scholarly journals Short communication: Applicability of feeding behaviour traits as high-throughput phenotyping methods for identifying protein-efficient pigs

2020 ◽  
Author(s):  
Esther Ewaoluwagbemiga ◽  
Giuseppe Bee ◽  
Claudia Kasper
Keyword(s):  
High Throughput ◽  
Feed Intake ◽  
Feeding Behaviour ◽  
Carcass Composition ◽  
Large White ◽  
Automatic Feeder ◽  
High Throughput Phenotyping ◽  
The Relationship ◽  
Feeding Behaviours ◽  
Selection Of

AbstractThe objective of this study was to explore the potential of using automatically recorded feeding behaviour as a proxy for protein efficiency (PE) by investigating the relationship between feeding behaviour and PE. A total of 402 Swiss Large White pigs were used in this experiment (204 females and 198 castrated males). Pigs were fed ad libitum on a reduced protein diet (80% of standard) from 20kg to 100kg BW. Individual daily feed intake was monitored and carcass composition at slaughter was determined by dual-energy X-ray absorptiometry (DXA). The PE was calculated as the ratio of protein in the carcass (estimated by DXA) to the total protein consumed. Feeding behaviour traits monitored were daily feed intake (DFI; g/day), feed intake per visit (FIV; g/visit), number of daily visits (NDV; visits/day), duration of visits (DUV; min/visit), feeding rate (FR; g/min), and feeder occupation (FO; min/day). Regression analysis was used to estimate the relationship between PE and feeding behaviour, while correcting for the effects of sex, experimental series and age. Weak Pearson’s correlations (−0.25 to 0.12) were found between PE and feeding behaviour traits. Beta (β) estimates from this analysis for feeding behaviours were also very low (0.0093% to 0.087%). An increase in FR (g/min) will increase PE by 0.087% and an increase in DFI (g/day) will decrease PE by 0.0093%. In conclusion, feeding behaviours are not suitable for the identification of protein-efficient pigs, as estimates are negligible.ImplicationsThis study suggests that feeding behaviour traits recorded via automatic feeder are not reliable predictors of protein efficiency in Swiss Large White pigs receiving a protein-reduced diet. Despite the large differences in protein efficiency, only negligible changes in a range of feeding behaviours were observed. Hence, feeding behaviours are not suitable proxies for the high-throughput phenotyping of protein efficiency and the selection of live animals for use in nutrition experiments or for breeding.

Effect of level of feed intake on the performance and carcass composition of growing pigs

1972 ◽  
Vol 14 (2) ◽  
pp. 199-208 ◽  
Author(s):  
R. S. Barber ◽  
R. Braude ◽  
K. G. Mitchell ◽  
R. J. Pittman
Keyword(s):  
Feed Intake ◽  
Genetic Background ◽  
Live Weight ◽  
Growing Pigs ◽  
Carcass Composition ◽  
Large White ◽  
Enzootic Pneumonia ◽  
Litter Mate ◽  
Different Genetic Background ◽  
Different Levels

SUMMARY1. Twelve blocks of six enzootic-pneumonia-free Large White litter-mate pigs were individually fed, wet, from 20 to 92 kg live weight on six different levels of feed intake. Four groups were fed according to scales based on live weight and two were fed on a ‘semi-ad libitum’ system. One of the scales used was based on the ARC (1967) recommendations.2. Pigs on ‘semi-ad libitum’ feeding grew significantly faster than those on scale feeding although the feed: gain ratios were similar. Differences in performance between the four scale-fed groups were relatively small.3. Although treatment differences in carcass measurements were in the main small, the commercial grading results favoured the carcasses from the scale-fed pigs. The firmness of backfat assessed by thumb pressure was reduced as the level of feeding was increased.4. The results were compared with those obtained in a similar trial carried out at Shinfield in 1957 using pigs of a completely different genetic background. The general conclusions reached were similar in the two trials, that to obtain the most satisfactory overall results some form of controlled scale-feeding was necessary.

scholarly journals Validity of Weight Estimation Models in Pigs Reared under Different Management Conditions

2014 ◽  
Vol 2014 ◽  
pp. 1-5 ◽  
Author(s):  
Marvelous Sungirai ◽  
Lawrence Masaka ◽  
Tonderai Maxwell Benhura
Keyword(s):  
Body Length ◽  
Live Weight ◽  
Linear Regression Method ◽  
Linear Measurements ◽  
Large White ◽  
High Positive Correlation ◽  
Positive Correlation ◽  
Positive Correlations ◽  
The Relationship ◽  
Selection Of

A study was carried out to determine the relationship between linear body measurements and live weight in Landrace and Large White pigs reared under different management conditions in Zimbabwe. Data was collected for body length, heart girth, and live weight in 358 pigs reared under intensive commercial conditions. The stepwise multiple linear regression method was done to develop a model using a random selection of 202 records of pigs. The model showed that age, body length, and heart girth were useful predictors of live weight in these pigs with significantly high positive correlations observed. The model was internally validated using records of the remaining 156 pigs and there was a significantly high positive correlation between the actual and predicted weights. The model was then externally validated using 40 market age pigs reared under communal conditions and there was a significantly low positive correlation between the actual and predicted weights. The results of the study show that while linear measurements can be useful in predicting pig weights the appropriateness of the model is also influenced by the management of the pigs. Models can only be applicable to pigs reared under similar conditions of management.

scholarly journals Toward high-throughput phenotyping: unbiased automated feature extraction and selection from knowledge sources

2015 ◽  
Vol 22 (5) ◽  
pp. 993-1000 ◽  
Author(s):  
Sheng Yu ◽  
Katherine P Liao ◽  
Stanley Y Shaw ◽  
Vivian S Gainer ◽  
Susanne E Churchill ◽  
...  
Keyword(s):  
Rheumatoid Arthritis ◽  
Feature Extraction ◽  
High Throughput ◽  
Knowledge Sources ◽  
Phenotype Classification ◽  
Feature Extraction And Selection ◽  
Automated Feature Extraction ◽  
High Throughput Phenotyping ◽  
Text Features ◽  
Selection Of

Abstract Objective Analysis of narrative (text) data from electronic health records (EHRs) can improve population-scale phenotyping for clinical and genetic research. Currently, selection of text features for phenotyping algorithms is slow and laborious, requiring extensive and iterative involvement by domain experts. This paper introduces a method to develop phenotyping algorithms in an unbiased manner by automatically extracting and selecting informative features, which can be comparable to expert-curated ones in classification accuracy. Materials and methods Comprehensive medical concepts were collected from publicly available knowledge sources in an automated, unbiased fashion. Natural language processing (NLP) revealed the occurrence patterns of these concepts in EHR narrative notes, which enabled selection of informative features for phenotype classification. When combined with additional codified features, a penalized logistic regression model was trained to classify the target phenotype. Results The authors applied our method to develop algorithms to identify patients with rheumatoid arthritis and coronary artery disease cases among those with rheumatoid arthritis from a large multi-institutional EHR. The area under the receiver operating characteristic curves (AUC) for classifying RA and CAD using models trained with automated features were 0.951 and 0.929, respectively, compared to the AUCs of 0.938 and 0.929 by models trained with expert-curated features. Discussion Models trained with NLP text features selected through an unbiased, automated procedure achieved comparable or slightly higher accuracy than those trained with expert-curated features. The majority of the selected model features were interpretable. Conclusion The proposed automated feature extraction method, generating highly accurate phenotyping algorithms with improved efficiency, is a significant step toward high-throughput phenotyping.

scholarly journals Aerial High-Throughput Phenotyping Enabling Indirect Selection for Grain Yield at the Early-generation Seed-limited Stages in Breeding Programs

2020 ◽  
Author(s):  
Margaret R. Krause ◽  
Suchismita Mondal ◽  
José Crossa ◽  
Ravi P. Singh ◽  
Francisco Pinto ◽  
...  
Keyword(s):  
Grain Yield ◽  
High Throughput ◽  
Vegetation Indices ◽  
Early Generation ◽  
Breeding Programs ◽  
Breeding Lines ◽  
High Throughput Phenotyping ◽  
Seed Increase ◽  
Yield Trials ◽  
Selection Of

ABSTRACTBreeding programs for wheat and many other crops require one or more generations of seed increase before replicated yield trials can be sown. Extensive phenotyping at this stage of the breeding cycle is challenging due to the small plot size and large number of lines under evaluation. Therefore, breeders typically rely on visual selection of small, unreplicated seed increase plots for the promotion of breeding lines to replicated yield trials. With the development of aerial high-throughput phenotyping technologies, breeders now have the ability to rapidly phenotype thousands of breeding lines for traits that may be useful for indirect selection of grain yield. We evaluated early generation material in the irrigated bread wheat (Triticum aestivum L.) breeding program at the International Maize and Wheat Improvement Center to determine if aerial measurements of vegetation indices assessed on small, unreplicated plots were predictive of grain yield. To test this approach, two sets of 1,008 breeding lines were sown both as replicated yield trials and as small, unreplicated plots during two breeding cycles. Vegetation indices collected with an unmanned aerial vehicle in the small plots were observed to be heritable and moderately correlated with grain yield assessed in replicated yield trials. Furthermore, vegetation indices were more predictive of grain yield than univariate genomic selection, while multi-trait genomic selection approaches that combined genomic information with the aerial phenotypes were found to have the highest predictive abilities overall. A related experiment showed that selection approaches for grain yield based on vegetation indices could be more effective than visual selection; however, selection on the vegetation indices alone would have also driven a directional response in phenology due to confounding between those traits. A restricted selection index was proposed for improving grain yield without affecting the distribution of phenology in the breeding population. The results of these experiments provide a promising outlook for the use of aerial high-throughput phenotyping traits to improve selection at the early-generation seed-limited stage of wheat breeding programs.

scholarly journals 227 Leveraging on high-throughput phenotyping technologies to optimize livestock genetic improvement and husbandry

2019 ◽  
Vol 97 (Supplement_3) ◽  
pp. 55-55
Author(s):  
Guilherme J M Rosa ◽  
João R R Dorea ◽  
Arthur Francisco Araujo Fernandes ◽  
Tiago L Passafaro
Keyword(s):  
Computer Vision ◽  
Image Analysis ◽  
High Throughput ◽  
Feed Intake ◽  
Genetic Improvement ◽  
Milk Composition ◽  
Sensor Technology ◽  
Efficient Data ◽  
High Throughput Phenotyping ◽  
Complex Relationships

Abstract The advent of fully automated data recording technologies and high-throughput phenotyping (HTP) systems has opened up a myriad of opportunities to advance breeding programs and livestock husbandry. Such technologies allow scoring large number of animals for novel phenotypes and indicator traits to boost genetic improvement, as well as for real-time monitoring of animal behavior and development for optimized management decisions. HTP tools include, for example, image analysis and computer vision, sensor technology for motion, sound and chemical composition, and spectroscopy. Applications span from health surveillance, precision nutrition, and control of meat and milk composition and quality. However, the application of HTP requires sophisticated statistical and computational approaches for efficient data management and appropriate data mining, as it involves large datasets with many covariates and complex relationships. In this talk we will discuss some of the challenges and potentials of HTP in livestock. Some examples to be presented include the utilization of automated feeders to record feed intake and to monitor feeding behavior in broilers, milk-spectra information to predict dairy cattle feed intake, and image analysis and computer vision to monitor growth and body condition in pigs and cattle. HTP and big data will become an essential component of modern livestock operations in the context of precision animal agriculture, boosting animal welfare, environmental footprint, and overall sustainability of animal production.

scholarly journals Brahman and Brahman crossbred cattle grown on pasture and in feedlots in subtropical and temperate Australia. 3. Feed efficiency and feeding behaviour of feedlot-finished animals

2009 ◽  
Vol 49 (6) ◽  
pp. 452 ◽  
Author(s):  
K. M. Schutt ◽  
P. F. Arthur ◽  
H. M. Burrow
Keyword(s):  
Feed Intake ◽  
Feed Efficiency ◽  
Feeding Behaviour ◽  
Eating Rate ◽  
Feed Conversion ◽  
Relative Growth ◽  
South Wales ◽  
Kleiber Ratio ◽  
Time Eating ◽  
Selection Of

The objective of this experiment was to quantify differences in feed efficiency and feeding behaviour of 470 heifers and steers by Brahman, Belmont Red, Santa Gertrudis, Angus, Hereford, Shorthorn, Charolais and Limousin sires mated to Brahman dams. Animals were bred in subtropical Queensland and finished in a temperate New South Wales feedlot. Animals averaged 598 days of age and 425.8 kg at the start of the feed intake test period. Sire breeds did not differ for eating rate, feed conversion ratio or relative growth rate. Generally, higher daily feed intakes (DFI) corresponded with higher average daily gains (ADG). Straightbred Brahmans fed the most frequently (16.6 ± 0.8 sessions/day; P < 0.05) but spent the least time eating of all breeds (67.4 ± 2.7 min/day; P < 0.001). Least squares means for Brahman, Belmont Red, Santa Gertrudis, Angus, Hereford, Shorthorn, Charolais and Limousin sired progeny, respectively, for residual feed intake (RFI; P < 0.05) were 0.02 ± 0.16, 0.14 ± 0.13, –0.10 ± 0.23, 0.54 ± 0.17, –0.27 ± 0.18, 0.29 ± 0.18, –0.46 ± 0.16 and –0.21 ± 0.13 kg/day, and for ADG (P < 0.001) were 1.06 ± 0.05, 1.17 ± 0.04, 1.52 ± 0.08, 1.47 ± 0.06, 1.46 ± 0.06, 1.46 ± 0.06, 1.35 ± 0.06 and 1.38 ± 0.05 kg/day. While straightbred Brahmans did not differ from all other sire breeds for RFI, their lower appetite relative to crossbred contemporaries resulted in the lowest DFI (P < 0.001) and lowest ADG (P < 0.001) overall. Angus sired crosses were the least efficient feeders and spent the most time eating, consumed the most feed and had the highest RFI, but were not significantly different to Santa Gertrudis and Shorthorn crosses for these traits. Angus sired crosses spent 24.1 and 15.4 min/day more time eating (P < 0.001) than straightbred Brahmans and Charolais crosses, and consumed 35 and 13% more feed (P < 0.001) respectively. Charolais sired crosses were the most feed efficient with the lowest RFI and intermediate DFI, and did not differ significantly from the highest ranking sire breeds for ADG or Kleiber ratio. While Belmont Red crosses did not differ from all breeds for RFI, they had significantly lower DFI than British and Santa Gertrudis crosses resulting in lower ADG (P < 0.001) relative to these sire breeds. Therefore, selection of Charolais, Hereford, Limousin and Santa Gertrudis sire breeds would result in the most feed efficient (low RFI) crosses with Brahman without any sacrifice in ADG.

The relationship between the polymorphism of the porcine CAST gene and productive traits in pigs

2015 ◽  
Vol 95 (3) ◽  
pp. 361-367 ◽  
Author(s):  
Paweł Urbański ◽  
Mariusz Pierzchała ◽  
Arkadiusz Terman ◽  
Marian Kamyczek ◽  
Marian Różycki ◽  
...  
Keyword(s):  
Extreme Values ◽  
Carcass Traits ◽  
Restriction Enzymes ◽  
Study Groups ◽  
Least Square ◽  
Large White ◽  
Productive Traits ◽  
The Relationship ◽  
Selection Of ◽  
Cast Gene

Urbański, P., Pierzchała, M., Terman, A., Kamyczek, M., Różycki, M., Roszczyk, A. and Czarnik, U. 2015. The relationship between the polymorphism of the porcine CAST gene and productive traits in pigs. Can. J. Anim. Sci. 95: 361–367. The aim of the study was to characterize the polymorphism of the calpastatin gene identified with ApaLI, Hpy188I and PvuII restriction enzymes in two pig breeds and one line bred in Poland, and to evaluate the relationship between the CAST genotype and carcass traits. The analysis covered a total of 617 pigs of two breeds, Polish Landrace (185) and Polish Large White (216), and synthetic line L990 (216). All animals studied appeared to be monomorphic at two loci: CAST/ApaLI and CAST/Hpy188I, while three genotypes were observed at CAST/PvuII locus. Statistical analysis was carried out for each breed separately using the least square methods of the GLM procedure. The model included the effect of the CAST genotype, fixed effect of the RYR1 genotype and the effect of the sire. Because the RYR1 genotype could significantly modify the effect of other genes, the effect of the RYR1 genotype was included in the statistical model. The relationship between the polymorphism and several productive traits was identified in each of the study groups of pigs. Animals carrying the heterozygous genotype at this locus showed most extreme values for some of the traits tested. Our results suggest that the CAST /PvuII genotype might be utilized in the selection of valuable pig carcass traits, particularly weight and size of the loin.

scholarly journals HIGH THROUGHPUT PHENOTYPING OF PHYSIOLOGICAL GROWTH DYNAMICS FROM UAS-BASED 3D MODELING IN SOYBEAN

2019 ◽  
Vol XLII-2/W13 ◽  
pp. 357-361 ◽  
Author(s):  
M. Herrero-Huerta ◽  
K. M. Rainey
Keyword(s):  
High Throughput ◽  
Digital Camera ◽  
Growth Dynamics ◽  
Cost Effective ◽  
Growing Season ◽  
3D Modelling ◽  
Crop Genetics ◽  
High Throughput Phenotyping ◽  
Research And Education ◽  
Selection Of

<p><strong>Abstract.</strong> Nowadays, an essential tool to improve the efficiency of crop genetics is automated, precise and cost-effective phenotyping of the plants. The aim of this study is to generate a methodology for high throughput phenotyping the physiological growth dynamics of soybeans by UAS-based 3D modelling. During the 2018 growing season, a soybean experiment was performed at the Agronomy Center for Research and Education (ACRE) in West-Lafayette (Indiana, USA). Periodic images were acquired by G9X Canon compact digital camera on board senseFly eBee. The study area is reconstructed in 3D by Image-based modelling. Algorithms and techniques were combined to analyse growth dynamics of the crop via height variations and to quantify biomass. Results provide practical information for the selection of phenotypes for breeding.</p>

Effect of selection for growth, FCR and lean % on feed intake corves in pigs

1994 ◽  
Vol 1994 ◽  
pp. 17-17
Author(s):  
H.A.M. van der Steen ◽  
P.W. Knap
Keyword(s):  
Feed Intake ◽  
Performance Test ◽  
Linear Models ◽  
Model Parameters ◽  
Large White ◽  
Simple Method ◽  
Selection Procedures ◽  
Available Technology ◽  
The Impact ◽  
The Relationship

Available technology allows pig breeding companies to automate feed intake recording during performance test. This provides data on ‘average daily feed intake’ as recorded with more traditional manual systems. It also results in feed intake curves, i.e. the relationship between ‘days on test’ and ‘daily feed intake’. This information can be used in different ways. The feed intake curve may be described using sophisticated linear or non-linear models; these may describe the feed intake curve accurately, but model parameters cannot be used easily in genetic/economic evaluation in the context of a breeding programme. A simple method to describe feed intake curves is used in this paper, allowing for easy interpretation of the results. The objective is to study the impact of existing selection procedures on the feed intake curve and the utilisation of variation in its shape in pig breeding.Performance test data of 1331 boars of a Large White based line, collected from November 1990 to March 1993 were analysed. Boars are tested over a 12 week period, starting at approximately 30 kg. Feed intake data are recorded with the Hunday FIRE system.

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