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- Jäderkvist Fegraeus, Kim, et al.
(författare)
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Lack of significant associations with early career performance suggest no link between the DMRT3 "Gait Keeper" mutation and precocity in Coldblooded trotters
- 2017
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Ingår i: PLOS ONE. - : PUBLIC LIBRARY SCIENCE. - 1932-6203. ; 12:5
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Tidskriftsartikel (refereegranskat)abstract
- The Swedish-Norwegian Coldblooded trotter (CBT) is a local breed in Sweden and Norway mainly used for harness racing. Previous studies have shown that a mutation from cytosine (C) to adenine (A) in the doublesex and mab-3 related transcription factor 3 (DMRT3) gene has a major impact on harness racing performance of different breeds. An association of the DMRT3 mutation with early career performance has also been suggested. The aim of the current study was to investigate this proposed association in a randomly selected group of CBTs. 769 CBTs (485 raced, 284 unraced) were genotyped for the DMRT3 mutation. The association with racing performance was investigated for 13 performance traits and three different age intervals: 3 years, 3 to 6 years, and 7 to 10 years of age, using the statistical software R. Each performance trait was analyzed for association with DMRT3 using linear models. The results suggest no association of the DMRT3 mutation with precocity (i.e. performance at 3 years of age). Only two traits (race time and number of disqualifications) were significantly different between the genotypes, with AA horses having the fastest times and CC horses having the highest number of disqualifications at 3 years of age. The frequency of the AA genotype was significantly lower in the raced CBT sample compared with the unraced sample and less than 50% of the AA horses participated in a race. For the age intervals 3 to 6 and 7 to 10 years the AA horses also failed to demonstrate significantly better performance than the other genotypes. Although suggested as the most favorable genotype for racing performance in Standardbreds and Finnhorses across all ages, the AA genotype does not appear to be associated with superior performance, early or late, in the racing career of CBTs.
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| 2. |
- Wiklund Lindström, Susanne, et al.
(författare)
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The importance of balanced data sets for partial least squares discriminant analysis : classification problems using hyperspectral imaging data
- 2011
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Ingår i: Journal of Near Infrared Spectroscopy. - : IM Publications. - 0967-0335 .- 1751-6552. ; 19:4, s. 233-241
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Tidskriftsartikel (refereegranskat)abstract
- This study investigates the effect of imbalanced spectral data in the training set, when developing partial least squares discriminant analysis (PLS-DA) classification models for use in future predictions. The experimental study was performed using a real hyperspectral short-wavelength infrared image data set collected from bakery products (buns) containing contaminants (flies) but similar applications for other insects, paper and plastic were also tested. The contaminants represent a very small proportion of the images relative to the bun. The PLS-DA model aims at accurately detecting and classifying the contaminants and this requires a modification of the calibration data set. The paper deals with problems caused by unbalanced calibration data sets and how to remedy them. In the example it was demonstrated that, by balancing the calibration data from 58,476 bun pixels + 279 fly pixels to 279 bun + 279 fly pixels, the number of true predictions could be improved with a smaller number of PLS components used in the model. The improvement for flies increased from 65% true predictions with ten PLS components to >99% true prediction with five to six PLS components. The true prediction for bun went from 100% to 99.5% with six PLS components which is an acceptable reduction. Theoretical explanations are included.
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