Management to Prevent Dystocia

Boakari, Yatta Linhares; Ali, Hesham A.

doi:10.1002/9781119602484.ch49

Cited by 6 publications

(6 citation statements)

References 25 publications

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“…In Experiment 1, we attempted to determine the relationship between the maternal pelvis and new‐born calves in normal and dystocia. As previous studies have shown, dystocia is generally more common in first‐calving heifers and age is an important predictor of dystocia independent of the pelvic region (Abera, 2017; Boakari & Ali, 2021; Hickson et al, 2006; Hohnholz et al, 2019; Kolkman et al, 2009; Weldeyohanes & Fesseha, 2020). In this study, although there was no significant difference in maternal parity between the two groups, there were more first‐calving heifers in the dystocia group.…”

Section: Discussionmentioning

confidence: 93%

“…Dystocia is caused by the interrelationship between foetal factors such as oversized, malposition, multiple, and malformed foetuses and maternal factors such as abnormalities in the birth canal and labour (Weldeyohanes & Fesseha, 2020). A major cause of dystocia is the physical imbalance between the dam's pelvis and the foetus (Abera, 2017; Bila et al, 2021; Boakari & Ali, 2021; Hickson et al, 2006; Holm et al, 2014; Mee, 2008; Mammi et al, 2021; Tiezzi et al, 2018). Such imbalance is more likely to occur in the first calving heifers.…”

Section: Introductionmentioning

confidence: 99%

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Establishment of a method to predict dystocia due to physical imbalance between foetus and maternal pelvis in Japanese black cattle

Maeda

Kitahara

Osawa

2022

Reprod Domestic Animals

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This study aimed to clarify the relationship between the maternal pelvis and calf size in normal and dystocia groups (Experiment 1) and to establish a method to predict dystocia due to physical imbalance between foetus and maternal pelvis before calving based on the parameters found in Experiment 1 (Experiment 2). In Experiment 1, 26 pairs of dams and their offspring were tested immediately after calving, and various parameters of offspring size and maternal pelvis were measured in normal and dystocia cases. The longitudinal diameter of the maternal pelvis was smaller (p < .01), and ratios of the offspring's birth weight and the width of the hoof crown (hoof width; measured using callipers) to the longitudinal diameter of the maternal pelvis were larger (p < .01) in the dystocia group than those in the normal group. In Experiment 2, 37 cows were tested, and in addition to the measurement items of Experiment 1, the inner pelvic diameter and the foetal hoof width were measured via ultrasonography at 285 days of gestation. The ratio of the internal diameter of the maternal pelvis (longitudinal diameter, transverse diameter and area) to the foetal hoof width was compared and was greater (p < .01) in the dystocia group than in the normal group. In conclusion, the risk of dystocia can be estimated by the ratio of the foetal hoof width to the longitudinal diameter of the maternal pelvis before calving.

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Section: Discussionmentioning

confidence: 93%

Section: Introductionmentioning

confidence: 99%

Establishment of a method to predict dystocia due to physical imbalance between foetus and maternal pelvis in Japanese black cattle

Maeda

Kitahara

Osawa

2022

Reprod Domestic Animals

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“…In addition to the imbalance in the dataset, any poor results might be attributed to the high proportion of missing values for BCS, which is a critical risk factor for calving difficulty since body size is one of the main maternal factors that impose calving difficulty. In addition, cows that did not receive an appropriate diet and have a low BCS are more susceptible to difficult births, while, at the same time, cows that have been fed excessively, will likely have a higher birth-weight calf (Boakari and Ali 2021) and more fat deposition in the pelvic area, leading to difficult calving (Zaborski and Grzesiak 2011;Boakari and Ali 2021).…”

Section: Evaluation Of Herd-cow Factors As Predictors Of Calving Diff...mentioning

confidence: 99%

Application of machine-learning algorithms to predict calving difficulty in Holstein dairy cattle

Avizheh,

Dadpasand,

Dehnavi

et al. 2023

Anim. Prod. Sci.

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Context An ability to predict calving difficulty could help farmers make better farm-management decisions, thereby improving dairy farm profitability and welfare. Aims This study aimed to predict calving difficulty in Iranian dairy herds using machine-learning (ML) algorithms and to evaluate sampling methods to deal with imbalanced datasets. Methods For this purpose, the history records of cows that calved between 2011 and 2021 on two commercial dairy farms were used. Using WEKA software, four commonly used ML algorithms, namely naïve Bayes, random forest, decision trees, and logistic regression, were applied to the dataset. The calving difficulty was considered as a binary trait with 0, normal or unassisted calving, and 1, difficult calving, i.e. receiving any help during parturition from farm personnel involvement to surgical intervention. The average rate of difficult calving was 18.7%, representing an imbalanced dataset. Therefore, down-sampling and cost-sensitive techniques were implemented to tackle this problem. Different models were evaluated on the basis of F-measure and the area under the curve. Key results The results showed that sampling techniques improved the predictive model (P = 0.07, and P = 0.03, for down-sampling and cost-sensitive techniques respectively). F-measure ranged from 0.387 (decision tree) to 0.426 (logistic regression) with the balanced dataset. However, when applied to the original imbalanced dataset, naïve Bayes had the best performance of up to 0.388 in terms of F-measure. Conclusions Overall, sampling techniques improved the prediction model compared with original imbalanced dataset. Although prediction models performed worse than expected (due to an imbalanced dataset, and missing values), the implementation of ML algorithms can still lead to an effective method of predicting calving difficulty. Implications This research indicated the capability of ML algorithms to predict the incidence of calving difficulty within a balanced dataset, but that more explanatory variables (e.g. genetic information) are required to improve the prediction based on an unbalanced original dataset.

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“…To maximize the advantages of reducing AFC, adequate BW control for heifers until first calving is essential. Unsuccessful weight management can frequently cause dystocia during first calving, which contributes to an increase in postpartum uterine diseases such as postpartum metritis and endometritis [5]. The most common cause of calving difficulties is fetal-maternal disproportion, that is, a calf that is too large and/or a pelvis that is too small [5].…”

Section: Introductionmentioning

confidence: 99%

“…Unsuccessful weight management can frequently cause dystocia during first calving, which contributes to an increase in postpartum uterine diseases such as postpartum metritis and endometritis [5]. The most common cause of calving difficulties is fetal-maternal disproportion, that is, a calf that is too large and/or a pelvis that is too small [5]. Therefore, replacement heifers must rapidly acquire a mature frame and sufficient BW before their first calving.…”

Section: Introductionmentioning

confidence: 99%

Association of age at first calving with longevity, milk yield, and fertility up to the third lactation in a herd of Holstein dairy cows in Japan

KUSAKA,

YAMAZAKI,

SAKAGUCHI

2023

Journal of Reproduction and Development

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Accelerating age at first calving (AFC) is a strategy for sustainable dairy farming, whereas the impact of a reduction in AFC on long-term performance remains unclear. In this study, longevity and milk productivity until the end of the third lactation period were investigated retrospectively according to AFC. A total of 169 cows were categorized according to AFC as young, moderate, old, and very old (< 22.5, 22.5-<24.0, 24.0-<25.5, and > 25.5 months). The young AFC group had approximately 70 kg lower body weight before first calving (620 vs. 695 kg, P < 0.05) and experienced their first calving approximately 4.2 months earlier than the very old AFC group (21.9 vs. 26.1 months, P < 0.05). The survival rate at the third calving stage was 61% in the young AFC group, which was higher than those in the moderate (42%), old (35%), and very old (33%) AFC groups. In the young AFC group, no cows were culled because of low productivity and hoof disease, compared to 5.0-8.1% of older AFC cows. The young AFC group had a higher overall lifetime milk yield (cumulative milk yield/days from birth to the end of final lactation) than the old AFC group (14.3 vs. 8.7 kg/d, P = 0.11). The cows that survived the third calving had better reproductive performance than non-surviving cows; however, no statistical difference was detected among the AFC groups. In conclusion, AFC as early as 22.5 months could be associated with better survivability and higher overall lifetime milk yield than older AFC without impairing reproductive performance. Our results suggest that accelerating AFC may lead to higher profitability.

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Management to Prevent Dystocia

Cited by 6 publications

References 25 publications

Establishment of a method to predict dystocia due to physical imbalance between foetus and maternal pelvis in Japanese black cattle

Establishment of a method to predict dystocia due to physical imbalance between foetus and maternal pelvis in Japanese black cattle

Application of machine-learning algorithms to predict calving difficulty in Holstein dairy cattle

Association of age at first calving with longevity, milk yield, and fertility up to the third lactation in a herd of Holstein dairy cows in Japan

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