Evaluating Information Obtained from Diagnosis of Pregnancy Status of Beef Herds

Larson, Robert L.; White, Brad J.

doi:10.1016/j.cvfa.2016.01.005

Cited by 5 publications

(4 citation statements)

References 8 publications

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“…Reproductive management, particularly data recording of breeding events, was significantly associated with CR, aligning with expert opinions and previous study (Larson & White, 2016). This study identified a negative correlation between synchronization hormone usage and CR, contrasting with previous findings highlighting its benefits (Johnson & Day, 2004;Mialot et al, 2003;Thomas et al, 2016).…”

Section: Discussionsupporting

confidence: 72%

Factors Influencing Productivity and Sustainability of Small-Scale Beef Farms in Thailand

Panbamrungkij,

Inchaisri,

Phan-iam

et al. 2023

ABAC J

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Over the past few decades, Thailand has witnessed a decline in production from small-scale beef cattle farming, accompanied by a reduced interest from younger generations in continuing family farming. The present study aimed to determine the state of these farms based on good agricultural practices (GAP) and explored factors influencing beef herd productivity and the willingness of the next generation to sustain the family business. Data from 1,175 questionnaires from 34 provinces was analyzed using SPSS. Beef herds with higher calving rates (CR ≥ 60%) had better herd, reproductive, and health management scores compared with the lower CR (<60%) group. Results from a negative binomial regression showed that factors, i.e., prediction of calving date and routine deworming positively impacted CR, while others like feeding types, mineral supplements, vaccination and hormonal estrus synchronization negatively correlated with CR. Expert opinions (N = 83) highlighted the importance of recording systems, heat detection programs, pregnancy diagnosis, feeding type, sufficient qualified water supply and mineral supplements. The use of Artificial Neural Network (ANN) and GLM analysis also noted that farm potential score, farmer gender, and occupations were pivotal for the sustainability of beef farming. This research aids in strategizing for enhanced sustainable beef production in Thailand.

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Section: Discussionsupporting

confidence: 72%

Factors Influencing Productivity and Sustainability of Small-Scale Beef Farms in Thailand

Panbamrungkij,

Inchaisri,

Phan-iam

et al. 2023

ABAC J

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“…Established, controlled breeding seasons for a herd increases productivity compared to long or year-around breeding seasons [22]. Analyzing the herd reproductive data from a single breeding season in 21-day intervals allows for an overall assessment of the herd to determine differences in reproductive success between 21-day intervals as the breeding season progresses compared to desired patterns [23]. Analyzing the percent of calves being born over these intervals serves as a method to evaluate herd-level reproductive efficiency, but does not assess the reproductive efficiency of individual bulls.…”

Section: Discussionmentioning

confidence: 99%

Calving distributions of individual bulls in multiple-sire pastures

et al. 2017

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The objective of this project was to quantify patterns in the calving rate of sires in multiple-sire pastures over seven years at a large-scale cow-calf operation. Data consisted of reproductive and genomic records from multiple-sire breeding pastures (n = 33) at the United States Meat Animal Research Center (USMARC) from 2007 to 2013. Calving intervals were analyzed in 21-day periods. A ranking system for each bull was developed based on the calving rate per pasture over the breeding season, with Rank 1 = the bull with greatest calving rate, Rank 3 = the bull with the least calving rate, and Rank 2 = all other bulls. A total of 179 bulls and 3703 calves were successfully genotyped over seven years. A uniform distribution described the expected percentage of calves sired per rank within pasture. Rank 1 bulls sired 113% greater calves than the expected pasture-average, Rank 2 bulls sired 6% less than expected, and Rank 3 bulls sired 81% less than expected. A rank by calving interval interaction effect was identified (P < 0.05). A Rank 1 bull in calving interval 1 produced a greater average percent of the total calf crop over the entire season, compared to a Rank 2 and Rank 3 bull. The calving rate for individual sires is not homogeneous and there is a large difference between bulls siring the greatest and least number of calves. More research is needed to determine how rank changes over multiple breeding years and its association with dominance, libido, and fertility.

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“…To be included, fetal age estimation had to be collected in a manner that allowed categorizing individual cows into 20-or 21-day intervals. 4,5,6,7 If a herd was presented with fetal age estimated by month or trimester, the entire herd was excluded. The initial dataset included 625 herds with pregnancy diagnosis staged into 20-or 21-day intervals.…”

Section: Herd Descriptionmentioning

confidence: 99%

Herd level factors associated with pregnancy success and distribution in beef cow-calf herds

Fountain¹,

Larson²,

White³

2021

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Identifying factors that influence pregnancy success is important in order to optimize beef cowcalfherd management. A logistic regression model was used to evaluate the effect of relevant factors(categories were: herd size, body condition score, breeding season length, and timing of start of breedingseason) on the probability of pregnancy status at 2 time-points (day 21 and end of the breeding season).Data were collected by convenience sampling from herds (n = 241) consisting of 8,217 head located inthe Midwest and Great Plains regions of the US from 2012 to 2017. Herds with < 50 head had reducedprobability of pregnancy (51 and 78%) compared to medium-sized (50 - 99 head) herds (63 and 84%).Cows in thin body condition (score ≤ 4 out of 9) at pregnancy diagnosis had reduced probability ofbecoming pregnant (44 and 64%) compared to cows in moderate body condition ([score 5 - 6 out of 9] 62and 86%) and fleshy condition ([score ≥ 7 out of 9] 66 and 91%). Herds with a short (< 63 days) ormedium (63 - 84 days) breeding season had increased probability of pregnancy (65 and 58%) for the first21-day interval compared to herds with a long (> 84 days) breeding season (49%). Herds that started thebreeding season in the fall (September 30 - December 31) had higher probability of pregnancy at the endof the breeding season (88%) compared to spring (April 1 - June 30) start dates (82%). Managementfactors (herd size, body condition score, breeding season length, and timing of start of breeding season)had substantial impacts on the probability of pregnancy.

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Evaluating Information Obtained from Diagnosis of Pregnancy Status of Beef Herds

Cited by 5 publications

References 8 publications

Factors Influencing Productivity and Sustainability of Small-Scale Beef Farms in Thailand

Factors Influencing Productivity and Sustainability of Small-Scale Beef Farms in Thailand

Calving distributions of individual bulls in multiple-sire pastures

Herd level factors associated with pregnancy success and distribution in beef cow-calf herds

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