AbstractBlueberries are susceptible to mechanical damage during the processes of transportation and storage. This article hopes to provide some theoretical basis for the improvement of blueberry packaging based on stack damage. The Finite Element Method was applied in this research. And to obtain an accurate friction factor between small spherical fruit, a new experimental platform was built. For the first time, it was found that the friction factor between blueberry surfaces was 0.4–0.6. Subsequently, the texture analyzer was employed to perform compression tests on unit cells composed of blueberries. Through the combination of slicing observation and finite element simulations, browning results of unit cells with different stack forms were gained. The stack method adopted the larger‐sized blueberries in the upper layer and the calyx of the upper blueberries was upward, which had the least damage to the blueberries, and the blueberries could be stacked up to 214 layers.Practical ApplicationUnderstanding the impact of different stacking methods on blueberry damage is crucial for avoiding serious damage to blueberries during storage and packaging. This article accurately determined the factor of friction between the surfaces of blueberries. Based on this, the influence of the calyx and size of blueberries on stacking damage was studied through a combination of stacking experiments and finite element method. This article not only solves the problem of the lack of friction factor between blueberries, providing an effective method for measuring the friction coefficient between small spherical fruits, but also provides directions for reducing stacking damage of blueberries and extending their post‐harvest life, as well as providing a theoretical basis for improving blueberry packaging and mechanization research.

AbstractThis study focuses on the relationship between local compression and local bruise volume of kiwifruits by means of finite element method (FEM). The effects of four indenter shapes and three compression directions on the local kiwifruit bruise were considered. The local bruise volume and the irregular cross section area of kiwifruit were calculated. Multi‐scale kiwifruit 3D modelling based on irregular cross‐sectional area computed by slice‐integration method. Local compression bruise was simulated by FEM. The results of the local bruise test show that the contact force and the bruise volume of kiwifruit are positive linear correlation. Comparing the simulation with the experimental, the mean absolute percentage error (MAPE) of the reconstructed model is 0.0394, and the R2 of contact force–bruise volume curve is 0.8203. The maximum equivalent forces and abrasions occur in the 0° and 90° loading directions with the square indenter has been showed by FEM results.Practical applicationsSe‐enriched kiwifruit has high nutrition and economic value. Kiwifruits are often influenced by a variety of factors and processes from harvest to consumption time. Cleaning, transport, and various processing operations including peeling and slicing in the kiwifruit industry are responsible for local bruise to kiwifruit. Therefore, understanding the mechanism of local bruise caused by local contact force of kiwifruit plays an important role in reducing kiwifruit waste in the postharvest stage. Local bruise mechanisms can be used in harvesting and post‐harvest mechanical design and product transportation and positioning equipment.

AbstractDetermining the ripening level of bananas in the environment of banana ripening plays an important role in ensuring the quality of bananas, reducing losses and waste, and improving economic benefits. Traditional monitoring methods face a series of challenges such as inefficiency, high energy consumption, and high cost. This paper aims to develop a flexible wireless in situ optical sensing system (FIS) for banana ripening monitoring with a good prediction effect, low energy consumption, and high economy. When monitoring the ripening process, the ripeness of the bananas can be accurately determined without taking out the bananas. Among them, the prediction effect on soluble solid content and a* is the best, the residual predictive deviation value is above 3, and the classification accuracy is as high as 95%. Compared to other commercially available spectrometers, the device exhibits the lowest power consumption characteristics. The theoretical maximum energy consumption of the FIS is only 627 mW, and a single measurement only consumes 15 J. The overall price of the FIS does not exceed $60. The application of the FIS can effectively reduce the waste of bananas during the ripening process, and greatly alleviate the labor‐intensive and inefficient problems of fruit maturity monitoring, thereby promoting more sustainable and cleaner production in the banana industry.

AbstractThe present study aims to conduct a comprehensive evaluation of the energetic and exergetic performance of a dehumidification system utilized in the processing of raw pistachios. The assessment involved the application of the first and second laws of thermodynamics to calculate the exergy aspects of each component of the system, including input and output exergy rates, output/input exergy efficiency, product/fuel exergy efficiency, exergy destruction rate, exergy loss rate, exergy improvement potential rate, and specific exergy consumption. Furthermore, the effect of variations in reference state temperature on the exergy parameters was also investigated. The results indicated that the pre‐dryer chamber had the highest input exergy rate among all the components of the dehumidification system. The product/fuel exergy efficiency is specified to be 35.10%, 9.47%, and 60.43%, for the electro‐fan, heater, and pre‐dryer chamber, respectively, while their output/input exergy efficiency are 87.87%, 22.10%, and 56.28%, respectively. The values of the exergy destruction rate of these components are 0.83, 147.14, and 1.12 kW whereas the exergy loss rate values are found to be 0.03, 4.12, and 9.24 kW, respectively. The improvement potential rate values of these components are obtained to be 0.10, 117.83, and 4.53 kW, while the amount of specific exergy consumption for the dehumidification system is determined as 481.85 kJ/kg. The study also reveals that the exergy parameters vary with changes in reference state temperature and that the exergy efficiencies decrease linearly as reference state temperature rises. Therefore, the findings of this investigation demonstrate the potential for using exergy analysis as an effective tool to improve the performance of dehumidification systems in industrial settings, specifically in the production of pistachios.Practical applicationsPistachio nut known as green gold because of its high economical value, is one of the popular nuts over the world. Dehumidification system based on drying technology could be used in food industry with many distinct advantages for processing of particulate crops like pistachios. For a comprehensive assessment of this system, analysis of the first and second laws of thermodynamics is applied. Exergy aspect based on the thermodynamic analysis the is an important stage for designing, modeling, optimizing, and performance assessment of the dehumidification system to produce processed pistachio. The results of this study show that the performance of dehumidification system could be improved by incorporating a steam compressor, a secondary heat exchanger, self‐heat recuperation technology, and a pinch method. It is believed that such a study would contribute to the industrial exploitation of pistachio which can provide insight into decreasing energy consumption and reducing capital costs for engineers and factory owners.

AbstractDrying plays a crucial role in preserving the quality of agricultural products. Nevertheless, suboptimal conditions in drying systems have an adverse effect on drying characteristics and energy efficiency. Machine learning approaches are innovative and reliable that have been successfully used to solve such challenges and achieve optimization in drying processes. In this study, five machine learning approaches (multilayer perceptron [MLP], gaussian processes [GP], support vector regression [SVR], k‐nearest neighbors [kN], and random forest [RF]) were used to estimate moisture content and moisture ratio of apricot in five various dryers (convective [CV], microwave [MW], infrared [IR], microwave‐convective [MW‐CV], and infrared‐convective [IR‐CV]). Also, the values of specific energy consumption (SEC) and effective moisture diffusivity (Deff) were calculated in these dryers. Accordingly, the best result of the Deff (3.14 × 10−10 m2/s) and the minimum value of the drying time (130 min) and SEC (18.67 MJ/kg) were obtained using MW‐CV hybrid dryer. While the lowest values of Deff (2.09 × 10−11 m2/s) and highest drying time (18.5 h) and SEC (209.34 MJ/kg) were detected in CV dryer at 50°C. The best correlation coefficients (R) for the estimation of moisture content were gained using RF technique for k‐fold cross validation and train‐test split with the values of 0.9908 and 0.9912, respectively. Moreover, moisture ratio results showed that the MLP achieved the highest R value over 0.9985 for both validation methodologies. In the discrimination of the drying methods, the MLP had the greatest accuracy as 82.00% and 86.00% for k‐fold cross validation and train‐test split, respectively. The results showed that the RF and ML models could potentially be used for estimation and discrimination for drying applications.Practical ApplicationsRecently, there has been an increased interest in healthy food choices such as foodstuffs, snacks, and dried products. This trend has captured the attention of both dietitians and conscious consumers. Apricots are a prime example of a valuable dried product that can be dry in various conditions. Machine learning techniques can be used for rapid and non‐destructive determination of drying characteristics and such techniques yield objective and accurate results. Present findings revealed that texture machine learning models could be used as an effective and reliable discrimination tool for dried products.

AbstractGiven the rising demand for cold brew coffee, innovative approaches are required to address the present difficulties in its production. This motivates the consideration of the planetary rotating bed reactor (PRBR) as a solid–liquid extraction technology. The PRBR consists of cylindrical mesh chambers that contain the solid phase and move in two superimposed rotations. This motion pattern enhances mass transfer through alternating radial forces: the pushback effect (PBE). To evaluate the utility of the PRBR and the role of PBE, we investigated the kinetics and energy demand of cold brew coffee extraction. For this purpose, we varied rotational speeds and PBE conditions in a 1 L lab‐scale reactor. Kinetics was determined by in‐line monitoring of electrical conductivity correlated with the eluate's weight‐based total dissolved solids and caffeine by high‐performance liquid chromatography. Energy consumption was derived from strain gauge torque measurements. Our findings reveal that saturation of the extraction rate with respect to the rotational speed is evident both with and without PBE. However, PBE significantly reduces extraction time by 75% while requiring 60% less mechanical energy. The fastest conditions probed 95% of the maximum extraction yield within 12 s, effectively being >99% faster than static immersion. We believe these findings, along with further procedural advantages, qualify the PRBR as a viable technology for cold brew coffee production.Practical ApplicationsThe relevance of an economical and sustainable preparation of cold brew coffee extends from the industrial to the gastronomic to the domestic environment. Challenges and limitations relate to process time, particle separation, product and extraction yield, and taste problems due to over‐extraction. The planetary rotating bed reactor (PRBR) promises to address all these issues by combining extraction and separation in a simultaneous and ultrafast process. The present study confirms the superiority of PRBR's action mechanisms in terms of rapidity and energetic efficiency for extraction. Due to the excellent scalability of both the design and the physical effect, the PRBR is intended for large‐scale production of ready‐to‐drink products and local production in coffee shops or private households. By modifying the particle feed, even continuous operation is conceivable. Further applications are, for example, dry‐hopping of beer, fast‐aging of spirits, and preparation of various liquid foods.

AbstractThe post‐harvesting procedures, such as grading, washing, transporting, and packaging can be made better with understanding of the attributes of agricultural commodities. The paper aims to estimate the asparagus roots' thermal, physical, and biochemical characteristics. The asparagus was found to vary in the range of 6.26–13.60 cm long. The width and thickness of the root were almost the same and ranged from .69 to 1.10 cm. The bulk density, true density, and porosity ranged from .561 to .771 g/cm3, 1.418 to 2.124 g cm3, and 60.437 to 63.689%, respectively. The water activity of the roots was observed to be in the range of .797–.828. The color characteristics of asparagus roots were found to be L* = 45.46, a* = 6.94, and b* = 23.23. The obtained values of the following thermal variables were: thermal diffusivity = 8.176 × 10−8 m2/s, thermal conductivity = .493 W/m °C, specific heat = 3.424 kJ/kg °C, and latent heat = 23442.74 J/kg. The total phenolic and tannin content in the roots were observed to be 24.41 ± .09 mg of gallic acid equivalent (GAE)/g and 1.73 ± .06 mg of tannic acid equivalent (TAE)/g, respectively. The flavonoid content in the roots was 10.33 ± .04 mg of quercetin equivalent (QE)/g. The root samples were found to be a high capacity to scavenge free radicals and also contain phytochemical components that may prove valuable in future research to combat oxidative stress. The findings of this study will also be advantageous in developing handling and processing equipment for the industrial production of asparagus root products.Practical applicationsAsparagus is a medicinal plant which is now widely used in food processing to produce the fortified‐functional food products because of its high nutritional and medicinal properties. The grading, sorting, conveying, pulping, processing, and handling equipment for various horticultural goods, including asparagus, are designed using machine designing parameters, which are vital and essential parameters. The size and shape of all agricultural commodities varies. The slight modifications to size and form could reduce the effectiveness of numerous procedures and their associated machinery. Therefore, the knowledge about these engineering and biochemical properties of asparagus will inspire researchers to create and upgrade machinery used for grading, sorting, conveying, pulping, and processing.

AbstractRed bell peppers (Capsicum annuum L.) are low in calories and high in nutrients, including vitamins A and C. Various factors such as weight loss, senescence, and microbial influence affect their quality during storage. To address this, the present study aims to preserve and retain the quality of red bell peppers using ultrasound‐assisted thin‐bed drying. The results were analyzed using an Artificial Neural Network (ANN) for more accurate prediction of variables involved in the process. Variations in moisture ratio and moisture content during drying were calculated and predicted. The Midilli model provided satisfactory curve fitting at an air velocity of 1.5 m/s, with R2 = 0.9993, χ2 = 0.0002, and RMSE = 0.0134. The two‐term and modified page models fit better with drying curves at air velocities of 2 and 2.5 m/s, with R2 = 0.9995, χ2 = 0.002, RMSE = 0.0016 and R2 = 0.9996, χ2 = 0.00003, RMSE = 0.00003, respectively. However, the trained standard backpropagation ANN algorithm demonstrated excellent predictive ability, outperforming the mathematical models with R2 = 0.9989 (training), MSE = 0.0001 (training), and R2 = 0.9996 (testing), MSE = 0.0002 (testing). Most importantly, the ultrasound‐assisted drying process retains the essential nutrients in red bell peppers, including vitamin C, carotenoids, polyphenols, and flavonoids, across various conditions. The antioxidant potential, as measured by DPPH and FRAP assays, remains largely unchanged compared to untreated samples. However, ABTS activity shows a significant difference at an air velocity of 1.5 m/s and temperatures of 60 and 70°C compared to the control sample.Practical applicationsIn terms of vitamins and antioxidants, red bell peppers are a great provider. Interestingly, capsaicin, the substance responsible for spiciness, is found in very little to no quantity in red bell peppers making it appealable to consumers. To achieve a certain level of processing, the quality of the dried product needs to be monitored while fulfilling the needs of consumers. Particularly, the quality‐determining parameters were vitamin C, total carotenoids, total polyphenols, total flavonoid content, DPPH, ABTS, and FRAP activity. These qualities were retained after drying with the potential novel combination of ultrasound with thin bed drying at low temperatures and air velocity. This means that the bioactive compounds responsible for improving the health of humans are readily available in dried form all year round. The drying kinetics were modeled, predicted, and compared with mathematical and ANN models.

AbstractIn many coffee‐producing countries, the ellipsoidal‐shaped seeds called peaberries are often labeled as a defect because of their shape and reduced size, going against the market demand for large‐sized standard coffee beans. Nevertheless, the peaberry natural occurrence on the coffee plantations is significant, accounting for 5%–7% of the total harvested coffee for Coffea arabica L. and Coffea canephora, the most planted species worldwide. Nevertheless, recent growth in the peaberry market has happened due to exceptional cupping scores for this specific bean type; however, the relationship between these scores and the shape of the bean was not yet recorded in the literature. Therefore, this research aimed to evaluate and compare the impact of the shape and size of the peaberry against the standard beans in different postharvest processes: Drying, roasting (colorimetry and inner roasting profiles), grinding (compressive and shear force tests) and overall quality by cupping analysis. Coffea arabica L. var. Cenicafé 1 was used throughout all the experiments, where advanced methods were used to increase the accuracy of the results and deeply characterize the process behavior. The results of this research allow to understand the peaberry postharvest behavior better and add significant value to this often‐underrated bean condition. The peaberries demonstrated shape influence in the different evaluated parameters, allowing them to dry faster, roast evenly, avoid burnt spots, and collapse at homogeneous forces while attaining the same high cup scores as a standard coffee bean.Practical applicationsUnderstanding the peaberries' shape and size influence different postharvest processes is crucial to comprehend their value. By gaining insights, into how these unique beans interact with stages of processing, producers can control and predict their behavior leading to more consistent and optimized results. The findings of this research provide an opportunity to fully incorporate peaberries into the coffee product without considering them as defective beans or expanding market trends. Generally, peaberries were often seen as undesirable because they did not match the bean size and shape. However, their exceptional performance in drying, roasting, grinding and cupping dispels these misconceptions, highlighting their value and contribution to coffee quality. As a result, coffee producers can embrace peaberries as valuable beans without discarding or downgrading them. This newfound appreciation for peaberries does not only reduce waste, but it also diversifies coffee offerings to meet consumer preferences and enriches the industry.

AbstractSoft wheat grains were treated with superheated steam (SS) at 165 and 190°C, respectively for 1–5 min to understand the changes in the structures and properties of wheat starch following SS treatment. The damaged starch contents, amylose ratio, gelatinization properties, surface morphology, viscosity, and crystalline structure of the starch in wheat flour were determined. Damaged starch content, amylose ratio, and starch viscosity significantly increased after SS treatment. The onset temperature (To) and peak temperature (Tp) of wheat starch increased with the extending of treatment time, while an opposite variation trend was observed for (Tc − To). Additionally, the gelatinization enthalpy (ΔH) decreased after 3–5 min of SS treatment. Starch aggregation was observed in scanning electron microscopy (SEM) graphs. Compared to traditional heat treatment methods, SS treatment of wheat grains may be preferable for modifying the starch properties of soft wheat since much time and energy could be saved.Practical ApplicationThe physicochemical properties and structure of soft wheat starch significantly affect the quality of cakes made with soft wheat flour. After SS treatment of wheat kernels, the amylose ratio and damaged starch content in wheat starch significantly increased. Moreover, gelatinization properties and starch viscosity of wheat starch were also significantly affected. The changes in physicochemical properties were mainly due to the changes in the structure of starch granules and starch molecules. The above results in the physicochemical properties and structure of starch led to the increase in the viscosity and gas retention capacity of cake batter, which might be the reason why the specific volumes and texture of cakes could be improved after SS treatment of wheat. This research verified SS treatment may be preferable for improving cake quality compared to traditional heat treatment methods, which promotes the application of SS in wheat process engineering.