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.
The deformation curve characteristics of rapeseeds and sunflower seeds compressed using the equipment ZDM 50-2313/56/18 and varying vessel diameters (40, 60, 80, and 100 mm) were investigated. Maximum compressive force of 100 kN was applied on bulk oilseeds of rape and sunflower of measured height 20-80 mm and deformed at a speed of 60 mm∙min-1. The compression test using the vessel diameters of 40 and 60 mm showed a serration effect while the vessel diameters of 80 and 100 mm indicated an increasing function effect on the force-deformation characteristic curves. Clearly, the increasing function effect described the region with oil flow and that of serration effect described the region without any oil flow. However, it was observed that the serration effect could be due to the higher compressive stress inside the smaller vessel diameters (40 and 60 mm) compared to those with bigger vessel diameters (80 and 100 mm). Parameters such as deformation, deformation energy, and energy density were determined from the force-deformation curves dependency showing both increasing function and serration effect. The findings of the study provide useful information for the determination of specific compressive force and energy requirements for extracting maximum oil from oilseed crops such as rape and sunflower.
Via image-based macroscopic, analysis of a briquettes' surface structure, particle size, and distribution was determined to better understand the behavioural pattern of input material during agglomeration in the pressing chamber of a briquetting machine. The briquettes, made of miscanthus, industrial hemp and pine sawdust were produced by a hydraulic piston press. Their structure was visualized by a stereomicroscope equipped with a digital camera and software for image analysis and data measurements. In total, 90 images of surface structure were obtained and quantitatively analysed. Using Nikon Instruments Software (NIS)-Elements software, the length and area of 900 particles were measured and statistically tested to compare the size of the particles at different surface locations. Results showed statistically significant differences in particles' size distribution: larger particles were generally on the front side of briquettes and vice versa, smaller particles were on the rear side. As well, larger particles were centred in the middle of cross sections and the smaller particles were centred on the bottom of the briquette.
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