Traulsen, Imke

[["dc.bibliographiccitation.firstpage","130"],["dc.bibliographiccitation.issue","4"],["dc.bibliographiccitation.journal","Agriculture"],["dc.bibliographiccitation.volume","10"],["dc.contributor.author","Gentz, Maria"],["dc.contributor.author","Lange, Anita"],["dc.contributor.author","Zeidler, Sebastian"],["dc.contributor.author","Lambertz, Christian"],["dc.contributor.author","Gauly, Matthias"],["dc.contributor.author","Burfeind, Onno"],["dc.contributor.author","Traulsen, Imke"],["dc.date.accessioned","2020-12-10T18:46:54Z"],["dc.date.available","2020-12-10T18:46:54Z"],["dc.date.issued","2020"],["dc.identifier.doi","10.3390/agriculture10040130"],["dc.identifier.eissn","2077-0472"],["dc.identifier.purl","https://resolver.sub.uni-goettingen.de/purl?gs-1/17402"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/78581"],["dc.language.iso","en"],["dc.notes.intern","DOI Import GROB-354"],["dc.notes.intern","Merged from goescholar"],["dc.publisher","MDPI"],["dc.relation.eissn","2077-0472"],["dc.rights","CC BY 4.0"],["dc.rights.uri","http://creativecommons.org/licenses/by/4.0/"],["dc.title","Tail Lesions and Losses of Docked and Undocked Pigs in Different Farrowing and Rearing Systems"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dc.type.version","published_version"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.firstpage","106056"],["dc.bibliographiccitation.journal","Computers and Electronics in Agriculture"],["dc.bibliographiccitation.volume","183"],["dc.contributor.author","Meckbach, Cornelia"],["dc.contributor.author","Tiesmeyer, Verena"],["dc.contributor.author","Traulsen, Imke"],["dc.date.accessioned","2021-06-01T09:41:14Z"],["dc.date.available","2021-06-01T09:41:14Z"],["dc.date.issued","2021"],["dc.identifier.doi","10.1016/j.compag.2021.106056"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/84856"],["dc.language.iso","en"],["dc.notes.intern","DOI-Import GROB-425"],["dc.relation.issn","0168-1699"],["dc.title","A promising approach towards precise animal weight monitoring using convolutional neural networks"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.firstpage","2184"],["dc.bibliographiccitation.issue","8"],["dc.bibliographiccitation.journal","Animals"],["dc.bibliographiccitation.volume","11"],["dc.contributor.author","Lange, Anita"],["dc.contributor.author","Hahne, Michael"],["dc.contributor.author","Lambertz, Christian"],["dc.contributor.author","Gauly, Matthias"],["dc.contributor.author","Wendt, Michael"],["dc.contributor.author","Janssen, Heiko"],["dc.contributor.author","Traulsen, Imke"],["dc.date.accessioned","2021-10-01T09:58:21Z"],["dc.date.available","2021-10-01T09:58:21Z"],["dc.date.issued","2021"],["dc.description.abstract","Feasible alternatives to stressful weaning and tail-docking are needed to inhibit tail biting. Therefore, we investigated the effects of housing systems for 1106 pigs that were weaned from: (1) conventional farrowing crates (FC), (2) free-farrowing pens (FF), or (3) group housing of lactating sows (GH) into (1) conventional rearing pens (Conv) or (2) piglets remained in their farrowing pens for rearing (Reaf). Tails were docked or left undocked batchwise. All pigs were regrouped for the fattening period. Pigs were scored for skin lesions, tail lesions and losses. After weaning, Conv-GH pigs had significantly less skin lesions than Conv-FC and Conv-FF pigs. After regrouping for fattening, Reaf-GH pigs had significantly less skin lesions than Conv pigs, Reaf-FC and Reaf-FF. The frequency of tail lesions of undocked Conv pigs peaked in week 4 (66.8%). Two weeks later, Reaf undocked pigs reached their maximum (36.2%). At the end of fattening, 99.3% of undocked Conv pigs and 43.1% of undocked Reaf pigs lost parts of their tail. In conclusion, the co-mingling of piglets during suckling reduced the incidence of skin lesions. Rearing in the farrowing pen significantly reduced the incidence of tail lesions and losses for undocked pigs. No housing system negatively affected the performance."],["dc.description.abstract","Feasible alternatives to stressful weaning and tail-docking are needed to inhibit tail biting. Therefore, we investigated the effects of housing systems for 1106 pigs that were weaned from: (1) conventional farrowing crates (FC), (2) free-farrowing pens (FF), or (3) group housing of lactating sows (GH) into (1) conventional rearing pens (Conv) or (2) piglets remained in their farrowing pens for rearing (Reaf). Tails were docked or left undocked batchwise. All pigs were regrouped for the fattening period. Pigs were scored for skin lesions, tail lesions and losses. After weaning, Conv-GH pigs had significantly less skin lesions than Conv-FC and Conv-FF pigs. After regrouping for fattening, Reaf-GH pigs had significantly less skin lesions than Conv pigs, Reaf-FC and Reaf-FF. The frequency of tail lesions of undocked Conv pigs peaked in week 4 (66.8%). Two weeks later, Reaf undocked pigs reached their maximum (36.2%). At the end of fattening, 99.3% of undocked Conv pigs and 43.1% of undocked Reaf pigs lost parts of their tail. In conclusion, the co-mingling of piglets during suckling reduced the incidence of skin lesions. Rearing in the farrowing pen significantly reduced the incidence of tail lesions and losses for undocked pigs. No housing system negatively affected the performance."],["dc.description.sponsorship","Bundesanstalt für Landwirtschaft und Ernährung"],["dc.description.sponsorship","Landwirtschaftliche Rentenbank"],["dc.identifier.doi","10.3390/ani11082184"],["dc.identifier.pii","ani11082184"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/90045"],["dc.language.iso","en"],["dc.notes.intern","DOI Import GROB-469"],["dc.publisher","MDPI"],["dc.relation.eissn","2076-2615"],["dc.rights","https://creativecommons.org/licenses/by/4.0/"],["dc.title","Effects of Different Housing Systems during Suckling and Rearing Period on Skin and Tail Lesions, Tail Losses and Performance of Growing and Finishing Pigs"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.issue","13"],["dc.bibliographiccitation.journal","Sustainability"],["dc.bibliographiccitation.volume","14"],["dc.contributor.affiliation","Pointke, Marcel; 1Division of Quality of Plant Products, Department of Crop Sciences, Faculty of Agriculture, University of Goettingen, 37075 Goettingen, Germany; epawelz@gwdg.de"],["dc.contributor.affiliation","Albrecht, Elke Herta; 2Division of Ecology of Livestock Production, Department of Animal Sciences, Faculty of Agriculture, University of Goettingen, 37075 Goettingen, Germany; elkeherta.albrecht@uni-goettingen.de (E.H.A.); katrin.geburt@uni-goettingen.de (K.G.); mgerken@gwdg.de (M.G.)"],["dc.contributor.affiliation","Geburt, Katrin; 2Division of Ecology of Livestock Production, Department of Animal Sciences, Faculty of Agriculture, University of Goettingen, 37075 Goettingen, Germany; elkeherta.albrecht@uni-goettingen.de (E.H.A.); katrin.geburt@uni-goettingen.de (K.G.); mgerken@gwdg.de (M.G.)"],["dc.contributor.affiliation","Gerken, Martina; 2Division of Ecology of Livestock Production, Department of Animal Sciences, Faculty of Agriculture, University of Goettingen, 37075 Goettingen, Germany; elkeherta.albrecht@uni-goettingen.de (E.H.A.); katrin.geburt@uni-goettingen.de (K.G.); mgerken@gwdg.de (M.G.)"],["dc.contributor.affiliation","Traulsen, Imke; 3Division Livestock Systems, Department of Animal Sciences, Faculty of Agriculture, University of Goettingen, 37075 Goettingen, Germany; imke.traulsen@uni-goettingen.de"],["dc.contributor.affiliation","Pawelzik, Elke; 1Division of Quality of Plant Products, Department of Crop Sciences, Faculty of Agriculture, University of Goettingen, 37075 Goettingen, Germany; epawelz@gwdg.de"],["dc.contributor.author","Pointke, Marcel"],["dc.contributor.author","Albrecht, Elke Herta"],["dc.contributor.author","Geburt, Katrin"],["dc.contributor.author","Gerken, Martina"],["dc.contributor.author","Traulsen, Imke"],["dc.contributor.author","Pawelzik, Elke"],["dc.date.accessioned","2022-07-11T06:54:09Z"],["dc.date.available","2022-07-11T06:54:09Z"],["dc.date.issued","2022-06-30"],["dc.date.updated","2022-07-08T13:18:20Z"],["dc.description.abstract","Consumers are becoming increasingly interested in reducing the consumption of animal-based foods for health, sustainability, and ethical reasons. The food industry is developing products from plant-based ingredients that mimic animal-based foods’ nutritional and sensory characteristics. In this study, the focus is on plant-based milk alternatives (PBMAs). A potential problem with plant-based diets is the deficiency of important micronutrients, such as vitamin B12, B2, and calcium. Therefore, an analysis of micronutrients in PBMAs was conducted to assess their nutritional value. The second main focus was on the sensory description of the PBMAs, done by a trained panel, and instrumental assessment to characterize the sensory attributes. Almond drinks met the daily micronutrient requirements the least, while soy drinks came closest to cow’s milk in macro- and micronutrients. The experimentally determined electronic tongue and volatile compound results confirmed the sensory panel’s evaluations and could therefore be used as a method for easy and effective assessments of PBMAs. The PBMAs evaluated in this study could not completely replace cow’s milk’s nutritional and sensory properties. They are products in their own product group and must be evaluated accordingly. Given the variety of products, consumers should experiment and make their decisions regarding the substitution of cow’s milk."],["dc.description.sponsorship","Volkswagenstif-tung"],["dc.description.sponsorship","Ministry for Science and Culture of Lower Saxony"],["dc.description.sponsorship","Open-Access-Publikationsfonds 2022"],["dc.identifier.doi","10.3390/su14137996"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/112428"],["dc.language.iso","en"],["dc.relation.eissn","2071-1050"],["dc.rights","CC BY 4.0"],["dc.title","A Comparative Analysis of Plant-Based Milk Alternatives Part 1: Composition, Sensory, and Nutritional Value"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dc.type.subtype","original_ja"],["dc.type.version","published_version"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.issue","14"],["dc.bibliographiccitation.journal","Sustainability"],["dc.bibliographiccitation.volume","14"],["dc.contributor.affiliation","Geburt, Katrin; 1Division of Ecology of Livestock Production, Department of Animal Sciences, Faculty of Agriculture, University of Goettingen, 37075 Goettingen, Germany; katrin.geburt@uni-goettingen.de (K.G.); elkeherta.albrecht@uni-goettingen.de (E.H.A.); mgerken@gwdg.de (M.G.)"],["dc.contributor.affiliation","Albrecht, Elke Herta; 1Division of Ecology of Livestock Production, Department of Animal Sciences, Faculty of Agriculture, University of Goettingen, 37075 Goettingen, Germany; katrin.geburt@uni-goettingen.de (K.G.); elkeherta.albrecht@uni-goettingen.de (E.H.A.); mgerken@gwdg.de (M.G.)"],["dc.contributor.affiliation","Pointke, Marcel; 2Division of Quality of Plant Products, Department of Crop Sciences, Faculty of Agriculture, University of Goettingen, 37075 Goettingen, Germany; marcel.pointke@uni-goettingen.de (M.P.); epawelz@gwdg.de (E.P.)"],["dc.contributor.affiliation","Pawelzik, Elke; 2Division of Quality of Plant Products, Department of Crop Sciences, Faculty of Agriculture, University of Goettingen, 37075 Goettingen, Germany; marcel.pointke@uni-goettingen.de (M.P.); epawelz@gwdg.de (E.P.)"],["dc.contributor.affiliation","Gerken, Martina; 1Division of Ecology of Livestock Production, Department of Animal Sciences, Faculty of Agriculture, University of Goettingen, 37075 Goettingen, Germany; katrin.geburt@uni-goettingen.de (K.G.); elkeherta.albrecht@uni-goettingen.de (E.H.A.); mgerken@gwdg.de (M.G.)"],["dc.contributor.affiliation","Traulsen, Imke; 3Division Livestock Systems, Department of Animal Sciences, Faculty of Agriculture, University of Goettingen, 37075 Goettingen, Germany"],["dc.contributor.author","Geburt, Katrin"],["dc.contributor.author","Albrecht, Elke Herta"],["dc.contributor.author","Pointke, Marcel"],["dc.contributor.author","Pawelzik, Elke"],["dc.contributor.author","Gerken, Martina"],["dc.contributor.author","Traulsen, Imke"],["dc.date.accessioned","2022-08-04T08:24:13Z"],["dc.date.available","2022-08-04T08:24:13Z"],["dc.date.issued","2022-07-09"],["dc.date.updated","2022-08-03T15:20:10Z"],["dc.description.abstract","Human food production is the largest cause of global environmental changes. Environmental benefits could be achieved by replacing diets with a high amount of animal-sourced foods with more plant-based foods, due to their smaller environmental impacts. The objective of this study was to assess the environmental impacts of the three most common plant-based milk alternatives (PBMAs)—oat, soy, and almond drink—in comparison with conventional and organic cow milk. Life cycle assessments (LCA) were calculated by the ReCiPe 2016 midpoint method, in addition to the single issue methods “Ecosystem damage potential” and “Water scarcity index”. PBMAs achieved lower impact values in almost all 12 of the calculated impact categories, with oat drink and the organic soy drink being the most environmentally friendly. However, when LCA results were expressed per energy and by the protein content of the beverages, the ranking of the beverages, in terms of their environmental impacts, changed greatly, and the results of PBMAs approached those of milk, particularly with regard to the protein index. The study highlights the importance of considering a broader range of impact categories when comparing the impacts of PBMAs and milk."],["dc.description.sponsorship","Volkswagenstiftung"],["dc.description.sponsorship","Ministry for Science and Culture of Lower Saxony"],["dc.identifier.doi","10.3390/su14148424"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/112623"],["dc.language.iso","en"],["dc.relation.eissn","2071-1050"],["dc.rights","CC BY 4.0"],["dc.title","A Comparative Analysis of Plant-Based Milk Alternatives Part 2: Environmental Impacts"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dc.type.subtype","original_ja"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.firstpage","9407"],["dc.bibliographiccitation.issue","10"],["dc.bibliographiccitation.journal","Journal of Dairy Science"],["dc.bibliographiccitation.lastpage","9417"],["dc.bibliographiccitation.volume","103"],["dc.contributor.author","Dirksen, N."],["dc.contributor.author","Gygax, L."],["dc.contributor.author","Traulsen, I."],["dc.contributor.author","Wechsler, B."],["dc.contributor.author","Burla, J.-B."],["dc.date.accessioned","2021-04-14T08:32:40Z"],["dc.date.available","2021-04-14T08:32:40Z"],["dc.date.issued","2020"],["dc.identifier.doi","10.3168/jds.2019-16464"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/83981"],["dc.language.iso","en"],["dc.notes.intern","DOI Import GROB-399"],["dc.relation.issn","0022-0302"],["dc.title","Body size in relation to cubicle dimensions affects lying behavior and joint lesions in dairy cows"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.firstpage","7585"],["dc.bibliographiccitation.issue","22"],["dc.bibliographiccitation.journal","Sensors"],["dc.bibliographiccitation.volume","21"],["dc.contributor.author","Meckbach, Cornelia"],["dc.contributor.author","Elsholz, Sabrina"],["dc.contributor.author","Siede, Caroline"],["dc.contributor.author","Traulsen, Imke"],["dc.date.accessioned","2022-01-11T14:07:54Z"],["dc.date.available","2022-01-11T14:07:54Z"],["dc.date.issued","2021"],["dc.description.abstract","Sensor technologies, such as the Global Navigation Satellite System (GNSS), produce huge amounts of data by tracking animal locations with high temporal resolution. Due to this high resolution, all animals show at least some co-occurrences, and the pure presence or absence of co-occurrences is not satisfactory for social network construction. Further, tracked animal contacts contain noise due to measurement errors or random co-occurrences. To identify significant associations, null models are commonly used, but the determination of an appropriate null model for GNSS data by maintaining the autocorrelation of tracks is challenging, and the construction is time and memory consuming. Bioinformaticians encounter phylogenetic background and random noise on sequencing data. They estimate this noise directly on the data by using the average product correction procedure, a method applied to information-theoretic measures. Using Global Positioning System (GPS) data of heifers in a pasture, we performed a proof of concept that this approach can be transferred to animal science for social network construction. The approach outputs stable results for up to 30% missing data points, and the predicted associations were in line with those of the null models. The effect of different distance thresholds for contact definition was marginal, but animal activity strongly affected the network structure."],["dc.description.abstract","Sensor technologies, such as the Global Navigation Satellite System (GNSS), produce huge amounts of data by tracking animal locations with high temporal resolution. Due to this high resolution, all animals show at least some co-occurrences, and the pure presence or absence of co-occurrences is not satisfactory for social network construction. Further, tracked animal contacts contain noise due to measurement errors or random co-occurrences. To identify significant associations, null models are commonly used, but the determination of an appropriate null model for GNSS data by maintaining the autocorrelation of tracks is challenging, and the construction is time and memory consuming. Bioinformaticians encounter phylogenetic background and random noise on sequencing data. They estimate this noise directly on the data by using the average product correction procedure, a method applied to information-theoretic measures. Using Global Positioning System (GPS) data of heifers in a pasture, we performed a proof of concept that this approach can be transferred to animal science for social network construction. The approach outputs stable results for up to 30% missing data points, and the predicted associations were in line with those of the null models. The effect of different distance thresholds for contact definition was marginal, but animal activity strongly affected the network structure."],["dc.description.sponsorship","Open-Access-Publikationsfonds 2021"],["dc.identifier.doi","10.3390/s21227585"],["dc.identifier.pii","s21227585"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/97889"],["dc.language.iso","en"],["dc.notes.intern","DOI-Import GROB-507"],["dc.relation.eissn","1424-8220"],["dc.relation.orgunit","Department für Nutztierwissenschaften"],["dc.rights","CC BY 4.0"],["dc.rights.uri","https://creativecommons.org/licenses/by/4.0/"],["dc.title","An Information-Theoretic Approach to Detect the Associations of GPS-Tracked Heifers in Pasture"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dc.type.subtype","original_ja"],["dc.type.version","published_version"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.artnumber","7512"],["dc.bibliographiccitation.issue","22"],["dc.bibliographiccitation.journal","Sensors"],["dc.bibliographiccitation.volume","21"],["dc.contributor.author","Wutke, Martin"],["dc.contributor.author","Heinrich, Felix"],["dc.contributor.author","Das, Pronaya Prosun"],["dc.contributor.author","Lange, Anita"],["dc.contributor.author","Gentz, Maria"],["dc.contributor.author","Traulsen, Imke"],["dc.contributor.author","Warns, Friederike K."],["dc.contributor.author","Schmitt, Armin Otto"],["dc.contributor.author","Gültas, Mehmet"],["dc.date.accessioned","2022-01-11T14:07:54Z"],["dc.date.available","2022-01-11T14:07:54Z"],["dc.date.issued","2021"],["dc.description.abstract","The identification of social interactions is of fundamental importance for animal behavioral studies, addressing numerous problems like investigating the influence of social hierarchical structures or the drivers of agonistic behavioral disorders. However, the majority of previous studies often rely on manual determination of the number and types of social encounters by direct observation which requires a large amount of personnel and economical efforts. To overcome this limitation and increase research efficiency and, thus, contribute to animal welfare in the long term, we propose in this study a framework for the automated identification of social contacts. In this framework, we apply a convolutional neural network (CNN) to detect the location and orientation of pigs within a video and track their movement trajectories over a period of time using a Kalman filter (KF) algorithm. Based on the tracking information, we automatically identify social contacts in the form of head–head and head–tail contacts. Moreover, by using the individual animal IDs, we construct a network of social contacts as the final output. We evaluated the performance of our framework based on two distinct test sets for pig detection and tracking. Consequently, we achieved a Sensitivity, Precision, and F1-score of 94.2%, 95.4%, and 95.1%, respectively, and a MOTA score of 94.4%. The findings of this study demonstrate the effectiveness of our keypoint-based tracking-by-detection strategy and can be applied to enhance animal monitoring systems."],["dc.description.sponsorship","Open-Access-Publikationsfonds 2021"],["dc.identifier.doi","10.3390/s21227512"],["dc.identifier.pii","s21227512"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/97888"],["dc.language.iso","en"],["dc.notes.intern","DOI-Import GROB-507"],["dc.relation.eissn","1424-8220"],["dc.rights","CC BY 4.0"],["dc.rights.uri","https://creativecommons.org/licenses/by/4.0/"],["dc.title","Detecting Animal Contacts—A Deep Learning-Based Pig Detection and Tracking Approach for the Quantification of Social Contacts"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dc.type.subtype","original_ja"],["dc.type.version","published_version"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.artnumber","920302"],["dc.bibliographiccitation.journal","Frontiers in Veterinary Science"],["dc.bibliographiccitation.volume","9"],["dc.contributor.affiliation","Rosengart, Stephan; 1Clinic for Swine and Small Ruminants, Forensic Medicine and Ambulatory Service, University of Veterinary Medicine Hannover, Foundation, Hanover, Germany"],["dc.contributor.affiliation","Chuppava, Bussarakam; 2Institute for Animal Nutrition, University of Veterinary Medicine Hannover, Foundation, Hanover, Germany"],["dc.contributor.affiliation","Trost, Lea-Sophie; 3Department of Animal Sciences, Livestock Systems, Georg-August-University Göttingen, Göttingen, Germany"],["dc.contributor.affiliation","Henne, Hubert; 4BHZP GmbH, Dahlenburg-Ellringen, Germany"],["dc.contributor.affiliation","Tetens, Jens; 5Department of Animal Sciences, University of Göttingen, Göttingen, Germany"],["dc.contributor.affiliation","Traulsen, Imke; 3Department of Animal Sciences, Livestock Systems, Georg-August-University Göttingen, Göttingen, Germany"],["dc.contributor.affiliation","Deermann, Ansgar; 6EVH Select GmbH, Meppen, Germany"],["dc.contributor.affiliation","Wendt, Michael; 1Clinic for Swine and Small Ruminants, Forensic Medicine and Ambulatory Service, University of Veterinary Medicine Hannover, Foundation, Hanover, Germany"],["dc.contributor.affiliation","Visscher, Christian; 2Institute for Animal Nutrition, University of Veterinary Medicine Hannover, Foundation, Hanover, Germany"],["dc.contributor.author","Rosengart, Stephan"],["dc.contributor.author","Chuppava, Bussarakam"],["dc.contributor.author","Trost, Lea-Sophie"],["dc.contributor.author","Henne, Hubert"],["dc.contributor.author","Tetens, Jens"],["dc.contributor.author","Traulsen, Imke"],["dc.contributor.author","Deermann, Ansgar"],["dc.contributor.author","Wendt, Michael"],["dc.contributor.author","Visscher, Christian"],["dc.date.accessioned","2022-10-04T10:21:51Z"],["dc.date.available","2022-10-04T10:21:51Z"],["dc.date.issued","2022"],["dc.date.updated","2022-11-11T13:14:27Z"],["dc.description.abstract","Precision livestock farming can combine sensors and complex data to provide a simple score of meaningful productivity, pig welfare, and farm sustainability, which are the main drivers of modern pig production. Examples include using infrared thermography to monitor the temperature of sows to detect the early stages of the disease. To take account of these drivers, we assigned 697 hybrid (BHZP db. Viktoria) sows to four parity groups. In addition, by pooling clinical findings from every sow and their piglets, sows were classified into three groups for the annotation: healthy, clinically suspicious, and diseased. Besides, the udder was thermographed, and performance data were documented. Results showed that the piglets of diseased sows with eighth or higher parity had the lowest daily weight gain [healthy; 192 g ± 31.2, clinically suspicious; 191 g ± 31.3, diseased; 148 g ± 50.3 (\r\n p\r\n < 0.05)] and the highest number of stillborn piglets (healthy; 2.2 ± 2.39, clinically suspicious; 2.0 ± 1.62, diseased; 3.91 ± 4.93). Moreover, all diseased sows showed higher maximal skin temperatures by infrared thermography of the udder (\r\n p\r\n < 0.05). Thus, thermography coupled with Artificial Intelligence (AI) systems can help identify and orient the diagnosis of symptomatic animals to prompt adequate reaction at the earliest time."],["dc.identifier.doi","10.3389/fvets.2022.920302"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/114517"],["dc.language.iso","en"],["dc.notes.intern","DOI-Import GROB-600"],["dc.publisher","Frontiers Media S.A."],["dc.relation.eissn","2297-1769"],["dc.rights.uri","https://creativecommons.org/licenses/by/4.0/"],["dc.title","Characteristics of thermal images of the mammary gland and of performance in sows differing in health status and parity"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.artnumber","100655"],["dc.bibliographiccitation.issue","11"],["dc.bibliographiccitation.journal","Animal: The International Journal of Animal Bioscience"],["dc.bibliographiccitation.volume","16"],["dc.contributor.author","Trost, L.S."],["dc.contributor.author","Zeidler, S."],["dc.contributor.author","Ammer, S."],["dc.contributor.author","Rosengart, S."],["dc.contributor.author","Wendt, M."],["dc.contributor.author","Visscher, C."],["dc.contributor.author","Tetens, J."],["dc.contributor.author","Traulsen, I."],["dc.date.accessioned","2022-11-01T10:17:43Z"],["dc.date.available","2022-11-01T10:17:43Z"],["dc.date.issued","2022"],["dc.description.sponsorship","Open-Access-Publikationsfonds 2022"],["dc.identifier.doi","10.1016/j.animal.2022.100655"],["dc.identifier.pii","S1751731122002129"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/116887"],["dc.language.iso","en"],["dc.notes.intern","DOI-Import GROB-605"],["dc.relation.issn","1751-7311"],["dc.rights","CC BY-NC-ND 4.0"],["dc.rights.uri","https://www.elsevier.com/tdm/userlicense/1.0/"],["dc.title","Development of a new grading system to assess the foster performance of lactating sows"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dc.type.version","unpublished"],["dspace.entity.type","Publication"]]