Die chronologische Liste zeigt aktuelle Veröffentlichungen aus dem Forschungsbetrieb der Hochschule Weihenstephan-Triesdorf. Zuständig ist das Zentrum für Forschung und Wissenstransfer (ZFW).
8 Ergebnisse
Prof. Dr. Martina Artmann,
Kathrin Specht,
Jan Vavra,
Marius Rommel
Berechtigungen: Peer Reviewed
Introduction to the Special Issue “A Systemic Perspective on Urban Food Supply: Assessing Different
Types of Urban Agriculture” (2021) Sustainability 13 7 , S. 3798.
Etliche Nutzpflanzen lassen sich umweltfreundlicher und ressourcenschonender erzeugen, wenn sie nicht draußen wachsen, sondern in Industriehallen oder Supermärkten. Ein neuer Trend der urbanen Landwirtschaft.
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Sabine Wittmann,
Ivonne Jüttner,
B.Sc. Marvin Spence,
Prof. Dr. Heike Susanne Mempel
Climate change and increasing global urbanization accelerate the expansion of protected cultivation systems. However, certain dependences to external weather conditions remain even in modern greenhouses. Indoor vertical farming, on the other hand, pursues complete inde-pendence from external weather conditions with the aim for highly accurate control of all crop parameters. Particularly with regard to the advancing climate change and the need for sustainable resource consumption, there are clear advantages due to the year-round and independent cultivation of plants and raw materials under optimal conditions. The complexity in the optimal networking of the plant-technology systems offers intensive development opportunities for dig-itization and interdisciplinary collaboration.
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Prof. Dr. Bernhard Bauer,
Prof. Dr. Peter Breunig,
B.Eng. Andreas Fleischmann,
Tobias Meyer,
Prof. Dr. Patrick Noack,
M.Sc. Muhammad Saeed,
M.Sc. Rolf Wilmes
In the past few years, portable and smartphone-based diagnostic technologies have found their way into the agri-food industry. The aim of this research was to evaluate the perfor-mance of portable near-infrared (NIR) spectrometers, so called food-scanners, with regard to their predictive accuracy of important quality parameters of fruit and vegetables. Food-scan-ner measurements were performed in combination with destructive measurements of the corresponding quality trait (sugar content, dry matter, relative water content) on a wide range of produce from the fruit and vegetable assortment. This study evaluated dry matter content of apple, avocado, blueberry, table grape and tangerine, which yielded cross validation re-sults (r²) of up to 0.95, 0.87, 0.94, 0.92 and 0.92 respectively. Furthermore, the evaluation of food-scanner spectra for the prediction of sugar content of blueberry, kiwi, mango, persim-mon, table grape, tangerine and tomato yielded cross validations (r²) of up to 0.95, 0.84, 0.80, 0.75, 0.95, 0.93, and 0.87. Furthermore, relative water content of ginger obtained a cross val-idation correlation of r² = 0.91. The results show that these traits can be predicted with a high degree of accuracy using non-destructive measurements performed with three commercially available food-scanners SCiOTM, F-750 Produce Quality Meter, and H-100F. Consequently, food-scanners can be used as objective measurement tools along the supply chain of fresh produce to quickly determine fruit quality. In addition, a practical example shows the poten-tial of these instruments for non-destructive quality assessment in incoming goods control at fruit and vegetable wholesalers over a time period of several weeks. Furthermore, possible areas of application of food-scanners along the supply chain of fresh produce are discussed, possibilities for practical applications are presented and time-saving means are highlightedLANDTECHNIK 76(1), 2021, 52–67Food-scanner applications in the fruit and vegetable sectorSimon Goisser, Sabine Wittmann, Heike MempelIn the past few years, portable and smartphone-based diagnostic technologies have found their way into the agri-food industry. The aim of this research was to evaluate the perfor-mance of portable near-infrared (NIR) spectrometers, so called food-scanners, with regard to their predictive accuracy of important quality parameters of fruit and vegetables. Food-scan-ner measurements were performed in combination with destructive measurements of the corresponding quality trait (sugar content, dry matter, relative water content) on a wide range of produce from the fruit and vegetable assortment. This study evaluated dry matter content of apple, avocado, blueberry, table grape and tangerine, which yielded cross validation re-sults (r²) of up to 0.95, 0.87, 0.94, 0.92 and 0.92 respectively. Furthermore, the evaluation of food-scanner spectra for the prediction of sugar content of blueberry, kiwi, mango, persim-mon, table grape, tangerine and tomato yielded cross validations (r²) of up to 0.95, 0.84, 0.80, 0.75, 0.95, 0.93, and 0.87. Furthermore, relative water content of ginger obtained a cross val-idation correlation of r² = 0.91. The results show that these traits can be predicted with a high degree of accuracy using non-destructive measurements performed with three commercially available food-scanners SCiOTM, F-750 Produce Quality Meter, and H-100F. Consequently, food-scanners can be used as objective measurement tools along the supply chain of fresh produce to quickly determine fruit quality. In addition, a practical example shows the poten-tial of these instruments for non-destructive quality assessment in incoming goods control at fruit and vegetable wholesalers over a time period of several weeks. Furthermore, possible areas of application of food-scanners along the supply chain of fresh produce are discussed, possibilities for practical applications are presented and time-saving means are highlighted.
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