Special Issue "Advances in Postharvest Process Systems"

A special issue of Processes (ISSN 2227-9717). This special issue belongs to the section "Food Processes".

Deadline for manuscript submissions: 16 May 2021.

Special Issue Editors

Dr. Daniel I. Onwude
Website
Guest Editor
Empa-Swiss Federal Laboratories of Material Science and Technology, Überland Str. 129, 8600 Dübendorf, Switzerland
Interests: postharvest engineering; agricultural and food process engineering; drying technology; modeling and simulation; nondestructive testing and computational engineering
Dr. Guangnan Chen
Website
Guest Editor
Faculty of Health, Engineering and Sciences, University of Southern Queensland, Toowoomba, QLD 4350, Australia
Interests: renewable energy and bio-energy; life-cycle assessment; sustainable agriculture and farming systems; crop postharvest and drying systems

Special Issue Information

Dear Colleagues,

It has been widely recognized that one of the biggest challenges in the agricultural production value chain is the issue of postharvest handling and processing of agricultural products. It is estimated that 25-30% of global food produced is lost during the postharvest value chain, mainly due to fallible chain management (especially during sorting, bulk storage, packaging, and transportation), spoilage, and pest infestation. Several systems and processes have been developed to reduce the postharvest losses of agricultural products during postharvest cooling, transport, and storage operations. For example, the use of "cold " handling and storage systems to prevent perishable food losses; the thermal and non-thermal processing of harvested agricultural products to reduce spoilage and enhance shelf-life; and the drying of agricultural products to also reduce spoilage, increase shelf-life, and reduce the bulk weight of products during transportation. Nevertheless, most of the systems developed are yet to be fully commercialized. This is a result of an inadequate understanding of the complex nature of different agricultural products, understanding of the physics behind different phenomena that occur during different postharvest processes (e.g drying, cooling...etc), and the upscaling of developed process systems. For instance, a lot of strongly coupled phenomena take place during cooling and dehydration of agricultural products, including (1) heat and mass transport inside the material, (2) their exchange with the airflow in the environment, (3) microstructural damages, (4) shrinkage,  and (5) reduction of nutritional density. These coupled physiochemical processes make it challenging to understand and optimize the relation between process parameters and final product properties and structure. Therefore, the successful design of a cooling, packaging, storage, transport and drying processes of fresh food requires linking materials science, fluid dynamics, mechanical deformation, food chemistry, and process control.

This Special Issue on “ Advances in Postharvest Process Systems” focusses on the latest research and development in this area. We target specifically the development and application of novel and sustainable postharvest process technologies as well as how modeling can help advance innovative processes or technologies by providing insight for process optimization. Contributions to cover materials such as meats, fruits and vegetables, grains, foods, and fibres are most welcome. In addition, review papers providing critical overviews of state-of-the-art developments on postharvest engineering research are welcomed. Topics include, but are not limited to:

  • Advances in drying technologies and modeling thereof (multiscale, multiphysics, multiphase);
  • Advances in food system and postharvest value chain management and modeling thereof (multiscale, multiphysics, multiphase);
  • Advances in packaging technologies
  • Emerging cold chain processing technologies and modeling thereof
  • Emerging storage technologies and modeling thereof
  • Emerging transport technologies and modeling thereof
  • New approaches on improving models and model accuracy (e.g. coupling of quality models, advanced material property models)
  • Model validation at different scales (e.g micro scales, macro scales), using advanced monitoring methods
  • Product separation
  • Intelligent process control using computational engineering
  • Scale-up studies from laboratory to process plant level (simulation and experimental driven)
  • Application of digital twins in cold-chain, storage, and drying systems
  • Environmental impact assessment.

We aim to have a rapid review process to provide a channel for the timely dissemination of fresh, and impactful manuscripts. Apart from providing research on recent trends in postharvest engineering, this research series is envisioned to catalyzed simulation research on different unit operations in the postharvest value chain to better understand process modeling and optimization towards a sustainable system

Dr. Daniel I. Onwude
Assoc. Prof. Guangnan Chen
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Processes is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2000 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • Postharvest engineering
  • Computational engineering
  • Fruits and vegetables
  • Food
  • Agricultural materials
  • Food security
  • Mechanistic modeling
  • Multiphase and multiphysics modeling
  • CFD and FEM
  • Packaging technology

Published Papers (8 papers)

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Research

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Open AccessFeature PaperArticle
Impact of Process Parameters and Bulk Properties on Quality of Dried Hops
Processes 2020, 8(11), 1507; https://doi.org/10.3390/pr8111507 - 20 Nov 2020
Abstract
Hops are critical to the brewing industry. In commercial hop drying, a large bulk of hops is dried in multistage kilns for several hours. This affects the drying behavior and alters the amount and chemical composition of the hop oils. To understand these [...] Read more.
Hops are critical to the brewing industry. In commercial hop drying, a large bulk of hops is dried in multistage kilns for several hours. This affects the drying behavior and alters the amount and chemical composition of the hop oils. To understand these changes, hops of the var. Hallertauer Tradition were dried in bulks of 15, 25 and 35 kg/m² at 60 °C and 0.35 m/s. Additionally, bulks of 25 kg/m² were also dried at 65 °C and 0.45 m/s to assess the effect of change in temperature and velocity, respectively. The results obtained show that bulk weights significantly influence the drying behavior. Classification based on the cone size reveals 45.4% medium cones, 41.2% small cones and 8.6% large cones. The highest ΔE value of 6.3 and specific energy consumption (113,476 kJ/kgH2O) were observed for the 15 kg/m² bulk. Increasing the temperature from 60 °C to 65 °C increased the oil yield losses by about 7% and myrcene losses by 22%. The results obtained show that it is important to define and consider optimum bulk and process parameters, to optimize the hop drying process to improve the process efficiency as well the product quality. Full article
(This article belongs to the Special Issue Advances in Postharvest Process Systems)
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Open AccessArticle
Some Physical Properties and Mass Modelling of Pepper Berries (Piper nigrum L.), Variety Kuching, at Different Maturity Levels
Processes 2020, 8(10), 1314; https://doi.org/10.3390/pr8101314 - 19 Oct 2020
Abstract
Pepper berry (Piper nigrum L.) is known as the king of spices and has sharp, pungent flavour and aroma. In this study, the physical properties (weight, dimensions, sphericity, volume, surface area, and projected area) were measured, and the mass of pepper berries [...] Read more.
Pepper berry (Piper nigrum L.) is known as the king of spices and has sharp, pungent flavour and aroma. In this study, the physical properties (weight, dimensions, sphericity, volume, surface area, and projected area) were measured, and the mass of pepper berries of the Kuching variety at different maturity levels (immature, mature, and ripe) was predicted using four models: linear, quadratic, s-curve, and power. When the models were based on volume and projected area, the mass could be predicted with maximum precision. The Quadratic model was best fitted for mass prediction at all mass maturity levels (immature, mature, and ripe). The results showed that mass modelling based on the actual volume of pepper berries was more applicable compared to other properties with the highest determination coefficient, 0.995, at the 1% probability level. From an economical point of view, mass prediction based on actual volume in the Quadratic form, M= 0.828 − 0.015 V + 7.376 ×105V2, is recommended. The findings of physical properties and mass modelling of the berries would be useful to the scientific knowledge base, which may help in developing grading, handling, and packaging systems. Full article
(This article belongs to the Special Issue Advances in Postharvest Process Systems)
Open AccessFeature PaperArticle
Classification, Force Deformation Characteristics and Cooking Kinetics of Common Beans
Processes 2020, 8(10), 1227; https://doi.org/10.3390/pr8101227 - 01 Oct 2020
Abstract
Post-harvest characteristics of common beans influences its classification, which significantly affects processing time and energy requirements. In this work, ten bean cultivars were classified as either easy-to-cook (ETC) or hard-to-cook (HTC) based on a traditional subjective finger pressing test and a scientific objective [...] Read more.
Post-harvest characteristics of common beans influences its classification, which significantly affects processing time and energy requirements. In this work, ten bean cultivars were classified as either easy-to-cook (ETC) or hard-to-cook (HTC) based on a traditional subjective finger pressing test and a scientific objective hardness test. The hardness study used seed coat rigidity to explain the structural deformation observed during cooking. The result shows that the average hardness of raw dry ETC and HTC beans was 102.4 and 170.8 N, respectively. The maximum seed coat resistance is observed within the first 30 min of cooking regardless of the classification. The results show that a modified three-parameter non-linear regression model could accurately predict the rate of bean softening (R2 = 0.994–0.999 and RMSE = 3.3–14.7%). The influence of bean softeners such as potassium carbonate (K2CO3) and sodium chloride (NaCl) to reduce cooking time was also investigated. The results showed that the addition of K2CO3 to the cooking water significantly reduced the cooking time by up to 50% for ETC and 57% for HTC. Full article
(This article belongs to the Special Issue Advances in Postharvest Process Systems)
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Open AccessArticle
Evaluation of Postharvest Processing of Hazelnut Kernel Oil Extraction Using Uniaxial Pressure and Organic Solvent
Processes 2020, 8(8), 957; https://doi.org/10.3390/pr8080957 - 08 Aug 2020
Abstract
Uniaxial loading and organic solvent are small-scale oil expression methods used to evaluate the mechanical behavior, oil content, and oil efficiency of oil-bearing materials aimed at designing a low-cost mechanical pressing system. Bulk kernels of pressing height 40 mm were heated from 40 [...] Read more.
Uniaxial loading and organic solvent are small-scale oil expression methods used to evaluate the mechanical behavior, oil content, and oil efficiency of oil-bearing materials aimed at designing a low-cost mechanical pressing system. Bulk kernels of pressing height 40 mm were heated from 40 to 60 °C and compressed at maximum force of 60 kN and speeds from 4 to 8 mm/min. Relaxation times between 3 and 12 min were applied to assess the kernel oil efficiency. The kernel oil point was identified at deformation levels between 15 and 25 mm at a speed of 4 mm/min using a litmus test. The kernel oil was analyzed for peroxide value and free fatty acid. Kernel oil content was determined by Soxhlet extraction. Increased speed caused a serration effect on the force–deformation curve leading to lower oil yield. Lower and upper oil point forces at 6.21 ± 0.58 and 10.61 ± 0.71 kN were observed to be useful for predicting the pressure for maximum output oil. The peroxide value and free fatty acid content of kernel oil decreased with increasing temperature, indicating its quality usage. The relaxation time of 12 min after compression increased kernel oil efficiency of 15.6%. In designing new presses, there is a need to consider compression and relaxation processes to reduce the residual kernel cake oil. Full article
(This article belongs to the Special Issue Advances in Postharvest Process Systems)
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Open AccessArticle
Physico-Chemical Changes, Microbiological Properties, and Storage Shelf Life of Cow and Goat Milk from Industrial High-Pressure Processing
Processes 2020, 8(6), 697; https://doi.org/10.3390/pr8060697 - 16 Jun 2020
Cited by 2
Abstract
Industrial high-pressure processing (HPP) was conducted on cow and goat milk in comparison to conventional heat pasteurization. No significant changes were found in the physico-chemical properties of the treated milk except for pH, where pasteurized cow milk experienced a decrease while goat milk’s [...] Read more.
Industrial high-pressure processing (HPP) was conducted on cow and goat milk in comparison to conventional heat pasteurization. No significant changes were found in the physico-chemical properties of the treated milk except for pH, where pasteurized cow milk experienced a decrease while goat milk’s pH increased for both pasteurized and HPP treated. HPP-treated cow and goat milk both achieved microbial shelf life of 22 days at 8 °C storage with no increase in Bacillus cereus, mesophilic aerobic spores, coliform, yeast and mold but slight increase in psychrotrophic bacteria and total plate count. Pasteurized goat milk was spoilt at the end of storage with exceeding count of psychrotrophic bacteria (9.0 × 108 CFU/mL) and total plate count (3.5 × 108 CFU/mL). HPP-treated cow milk exhibited higher physico-chemical stability than goat milk as evidenced by non-significant change of titratable acidity but goat milk experienced an increase of 0.04% averagely. Full article
(This article belongs to the Special Issue Advances in Postharvest Process Systems)
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Open AccessArticle
Application of Computational Intelligence in Describing the Drying Kinetics of Persimmon Fruit (Diospyros kaki) During Vacuum and Hot Air Drying Process
Processes 2020, 8(5), 544; https://doi.org/10.3390/pr8050544 - 07 May 2020
Cited by 4
Abstract
This study examines the potential of applying computational intelligence modelling to describe the drying kinetics of persimmon fruit slices during vacuum drying (VD) and hot-air-drying (HAD) under different drying temperatures of 50 °C, 60 °C and 70 °C and samples thicknesses of 5 [...] Read more.
This study examines the potential of applying computational intelligence modelling to describe the drying kinetics of persimmon fruit slices during vacuum drying (VD) and hot-air-drying (HAD) under different drying temperatures of 50 °C, 60 °C and 70 °C and samples thicknesses of 5 mm and 8 mm. Kinetic models were developed using selected thin layer models and computational intelligence methods including multi-layer feed-forward artificial neural network (ANN), support vector machine (SVM) and k-nearest neighbors (kNN). The statistical indicators of the coefficient of determination (R2) and root mean square error (RMSE) were used to evaluate the suitability of the models. The effective moisture diffusivity and activation energy varied between 1.417 × 10−9 m2/s and 1.925 × 10−8 m2/s and 34.1560 kJ/mol to 64.2895 kJ/mol, respectively. The thin-layer models illustrated that page and logarithmic model can adequately describe the drying kinetics of persimmon sliced samples with R2 values (>0.9900) and lowest RMSE (<0.0200). The ANN, SVM and kNN models showed R2 and RMSE values of 0.9994, 1.0000, 0.9327, 0.0124, 0.0004 and 0.1271, respectively. The validation results indicated good agreement between the predicted values obtained from the computational intelligence methods and the experimental moisture ratio data. Based on the study results, computational intelligence methods can reliably be used to describe the drying kinetics of persimmon fruit. Full article
(This article belongs to the Special Issue Advances in Postharvest Process Systems)
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Review

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Open AccessReview
A Review on Individual and Combination Technologies of UV-C Radiation and Ultrasound in Postharvest Handling of Fruits and Vegetables
Processes 2020, 8(11), 1433; https://doi.org/10.3390/pr8111433 - 10 Nov 2020
Abstract
Ultraviolet-C radiation and ultrasound technology are widely accepted and continuously being appraised as alternatives to conventional thermal techniques for decontamination of fruits and vegetables. However, studies in these areas have presented challenges related to quality, safety, limited capability, and cost of energy. This [...] Read more.
Ultraviolet-C radiation and ultrasound technology are widely accepted and continuously being appraised as alternatives to conventional thermal techniques for decontamination of fruits and vegetables. However, studies in these areas have presented challenges related to quality, safety, limited capability, and cost of energy. This review paper presents an up-to-date summary of applications of ultraviolet-C radiation and ultrasound technology for postharvest handling of fruits and vegetables from relevant literature. The limitations associated with applications of ultraviolet-C radiation and ultrasound technology individually has prompted their combination alongside other antimicrobial strategies for enhanced bactericidal effect. The combination of ultraviolet-C radiation and ultrasound technology as a hurdle approach also provides enhanced efficiency, cost effectiveness, and reduced processing time without compromising quality. The review includes further scope of industrial-led collaboration and commercialization of ultraviolet-C radiation and ultrasound technology such as scale-up studies and process optimization. Full article
(This article belongs to the Special Issue Advances in Postharvest Process Systems)
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Open AccessReview
Recent Advances in Reducing Food Losses in the Supply Chain of Fresh Agricultural Produce
Processes 2020, 8(11), 1431; https://doi.org/10.3390/pr8111431 - 09 Nov 2020
Abstract
Fruits and vegetables are highly nutritious agricultural produce with tremendous human health benefits. They are also highly perishable and as such are easily susceptible to spoilage, leading to a reduction in quality attributes and induced food loss. Cold chain technologies have over the [...] Read more.
Fruits and vegetables are highly nutritious agricultural produce with tremendous human health benefits. They are also highly perishable and as such are easily susceptible to spoilage, leading to a reduction in quality attributes and induced food loss. Cold chain technologies have over the years been employed to reduce the quality loss of fruits and vegetables from farm to fork. However, a high amount of losses (≈50%) still occur during the packaging, pre-cooling, transportation, and storage of these fresh agricultural produce. This study highlights the current state-of-the-art of various advanced tools employed to reducing the quality loss of fruits and vegetables during the packaging, storage, and transportation cold chain operations, including the application of imaging technology, spectroscopy, multi-sensors, electronic nose, radio frequency identification, printed sensors, acoustic impulse response, and mathematical models. It is shown that computer vision, hyperspectral imaging, multispectral imaging, spectroscopy, X-ray imaging, and mathematical models are well established in monitoring and optimizing process parameters that affect food quality attributes during cold chain operations. We also identified the Internet of Things (IoT) and virtual representation models of a particular fresh produce (digital twins) as emerging technologies that can help monitor and control the uncharted quality evolution during its postharvest life. These advances can help diagnose and take measures against potential problems affecting the quality of fresh produce in the supply chains. Plausible future pathways to further develop these emerging technologies and help in the significant reduction of food losses in the supply chain of fresh produce are discussed. Future research should be directed towards integrating IoT and digital twins for multiple shipments in order to intensify real-time monitoring of the cold chain environmental conditions, and the eventual optimization of the postharvest supply chains. This study gives promising insight towards the use of advanced technologies in reducing losses in the postharvest supply chain of fruits and vegetables. Full article
(This article belongs to the Special Issue Advances in Postharvest Process Systems)
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