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Animal : An International Journal of... Jun 2024Alternatives to hormonal treatments (HTs) in dairy sheep reproduction management are being explored in response to increasing societal concerns regarding animal welfare...
Alternatives to hormonal treatments (HTs) in dairy sheep reproduction management are being explored in response to increasing societal concerns regarding animal welfare and food safety. However, hormone-free reproduction implies higher variability in flock performances and additional constraints for timely synchronised artificial insemination (AI) in the flock, impacting the diffusion of genetic progress. The use of the male effect, a well-known practice to induce synchronised oestrus, combined with precision tools (e.g., heat detector), is a plausible way to implement AI without HT in dairy sheep farms. To date, the consequences of such alternative reproduction management on the whole farm sustainability remain unknown. To anticipate these potential impacts, a multiagent model (REPRIN'OV) was used to simulate dairy sheep farms' sustainability indicators (biotechnical, economic, environmental and workload). A reproduction management scenario, including the use of the male effect followed by AI on the adult ewes (HFAI), was simulated and compared to the current reproduction management of four case study farms (Early_conv, Late_conv, Early_org and Late_org). They were selected to represent the different agricultural models (Conventional or Organic) and reproduction seasons (Early - during spring, out of ewes' natural reproduction season - or Late -from early summer to the end of autumn) of the Roquefort Basin's farms in Southern France. Simulation results showed that the HFAI scenario had different consequences depending on the farm's production system type. A negative effect on most key sustainability indicators of the Conv farms was observed, as a significant reduction in the fertility rate, in the proportion of young ewes born from AI (-54% in both farms; P < 0.05) and in the flock's milk production were observed; while the workload and greenhouse gas (GHG) emissions were increased compared to the initial scenario. In the Org farms, HFAI had neutral to positive effects on most indicators as the fertility, milk production of the flock, workload during milking and GHG emissions were barely affected by this scenario, while an increase in the proportion of young ewes born from AI was observed (+39% and + 43% in each farm, respectively; P < 0.05), allowing a better farm gross margin. Still, the workload during lambing was increased in Early_org (+18%; P < 0.05), as Early farms, tended to be more negatively impacted by HFAI than Late ones. Overall, our simulation approach provides interesting elements to exchange with stakeholders on how to progress towards a socially acceptable reproduction management system, for the dairy sheep sector.
PubMed: 38917727
DOI: 10.1016/j.animal.2024.101210 -
Veterinary World May 2024Sexed semen (SS), a reproductive biotechnology tool, can alter the sex ratio of offspring in bovines. This study elucidates a comparative analysis of estrus-related...
BACKGROUND AND AIM
Sexed semen (SS), a reproductive biotechnology tool, can alter the sex ratio of offspring in bovines. This study elucidates a comparative analysis of estrus-related parameters influencing conception rate and pregnancy losses under field conditions between conventional and SS.
MATERIALS AND METHODS
In the present study, artificial insemination with (SS; n = 143) and conventional semen (CS; n = 143) was performed at spontaneous estrus, i.e., 16-18 h after the onset of estrus signs, to analyze their comparative evaluation in terms of conception rates in crossbred cows under field conditions. Different parameters such as age, parity, body condition score (BCS), estrus duration, inter-estrus interval (IEI), diameter of pre-ovulatory follicle (DPOF) at estrus, and cervical mucus properties (pH and spinnbarkeit [SBK]) were recorded for each cow.
RESULTS
The first insemination conception rates for sexed and conventional semen were 55.24% and 63.63% whereas the overall conception rates were 49.14% and 57.37% on days 35 and 75 post-insemination, respectively, with no significant difference (p > 0.05). Conception rates between sexed and CS inseminations were statistically significant (p < 0.01), whereas factors such as age, parity, BCS, DPOF, IEI), and SBK value exhibited no substantial variance (p > 0.05) for both types of semen straw.
CONCLUSION
SS straws yielded a conception rate equivalent to CS straws, with estrus duration being the key factor affecting conception under field conditions.
PubMed: 38911088
DOI: 10.14202/vetworld.2024.1119-1123 -
Animal : An International Journal of... May 2024Small ruminant farming is of socio-economic and environmental importance to many rural communities around the world. The SMARTER H2020 project aims to redefine genetic...
Small ruminant farming is of socio-economic and environmental importance to many rural communities around the world. The SMARTER H2020 project aims to redefine genetic selection criteria to increase the sustainability of the sector. The objective of this study was to analyse the selection and breeding management practices of small ruminant producers and breeders, linked with socio-technical elements that shape them. The study is based on farm surveys using semi-structured interviews conducted in five countries (France, Spain, Italy, Greece, and Uruguay) across 272 producers and breeders of 13 sheep and goat breeds, and 15 breed × system combinations. The information was collected in four sections. The first and second sections dealt with general elements of structure and management of the system and the flock/herd. The third section focused on selection and breeding management practices: criteria for culling and replacement of females, selection criteria for males, use of estimated breeding values and global indexes, and preferences for indexing new traits to increase the sustainability of their system. The fourth section aimed to collect socio-technical information. We used a data abstraction method to standardise the representation of these data. A mixed data factor analysis followed by a hierarchical ascending classification allowed the characterisation of three profiles of selection and breeding management: (1) a profile of producers (n = 93) of small flocks/herds, with little knowledge or use of genetic selection and improvement tools (selection index, artificial insemination, performance recording); these farmers do not feel that new traits are needed to improve the sustainability of their system. (2) a profile of producers (n = 34) of multibreed flocks/herds that rely significantly on grazing; they are familiar with genetic tools, they currently use AI; they would like the indexes to include more health and robustness characteristics, to make their animals more resistant and to increase the sustainability of their system. And (3) a profile of producers or breeders (n = 145) of large flocks/herds, with specific culling criteria; these farmers are satisfied with the current indexes to maintain the sustainability of their system. These results are elements that can be used by private breeding companies and associations to support the evolution of selection objectives to increase the resilience of animals and to improve the sustainability of the small ruminant breeding systems.
PubMed: 38905776
DOI: 10.1016/j.animal.2024.101208 -
Frontiers in Microbiology 2024The concept of a sterile uterus was challenged by recent studies that have described the microbiome of the virgin and pregnant uterus for species including humans and...
INTRODUCTION
The concept of a sterile uterus was challenged by recent studies that have described the microbiome of the virgin and pregnant uterus for species including humans and cattle. We designed two studies that tested whether the microbiome is introduced into the uterus when the virgin heifer is first inseminated and whether the origin of the microbiome is the vagina/cervix.
METHODS
The uterine microbiome was measured immediately before and after an artificial insemination (AI; Study 1; = 7 AI and = 6 control) and 14 d after insemination (Study 2; = 12 AI and = 12 control) in AI and non-AI (control) Holstein heifers. A third study (Study 3; = 5 Holstein heifers) that included additional negative controls was subsequently conducted to support the presence of a unique microbiome within the uterus despite the low microbial biomass and regardless of insemination. Traditional bacteriological culture was performed in addition to 16S rRNA gene sequencing on the same samples to determine whether there were viable organisms in addition to those detected based on DNA sequencing (16S rRNA gene sequence).
RESULTS AND DISCUSSION
Inseminating a heifer did not lead to a large change in the microbiome when assessed by traditional methods of bacterial culture or metataxonomic (16S rRNA gene) sequencing (results of Studies 1 and 2). Very few bacteria were cultured from the body or horn of the uterus regardless of whether an AI was or was not (negative control) performed. The cultured bacterial genera (e.g., , and ) were typical of those found in the soil, environment, skin, mucous membranes, and urogenital tract of animals. Metataxonomic sequencing of 16S rRNA gene generated a large number of amplicon sequence variants (ASV), but these larger datasets that were based on DNA sequencing did not consistently demonstrate an effect of AI on the abundance of ASVs across all uterine locations compared with the external surface of the tract (e.g., perimetrium; positive control samples for environment contamination during slaughter and collection). Major genera identified by 16S rRNA gene sequencing overlapped with those identified with bacterial culture and included , and .
PubMed: 38903779
DOI: 10.3389/fmicb.2024.1385505 -
Animals : An Open Access Journal From... May 2024Circulating microRNAs (miRNAs) were investigated as biomarkers for the diagnosis of early pregnancy in cattle. The levels of prospective miRNA biomarkers and the...
Circulating microRNAs (miRNAs) were investigated as biomarkers for the diagnosis of early pregnancy in cattle. The levels of prospective miRNA biomarkers and the features of extracellular vesicles (EVs) in the blood were evaluated. In Study 1, plasma samples from cows 21 days after artificial insemination (AI) were examined using RT-qPCR to determine the levels of seven circulating miRNAs. Only the levels of miR-126-3p were significantly lower in the pregnant group than in the non-pregnant group. In Study 2, among individuals not pregnant at the first AI, the miRNA levels were compared between the individuals pregnant at the second AI and those who remained non-pregnant. The miR-25 levels were significantly higher in the pregnant group at the second AI than in the pregnant group at the first AI; miR-19b, miR-27b, and miR-29a levels were also high. In the non-pregnant group, changes were absent in the miRNA levels in the same individual between the first and second AIs. In Study 3, Western blotting and RT-qPCR showed the presence of miRNAs in EVs and their levels were lower than in plasma. Thus, circulating miR-126-3p may serve as a biomarker for the diagnosis of early pregnancy in cattle. In addition, the expression of some miRNAs tended to be higher during pregnancy than during non-pregnancy in the same individual, suggesting their potential as an index to determine pregnancy and non-pregnancy rates using a comparative method.
PubMed: 38891639
DOI: 10.3390/ani14111592 -
Animals : An Open Access Journal From... May 2024Automated activity monitoring (AAM) systems are critical in the dairy industry for detecting estrus and optimizing the timing of artificial insemination (AI), thus...
Automated activity monitoring (AAM) systems are critical in the dairy industry for detecting estrus and optimizing the timing of artificial insemination (AI), thus enhancing pregnancy success rates in cows. This study developed a predictive model to improve pregnancy success by integrating AAM data with cow-specific and environmental factors. Utilizing data from 1,054 cows, this study compared the pregnancy outcomes between two AI timings-8 or 10 h post-AAM alarm. Variables such as age, parity, body condition, locomotion, and vaginal discharge scores, peripartum diseases, the breeding program, the bull used for AI, milk production at the time of AI, and environmental conditions (season, relative humidity, and temperature-humidity index) were considered alongside the AAM data on rumination, activity, and estrus intensity. Six predictive models were assessed to determine their efficacy in predicting pregnancy success: logistic regression, Bagged AdaBoost algorithm, linear discriminant, random forest, support vector machine, and Bagged Classification Tree. Integrating the on-farm data with AAM significantly enhanced the pregnancy prediction accuracy at AI compared to using AAM data alone. The random forest models showed a superior performance, with the highest Kappa statistic and lowest false positive rates. The linear discriminant and logistic regression models demonstrated the best accuracy, minimal false negatives, and the highest area under the curve. These findings suggest that combining on-farm and AAM data can significantly improve reproductive management in the dairy industry.
PubMed: 38891614
DOI: 10.3390/ani14111567 -
Animals : An Open Access Journal From... May 2024This retrospective study aimed to evaluate the performance of hormone treatment protocols, determine the factors associated with pregnancy success after hormone...
This retrospective study aimed to evaluate the performance of hormone treatment protocols, determine the factors associated with pregnancy success after hormone treatment, and compare the cost-efficiencies of two types of hormone treatment among cyclic and noncyclic anestrous dairy cows. The clinical records of 279 anestrous cows that received hormone treatment for artificial insemination (AI) from 64 herds in the western region of Thailand were obtained from Kasetsart University Veterinary Teaching Hospital from January to August 2017. The performance of the hormone treatment protocols, fixed-time AI (TAI) and estrus detection before AI (EAI), showed that the pregnancy risk for the TAI protocol was higher than that for the EAI protocol, but pregnancy per AI did not differ significantly between the two protocols in cyclic and noncyclic cows. Multivariate logistic regression analysis showed that cows receiving the TAI protocol were more likely to be pregnant compared to those treated with the EAI protocol. Cows with a 3.00 body condition score (BCS) < 3.75 after treatment and loose-housed cows were more likely to become pregnant. Treatment during winter showed higher pregnancy success than that in the summer and rainy seasons. The cost-efficiency analysis showed that the TAI protocol was the most cost-efficient option for noncyclic cows, whereas the EAI protocol was the most cost-efficient option for cyclic cows.
PubMed: 38891611
DOI: 10.3390/ani14111564 -
Animals : An Open Access Journal From... May 2024This review aims to provide an insight into the application and efficiency of CIDR-based protocols for ES in goats raised under tropical and subtropical environments. In... (Review)
Review
This review aims to provide an insight into the application and efficiency of CIDR-based protocols for ES in goats raised under tropical and subtropical environments. In temperate regions, short-term CIDR treatments are replacing long-term treatments and sponges used in earlier decades. In addition, the use of co-treatments for the induction of ovulation is gradually changing from hormonal to non-hormonal methods, given the drive towards clean, green, and ethical techniques for reproductive management. Whereas the subtropical region registers ongoing research in the development of new ES protocols, there are few reports from the tropics, particularly Africa, one of the regions with the highest population of goats. Therefore, this calls for research to develop the most appropriate protocols for these regions, since the protocols currently used are largely hormonal based, as they were developed for goats at higher latitudes. Management and environmental factors determine the breeding pattern of goats at tropical latitudes rather than photoperiods, and they are the main causes of reproductive seasonality. The use of ES methods, particularly short-term CIDR-based protocols, along with artificial insemination, may have a significant impact on the productivity of goats in these regions when these factors are controlled.
PubMed: 38891607
DOI: 10.3390/ani14111560 -
Frontiers in Artificial Intelligence 2024The most common Assisted Reproductive Technology is Fertilization (IVF). During IVF, embryologists commonly perform a morphological assessment to evaluate embryo...
BACKGROUND
The most common Assisted Reproductive Technology is Fertilization (IVF). During IVF, embryologists commonly perform a morphological assessment to evaluate embryo quality and choose the best embryo for transferring to the uterus. However, embryo selection through morphological assessment is subjective, so various embryologists obtain different conclusions. Furthermore, humans can consider only a limited number of visual parameters resulting in a poor IVF success rate. Artificial intelligence (AI) for embryo selection is objective and can include many parameters, leading to better IVF outcomes.
OBJECTIVES
This study sought to use AI to (1) predict pregnancy results based on embryo images, (2) assess using more than one image of the embryo in the prediction of pregnancy but based on the current process in IVF labs, and (3) compare results of AI-Based methods and embryologist experts in predicting pregnancy.
METHODS
A data set including 252 Time-lapse Videos of embryos related to IVF performed between 2017 and 2020 was collected. Frames related to 19 ± 1, 43 ± 1, and 67 ± 1 h post-insemination were extracted. Well-Known CNN architectures with transfer learning have been applied to these images. The results have been compared with an algorithm that only uses the final image of embryos. Furthermore, the results have been compared with five experienced embryologists.
RESULTS
To predict the pregnancy outcome, we applied five well-known CNN architectures (AlexNet, ResNet18, ResNet34, Inception V3, and DenseNet121). DeepEmbryo, using three images, predicts pregnancy better than the algorithm that only uses one final image. It also can predict pregnancy better than all embryologists. Different well-known architectures can successfully predict pregnancy chances with up to 75.0% accuracy using Transfer Learning.
CONCLUSION
We have developed DeepEmbryo, an AI-based tool that uses three static images to predict pregnancy. Additionally, DeepEmbryo uses images that can be obtained in the current IVF process in almost all IVF labs. AI-based tools have great potential for predicting pregnancy and can be used as a proper tool in the future.
PubMed: 38881952
DOI: 10.3389/frai.2024.1375474 -
Journal of Dairy Science Jun 2024Negative associations of health disorders with reproductive performance, often measured with pregnancy risk per artificial insemination (AI) or the risk of pregnancy...
Negative associations of health disorders with reproductive performance, often measured with pregnancy risk per artificial insemination (AI) or the risk of pregnancy loss, have been demonstrated extensively. Most studies investigated common clinical diseases but did not include subclinical disorders comprehensively. They often evaluated cows subjected to hormonal synchronization protocols for timed AI, limiting the ability to understand how disease may affect spontaneous reproductive function, which is essential for targeted management programs with selective hormonal intervention. It is plausible that metabolic and inflammatory disorders have short- and long-term detrimental effects on different features of reproductive function that result in or contribute to reduced fertility. These may include: 1) reestablishment of endocrine function to promote follicular growth and first ovulation postpartum, 2) corpus luteum (CL) function, 3) estrus expression, and 4) uterine environment, fertilization, and embryonic development. In this narrative literature review, we discuss insights and knowledge gaps linking health disorders with these processes of reproductive function. A growing set of observational studies with adequate internal validity suggest that these outcomes may be affected by metabolic and inflammatory disorders that are common in the early postpartum period. A better characterization of these risk factors in multi-site studies with greater external validity is warranted to develop decision-support tools to identify subgroups of cows that are more or less likely to be successful in targeted reproductive management programs.
PubMed: 38876223
DOI: 10.3168/jds.2023-24562