@article{c401f4b1e3b4434b9f02bf18b70b348c,
title = "Assessing the Feasibility of Using Kinect 3D Images to Predict Light Lamb Carcasses Composition from Leg Volume",
abstract = "This study aimed to evaluate the accuracy of the leg volume obtained by the Microsoft Kinect sensor to predict the composition of light lamb carcasses. The trial was performed on carcasses of twenty-two male lambs (17.6 ± 1.8 kg, body weight). The carcasses were split into eight cuts, divided into three groups according to their commercial value: high-value, medium value, and low-value group. Linear, area, and volume of leg measurements were obtained to predict carcass and cuts composition. The leg volume was acquired by two different methodologies: 3D image reconstruction using a Microsoft Kinect sensor and Archimedes principle. The correlation between these two leg measurements was significant (r = 0.815, p < 0.01). The models to predict cuts and carcass traits that include leg Kinect 3D sensor volume are very good in predicting the weight of the medium value and leg cuts (R 2 of 0.763 and 0.829, respectively). Furthermore, the model, which includes the Kinect leg volume, explained 85% of its variation for the carcass muscle. The results of this study confirm the good ability to estimate cuts and carcass traits of light lamb carcasses with leg volume obtained with the Kinect 3D sensor. ",
keywords = "Microsoft Kinect, 3D image, leg volume, carcass composition, lambs, Leg volume, Lambs, Carcass composition",
author = "Silva, {Severiano R.} and Mariana Almeida and Isabella Condotta and Andr{\'e} Arantes and Cristina Guedes and Virg{\'i}nia Santos",
note = "Funding Information: Funding: The authors acknowledge financial support through project INTERACT—“Integrative Research in Environment, Agro-Chains and Technology”, reference NORTE-01-0145-FEDER-000017, in its line of research entitled ISAC, co-financed by the European Regional Development Fund through NORTE 2020 (North Regional Operational Program 2014/2020). Authors integrated into the research unit CECAV, and research, was further financed by the National Funds from FCT, the Portuguese Foundation for Science and Technology, project number UIDB/CVT/00772/2020. Funding Information: The authors acknowledge financial support through project INTERACT??Integrative Research in Environment, Agro-Chains and Technology?, reference NORTE-01-0145-FEDER-000017, in its line of research entitled ISAC, co-financed by the European Regional Development Fund through NORTE 2020 (North Regional Operational Program 2014/2020). Authors integrated into the research unit CECAV, and research, was further financed by the National Funds from FCT, the Portuguese Foundation for Science and Technology, project number UIDB/CVT/00772/2020. The authors thank and acknowledge the University of Tr?s-os-Montes and Alto Douro experimental farm and animal nutrition laboratory staff. Publisher Copyright: {\textcopyright} 2021 by the authors. Licensee MDPI, Basel, Switzerland.",
year = "2021",
month = dec,
doi = "10.3390/ani11123595",
language = "English (US)",
volume = "11",
journal = "Animals",
issn = "2076-2615",
publisher = "Multidisciplinary Digital Publishing Institute (MDPI)",
number = "12",
}