaluate the mold growth and bread quality during refrigerated storage. Using a simplex-lattice mixture design, various combinations of Lactiplantibacillus plantarum, Lacticaseibacillus casei, and Lactobacillus acidophilus were evaluated for their ability to produce organic acids and inhibit mold growth. The mixture containing only Lpb. plantarum significantly reduced the growth rates and extended the lag time of Penicillium chrysogenum and P. corylophilum compared with the control. The AEs' pH values ranged from 3.50 to 3.04. Organic acid analysis revealed that using Lpb. plantarum yielded higher acetic acid concentrations than when using mixed LAB. This suggests that LAB-specific interactions significantly influence organic acid production during fermentation. The reduced radial growth rates and extended lag times for both molds compared to the control confirmed the antifungal properties of the AEs from the sourdoughs. Statistical analyses of the mixture design using polynomial models demonstrated a good fit for the analyzed responses. Two optimized LAB mixtures were identified that maximized mold lag time, targeted the desired acetic acid concentration, and balanced the lactic to acetic acid ratio. The addition of sourdough with optimized LAB mixtures to PBB resulted in a longer shelf life (21 days) and adequately maintained product quality characteristics during storage. PBB was subjected to complete baking and sensory evaluation. The overall acceptability was slightly higher in the control without sourdough (7.50), followed by bread formulated with the optimized sourdoughs (ranging from 6.78 to 7.10), but the difference was not statistically significant (p > 0.05). The sensory analysis results indicated that the optimization was used to successfully formulate a sourdough bread with a sensory profile closely resembling that of a nonsupplemented one. The designed LAB mixtures can effectively enhance sourdough bread's antifungal properties and quality, providing a promising approach for extending bread shelf life while maintaining desirable sensory attributes.

The Effects of a Natural Citrus Phenolic Extract on the Quality Attributes and Oxidative Stability of Pariza-Type Meat Emulsion Product

Several synthetic food additives that bear an E-number are used by the meat industry as antioxidants/preservatives of cured meat products, such as pariza-type meat emulsion products. However, these agents have been associated with health problems, namely cardiovascular disease, metabolic syndrome, and potential carcinogenic effects. As a result, natural alternatives are constantly under evaluation with the intention of replacing/minimizing their applications in the meat industry. The aim of the present study was therefore to evaluate the effects of a natural citrus phenolic complex extract on the quality characteristics of pariza-type meat emulsion products. The following three batches of pariza were produced based on the same raw material and recipe: a control group without natural antioxidants and two groups with the addition of the polyphenol complex at the levels of 500 and 1000 ppm. The pH, color, tenderness, and oxidative stability of the meat products were assessed immediately after pariza manufacture (day 0), and 30 and 72 days after the start of its refrigerated storage. As indicated, the oxidative stability of pariza was improved as a result of the natural polyphenol complex addition, since the values of malondialdehyde (MDA), an index of lipid peroxidation, were linearly decreased. Parameters such as pH, lightness (L), and yellowness (b*) were linearly increased, while redness (a*) was linearly decreased, and tenderness was not significantly influenced in the treatment groups compared to the control group. It can be concluded that the natural polyphenol complex under examination can be utilized for the improvement of oxidative stability in pariza.

Research on dynamic pricing and coordination model of fresh produce supply chain based on differential game considering traceability goodwill

This study aims to solve the current pricing and coordination problems in the fresh produce supply chain by proposing a dynamic pricing and coordination differential game model based on traceability goodwill to optimize the operational efficiency and profitability of the supply chain. Freshness and traceability are critical consumer trust and brand value factors incorporated into the dynamic pricing and coordination model in the agricultural supply chain. The research methodology of this paper integrates critical factors such as supply chain cost and market demand to construct a comprehensive differential game model. It also highlights the motivation of dynamic pricing strategy and coordination mechanism based on traceability goodwill. Through traceability goodwill, operating companies can better assess and manage product quality and improve consumer trust in agricultural products, thus enhancing brand value. The dynamic pricing strategy based on traceability goodwill can flexibly adjust prices according to changes in the quality characteristics of agricultural products and market demand, realizing a dynamic balance between supply and demand. On the other hand, the mutual cost-sharing and coordination mechanism promotes the synergy between the various links of the supply chain. It improves overall efficiency through cooperation coo, coordination, and other means. The validity and reliability of the model are verified through numerical simulation experiments. The numerical simulation results show that the dynamic pricing and coordination model based on traceability will significantly improve supply chain efficiency and profitability compared with the traditional model. Specifically, the interests of supply chain participants are balanced, and the overall supply chain operational efficiency is improved. The main contribution of this study is to propose a dynamic pricing and coordination model based on traceability goodwill and verify its superiority through numerical simulation experiments. This study provides a valuable reference for fresh agricultural products supply chain management and offers new ideas for improving supply chain efficiency and profitability.

Effect of Turmeric Powder Supplementation on Egg Production, Hatchability and Internal Egg Quality Characteristics of Quail Eggs

Effect of Turmeric Powder Supplementation on Egg Production, Hatchability and Internal Egg Quality Characteristics of Quail Eggs

COMPETITION AS A KEY PROPERTY OF THE AGRICULTURAL PRODUCTS MARKET

Competition in the agricultural sector results from the unity of conflicting factors: the maximum freedom of activity of market forces and the significant influence of the state on the processes taking place in the industry, which ensures the overall efficiency of social production. Regulation of competition in the agricultural market in developed countries is a developed and expensive system. Currently, it is impossible to provide the same robust support to the agricultural sector in the country, but the principles and methods used for this can be taken into account. Different types of competition are developing in the agri-food market. Intra-industry competition is possible only if production and sales costs are reduced and weak, technically backward enterprises are pushed out of the market. Interindustry competition leads to the redistribution of capital and other resources between industries, taking into account the rate of return. Participation in agriculture in this competition is only possible with state support due to the low speed of capital turnover and high capital intensity in this field. Intra-industry competition initiates technical progress, and inter-industry competition contributes to the structural development of the agricultural industry. To a certain extent, agricultural product markets are characterized by perfect competition, and food markets are characterized by monopolistic competition. It is emphasized that competition covers all spheres of commodity production, distribution, market exchange, and consumption. It manifests differently in each branch of the economy, which is determined by the specifics of their activity. Conducted studies of competition in the market of agricultural raw materials and food indicate the need to strengthen the competitiveness of domestic agricultural products and ensure consumer, quality, and price characteristics of agricultural products, raw materials, and food that are comparable to the world level, regardless of orientation to domestic or foreign markets. It is noted that competition in agriculture is characterized by many competitors on the market and obstacles in the production and sale of agricultural products.

Use of GC-IMS and Stoichiometry to Characterize Flavor Volatiles in Different Parts of Lueyang Black Chicken during Slaughtering and Cutting.

Chilled and cut chicken is preferred by consumers for its safeness and readiness to cook. To evaluate the quality characteristics of various chilled chicken products, differences in volatile organic components (VOCs) of six different cut parts (breast, back, leg, heart, liver, and gizzard) of Lueyang black chicken were characterized through gas chromatography-ion mobility spectroscopy (GC-IMS) combined with stoichiometry. A total of 54 peaks in the signal of VOCs were detected by GC-IMS, and 43 VOCs were identified by qualitative analysis. There were 22 aldehydes (20.66-54.07%), 8 ketones (25.74-62.87%), 9 alcohols (4.17-14.69%), 1 ether (0.18-2.22%), 2 esters (0.43-1.54%), and 1 furan (0.13-0.52%), in which aldehydes, ketones, and alcohols were the main categories. Among the six cut parts, the relative content of aldehydes (54.07%) was the highest in the gizzard, and the relative content of ketones (62.87%) was the highest in the heart. Meanwhile, the relative content of alcohols (14.69%) was the highest in the liver. Based on a stable and reliable predictive model established by orthogonal partial least squares-discriminant analysis (OPLS-DA), 3-hydroxy-2-butanone (monomer and dimer), acetone, 2-butanone monomer, hexanal (monomer and dimer), isopentyl alcohol monomer, and n-hexanol monomer were picked out as characteristic VOCs based on variable importance in projection (VIP value > 1.0, p < 0.05). Principal component analysis (PCA) and the clustering heatmap indicated that the characteristic VOCs could effectively distinguish the six cut parts of Lueyang black chicken. The specific VOCs responsible for flavor differences among six different cut parts of Lueyang black chicken were hexanal (monomer and dimer) for the gizzard, 2-butanone monomer and hexanal dimer for the breast, hexanal monomer for the back, 3-hydroxy-2-butanone monomer for the leg, 3-hydroxy-2-butanone (monomer and dimer) for the heart, and acetone and isopentyl alcohol monomer for the liver. These findings could reveal references for quality assessment and development of chilled products related to different cut parts of Lueyang black chicken in the future.

Quality characteristics of a red chili oil product processed via oil infusion: effects of pre-heated oil temperature

Quality characteristics of a red chili oil product processed via oil infusion: effects of pre-heated oil temperature

Exploring the efficacy of pulsed electric fields (PEF) in microbial inactivation during food processing: A deep dive into the microbial cellular and molecular mechanisms

Pulsed electric field (PEF) is a food processing technology based on the phenomenon of electroporation for the inactivation of microorganisms with main advantage the minimal effect on the quality (nutritional, functional, and sensorial) characteristics of the food products. Despite the plethora of research literature on PEF-processed food safety, PEF's industrial application as an alternative of classical pasteurization is limited and mainly at industrial level is focused on high acid-liquid food products. Thus, the thorough assessment of the antimicrobial efficiency of PEF, coupled with the meticulous identification of key microbial resistance mechanisms is scientifically imperative. These efforts are essential for refining the process and exploring potential enhancements through synergistic integration and combination with other methods or/and hurdles. On this basis this manuscript aims to critically review and summarise: a) the antimicrobial mechanism of action, b) the microbial inactivation efficiency, and c) the effect of PEF at a microbial genomic/transcriptomic level. Industrial applicationEvaluating the effectiveness of inactivation and understanding the underlying resistance mechanisms can help on strategies to optimize PEF-mediated decontamination practices, and thereby enhancing the overall process efficiency.

Prediction of prunoideae fruit quality characteristics based on machine learning and spectral characteristic acquisition optimization

Machine learning algorithms have been widely used in the estimation and prediction of various quality characteristics of food and agricultural products. The purpose of this study is to study the availability and accuracy of the prediction model of Prunoideae fruit quality characteristics based on machine learning algorithms. XGBoost, LightGBM, CatBoost, and Random Forest (RF) are the four machine learning algorithms used in this work to create prediction models for the soluble solids content (SSC) and titratable acidity (TA) of peach, apricot, and cherry. The study investigated three hyperspectral denoising methods and used two feature extraction techniques to lower the dimensionality of hyperspectral data. The models' accuracy was further improved by adding multiple types of spectral data. Based on opposite spectral data input, the MLP-SG-XGBoost model produced the best SSC predictions for peach and apricot, with R2 values of 0.9162 and 0.9251, respectively, according to experimental results. When inputting opposite spectral data, the LGR-SG-LightGBM model showed the highest accuracy in predicting TA for peach and apricot, with R2 values of 0.9193 and 0.9206, respectively. The outcomes imply that the models can accurately forecast the qualities of Prunoideae fruit.