Effect of relative humidity on drying characteristics of microwave assisted hot air drying and qualities of dried finger citron slices

The grading detection model for fingered citron slices (citrus medica 'fingered') based on YOLOv8-FCS

Introduction

Fingered citron slices possess significant nutritional value and economic advantages as herbal products that are experiencing increasing demand. The grading of fingered citron slices plays a crucial role in the marketing strategy to maximize profits. However, due to the limited adoption of standardization practices and the decentralized structure of producers and distributors, the grading process of fingered citron slices requires substantial manpower and lead to a reduction in profitability. In order to provide authoritative, rapid and accurate grading standards for the market of fingered citron slices, this paper proposes a grading detection model for fingered citron slices based on improved YOLOv8n.

Methods

Firstly, we obtained the raw materials of fingered citron slices from a dealer of Sichuan fingered citron origin in Shimian County, Ya'an City, Sichuan Province, China. Subsequently, high-resolution fingered citron slices images were taken using an experimental bench, and the dataset for grading detection of fingered citron slices was formed after manual screening and labelling. Based on this dataset, we chose YOLOv8n as the base model, and then replaced the YOLOv8n backbone structure with the Fasternet main module to improve the computational efficiency in the feature extraction process. Then we redesigned the PAN-FPN structure used in the original model with BiFPN structure to make full use of the high-resolution features to extend the sensory field of the model while balancing the computation amount and model volume, and finally we get the improved target detection algorithm YOLOv8-FCS.

Results

The findings from the experiments indicated that this approach surpassed the conventional RT-DETR, Faster R-CNN, SSD300 and YOLOv8n models in most evaluation indicators. The experimental results show that the grading accuracy of the YOLOv8-FCS model reaches 98.1%, and the model size is only 6.4 M, and the FPS is 130.3.

Discussion

The results suggest that our model offers both rapid and precise grading for fingered citron slices, holding significant practical value for promoting the advancement of automated grading systems tailored to fingered citron slices.

Dehydration study of apple slices by a non-thermal process

This study investigated the impacts of a drying process under low temperature and reduced pressure (non-thermal drying) on the final dehydrated products characteristics. This process is based on the retention of water on molecular sieves with a good selectivity against these molecules. In this study, drying experiments of 7mm thick apple slices (AS) were performed and compared to apple slices pretreated by freezing. It was concluded that the dehydrated apple slices were depleted of the maximum amount of water after 12 hours of drying, with a final water content equal to 12 ± 1.75%, whereas after freezing pretreatment, a decrease in drying time to 7 hours was observed, as well as a decrease in water content to 10 ± 0.5%. This explains the effect of freezing pretreatment on accelerating water transfer. In addition, a convective drying was performed on the apple slices at 60°C, which allows comparison with the slices dried by our non-thermal drying process. In order to characterize the obtained fruits, characteristic analyses such as water activity (Aw), color, texture (hardness), and dimensions (diameter and thickness) were performed before and after each drying experiment. Thus, continuous measurements of temperature, humidity, and pressure, within the enclosure, were determined during the experiments using a wireless sensor system controlled by a programming Arduino. Finally, mathematical modeling by various models (Newton, Page, Midilli, etc.) was performed to determine the most suitable model describing the non-thermal and convective drying of apple slices.

Heat source replacement strategy using catalytic infrared: A future for energy saving drying of fruits and vegetables

Drying is an important process for fruits and vegetables, which requires a lot of heat and the heat sources are mainly coal, electricity, natural gas, and solar energy. Most of the heat is usually wasted due to the long drying process and poor transfer efficiency. The use of coal also pollutes the environment. The national electricity curtailment policy regulates the drying industry. Therefore, the fruits and vegetables drying industry is facing new challenges due to its own development needs and external factors. Catalytic infrared drying (CIR) technology brings solutions to these problems. Compared with other drying technologies, CIR has a high drying efficiency and can effectively reduce the use of electric energy, avoid waste, and minimize pollution of water. However, improper processing conditions still cause quality deficits such as severe browning, and the drying is difficult due to weak infrared penetration. Although CIR has shortcomings, it is still expected to establish an energy-saving and efficient fruit and vegetable drying system.

Online Machine Vision-Based Modeling during Cantaloupe Microwave Drying Utilizing Extreme Learning Machine and Artificial Neural Network

Online microwave drying process monitoring has been challenging due to the incompatibility of metal components with microwaves. This paper developed a microwave drying system based on online machine vision, which realized real-time extraction and measurement of images, weight, and temperature. An image-processing algorithm was developed to capture material shrinkage characteristics in real time. Constant-temperature microwave drying experiments were conducted, and the artificial neural network (ANN) and extreme learning machine (ELM) were utilized to model and predict the moisture content of materials during the drying process based on the degree of material shrinkage. The results demonstrated that the system and algorithm operated effectively, and ELM provided superior predictive performance and learning efficiency compared to ANN.

Estimating the Moisture Ratio Model of Cantaloupe Slices by Maximum Likelihood Principle-Based Algorithms

As an agricultural plant, the cantaloupe contains rich nutrition and high moisture content. In this paper, the estimation problem of the moisture ratio model during a cantaloupe microwave drying process was considered. First of all, an image processing-based cantaloupe drying system was designed and the expression of the moisture ratio with regard to the shrinkage was built. Secondly, a maximum likelihood principle-based iterative evolution (MLP-IE) algorithm was put forward to estimate the moisture ratio model. After that, aiming at enhancing the model fitting ability of the MLP-IE algorithm, a maximum likelihood principle-based improved iterative evolution (MLP-I-IE) algorithm was proposed by designing the improved mutation strategy, the improved scaling factor, and the improved crossover rate. Finally, the MLP-IE algorithm and MLP-I-IE algorithm were applied for estimating the moisture ratio model of cantaloupe slices. The results showed that both the MLP-IE algorithm and MLP-I-IE algorithm were effective and that the MLP-I-IE algorithm performed better than the MLP-IE algorithm in model estimation and validation.

Predicting the Moisture Ratio of a Hami Melon Drying Process Using Image Processing Technology

For food drying, moisture content and shrinkage are vital in the drying process. This paper is concerned with the moisture ratio modeling and prediction issues of the Hami melon drying process. First, an experimental system was developed; it included an adjustable-power microwave drying unit and an image-processing unit. The moisture contents and the areas of Hami melon slices at different times were sampled in real time. Then, the expression of the moisture ratio with regard to shrinkage was derived by using the Weierstrass approximation theorem. A maximum likelihood fitness function-based population evolution (MLFF-PE) algorithm was then put forward to fit the moisture ratio model and predict the moisture ratio. The results showed that the proposed MLFF-PE algorithm was effective at fitting and predicting the moisture ratio model of the drying process of Hami melon slices.

Functional constituents of plant-based foods boost immunity against acute and chronic disorders

Plant-based foods are becoming an increasingly frequent topic of discussion, both scientific and social, due to the dissemination of information and exchange of experiences in the media. Plant-based diets are considered beneficial for human health due to the supply of many valuable nutrients, including health-promoting compounds. Replacing meat-based foods with plant-based products will provide many valuable compounds, including antioxidants, phenolic compounds, fibers, vitamins, minerals, and some ω3 fatty acids. Due to their high nutritional and functional composition, plant-based foods are beneficial in acute and chronic diseases. This article attempts to review the literature to present the most important data on nutrients of plant-based foods that can then help in the prevention of many diseases, such as different infections, such as coronavirus disease, pneumonia, common cold and flu, asthma, and bacterial diseases, such as bronchitis. A properly structured plant-based diet not only provides the necessary nutrients but also can help in the prevention of many diseases.

Research progress in fluid and semifluid microwave heating technology in food processing

Microwave is a form of electromagnetic radiation that has high penetration and heating efficiency in food processing. Uneven heating is the main problem of microwave processing, especially in solid foods. Fluid and semifluid media, which are good carriers in microwave processing, have uniform dielectric properties and good material fluidity. Herein, we review the development, application prospects, and limitations of microwave in fluid and semifluid food processing and the research progress in microwave heating with steam as carrier. The mixture of generated steam and tiny micro droplets from food material under the action of microwave can absorb microwave and transfer heat evenly, which effectively improves the uniformity of microwave heating. Due to the relatively uniform dielectric properties and consistent texture of fluid and semifluid food materials, uneven heating phenomenon during their microwave processing can be significantly inhibited. Based on the development of microwave heating technology and equipment design, the microbial inactivation and enzyme inhibition in fluid and semifluid food were improved and food product with better retention of nutrients and sensory profile were produced. Also, microwave radiation can be used to prepare the printing material or process the printed product for 3D food printing, which enhances the added value of 3D printed products and the personalization of food manufacturing. In future research, intelligent control technology can be applied in the microwave processing of fluid and semifluid food materials for various applications. Therefore, the processing conditions can be adjusted automatically.

Heat Pump Drying of Kelp (Laminaria japonica): Drying Kinetics and Thermodynamic Properties

The main objective of this research is the study of the drying kinetics and thermodynamic properties of kelp using heat pump drying technology. The effects of the independent variables of temperature (20–50 °C), air velocity (0.3–1.3 m/s), humidity (20–50%), and thickness (0.8–4.2 mm) on the drying time, moisture uniformity, effective moisture diffusivity (Deff), activation energy (Ea), enthalpy (ΔH), entropy (ΔS), and Gibbs free energy (ΔG) were investigated. The results show that the Page model was effective in describing the moisture content change of kelp during heat pump drying. The Deff varied from 1.00 × 10−11 to 13.00 × 10−11 m2/s and the temperature, air velocity, humidity, and thickness had significant effects on drying time and moisture uniformity. Higher temperature and air velocity with proper humidity shortened the drying time and lessened the influence of thickness on moisture uniformity. The Ea (16.38–26.66 kJ/mol) and ΔH (13.69–24.22 kJ/mol) were significantly increased by thickness. When the temperature was 40 °C, air velocity 1.3 m/s, and air humidity 40%, the moisture content was reduced to 18% in 5 h, with a homogeneous moisture content. This study clarifies the regularity of moisture change inside kelp and provides a theoretical reference for the development of macroalgae drying technology.