| Title: | Study on the Discrimination of Possible Error Sources That Might Affect the Quality of Volatile Organic Compounds Signature in Dairy Cattle Using an Electronic Nose |
| Author(s): | Ali AS; Jacinto JGP; Mupsilonnchemyer W; Walte A; Kuhla B; Gentile A; Abdu MS; Kamel MM; Ghallab AM; |
| Address: | "Department of Theriogenology, Faculty of Veterinary Medicine, Cairo University, Giza P.O. Box 12211, Egypt. Department of Veterinary Medical Sciences, University of Bologna, Ozzano dell'Emilia, 40064 Bologna, Italy. AIRSENSE Analytics GmbH, 19061 Schwerin, Germany. Research Institute for Farm Animal Biology (FBN), Institute of Nutritional Physiology 'Oskar Kellner', 18196 Dummerstorf, Germany. Department of Animal Management and Behavior, Faculty of Veterinary Medicine, Cairo University, Giza P.O. Box 12211, Egypt" |
| ISSN/ISBN: | 2306-7381 (Electronic) 2306-7381 (Linking) |
| Abstract: | "Electronic nose devices (EN) have been developed for detecting volatile organic compounds (VOCs). This study aimed to assess the ability of the MENT-EGAS prototype-based EN to respond to direct sampling and to evaluate the influence of possible error sources that might affect the quality of VOC signatures. This study was performed on a dairy farm using 11 (n = 11) multiparous Holstein-Friesian cows. The cows were divided into two groups housed in two different barns: group I included six lactating cows fed with a lactating diet (LD), and group II included 5 non-lactating late pregnant cows fed with a far-off diet (FD). Each group was offered 250 g of their respective diet; 10 min later, exhalated breath was collected for VOC determination. After this sampling, 4 cows from each group were offered 250 g of pellet concentrates. Ten minutes later, the exhalated breath was collected once more. VOCs were also measured directly from the feed's headspace, as well as from the environmental backgrounds of each. Principal component analyses (PCA) were performed and revealed clear discrimination between the two different environmental backgrounds, the two different feed headspaces, the exhalated breath of groups I and II cows, and the exhalated breath within the same group of cows before and after the feed intake. Based on these findings, we concluded that the MENT-EGAS prototype can recognize several error sources with accuracy, providing a novel EN technology that could be used in the future in precision livestock farming" |
| Keywords: | VOCs electronic nose exhaled breath non-invasive analysis precision livestock farming precision medicine; |
| Notes: | "PubMed-not-MEDLINEAli, Asmaa S Jacinto, Joana G P Mupsilonnchemyer, Wolf Walte, Andreas Kuhla, Bjorn Gentile, Arcangelo Abdu, Mohamed S Kamel, Mervat M Ghallab, Abdelrauf Morsy eng Switzerland 2022/09/23 Vet Sci. 2022 Aug 29; 9(9):461. doi: 10.3390/vetsci9090461" |
