Institut für Agrartechnik

Permanent URI for this collectionhttps://hohpublica.uni-hohenheim.de/handle/123456789/19

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Challenges of green production of 2,5‐furandicarboxylic acid from bio‐derived 5‐hydroxymethylfurfural: Overcoming deactivation by concomitant amino acids
(2022) Neukum, Dominik; Baumgarten, Lorena; Wüst, Dominik; Sarma, Bidyut Bikash; Saraçi, Erisa; Kruse, Andrea; Grunwaldt, Jan‐Dierk
The oxidation of 5‐hydroxymethylfurfural (HMF) to 2,5‐furandicarboxylic acid (FDCA) is highly attractive as FDCA is considered as substitute for the petrochemically derived terephthalic acid. There are only few reports on the direct use of unrefined HMF solutions from biomass resources and the influence of remaining constituents on the catalytic processes. In this work, the oxidation of HMF in a solution as obtained from hydrolysis and dehydration of saccharides in chicory roots was investigated without intermediate purification steps. The amount of base added to the solution was critical to increase the FDCA yield. Catalyst deactivation occurred and was attributed to poisoning by amino acids from the bio‐source. A strong influence of amino acids on the catalytic activity was found for all supported Au, Pt, Pd, and Ru catalysts. A supported AuPd(2 : 1)/C alloy catalyst exhibited both superior catalytic activity and higher stability against deactivation by the critical amino acids.
Effects of different ground segmentation methods on the accuracy of UAV-based canopy volume measurements
(2024) Han, Leng; Wang, Zhichong; He, Miao; He, Xiongkui; Han, Leng; College of Science, China Agricultural University, Beijing, China; Wang, Zhichong; Tropics and Subtropics Group, Institute of Agricultural Engineering, University of Hohenheim, Stuttgart, Germany; He, Miao; College of Science, China Agricultural University, Beijing, China; He, Xiongkui; College of Science, China Agricultural University, Beijing, China
The nonuniform distribution of fruit tree canopies in space poses a challenge for precision management. In recent years, with the development of Structure from Motion (SFM) technology, unmanned aerial vehicle (UAV) remote sensing has been widely used to measure canopy features in orchards to balance efficiency and accuracy. A pipeline of canopy volume measurement based on UAV remote sensing was developed, in which RGB and digital surface model (DSM) orthophotos were constructed from captured RGB images, and then the canopy was segmented using U-Net, OTSU, and RANSAC methods, and the volume was calculated. The accuracy of the segmentation and the canopy volume measurement were compared. The results show that the U-Net trained with RGB and DSM achieves the best accuracy in the segmentation task, with mean intersection of concatenation (MIoU) of 84.75% and mean pixel accuracy (MPA) of 92.58%. However, in the canopy volume estimation task, the U-Net trained with DSM only achieved the best accuracy with Root mean square error (RMSE) of 0.410 m 3 , relative root mean square error (rRMSE) of 6.40%, and mean absolute percentage error (MAPE) of 4.74%. The deep learning-based segmentation method achieved higher accuracy in both the segmentation task and the canopy volume measurement task. For canopy volumes up to 7.50 m 3 , OTSU and RANSAC achieve an RMSE of 0.521 m 3 and 0.580 m 3 , respectively. Therefore, in the case of manually labeled datasets, the use of U-Net to segment the canopy region can achieve higher accuracy of canopy volume measurement. If it is difficult to cover the cost of data labeling, ground segmentation using partitioned OTSU can yield more accurate canopy volumes than RANSAC.
Fed-batch bioreactor cultivation of Bacillus subtilis using vegetable juice as an alternative carbon source for lipopeptides production: a shift towards a circular bioeconomy
(2024) Gugel, Irene; Vahidinasab, Maliheh; Benatto Perino, Elvio Henrique; Hiller, Eric; Marchetti, Filippo; Costa, Stefania; Pfannstiel, Jens; Konnerth, Philipp; Vertuani, Silvia; Manfredini, Stefano; Hausmann, Rudolf; Gugel, Irene; Department of Life Sciences and Biotechnology, University of Ferrara, 44121 Ferrara, Italy, (S.V.);; Vahidinasab, Maliheh; Department of Bioprocess Engineering (150k), Institute of Food Science and Biotechnology, University of Hohenheim, Fruwirthstrasse 12, 70599 Stuttgart, Germany; (E.H.B.P.);; Benatto Perino, Elvio Henrique; Department of Bioprocess Engineering (150k), Institute of Food Science and Biotechnology, University of Hohenheim, Fruwirthstrasse 12, 70599 Stuttgart, Germany; (E.H.B.P.);; Hiller, Eric; Department of Bioprocess Engineering (150k), Institute of Food Science and Biotechnology, University of Hohenheim, Fruwirthstrasse 12, 70599 Stuttgart, Germany; (E.H.B.P.);; Marchetti, Filippo; Department of Life Sciences and Biotechnology, University of Ferrara, 44121 Ferrara, Italy, (S.V.);; Costa, Stefania; Department of Life Sciences and Biotechnology, University of Ferrara, 44121 Ferrara, Italy, (S.V.);; Pfannstiel, Jens; Core Facility Hohenheim, Mass Spectrometry Unit, University of Hohenheim, Ottlie-Zeller-Weg 2, 70599 Stuttgart, Germany; Konnerth, Philipp; Department of Conversion Technology of Biobased Resources, University of Hohenheim, Garbenstrasse 9, 70599 Stuttgart, Germany;; Vertuani, Silvia; Department of Life Sciences and Biotechnology, University of Ferrara, 44121 Ferrara, Italy, (S.V.);; Manfredini, Stefano; Department of Life Sciences and Biotechnology, University of Ferrara, 44121 Ferrara, Italy, (S.V.);; Hausmann, Rudolf; Department of Bioprocess Engineering (150k), Institute of Food Science and Biotechnology, University of Hohenheim, Fruwirthstrasse 12, 70599 Stuttgart, Germany; (E.H.B.P.);; Gudiña, Eduardo
In a scenario of increasing alarm about food waste due to rapid urbanization, population growth and lifestyle changes, this study aims to explore the valorization of waste from the retail sector as potential substrates for the biotechnological production of biosurfactants. With a perspective of increasingly contributing to the realization of the circular bioeconomy, a vegetable juice, derived from unsold fruits and vegetables, as a carbon source was used to produce lipopeptides such as surfactin and fengycin. The results from the shake flask cultivations revealed that different concentrations of vegetable juice could effectively serve as carbon sources and that the fed-batch bioreactor cultivation strategy allowed the yields of lipopeptides to be significantly increased. In particular, the product/substrate yield of 0.09 g/g for surfactin and 0.85 mg/g for fengycin was obtained with maximum concentrations of 2.77 g/L and 27.53 mg/L after 16 h, respectively. To conclude, this study provides the successful fed-batch cultivation of B. subtilis using waste product as the carbon source to produce secondary metabolites. Therefore, the consumption of agricultural product wastes might be a promising source for producing valuable metabolites which have promising application potential to be used in several fields of biological controls of fungal diseases.
Food informatics - Review of the current state-of-the-art, revised definition, and classification into the research landscape
(2021) Krupitzer, Christian; Stein, Anthony
Background: The increasing population of humans, changing food consumption behavior, as well as the recent developments in the awareness for food sustainability, lead to new challenges for the production of food. Advances in the Internet of Things (IoT) and Artificial Intelligence (AI) technology, including Machine Learning and data analytics, might help to account for these challenges. Scope and Approach: Several research perspectives, among them Precision Agriculture, Industrial IoT, Internet of Food, or Smart Health, already provide new opportunities through digitalization. In this paper, we review the current state-of-the-art of the mentioned concepts. An additional concept is Food Informatics, which so far is mostly recognized as a mainly data-driven approach to support the production of food. In this review paper, we propose and discuss a new perspective for the concept of Food Informatics as a supportive discipline that subsumes the incorporation of information technology, mainly IoT and AI, in order to support the variety of aspects tangent to the food production process and delineate it from other, existing research streams in the domain. Key Findings and Conclusions: Many different concepts related to the digitalization in food science overlap. Further, Food Informatics is vaguely defined. In this paper, we provide a clear definition of Food Informatics and delineate it from related concepts. We corroborate our new perspective on Food Informatics by presenting several case studies about how it can support the food production as well as the intermediate steps until its consumption, and further describe its integration with related concepts.

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