Food Process Control Research Articles

Psychosocial risks in food processing establishments related to burnout syndrome

Examine psychosocial risks in the food sector of Cartagena, Colombia, focused on the processing, transformation and quality control of food, with the purpose of proposing preventive strategies to mitigate burnout syndrome. A mixed methodology will be used, integrating quantitative and qualitative approaches through the application of questionnaires and semi-structured interviews. Variables such as job demands, the degree of control over work and the manifestation of burnout symptoms will be explored. The results obtained will allow the predominant risk factors to be identified and will facilitate the design of specific interventions adapted to the particularities of the sector. The mental health and well-being of workers in the food processing, transformation and quality control sector in the city of Cartagena will be improved by these measures, while providing valuable information for future research in the field of safety and health at work. In summary, this study aims to provide a comprehensive view of the psychosocial risks present in the food sector, underlining the importance of addressing these challenges to foster a healthier, more productive and sustainable work environment in the long term.

Special Issue on “Drying Kinetics and Quality Control in Food Processing”

The study of drying kinetics and quality control in food processing is critical for enhancing food preservation and safety [...]

Revolutionizing food science with mass spectrometry imaging: A comprehensive review of applications and challenges.

Food science encounters increasing complexity and challenges, necessitating more efficient, accurate, and sensitive analytical techniques. Mass spectrometry imaging (MSI) emerges as a revolutionary tool, offering more molecular-level insights. This review delves into MSI's applications and challenges in food science. It introduces MSI principles and instruments such as matrix-assisted laser desorption/ionization, desorption electrospray ionization, secondary ion mass spectrometry, and laser ablation inductively coupled plasma mass spectrometry, highlighting their application in chemical composition analysis, variety identification, authenticity assessment, endogenous substance, exogenous contaminant and residue analysis, quality control, and process monitoring in food processing and food storage. Despite its potential, MSI faces hurdles such as the complexity and cost of instrumentation, complexity in sample preparation, limited analytical capabilities, and lack of standardization of MSI for food samples. While MSI has a wide range of applications in food analysis and can provide more comprehensive and accurate analytical results, challenges persist, demanding further research and solutions. The future development directions include miniaturization of imaging devices, high-resolution and high-speed MSI, multiomics and multimodal data fusion, as well as the application of data analysis and artificial intelligence. These findings and conclusions provide valuable references and insights for the field of food science and offer theoretical and methodological support for further research and practice in food science.

Enhancing Food Integrity through Artificial Intelligence and Machine Learning: A Comprehensive Review

Herein, we examined the transformative potential of artificial intelligence (AI) and machine learning (ML) as new fronts in addressing some of the pertinent challenges posed by food integrity to human and animal health. In recent times, AI and ML, along with other Industry 4.0 technologies such as big data, blockchain, virtual reality, and the internet of things (IoT), have found profound applications within nearly all dimensions of the food industry with a key focus on enhancing food safety and quality and improving the resilience of the food supply chain. This paper provides an accessible scrutiny of these technologies (in particular, AI and ML) in relation to food integrity and gives a summary of their current advancements and applications within the field. Key areas of emphasis include the application of AI and ML in quality control and inspection, food fraud detection, process control, risk assessments, prediction, and management, and supply chain traceability, amongst other critical issues addressed. Based on the literature reviewed herein, the utilization of AI and ML in the food industry has unequivocally led to improved standards of food integrity and consequently enhanced public health and consumer trust, as well as boosting the resilience of the food supply chain. While these applications demonstrate significant promise, the paper also acknowledges some of the challenges associated with the domain-specific implementation of AI in the field of food integrity. The paper further examines the prospects and orientations, underscoring the significance of overcoming the obstacles in order to fully harness the capabilities of AI and ML in safeguarding the integrity of the food system.

ResNet101-SVM: Hybrid convolutional neural network for citrus fruits classification

Recognizing and classifying citrus fruits is a challenging yet crucial task for agriculture, food processing, and quality control. Classifying citrus fruits is challenging because of their wide variety, often with a similar flesh appearance, shape, and size. Therefore, efficient and effective approaches are required for accurate identification. Our study focused on efficiently identifying citrus fruit types by utilizing a hybrid ResNet101-SVM model. ResNet101-SVM is the combination of the feature extraction capabilities of the ResNet101 with the classification power of SVM. This hybrid approach leverages the strengths of both deep learning (feature extraction) and traditional machine learning (SVM classification) to improve the accuracy and robustness of citrus fruit classification. The model outperformed the standard ResNet101 model across various performance metrics, achieving impressive accuracy, sensitivity, specificity, precision, F1 Score, MCC, and Kappa values of 99.81%, 99.81%, 99.8%, 99.82%, 0.18%, 99.81%, 99.80%, and 98.77%, respectively. This study holds significant promise for various applications, particularly in the domains of food processing and quality control.

E-eye and FT-NIR combined with multivariate algorithms to rapidly evaluate the dynamic changes in the quality of Gastrodia elata during steaming process

Gastrodia elata (GE) is traditionally subjected to steaming, and steaming duration plays a crucially important role in determining GE quality. This study examined the variations in bioactive components during the steaming process and proposed the utilization of electronic eye and Fourier Transform near-infrared (FT-NIR) spectroscopy for quality assessment. The findings revealed that the levels of parishin E parishin B, parishin A, and gastrodin initially rose and subsequently declined, while 4-Hydroxybenzyl alcohol exhibited a rapid decrease followed by stabilization. With prolonged steaming, the brightness of GE decreased, while the red and yellow tones became more pronounced and the color saturation increased. FT-NIR divided the steaming process into three stages: 0 min (raw GE), 0–9 min (partially steamed GE), and 9–30 min (fully steamed GE), and the partial least squares regression models effectively predicted the levels of five components. Overall, this study provided valuable insights into quality control in food processing.

Cabaran dan Strategi Menghadapi Perubahan Kurikulum dalam Kalangan Pensyarah Bidang Agroteknologi Kolej Komuniti

Climate change, shortages of resources, advancements in artificial intelligence, technological explosions, and globalization have an impact on the agricultural labour market. As a result, the Institute of Technical and Vocational Training Education (PLTV) is under pressure to produce highly trained graduates in order to meet its objectives. In an effort to resolve this issue, PLTV, particularly Community College, is urgently needed to revise the curriculum of the Community College Certificate Programme (SKK), particularly in the field of agrotechnology. The study aims at exploring the challenges and strategies of agrotechnology lecturers at Community College in facing the prospect of curriculum changes. The survey study was designed implementing a qualitative methodology. The collection of survey data is carried out through semi-structured interviews using adapted interview protocols. The study population consisted of lecturers in the field of agrotechnology at Community College covering three clusters namely agriculture technology, aquaculture and food processing and quality control. The purposive sampling method is used to select six survey informan who meet the set criteria. The data obtained is analyzed thematically. The findings of the study find lecturers facing challenges from aspects of expertise, knowledge, and competence; time constraints; lack of resources; and curriculum design. The lecturers also recommended strategies to overcome the challenges in curriculum change from the practice aspect; resource improvement; curricular improvements; and quality assurance. This finding is expected to contribute to the the curriculum change process especially for the Agrotechnology Certificate Program.

Screening, identification and control of unknown estrogen-like compounds in Maillard reaction products of glucose-arginine/lysine model systems

It was speculated that estrogen-like compounds may be produced by chemical reactions during food processing, such as Maillard reaction, which would disrupt the endocrine system of organisms. Herein, the Maillard reaction in the process of high temperature for long time was simulated by using model system, and unknown estrogen-like compounds produced during Maillard reaction were screened by colorimetric assay based on dual estrogen receptor (ER)-gold nanoparticles (AuNPs) and enzyme-linked immunosorbent assay (ELISA). Possible structures of estrogen-like compounds were inferred by ultra-performance liquid chromatography-quadrupole time of flight tandem mass spectrometry (UPLC-QTOF/MS) in combination with a mass database, and finally the structure of estrogen-like compound, 2, 4-dihydroxy-1, 4-benzoxazin-3-one-2-o-β-D-glucopyranoside (DIBOA-glc), was identified by high resolution orbitrap mass spectrometry (Orbitrap HRMS). This is the first study of the screening and identification of unknown estrogen-like compounds produced in Maillard reaction. Additionally, strategy of controlling the formation of DIBOA-glc by adding vitamin B6 in Maillard reaction was proposed, providing effective proposals for the safety control in actual food processing.

Analytical Methods for Allergen Control in Food Processing

Food allergy and food-related anaphylaxis have become a growing public health and food safety issue worldwide [...].

High fluorescent nitrogen − doped carbon dots derived from Sanghuangporus lonicericola for detecting tetracyclines in aquaculture water and rat serum samples

Tetracyclines (TCs) are a kind of broad − spectrum and effective antibiotics that have been widely used in veterinary and human medicine, which may pose serious risk to human health if they are accumulated in human body. The fluorescence method using nanomaterials as probes has been gradually used for the detection of TCs because of its simple operation, high sensitivity and recognition ability. Herein, a novel nitrogen doped carbon dots (N − CDs) derived from Sanghuangporus lonicericola was synthesized by hydrothermal method. The N − CDs exhibited bright blue fluorescence, high quantum yield (QY) of 60.99 %, and excellent photostability, which was employed as a fluorescent probe for selective detection of TCs, including oxytetracycline (OXY), doxycycline (DOX), tetracycline (TCY) and minocycline (MNO). The fluorescence intensity of the N − CDs decreased linearly with the increasing concentration of OXY, DOX, TCY and MNO, and their concentrations were in the range of 0.6 – 73.3 μM, 0 – 95.2 μM, 6.5 – 72.3 μM and 10 – 52.6 μM, respectively. As for practical application, the as − prepared N − CDs could not only be effectively applied for determination of TCs in aquaculture water and rat serum samples with low relative standard deviation (RSD) and good recoveries, but also track the concentration change of TCs in rats blood model over time. Towards the fluorescence detection mechanism, the results of UV–vis absorption spectra and fluorescence lifetimes proved that the fluorescent quenching of N − CDs occurred from internal filtration effect (IFE) in the presence of TCs. This work provides guidance for the development of new TCs sensors based on fluorescent nanomaterials, and has a good application prospect in the quality control of agriculture, food and pharmaceutical production processes.

Atmospheric cold plasma: A potential technology to control Shewanella putrefaciens in stored shrimp

This work aimed to investigate the inactivation mechanism of atmospheric cold plasma (ACP) against Shewanella putrefaciens both in PBS and sterile shrimp juice (SSJ). Reductions in cell density, cell viability, and biofilm formation activity were observed after ACP treatment. ACP cyclical treatment (1 min, 5 times) was more efficient than a one-time treatment (5 min, 1 time). After ACP cyclical treatment, the cell counts and cell viability of S. putrefaciens in PBS were decreased by 3.41 log CFU/mL and 85.30 %, respectively. As for SSJ group, the antibacterial efficiency of ACP declined, but the antibacterial effect of ACP cyclical treatment was still stronger than that of ACP one-time treatment. The biofilm formation activity of S. putrefaciens in PBS was almost completely inhibited, while it gradually returned to normal level with the prolonged of storage time for the SSJ counterpart. The rapid decrease in AKP activity after ACP treatment indicated the damage to cell wall integrity, which was also demonstrated by TEM. In addition, cell membrane and DNA damage of the strain also occurred after ACP treatment. The ROS fluorescence intensity in PBS was higher for the one-time treatment group, while the cyclical treatment group exhibited higher and more stable ozone levels. It was also detected that the total nitric oxide concentration in bacterial suspension depended on the dose of ACP treatment time. ACP treatment (35 kV) for 5 min, especially cyclical treatment, displayed its antibacterial properties on packaged shrimp contaminated with high concentration of S. putrefaciens. ACP cyclical treatment reduced surface bacterial counts of whole shrimps by 0.52 log CFU/mL, while ACP one-time treatment only achieved a decrease of 0.18 log CFU/mL. Therefore, ACP treatment could be considered as a potential alternative to enhance microbial control in food processing.

Research on quality control and safety management in food processing

Research on quality control and safety management in food processing

Resistant starch structure, food processing, and glycaemic control: investigating how the synergy of starch synthesis variation and processing influences glycaemia

Resistant starch structure, food processing, and glycaemic control: investigating how the synergy of starch synthesis variation and processing influences glycaemia

Study of microwave and convective drying kinetics of pea pods (Pisum sativum L.): A new modeling approach using support vector regression methods optimized by dragonfly algorithm techniques

AbstractMachine learning and mathematical modeling techniques have been conducted to model the thin layer drying kinetics of pea pods, under either microwave or conventional air drying,. The effect of nine different microwave output powers (200–1000 W) and five different ventilated oven temperatures (40, 60, 80, 100, and 120°C) on drying kinetics was studied. The experimental drying rates were fitted to 11 literature semi‐empirical models to determine the kinetic parameters, finding the higher goodness‐of‐fit for the Midilli et al. model (average R2 = 0.999 for both drying methods). Moreover, the data were modeled using support vector machine (SVM) for regression which was optimized with dragonfly algorithm (DA) technique. The best result was obtained by Gaussian kernel with the optimal parameters σ, C, and ε values estimated as 0.2871, 78.45, and 0, respectively. The small root mean square error (RMSE = 0.0132) and the high determination coefficient (R2 = 0.9983) values proved how robust the SVM model is. DA‐SVM techniques can reliably be utilized to describe the thin layer drying kinetics of pea pods. It is useful to provide models that can assist in the development of food process control algorithms, and provided insights into complex processes, for the technological design of microwave or convective drying for pea pods preservation.Practical applicationsDrying of by‐products from pea processing industry was investigated as a critical step prior to their valorization. The drying of pea pods has never been investigated before which is the case of the present study whose objective was to study and model the microwave and convective drying kinetics of pea pods. Our research work reported that the Midilli et al. model was the most appropriate to describe the thin layer drying kinetics of pea pods for both drying methods, but mathematical drying models, although a useful tool, remains empirical in nature and product specific. Because of these limitations the new model DA‐SVM, developed using artificial intelligence techniques, can reliably be used to describe the nonlinear behavior of pea pods drying. These results could be further used for scale up calculation, which would further allow industrial scale preservation by microwave or convective drying of pea pods.

Optofluidic Fabry-Perot interferometric sensor for the real-time measurement of refractive index

In this work, a microfluidic system combined with a fibre-optic extrinsic Fabry-Perot interferometer is proposed to measure refractive index continuously and in real time. A microfluidic platform was designed and created for this purpose through 3D printing. The Fabry-Perot cavity is an integral part of the microfluidic chip and is perpendicular to the sample flow. The light is conducted through a single mode optical fibre and the refractive index measurements were based on the optical power and wavelength shift of the reflected spectra. The developed optofluidic setup was characterised using different concentrations of glucose solutions. A sensitivity of 1102 nm/RIU was obtained when using the wavelength shift, however, when the same solution was analysed over time, the signal for wavelength shift measurements was found to be unstable. The optical power shift was correlated with the refractive index and a sensitivity of -79.6 dB/RIU was obtained, with a good linearity (r2 = 0.996). Good results were verified in terms of stability with a maximum standard deviation of 0.028 dB and a sensor resolution of 4.3×10−4 RIU. This sensor has a great potential for applications in which refractive index real-time measurements are required, such as food and beverages industry process control.

Current Trends in Intelligent Control Neural Networks for Thermal Processing (Foods): Systematic Literature Review

Thermal processing is a technique for sterilizing foods through heating at high temperatures. Thermal processing plays a significant role in preserving foods economically, efficiently, reliably, and safely. Control in thermal processing of foods is necessary to avoid any decrease in food quality, i.e., color change, reduced content, sensory quality, and nutrition. Artificial Neural Network (ANN) has been developed as a computing method in research and developments on thermal processing methods to discover one suitable for food processing without damaging food quality. To this date, ANN has been used in food industries for modeling many processes. The paper aims to identify the latest trend in intelligent neural network control for the thermal processing of foods. The paper conducted a systematic literature review with five research questions using Preferred Reporting Items for Systematic Review (PRISMA). According to screening results and article selection, 240 potential articles have fulfilled the inclusion criteria. Then, each article was explored to identify the advantage and the advance of intelligent network control in thermal food processing. It can be concluded that the technology in information and computations of food processing has rapidly developed and advanced through the utilization of a combination of ANN with fuzzy logic and/or genetic algorithms.

Factors Influencing Students' Selection to the Certificate In Food Processing and Quality Control Program at Sik Community College, Ministry Of Higher Education (MOHE), Malaysia

Selection of field of study is an important matter for every student when furthering their studies in higher education. Each individual has different interests. In determining the success of one's life, the selection of the right course is important, especially in determining a career upon graduation and entering the industry. Individual talent and abilities towards courses offered by higher education institutions are also important to ensure that every individual who chooses a field of study at the Higher Education level achieves excellence in studies. This is a qualitative study that employs a semi-structured interview tool. The goal of this research was to identify the factors that influence students' decisions to enroll in the Certificate in Food Processing and Quality Control Certificate program at Sik Community College. The research was carried out at Sik Community College, Ministry of Higher Education Malaysia. Five informants were chosen at random for the interview session based on sampling. Based on the results of interviews with informants, the study's findings were recorded and reviewed. According to the study's findings, the factor of continuing their studies to a higher level is the main factor for students to choose to take this course, along with job opportunities and family influence factors that also play a role in course selection. As a result, some suggestions for improvement have been made in order to increase student enrollment and the institution may also define student interest to implement promotion for intake to College's Certificate in Food Processing and Quality Control program.

Critical assessment of methods for measurement of temperature profiles and heat load history in microwave heating processes-A review.

Limitations of microwave processing due to inhomogeneities of power input and energy absorption have been widely described. Over- and underheated product areas influence reproducibility, product quality, and possibly safety. Although a broad range of methods is available for temperature measurement and evaluation of time/temperature effects, none of them is sufficiently able to detect temperature differences and thermally induced effects within the product caused by inhomogeneous heating. The purpose of this review is to critically assess different methods of temperature measurement for their suitability for different microwave applications, namely metallic temperature sensors, thermal imaging, pyrometer measurement, fiber optic sensors, microwave radiometry, magnetic resonance imaging, liquid crystal thermography, thermal paper, and biological and chemical time-temperature indicators. These methods are evaluated according to their advantages and limitations, method characteristics, and potential interference with the electric field. Special attention is given to spatial resolution, accuracy, handling, and purpose of measurement, that is, development work or online production control. Differences of methods and examples of practical application and failure in microwave-assisted food processing are discussed with a special focus on microwave pasteurization and microwave-assisted drying. Based on this assessment, it is suggested that infrared cameras for measuring temperature distribution at the product surface and partially inside the product in combination with a chemical time/temperature indicator (e.g., Maillard reaction, generating heat-induced color variations, depending on local energy absorption) appear to be the most appropriate system for future practical application in microwave food process control, microwave system development, and product design. Reliable detection of inhomogeneous heating is a prerequisite to counteracte inhomogeneity by a targeted adjustment of process and product parameters in microwave applications.

Logistics cost control in food processing enterprises based on TD-ABC

In order to improve the logistics operation of food processing enterprises and control the logistics cost, this paper starts from the analysis of the logistics operation process and characteristics of enterprises, analyzes the logistics cost classification and composition of food processing enterprises, puts forward the basic process of applying TD-ABC to control the logistics cost, constructs the logistics cost accounting model of food processing enterprises based on TD-ABC, and puts forward relevant logistics cost control methods including the design of logistics cost control system, the determination of logistics cost control points and specific implementation steps. The typical food processing enterprises are selected for the empirical study of logistics cost accounting and controlling. By comparing the cost accounting results of TD-ABC and ABC, the result shows that TD-ABC (Time-Driven Activity-Based Costing) method can accurately grasp the logistics cost composition, identify inefficient logistics operations and non-value-added operations, and analyze the efficiency of various logistics departments, verify the feasibility and effectiveness of logistics cost accounting model and control method system, and provide some advice for logistics cost control and logistics process transformation of food processing enterprises.

Potential Activity of Albino Grifola frondosa Mushroom Extract against Biofilm of Meticillin-Resistant Staphylococcus aureus.

Mushroom extracts are a rich source of natural compounds with antimicrobial properties, which are able to prevent, to some extent, the growth of foodborne pathogens. The aim of this study was to investigate the potential of extracts from albino Grifola frondosa (GF), commonly known as maitake, to inhibit the growth of some bacteria and the biofilm production by Staphylococcus aureus. We obtained not only a significant reduction of OD score between biofilm and biofilm plus albino G. frondosa extract group, but also a reduction of category of biofilm. In addition, we observed a significant presence of isolates with strong category for the biofilm group and a significant presence of isolates with absent category for the biofilm plus albino G. frondosa extract group. These results confirm that the use of albino G. frondosa extract reduces in significant way the presence of biofilm. Our results suggest and confirm that albino G. frondosa extracts could be employed as functional food and could be used as a natural additive for food process control and food safety.