Publications by authors named "Ravagnolo O"

Selection for feed efficiency is the goal for many genetic breeding programs in beef cattle. Residual feed intake has been included in genetic evaluations to reduce feed intake without compromising performance traits as liveweight, body gain or carcass traits. However, measuring feed intake is expensive, and only a small percentage of selection candidates are phenotyped.

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  • Crossbreeding can enhance reproductive traits in cattle herds through advantages like breed differences, heterosis, and breed complementarity.
  • The study analyzed reproductive data from 1,164 females across various genetic groups of Hereford, Angus, Nellore, and Salers under grazing conditions, focusing on traits like artificial insemination probability, calving success, and days to calving.
  • Results showed that F1 crossbred females had better artificial insemination rates compared to purebreds, particularly crossbred A/H heifers and N/H cows, with dominance effects boosting the performance of heifers in terms of artificial insemination and calving success.
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  • Model-based accuracy in genetic evaluations is influenced by prediction error variance (PEV) and inbreeding coefficient (F), but ignoring inbreeding can lead to significant errors.
  • Ignoring inbreeding in reliability calculations and in the pedigree relationship matrix A results in skewed estimates, especially in rabbits, where inbreeding increases substantially over generations.
  • The study emphasizes the necessity of incorporating inbreeding in both settings to improve the accuracy of BLUP and SSGBLUP evaluations for various animal populations.
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Growth curves are useful for describing the sigmoid shape of an animal's weight pattern over time. The purpose of the present study was to describe, for the first time, a complete growth curve for pasture-fed Angus cows in Uruguay and to analyze the major fixed effects that affect the estimation of mature cow weight (CW). A total of 22,743 records from 5,284 cows belonging to 73 herds were used in the statistical analysis.

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The objective of this study was to examine the relationship between reproductive traits and heat stress. Nonreturn rate at 45 d (NR45) was analyzed in a fixed-effect model that included the temperature-humidity index (THI) from a nearby weather station as a measurement of heat stress. Data consisted of 150,200 first inseminations at first and later parities of 110,860 Holstein cows from 550 herds in Georgia, Tennessee, and Florida with weather information from 16 weather stations.

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The genetic component in heat tolerance for nonreturn rate in Holsteins was estimated using an animal linear model augmented by a random regression on a temperature-humidity index (THI). Data consisted of 18,059 nonreturn rates at 45,60, and 90 d after insemination and 81,674 first-parity test-day milk yields from 78 herds in Florida. The THI on the day of insemination or test day was added to each record.

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The objective of this study was to explore the possibility of reducing the number of weather stations for studies on genetics of heat tolerance in dairy cattle. The similarity of information from 21 Georgia weather stations was analyzed by cluster analysis. Two major clusters have been found, separating Georgia along the NE and SW line.

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Our data included 119,205 first-parity, test-day records from 15,002 Holsteins in 134 Georgia farms with temperature and humidity data from 21 weather stations throughout Georgia. The test-day model included the effects of herd test date, days-in-milk (DIM) classes, age, milking frequency, general additive effect, random regression on the heat-humidity index for heat-tolerance additive effect, general permanent environment, and the random regression on the heat-humidity index for a permanent environment. The general effects, which corresponded to effects in the current repeatability models, were assumed to be correlated with the heat-tolerance effects.

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Production data obtained from AIPL USDA included 119,337 first-parity, test-day records of 15,012 Holsteins from 134 Georgia farms collected in 1990 to 1997. Weather information was obtained from the Georgia Automated Environmental Monitoring Network and included daily minimum, average, and maximum temperatures and humidity for 21 stations throughout the state. Each test-day record was augmented with weather information from the closest weather station.

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