Special issue 'Advances in postharvest process systems' [Editorial]

The world population is predicted to increase from the present 7.7 billion to 9.7 billion in 2050, demanding a significant increase in food supply and production. However, around 25–30% of food is wasted worldwide every year due to poor postharvest supply chain design and management in different stages of the food supply chain, including postharvest handling, processing, and storage systems. This special issue presents state-of-the-art information on the important innovations and research in the agricultural and food industry. Different novel technologies and their implementation to optimize postharvest processes and reduce losses are reviewed and explored. In particular, it examines a range of recently developed and improved technologies and systems to help the industry and growers to manage and minimize postharvest losses, enhance reliability and sustainability in the postharvest food value chain, and generate high-quality products that are both healthy and appealing to consumers. This special issue consists of three sections, focusing on food storage and preservation technologies [1–4], food processing technologies [5–8], and the applications of advanced mathematical modeling and computer simulations [9–11]. We wish to acknowledge the expert contributions of all authors here. We also wish to acknowledge and thank MDPI staff for their professional assistance in editing the published articles. We sincerely hope that this special issue will assist all readers and stakeholders working in or are associated with the fields of agriculture, agri-food chain, and technology development and promotion. After all, efficient postharvest technology is an essential and key factor underlying future global food security, and ultimately human survival and development

Advances in postharvest process systems

This books presents a range of recent technologies and innovations to help the agricultural and food industry to manage and minimize postharvest losses, enhance reliability and sustainability, and generate high-quality products that are both healthy and appealing to consumers. It focuses on three main topics of food storage and preservation technologies, food processing technologies, and the applications of advanced mathematical modelling and computer simulations. This latest research and information is particularly useful for people who are working in or are associated with the fields of agriculture, agri-food chain and technology development and promotion

Laser-based imaging for cocoa pods maturity detection

Non-destructive and laser-based technologies have been explored widely in recent years as a way to monitor fresh produce and crops quality in the agriculture sector. In this study, the effectiveness of laser-induced backscattering imaging (LLBI) was investigated to determine the firmness and colour of cocoa pods at different maturity stages. The LLBI system with 1 mm laser diode beam diameter emitting at 658 nm and 705 nm wavelengths were used to capture backscattered images of Theobroma cacao at three different maturity stages, which were unripe, ripe and over-ripe. The samples were also measured using reference measurement such as colorimeter and handheld penetrometer for measuring colour and firmness, respectively, in order to compare with the LLBI. Results indicated that chroma (C) regressed linearly well with the backscattering parameters with a coefficient of determination (R2) of 0.755 for 658 nm and 0.800 for 705 nm. Classification of samples according to their maturity stages resulted in 90% correctly classified samples into an unripe group using a laser diode at 658 nm and 95% at 705 nm. These findings also revealed that LLBI with laser diode emitted light at 705 nm wavelength gave better evaluation and classification results compared with 658 nm. This study has demonstrated the ability of non-destructive LLBI technique to evaluate the maturity stages of cocoa pods

Electrohydrodynamic drying versus conventional drying methods: A comparison of key performance indicators

Preserving fruits and vegetables by drying is a traditional yet effective way of reducing food waste. Existing drying methods are either energy-intensive or lead to a significant reduction in product quality. Electrohydrodynamic (EHD) drying is an energy-efficient low-temperature drying method that presents an opportunity to comply with the current challenges of existing drying methods. However, despite its promising characteristics, EHD drying is yet to be accepted by industry and farmers. The adoption of EHD drying is hindered due to different reasons, such as uncertainties surrounding its scalability, quality of dried product, cost of operation, and sustainability compared to conventional drying methods. To address these concerns, this study quantifies and benchmarks the Key Performance Indicators (KPIs) of EHD drying compared to the standard conventional drying methods based on lab-scale experiments. These drying methods include hot-air, freeze, microwave, and solar drying. The results show that drying food using EHD is at least 1.6, 20, and 70 times more energy-efficient than the microwave, freeze, and hot-air, respectively. Similar results could be observed for exergy efficiency. EHD drying has superior product quality compared to other drying methods. For instance, it could retain 62% higher total phenolic content with 21% less color degradation than freeze-drying. Although microwave drying resulted in significantly higher drying kinetics than other techniques, EHD performed better than solar and freeze-drying but was comparable with hot-air drying. EHD drying also shows promising results in economic performance assessment. It is the cheapest drying method after solar drying and has the highest estimated net present value (NPV) after hot-air drying. Overall, compared to the currently used drying methods for small to medium-scale drying, EHD was found to be a more exergy and energy-efficient, cost-effective, and sustainable alternative that can provide higher-quality dried products. However, its drying kinetics should be improved for industrial applications

Mechanisation of large-scale agricultural fields in developing countries – a review

Mechanisation of large‐scale agricultural fields often requires the application of modern technologies such as mechanical power, automation, control and robotics. These technologies are generally associated with relatively well developed economies. The application of these technologies in some developing countries in Africa and Asia is limited by factors such as technology compatibility with the environment, availability of resources to facilitate the technology adoption, cost of technology purchase, government policies, adequacy of technology and appropriateness in addressing the needs of the population. As a result, many of the available resources have been used inadequately by farmers, who continue to rely mostly on conventional means of agricultural production, using traditional tools and equipment in most cases. This has led to low productivity and high cost of production among others. Therefore this paper attempts to evaluate the application of present day technology and its limitations to the advancement of large‐scale mechanisation in developing countries of Africa and Asia. Particular emphasis is given to a general understanding of the various levels of mechanisation, present day technology, its management and application to large‐scale agricultural fields. This review also focuses on/gives emphasis to future outlook that will enable a gradual, evolutionary and sustainable technological change. The study concludes that large‐scale‐agricultural farm mechanisation for sustainable food production in Africa and Asia must be anchored on a coherent strategy based on the actual needs and priorities of the large‐scale farmers

Recent Advances in Reducing Food Losses in the Supply Chain of Fresh Agricultural Produce

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, 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 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

The effectiveness of combined infrared and hot-air drying strategies for sweet potato

This study examined the performance of different combined infrared (IR) and hot-air drying (HAD) strategies for sweet potato. Experiments were conducted for simultaneous infrared and hot-air drying, two-stage sequential hot-air and infrared drying, two-stage sequential infrared and hot-air drying, and intermittent infrared and hot-air drying in a laboratory scale combined infrared and hot-air dryer. The drying air temperature varied between 50 and 70 °C, the infrared intensity was 1100 W/m2, the air-velocity was 1.5 m/s, and the pulse ratio (PR) ranged from 1 to 3. Results indicated that the drying rate, drying time, effective moisture diffusivity, shrinkage, specific energy consumption (SEC), colour attributes and phytochemical compounds of sweet potato were affected by the different drying combination strategies. The drying kinetics, product shrinkage, and sample temperature were also influenced by drying time and air temperature. The two-term exponential model adequately explained the drying behaviour of sweet potato for all the different combination strategies. The intermittent IR and HAD combination strategy proved to be the most suitable based on the combined effect of total drying time (113–120 min), SEC (27.67–41.44 kWh/kg), total colour change (17.15–26.48) and bioactive compounds

A Fully Coupled Multiphase Model for Infrared‐Convective Drying of Sweet Potato

Background Combined infrared and convective drying is a promising technology in dehydrating heat‐sensitive foods, such as fruits and vegetables. This novel thermal drying method, which involves the application of infrared (IR) energy and hot air during a drying process, can drastically enhance energy efficiency and improve overall product quality at the end of the process. Understanding the dynamics of what goes on inside the product during drying is important for further development, optimization and upscaling of the drying method. In this study, a multiphase porous media model considering liquid water, gases and solid matrix was developed for the combined infrared and hot‐air drying (CIR‐HAD) of sweet potato slices in order to capture the relevant physics and obtain an in‐depth insight on the drying process. The model was simulated using MATLAB with user‐friendly GUI interface for easy coupling and faster computational time. Results The gas pressure for CIR‐HAD was higher centrally and decreased gradually towards the surface of the product. This implies that drying force is stronger at the product core than at the product surface. Phase change from liquid water to vapour occurs almost immediately after the start of the drying process for CIR‐HAD. The evaporation rate as expected was observed to increase with increased drying time. Evaporation during the CIR‐HAD increased with increasing distance from the centerline of the sample surface. The simulation results of water and vapour flux revealed that moisture transport around the surfaces and sides of the sample is as a result of capillary diffusion, binary diffusion and gas pressure in both the vertical and horizontal directions. The nonuniform dominant infrared heating caused the heterogeneous distribution of product temperature. These results suggest that CIR‐HAD of food occur in a non‐uniform manner with high vapour and water concentration gradient between the product core and the surface. Conclusions This study provides better insight into the physics and phase changes of food during CIR‐HAD. The multiphase model has the advantage that phase change and impact of CIR‐HAD operating parameters can be swiftly quantified. Such modelling approach is thereby significant for further development and process optimization of CIR‐HAD towards industrial upscaling

Mechanization of agricultural production in developing countries

Agriculture is a main source of income, employment, and livelihood of a significant proportion of the populations of developing countries. Agricultural mechanization has now been in progress for several decades. However, it has been mainly confined to developed countries and a small number of developing countries. Some of the developing nations have had little or no progress in this area of agriculture production until recent times. Particularly, in sub-Saharan Africa, where 65% of agriculture is still carried out by manual labor, 25% by animal traction, and only 10% is mechanized (Esdaile, 2016). This is compared with the rapidly improved situation in countries like China,Sri Lanka, and Cambodia. Mechanization of agricultural production requires the applications of modern technologies. These technologies, however, are generally associated with relatively well-developed economies or largescale farms. The application of these technologies in many developing countries in Africa, Asia, and Latin America are limited by factors such as the technology’s compatibility with the environment, availability of resources to facilitate the technology’s adoption, cost of the technology, government policies, adequacy of the technology, and appropriateness in addressing the needs of the population. As a result, many of the available resources have been inadequately used by farmers. This has led to low productivity and high cost of production

Technological advances in postharvest management of food grains

Food grains such as cereals, legumes, and oilseeds are important food crops that contribute to most of the world’s staple food, especially in developing countries. However, up to ~   70% of food grains produced can be lost during postharvest management activities such as storage, transport, milling, drying, threshing, etc. The current challenge is to develop sustainable ways to reduce postharvest losses of food grains while increasing production. Several technological advancements have been made in recent years. In this chapter, the current state of the art of various advanced technologies used to reduce food grain losses during drying, milling, sorting, packaging, and storage is discussed. A future outlook to further develop these advances to drastically reduce the postharvest losses of food grains is also elucidated. Future research should be directed towards intensifying the use of smart sensors, IoT resources, and digital twins to enhance postharvest management practices. This book chapter provides valuable insight into sustainable technologies to improve postharvest management practices and reduce postharvest losses of food grains