SusOrgPlus – Intelligente Lebensmittelverarbeitung, natürliche Zusatz- und Farbstoffe

SusOrgPlus ist ein multi- und transdisziplinäres Projekt, das die Entwicklung von Systemlösungen zur Verarbeitung ökologischer Lebensmittel beabsichtigt welche unter anderem Ressourceneffizienz, hohe Produktqualität und Nutzungswege für unzureichend genutzte Rohwaren und die Entwicklung neuer Produkte mit Mehrwert beinhalten. Somit wird SusOrgPlus dazu beitragen, die Nachhaltigkeit der ökologischen Lebensmittelbranche sowie die Verbraucherakzeptanz zu steigern und dadurch die Wettbewerbsfähigkeit der Verarbeiter zu verbessern. Die Einbindung von führenden Lebensmittelwissenschaftlern, Verfahrens- und Regelungstechnikern aus Mittel-, Nord-, Süd- und Osteuropa wird sichergestellt, dass alle Aspekte, welche für Prozessoptimierung und Ressourceneffizienz von Bedeutung sind, adäquat berücksichtigt werden. Dadurch ist die Relevanz des Projektes für den europäischen Raum, sowie darüber hinaus, gewährleistet

Development of an Optical System Based on Spectral Imaging Used for a Slug Control Robot

The state-of-the-art technique to control slug pests in agriculture is the spreading of slug pellets. This method has some downsides, because slug pellets also harm beneficials and often fail because their efficiency depends on the prevailing weather conditions. This study is part of a research project which is developing a pest control robot to monitor the field, detect slugs, and eliminate them. Robots represent a promising alternative to slug pellets. They work independent of weather conditions and can distinguish between pests and beneficials. As a prerequisite, a robot must be able to reliably identify slugs irrespective of the characteristics of the surrounding conditions. In this context, the utilization of computer vision and image analysis methods are challenging, because slugs look very similar to the soil, particularly in color images. Therefore, the goal of this study was to develop an optical filter-based system that distinguishes between slugs and soil. In this context, the spectral characteristics of both slugs and soil in the visible and visible near-infrared (VNIR) wavebands were measured. Conspicuous maxima followed by conspicuous local minima were found for the reflection spectra of slugs in the near infrared range from 850 nm to 990 nm]. Thus, this enabled differentiation between slugs and soils; soils showed a monotonic increase in the intensity of the relative reflection for this wavelength. The extrema determined in the reflection spectra of slugs were used to develop and set up a slug detector device consisting of a monochromatic camera, a filter changer and two narrow bandpass filters with nominal wavelengths of 925 nm and 975 nm. The developed optical system takes two photographs of the target area at night. By subtracting the pixel values of the images, the slugs are highlighted, and the soil is removed in the image due to the properties of the reflection spectra of soils and slugs. In the resulting image, the pixels of slugs were, on average, 12.4 times brighter than pixels of soil. This enabled the detection of slugs by a threshold method.Peer Reviewe

Investigating the Effect of Different Drying Strategies on the Quality Parameters of Daucus carota L. Using Dynamic Process Control and Measurement Techniques

The present work aims to improve the understanding of the effect of different drying strategies at varying temperatures on the dynamic drying behaviour and quality of organic products such as carrots using non-invasive measurement techniques. For this purpose, carrot slices of 3 mm thickness were dried under three different strategies namely air temperature controlled (A), product temperature controlled (P) and stepwise temperature controlled (S) at different temperatures (50 °C, 60 °C and 70 °C) to measure and analyse the changes in moisture content, colour, total carotenoid retention, water activity, rehydration ratio and specific energy consumption. From the investigation performed, it was incurred that the application of different drying strategies influences rather significantly both the product quality as well as the overall process efficiency. Modelling the drying curves deemed Page model to be a good fit for all the strategies with R2adj = 0.99 and RMSE = 0.01. The results also show that implementing strategy P not only led to shorter drying times but also led to higher total carotenoid retention within the samples (TCR = 0.59–0.73). Colour changes, however, were observed to be maximum with strategy P as compared to strategy A and strategy S. Furthermore, the use of a non-invasive measurement technique such as infrared camera proved to be reliable in order to detect the phase transition of the product during the drying process

Influence of storage time on essential oil components in dried hops

Hop processors often store fresh hops in silos prior to drying. There has been little knowledge regarding the effect of storage on hops. To investigate the effects on product quality, freshly harvested hop cones were stored for 5 and 24 hr respectively and dried for 210 min at 65°C thereafter. The results obtained from gas chromatography (GC) investigations show an increase in linalool, ß-carophyllen, humulen and geraniol content and decrease in myrcene content based on the period of storage

Impact of processing temperature on drying behavior and quality changes in organic beef

[EN] The drying of beef has gained an increasing interest and the organic market shows an increasing demand for dried beef products. In this study, organic beef meat slices were dried at 50 °C, 60 °C and 70 °C. Moisture content and color was measured throughout the drying process alongside Vis/VNIR hyperspectral images of the slices. The results of the total color difference (ΔE) showed the biggest change for samples dried at 50 °C (ΔE = 25.6). The aw value was the lowest for slices dried at 50 °C (0.744). The hyperspectral data gave promising results regarding non-invasive prediction of moisture content and color.The Authors wish to thank the Core Organic Plus Programme for the financial support within the SusOrganic project (Project Number: BLE - 2814OE006), and the SusOrgPlus Project (Project Number: BLE – 2817OE005) and the Reload Project (Project No.: BMBF - 031A247A).Von Gersdorff, G.; Shrestha, L.; Raut, S.; Retz, S.; Hensel, O.; Sturm, B. (2018). Impact of processing temperature on drying behavior and quality changes in organic beef. En IDS 2018. 21st International Drying Symposium Proceedings. Editorial Universitat Politècnica de València. 1823-1830. https://doi.org/10.4995/IDS2018.2018.7792OCS1823183

Feasibility of Vis/NIR spectroscopy and image analysis as basis of the development of smart-drying technologies

[EN] Drying is a complex, dynamic, unsteady and nonlinear process that, when not optimized on a system level, may be responsible for (1) significant quality degradation and (2) energy wastage. Consequently, new drying technologies must be designed combining non-invasive at-/on-/in-line advanced measurement and control systems with models cross-linking all relevant aspects of product quality changes and heat and mass transfer phenomena. This paper presents preliminary results on the use of RGB imaging, NIR spectroscopy and Vis-NIR hyperspectral imaging for real-time monitoring of physicochemical changes of apples and carrots during drying.The authors gratefully acknowledge CORE Organic Plus for financial support through the SusOrganic project titled: ‘Development of quality standards and optimized processing methods for organic produce’ (Nr: 2814OE006).Sturm, B.; Moscetti, R.; Crichton, S.; Raut, S.; Bantle, M.; Massantini, R. (2018). Feasibility of Vis/NIR spectroscopy and image analysis as basis of the development of smart-drying technologies. En IDS 2018. 21st International Drying Symposium Proceedings. Editorial Universitat Politècnica de València. 171-178. https://doi.org/10.4995/IDS2018.2018.7616OCS17117

Digitalization of agriculture for sustainable crop production: a use-case review

The digitalization of agriculture is rapidly changing the way farmers do business. With the integration of advanced technology, farmers are now able to increase efficiency, productivity, and precision in their operations. Digitalization allows for real-time monitoring and management of crops, leading to improved yields and reduced waste. This paper presents a review of some of the use cases that digitalization has made an impact in the automation of open-field and closed-field cultivations by means of collecting data about soils, crop growth, and microclimate, or by contributing to more accurate decisions about water usage and fertilizer application. The objective was to address some of the most recent technological advances that are leading to increased efficiency and sustainability of crop production, reduction in the use of inputs and environmental impacts, and releasing manual workforces from repetitive field tasks. The short discussions included at the end of each case study attempt to highlight the limitations and technological challenges toward successful implementations, as well as to introduce alternative solutions and methods that are rapidly evolving to offer a vast array of benefits for farmers by influencing cost-saving measures. This review concludes that despite the many benefits of digitalization, there are still a number of challenges that need to be overcome, including high costs, reliability, and scalability. Most of the available setups that are currently used for this purpose have been custom designed for specific tasks and are still too expensive to be implemented on commercial scales, while others are still in their early stages of development, making them not reliable or scalable for widespread acceptance and adoption by farmers. By providing a comprehensive understanding of the current state of digitalization in agriculture and its impact on sustainable crop production and food security, this review provides insights for policy-makers, industry stakeholders, and researchers working in this field.Peer Reviewe

Optimizing drying processes for agricultural products utilising non-invasive measurement and adaptive control systems

SusOrgPlus Project, UPGRADE Plus Projec

Development of an Optical System Based on Spectral Imaging Used for a Slug Control Robot

Gefördert durch den Publikationsfonds der Universität Kasse