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REPRODUCTIVE AND ADAPTATION QUALITIES OF CANADIAN BREEDING HOGS COMMERCIALLY REARED IN LOWER VOLGA REGION

2017· article· en· W2753493176 on OpenAlexaboutno aff
М И Сложенкина, Д.В. Николаев, Yu.N. Fedorov

Bibliographic record

VenueSel skokhozyaistvennaya Biologiya · 2017
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAnimal Nutrition and Health
Canadian institutionsnot available
FundersRussian Science Foundation
KeywordsPurebredBiologyAnimal scienceLivestockCrossbreedBOARPig breedingVeterinary medicineSemenEcology

Abstract

fetched live from OpenAlex

A purchase of foreign genetic material, including Canadian Yorkshire, Landrace and Duroc pigs, in order to increase the productivity of dpmestic pig breeds has recently been a steady trend in Russia.The adaptive ability of pigs is the most important feature determining their availability for industrial growing technology.The purpose of our work was to study the adaptiveness and performance of purebred Yorkshire, Landrace and Duroc pigs of Canadian selection under the conditions of OAO Cossack Holding Krasnodonskoe (Ilovlinskii Region, Volgograd Province), a large regional commercial farm for growing and fattening pigs.The study was carried out in 2013-2014.In assessing natural resistance, the auto microflora of deep skin layers was estimated.The number of erythrocytes, leukocytes, the percentage of leukocytes, the phagocytic index, total blood proteins, protein fractions, and the concentration of immunoglobulins (Ig) G-, M-and A-isotypes in blood serum were also determined as parameters of natural resistance.The reproductive performance of pigs was assessed according to the data of evaluation and livestock records.On fattening, the early maturity, overall, average per day and relative live weight gain were recorded.Sperm production in boar-producers was estimated using conventional methods, based on the volume of ejaculate and sperm concentration and motility.The economic efficiency of different pig breeds was assessed on the basis of analysis of actual and on-farm annual activities.In 2014, the analysis of populations of different breeds showed that there were 832 Yorkshire breeding sows, 50 Landrace breeding sows and 58 Duroc breeding sows.The Yorkshire sows produced 2028 piglets, their livability by weaning reached 90.83 %; for the Landrace breed, there were 85 piglets and 85.88 %, respectively (4.95 % less compared to that in Yorkshire piglets), and for the Duroc breed, these figures were 88 and 85.30 % (5.53 % less compared to that in Yorkshire piglets).Among the five families of the Yorkshire sows, the largest part of the population belonged to the families of Volga (42.17 %), Soya (17.07 %) and Oka (15.86 %).The Landrace breed sows herd was concentrated in the families of Loga (23.81 %) and Luna (23.81 %).The greatest part of the Duroc sows was related to Dakota (28.00 %) and Dama (28.00 %) families.The Yorkshire boars had a fat thickness above 6-7th thoracic vertebrae equal to 14.8 mm, which was 6.61 % less compared to the Landrace breed, and 5.40 % less compared to Duroc breed.The prolificacy of Yorkshire boars was 12.16 heads, which was 0.23 and 1.46 heads more than in Landrace and Duroc breeds, respectively.In assessing the exterior indices, the Yorkshire boars were superior to the boars of Landrace and Duroc breeds by 0.33 and 0.20 points, respectively.The natural resistance characteristics have shown a higher potential for adaptability of the Yorkshire breed to new climatic conditions and technologies.Calculation of economic efficiency of pork production has shown that the income for the Yorkshire piglet sale by live weight was 1,520 and 10,640 rubles higher compared to that for the Landrace and Duroc piglets, and the profitability was 0.86 and 4.99 % higher, respectively; for the carcasses the income exceeding amounted to 0.92 and 5.30 %, respectively.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.258
Threshold uncertainty score0.519

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.155
GPT teacher head0.282
Teacher spread0.127 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations1
Published2017
Admission routes1
Has abstractyes

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