Biology subjects

De Ketelaere, B.

Publications and source records attributed to De Ketelaere, B..

5 recordsLinked to original sources

bioRxiv2023

Allantoic fluid-based qPCR for early-onset in ovo sexing

The culling of day-old male chickens remains an important welfare issue in the poultry industry. Several governments (e.g., Germany, France or Italy) have prohibited this practice, pushing the hatcheries to look for alternatives. Although different solutions exist for solving this problem, sex determination during embryos incubation (so called in ovo sexing) is considered the most suitable both for consumers and the industry since it aligns with the increasing demand for ethical and sustainable agriculture. However, to be applied in the market, in ovo sexing technologies have to meet a number of requirements, such as being compatible with all egg colors and early developmental stages, while maintaining high hatchability rate and accuracy at low cost and high throughput. To meet these requirements, we studied the use of the sexual genes HINTW (female-specific) and DMRT-1 (present in both males and females) between incubation days 6 and 9. By utilizing quantitative polymerase chain reaction (qPCR) as analysis method and allantoic fluid (AF) as sample, our study confirmed specific detection of these genes in AF, remarkably already at day 6 of development. In a blind study performed with 80 eggs, we achieved a 95% accuracy rate in sorting embryos when using the HINTW gene alone and an outstanding 100% accuracy rate when using {Delta}{lambda} values (difference between the HINTW and DMRT-1 qPCR cycle threshold (Ct)). Importantly, the AF sampling procedure did not reveal any significant detrimental effects on hatchability or embryo development, revealing high potential for this understudied type of sample to be used. In conclusion, the developed assay can provide more in-depth information about AF as a sample for genomic in ovo sexing and open new industrial possibilities for developing faster and cheaper assays. Research highlightsO_LIA highly reliable and accurate method for in ovo sexing in early incubation stages is established. C_LIO_LIAllantoic fluid can be easily extracted with minimal invasiveness while providing the necessary genomic material for sexual sorting. C_LIO_LIHINTW was found to be present in both female and male samples due to possible maternal contamination. C_LIO_LIHINTW alone or combined with DMRT-1 gene enables early-onset sexing with 100% accuracy. C_LI

bioengineering↗

bioRxiv2019

SHORT COMMUNICATION: Validation of a novel milk progesterone based tool to monitor luteolysis in dairy cows. Performance on cost-effective, on-farm measured data

INTERPRETATIVE SUMMARYValidation of luteolysis monitoring tool Adriaens. Recently, a novel progesterone-based monitoring algorithm using synergistic control, PMASC, was developed. This algorithm employs the known luteal dynamics of the progesterone profile to estimate the moment of luteolysis with minimal dependence on the absolute measurement values. As its value and implementability strongly dependends on the number of samples it requires to obtain the desired accuracy, its performance on cost-effective, smart sampled and on-farm measured data is demonstrated. SHORT COMMUNICATIONValidation of a novel milk progesterone based tool to monitor luteolysis in dairy cows. Performance on cost-effective, on-farm measured data

bioengineering↗

bioRxiv2019

Validation of a novel milk progesterone-based tool to monitor luteolysis in dairy cows. Timing of the alerts and robustness against missing values

Automated monitoring of fertility in dairy cows using milk progesterone is based on the accurate and timely identification of luteolysis. In this way, well-adapted insemination advice can be provided to the farmer to further optimize the fertility management. To properly evaluate and compare the performance of new and existing data-processing algorithms, a test dataset of progesterone time-series that fully covers the desired variability in progesterone profiles is needed. Further, the data should be measured with a high frequency to allow rapid onset events, such as luteolysis, to be precisely determined. Collecting this type of data would require a lot of time, effort and budget. In the absence of such data, an alternative was developed using simulated progesterone profiles for multiple cows and lactations, in which the different fertility statuses were represented. To these, relevant variability in terms of cycle characteristics and measurement error was added, resulting in a large cost-efficient dataset of well-controlled but highly variable and farm-representative profiles. Besides the progesterone profiles, information on (the timing of) luteolysis was extracted from the modelling approach and used as a reference for the evaluation and comparison of the algorithms. In this study, two progesterone monitoring tools were compared: a multiprocess Kalman filter combined with a fixed threshold on the smoothed progesterone values to detect luteolysis, and a progesterone monitoring algorithm using synergistic control PMASC, which uses a mathematical model based on the luteal dynamics and a statistical control chart to detect luteolysis. The timing of the alerts and the robustness against missing values of both algorithms were investigated using two different sampling schemes: one sample per cow every eight hours versus one sample per day. The alerts for luteolysis of the PMASC algorithm were on average 20 hours earlier compared to the ones of the multiprocess Kalman filter, and their timing was less sensitive to missing values. This was shown by the fact that, when one sample per day was used, the Kalman filter gave its alerts on average 24 hours later, and the variability in timing of the alerts compared to simulated luteolysis increased with 22%. Accordingly, we postulate that implementation of the PMASC system could improve the consistency of luteolysis detection on farm and lower the analysis costs compared to the current state of the art.\n\nInterpretative SummaryValidation of luteolysis monitoring tool for dairy cows.\n\nAdriaensIn this study, the performance of two monitoring algorithms to detect luteolysis using milk progesterone measurements was validated on a simulated dataset of realistic milk progesterone profiles. The synergistic control-based algorithm, PMASC, was able to identify luteolysis almost simultaneously with its occurrence. It was found to be more robust against missing samples and less dependent on the absolute milk progesterone values compared to a multiprocess Kalman filter combined with a fixed threshold. This research showed that implementation of PMASC could improve progesterone-based fertility monitoring on farm.

bioengineering↗

bioRxiv2018

A novel system for online fertility monitoring based on milk progesterone

Timely identification of a cows reproduction status is essential to minimize fertilityrelated losses on dairy farms. This includes optimal estrus detection, pregnancy diagnosis and the timely recognition of early embryonic death and ovarian problems. On farm milk progesterone (P4) analysis could indicate all of these fertility events simultaneously. However, milk P4 measurements are subject to a large variability both in terms of measurement errors and absolute values between cycles. In this study, an innovative monitoring system based on milk P4 using the principles of synergistic control is presented. Instead of using filtering techniques and fixed thresholds, the present system employs an individually updated online model to describe the P4 profile, combined with a statistical process control chart to identify the cows fertility status. The inputs for the latter are the residuals of the online model, corrected for the concentration-dependent variability which is typical for milk P4 measurements. The objective of this paper is to present the developed methodology and give an indication of its use on farm. To this end, the system was validated on the P4 profiles of 38 dairy cows. The positive predictive value for luteolysis followed by estrus was 100%, meaning that the monitoring system picked up all estrous periods identified by the experts. Pregnancy or embryonic mortality was characterized by the absence or detection of luteolysis following an insemination, respectively. For thirteen cows, no luteolysis was detected by the system within the 25-32 days after insemination, indicating pregnancy, which was confirmed later by rectal palpation. It was also shown that the system is able to cope with deviating P4 profiles having prolonged follicular or luteal phases, which may suggest the occurrence of cysts. Future research is recommended for optimizing sampling frequency, prediction of the optimal insemination window and the establishment of rules to detect problems based on deviating P4 patterns.\n\nINTERPRETIVE SUMMARY. Progestrone-based online fertility monitoring. Adriaens.Milk progesterone based monitoring systems can be valuable for indicating fertility events in dairy cows, as the evolution of the milk progesterone levels can be related to acyclicity, estrus, pregnancy, and ovarian problems. We developed a system to translate raw progesterone measurements into clear information for the farmer, based on a mathematical model and a statistical control chart. In this way, a detailed image of a cows reproduction status on-farm can be obtained and fertility-related losses minimized.

bioengineering↗

bioRxiv2018

Linking heat attentions and the moment of LH surge in dairy cows - how close can we get?

Both estrus detection and timely insemination are important factors in optimizing fertility management. The latter is dependent on ovulation time, which is preceded by the LH surge. The performance of an estrus detection system based on activity and based on milk progesterone was evaluated and the timing of the alerts was contrasted against the moment of the LH surge. Activity alerts had a sensitivity of 83% and a positive predictive value of 66%; the LH surge followed average 9.4 {+/-} 16.1 hours later. Using milk progesterone, one can reliably detect luteolysis, which is followed by the LH surge after 62 {+/-} 12 hours.

bioengineering↗