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Oslo, Norway

Gangsei L.E.,Animalia | Kongsro J.,Norsvin SA
Computers and Electronics in Agriculture | Year: 2016

A 3D expansion of Dijkstra's algorithm used for automatic segmentation and identification of the bones in CT images of live pigs was developed and validated. The major bones in the skeletons of 208 out of 485 live pigs (43%) were segmented and identified from the images without major errors. The segmentation and identification is executed through 8 main operations: (1) identify the full bone structure by a threshold of Hounsfield units, (2) identify forelimbs by voxel connectivity and set landmarks, (3-8) segment out and identify the individual bones in different main parts of the bone structure by the 3D expansion of Dijkstra's algorithm. The algorithms described will constitute an important basis for further work applying CT in pig breeding and management. © 2015 Elsevier B.V.


Haseth T.T.,Animalia | Haseth T.T.,Norwegian University of Life Sciences | Sorheim O.,NOFIMA Materials | Hoy M.,NOFIMA Materials | Egelandsdal B.,Norwegian University of Life Sciences
Meat Science | Year: 2012

Varying salt content in hams of equal brand is a major challenge for Norwegian dry-cured ham producers. This study was thus undertaken to test existing computed tomography (CT) calibration models for salt on entire hams, regarding predictability of salt content at different processing times including final ham and to study salt distribution during processing of dry-cured ham. Twenty-six hams were scanned by computed tomography (CT) 11 times during dry-curing for this purpose. However, previously established calibration models had to be adjusted as they overestimated salt in dry samples. Prediction of ultimate salt content was more accurate approaching the end of the dry-curing process (RMSEP = 0.351-0.595% salt). Inclusion of remaining weight loss improved the prediction accuracy in un-dried samples by approximately 0.1% NaCl. The prediction errors were sufficiently low to be of practical interest. © 2011 Elsevier Ltd.


Valle P.S.,Animalia | Valle P.S.,Molde University College
Animal Welfare | Year: 2010

The aim of this study was to explore the use of a hand-held algometer for the measurement of mechanical nociceptive thresholds (MNT) in sheep (Ovis aries). Twelve ewes were tested over three consecutive days by two operators, and MNTs were measured over six predetermined sites on both forelimbs every five minutes for 30 min. The effects of test period, measurement number within test period and different anatomical points on MNT levels were investigated, in addition to establishing baseline MNT levels for the sheeps' forelimbs. A significant decrease of MNT values was observed over the three consecutive test days and within each test period. The anatomical points located closest to the carpus and fetlock joints had significantly higher MNT values compared to the anatomical points located over the middle part of the metacarpus, possibly due to the protective function of the distal part of the extensor retinaculum and the dorsal pouch of the fetlock joint capsules. There was no difference in MNT values between the right and left foreleg. There was a tendency for a flattening out of the drop in MNT towards the last measurement. Hence, we suggest using the values from the last two measurements when determining normative values, and to habituate the ewes to the procedure of measuring MNT levels. Taking these factors into consideration, a hand-held algometer is a useful tool to measure MNTs in sheep. © 2010 Universities Federation for Animal Welfare.


Mage I.,Nofima AS | Wold J.P.,Nofima AS | Bjerke F.,Animalia | Segtnan V.,Nofima AS
Journal of Food Engineering | Year: 2013

A system for on-line sorting of meat trimmings into categories with different fat levels was developed and tested by simulations and pilot-plant trials. The system consists of a conveyor belt, a NIR imaging scanner (QV500, Tomra Sorting Solutions, Asker, Norway), a flow weigher and grader (both Marel hf, Iceland) and a host computer containing synchronising software and a sorting algorithm. The sorting algorithm is based on desirability functions, which makes it flexible when it comes to selecting number of categories, target values, limits for deviations and other restrictions. The results showed that the sorting algorithm works when the fat measurements are accurate, giving deviations from target lower than the selected ±1 percentage point limits. In reality there are some inaccuracies in the on-line fat measurements due to inhomogeneous meat trimmings. This leads to a systematic under-estimation of the fat percentage in low-fat categories and over-estimation in the high-fat categories. These biases can be reduced by e.g. improving the on-line fat measurement technology. However, simulations showed that the bias for either category was generally low (below 2 percentage points) and the current system therefore has potential for on-line implementation. © 2012 Elsevier Ltd. All rights reserved.


Trademark
Animalia | Date: 2003-03-25

Collars and leashes for animals; saddlery; animal blankets; animal carriers.

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