Biomimetics of fish scales: value and prospects

The body of an ideal fish is covered by scales which are either thin or thick. These scales arise as external growths from the epidermis of the skin. Fish scales are known to contain pigmentation that gives colour to the scales for example, the Minytrema melanops is greyish brown in colour because of the grey colour from the scales while its close relative the small mouth buffalo Ictiobus bubalus is Olive-bronze in colour. Fish scales in general contain a variety of pigments that give the fish a variety of colors. Fish scales constitute about 2% of the total body weight, but said to be rich in nutritive components just as the flesh of the fish. The scale of fish is similar to the structure of a typical bone. Fish scales comprise of 40% -55%collagen type 1, hydroxyapatite and calcium carbonate fat, lecithin and scleroprotein. The mechanical testing of fish scales was reported to show that the unique design of the strength of scales is significant for mechanical characteristics. Again, the mechanical strength and toughness displayed by fish scale composition (external ganoine layer and internal layer) with enforced mineral properties enable the protective nature of the scales. Fish skin can be used like any other leather for various wear-resistant items such as shoes bags and purses. With the use of various tanning processes and chemicals, fish skin is successfully used for shoes and clothing

Evaluation of a suitable thin layer model for drying of pumpkin under forced air convection

The thin layer drying kinetics of pumpkin slices (Cucurbita moschata) were experimentally investigated in a convective hot air dryer. In order to select the appropriate model for predicting the drying kinetics of pumpkin (Cucurbita moschata), twelve thin layer semi theoretical, theoretical and empirical models, widely used in describing the drying behaviour of agricultural products were fitted to the experimental data. The Page and Two term exponential models showed the best fit under certain drying conditions. The Hii et al. (2009) model, which was adopted from a combination of the Page and Two term models was compared to the other 11 selected thin layer models based on the coefficient of determination (R2) and sum of squares error (SSE). Comparison was made between the experimental and model predicted moisture ratio by non-linear regression analysis. Furthermore, the effect of drying temperature and slice thickness on the best model constants was evaluated. Consequently, the Hii et al. (2009) model showed an excellent fit with the experimental data (R2 > 0.99 and SSE < 0.012) for the drying temperatures of 50, 60, 70 and 80 °C and at different sample thicknesses of 3 mm, 5 mm and 7 mm respectively. Thus, the Hii et al. (2009) model can adequately predict the drying kinetics of pumpkin

Development and preliminary testing of a bambara groundnut sheller

A centrifugal bambara groundnut pod shelling machine was designed and constructed to crack various sizes and varieties of bambara groundnut. The sheller was fabricated with locally available materials from the formation of a new idea which aimed at easing the pain, stress, intensive labour, time consumption, undue cost and the cumbersome operation encountered in the traditional method of shelling. The machine consists of three main units, namely the hopper, shelling unit and power transmission unit. The sheller uses impact technique and was designed to shell bambara groundnuts effectively and also to eliminate drudgery associated with the traditional methods of shelling legumes. Five hundred (500) samples of sundried bambara groundnuts at 6% (wet basis) which were randomly selected were shelled at an impeller rotation speed of 1636 rpm. The results of the test showed that the shelling efficiency, seed damage, partially shelled pods, unshelled pods and the machine capacity were 83.2%, 17.4%, 7.8%, 9% and 75000 seeds/hr respectively

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

Modelling the convective drying process of pumpkin (Cucurbita moschata) using an artificial neural network

This study investigated the drying kinetic of pumpkin under different drying temperatures (50, 60, 70 and 80°C), samples thickness (3, 4, 5 and 7mm), air velocity (1.2m/s) and relative humidity (40 - 50%). Kinetic models were developed using semi-theoretical thin layer models and multi-layer feed-forward artificial neural network (ANN) method. The Hii et al. (2009) semi-theoretical model was found to be the most suitable thin layer model while two hidden layers with 20 neurons was the best for the ANN method. The selections were based on the statistical indicators of coefficient of determination (R2), root mean square error (RMSE) and sum of squares error (SSE). Results indicated that the ANN demonstrated better prediction than those of the theoretical models with R2, RMSE and SSE values of 0.992, 0.036 and 0.207 as compared to the Hii et al. (2009) model values of 0.902, 0.088 and 1.734 respectively. The validation result also showed good agreement between the predicted values obtained from the ANN model and the experimental moisture ratio data. This indicates that an ANN can effectively describe the drying process of pumpkin

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

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

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

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

Recent advances of novel thermal combined hot air drying of agricultural crops

Background: Developing an efficient drying system with combined novel thermal and conventional hot-air drying of agricultural crops has become potentially a viable substitute for conventional drying techniques. Due to the synergistic effect, the total energy and time required can be drastically reduced, and the final quality of agricultural crops preserved. The growing interest and research in recent years have already shown that novel thermal with hot-air drying technology can adequately be used in the drying of agricultural crops. Scope and approach: This review attempts to give a summary of recent advances in the research and applications of novel thermal combined hot-air drying technology for agricultural crops, with particular emphasis on the combination mode, process conditions, process-quality interaction, drying kinetics, energy demand and drying efficiency. Key findings and conclusions: The combination of novel thermal with hot-air drying provides distinctive opportunities in the development of advanced agricultural crop drying technologies. The most significant advantages of using the above method were the reduction in the drying time and energy consumption as well as, an increase in the drying rate and overall efficiency. More so, the application of infrared and hot-air drying on agricultural crops is advantageous in obtaining dried products of better quality. In conclusion, the findings suggest that these technologies have great potentials. Therefore, more studies, especially in their industrial and commercial application are indispensable