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Modern Technology in Farm Animals’ Reproductive Services

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A special issue of Animals (ISSN 2076-2615). This special issue belongs to the section "Animal Reproduction".

Deadline for manuscript submissions: closed (15 December 2022) | Viewed by 18261

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Special Issue Editor

Dr. Ioannis A. Tsakmakidis

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Guest Editor

School of Veterinary Medicine, Faculty of Health Sciences, Aristotle University of Thessaloniki, 54627 Thessaloniki, Greece
Interests: semen quality; pig; boar; rabbit
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Reproductive performance is a key parameter for the economic efficiency of a livestock company. However, fertilization is affected by several seasonal, environmental and animal-related factors. Technological tools have been involved in the prognosis of animals’ subfertility to support the good reproductive management of the farms. New diagnostic laboratory tests and protocols, imaging, infrared thermography, improvement and establishment of special software, artificial intelligence, nanotechnology, antibiotics’ alternatives, sensors to measure animals’ physiological and environmental/climate variables, as well as other modern technological applications, serve the improvement of the reproductive performance.

The scope of this Special Issue is to make public information about technological applications concentrated on the improvement of reproductive efficiency; fertilizing capacity; prognosis of fertility.

We invite you to share your recent findings via this Special Issue.

Dr. Ioannis A. Tsakmakidis
Guest Editor

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Keywords

reproductive technology
biomedical measurements
environmental measurements
technological applications
imaging
sensors
laboratory modern techniques
semen analysis
in vitro embryo production
farm animals’ reproduction

Related Special Issue

Technological Applications in Farm Animal Reproduction in Animals

Published Papers (9 papers)

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Research

15 pages, 1212 KiB

Open AccessArticle

Uncovering Patterns in Dairy Cow Behaviour: A Deep Learning Approach with Tri-Axial Accelerometer Data

by Paolo Balasso, Cristian Taccioli, Lorenzo Serva, Luisa Magrin, Igino Andrighetto and Giorgio Marchesini

Animals 2023, 13(11), 1886; https://0-doi-org.brum.beds.ac.uk/10.3390/ani13111886 - 05 Jun 2023

Cited by 2 | Viewed by 1798

Abstract

The accurate detection of behavioural changes represents a promising method of detecting the early onset of disease in dairy cows. This study assessed the performance of deep learning (DL) in classifying dairy cows’ behaviour from accelerometry data acquired by single sensors on the cows’ left flanks and compared the results with those obtained through classical machine learning (ML) from the same raw data. Twelve cows with a tri-axial accelerometer were observed for 136 ± 29 min each to detect five main behaviours: standing still, moving, feeding, ruminating and resting. For each 8 s time interval, 15 metrics were calculated, obtaining a dataset of 211,720 observation units and 15 columns. The entire dataset was randomly split into training (80%) and testing (20%) datasets. The DL accuracy, precision and sensitivity/recall were calculated and compared with the performance of classical ML models. The best predictive model was an 8-layer convolutional neural network (CNN) with an overall accuracy and F1 score equal to 0.96. The precision, sensitivity/recall and F1 score of single behaviours had the following ranges: 0.93–0.99. The CNN outperformed all the classical ML algorithms. The CNN used to monitor the cows’ conditions showed an overall high performance in successfully predicting multiple behaviours using a single accelerometer. Full article

(This article belongs to the Special Issue Modern Technology in Farm Animals’ Reproductive Services)

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16 pages, 4974 KiB

Open AccessArticle

Udder Ultrasonography of Dairy Cows: Investigating the Relationship between Echotexture, Blood Flow, Somatic Cell Count and Milk Yield during Dry Period and Lactation

by Konstantinos S. Themistokleous, Iraklis Papadopoulos, Nikolaos Panousis, Antonios Zdragas, Georgios Arsenos and Evangelos Kiossis

Animals 2023, 13(11), 1779; https://0-doi-org.brum.beds.ac.uk/10.3390/ani13111779 - 26 May 2023

Cited by 1 | Viewed by 1790

Abstract

Udder health of dairy cows is related to their productivity and welfare. The period from dry-off to calving and early lactation is crucial. Ultrasonography is a useful and practical tool for the examination of the mammary parenchyma and blood flow. This observational study investigated the relationship between udder echotexture features, blood flow volume (BFVol) in the milk vein, milk somatic cell count (SCC) and daily milk yield (DMY) from late lactation, throughout the dry period and consecutive early lactation. Seventeen repeated measurements were performed on twenty-one Holstein cows. The udder parenchyma was examined with B-mode ultrasonography. Udder echotexture was studied using 15 features: Numerical Pixel Value (NPV), Pixel Standard Deviation (PSD), Skewness, Excess, Contrast, Homogeneity, Correlation, Entropy, Run Percentage, Long-Run Emphasis, Grey Value Distribution, Runlength Distribution, Gradient Mean Value, Gradient Variance and Percentage of Non-zero Gradients. Blood flow in the milk vein was examined with spectral Doppler. Linear mixed-effects models were employed to investigate relationships between BFVol, udder echotexture features, SCC and DMY throughout the study period. Our models showed that a 1 kg increase in DMY was associated with a significant increase of 0.25 L/min in the expected BFVol and that a 1,000,000-cells/mL increase in SCC was associated with a significant BFVol decrease of 0.49 L/min, keeping all other variables constant. Multivariable models showed significant associations between DMY and NPV, between PSD and Long-Run Emphasis, and between SCC and NPV, PSD, Gradient Mean Value, Homogeneity, Gradient Variance and Entropy. In conclusion, udder echotexture and BFVol in the milk vein are related to SCC and milk yield. Ultrasonography can be used for the comprehensive assessment of udder health in support of precision dairy farming. Full article

(This article belongs to the Special Issue Modern Technology in Farm Animals’ Reproductive Services)

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11 pages, 1329 KiB

Open AccessArticle

Intensity and Duration of Vibration Emissions during Shipping as Interacting Factors on the Quality of Boar Semen Extended in Beltsville Thawing Solution

by Tim Hafemeister, Paul Schulze, Christian Simmet, Markus Jung, Frank Fuchs-Kittowski and Martin Schulze

Animals 2023, 13(5), 952; https://0-doi-org.brum.beds.ac.uk/10.3390/ani13050952 - 06 Mar 2023

Cited by 3 | Viewed by 1556

Abstract

Vibration emissions during the transport of boar semen for artificial insemination (AI) affect sperm quality. In the present study, the common influence of the following factors was investigated: vibrations (displacement index (D_i) = 0.5 to 6.0), duration of transport (0 to 12 h) and storage time (days 1 to 4). Normospermic ejaculates were collected from 39 fertile Pietrain boars (aged 18.6 ± 4.5 months) and diluted in a one-step procedure with an isothermic (32 °C) BTS (Minitüb) extender (n = 546 samples). Sperm concentration was adjusted to 22 × 10⁶ sperm·mL⁻¹. Extended semen (85 ± 1 mL) was filled into 95 mL QuickTip Flexitubes (Minitüb). For transport simulation on day 0, a laboratory shaker IKA MTS 4 was used. Total sperm motility (TSM) was evaluated on days 1 to 4. Thermo-resistance test (TRT), mitochondrial activity (MITO) and plasma membrane integrity (PMI) were assessed on day 4. Sperm quality dropped with increasing vibration intensity and transport duration, and the effect was enhanced by a longer storage time. A linear regression was performed using a mixed model, accounting for the boar as a random effect. The interaction between D_i and transport duration significantly (p < 0.001) explained data for TSM (−0.30 ± 0.03%), TRT (−0.39 ± 0.06%), MITO (−0.45 ± 0.06%) and PMI (−0.43 ± 0.05%). Additionally, TSM decreased by 0.66 ± 0.08% with each day of storage (p < 0.001). It can be concluded that boar semen extended in BTS should be transported carefully. If this is not possible or the semen doses are transported a long way, the storage time should be reduced to a minimum. Full article

(This article belongs to the Special Issue Modern Technology in Farm Animals’ Reproductive Services)

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9 pages, 1547 KiB

Open AccessArticle

Effects of Intra-Uterine Fluid Accumulation after Artificial Insemination on Luteal Function in Mares

by Francesca Freccero, Beatrice Mislei, Diego Bucci, Francesco Dondi and Gaetano Mari

Animals 2023, 13(1), 67; https://0-doi-org.brum.beds.ac.uk/10.3390/ani13010067 - 23 Dec 2022

Cited by 1 | Viewed by 1578

Abstract

After breeding or artificial insemination, especially with frozen/thawed semen, mares often develop a persistent uterine inflammation, which is diagnosed by intra-uterine fluid accumulation. Here, we explored whether intra-uterine fluid accumulation affects corpus luteum function and tested the hypothesis that intra-uterine fluid accumulation after artificial insemination alters blood flow in the corpus luteum and plasma progesterone concentrations. A total of 40 Standardbred mares were artificially inseminated with frozen-thawed semen 30 to 36 h after induction of ovulation, and cases with or without intra-uterine fluid accumulation were detected by ultrasound 12 h after insemination. Luteal blood flow was measured by Power Doppler ultrasonography 3 and 6 days after ovulation, progesterone concentration was measured in peripheral plasma by ELISA 6 days after ovulation, and pregnancy was diagnosed by ultrasonography 14 days after ovulation. Luteal blood flow increased between 3 and 6 days after ovulation, but blood flow did not differ significantly between cases with (n = 28) and without (n = 25) intra-uterine fluid accumulation after insemination. Surprisingly, progesterone concentrations were higher in cases of intra-uterine fluid accumulation than cases without (9.3 ± 1.1 vs. 6.6 ± 0.5 ng/mL, p = 0.048). Pregnancy was less likely in cases with intra-uterine fluid accumulation than in cases without (10/28 vs. 17/25, p = 0.019), and there was a negative correlation between the severity of intra-uterine fluid accumulation and per cycle pregnancy rate. These data suggest that although intra-uterine fluid accumulation increases the secretion of progesterone, pregnancy is more dependent on uterine health than ovarian function. Full article

(This article belongs to the Special Issue Modern Technology in Farm Animals’ Reproductive Services)

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11 pages, 563 KiB

Open AccessArticle

The Role of Housing Conditions on the Success of Artificial Insemination in Intensively Reared Dairy Ewes in Greece

by Stergios Priskas, Georgios Valergakis, Ioannis Tsakmakidis, Sotiria Vouraki, Vasiliki Papanikolopoulou, Alexandros Theodoridis and Georgios Arsenos

Animals 2022, 12(19), 2693; https://0-doi-org.brum.beds.ac.uk/10.3390/ani12192693 - 07 Oct 2022

Cited by 1 | Viewed by 1399

Abstract

The objective was to assess the effect of housing conditions during the summer months on the success rates of cervical artificial insemination (AI) with cooled semen, in intensively reared dairy ewes in Greece. The study involved 2083 Lacaune ewes from 23 flocks that were serviced during May to September. An estrous synchronization protocol with the insertion of progestogen sponges for 14 days and eCG administration at sponge removal, was used. All ewes were inseminated 54–57 h after sponge removal with cooled semen (15 °C) from 10 Lacaune rams. Pregnancy diagnosis was performed via trans-dermal ultrasonography at 35–40 days after AI. Data recording started the day after sponge placement (15 days prior to AI), and lasted up to 14 days after AI. Daily records included temperature, relative humidity, and Temperature-Humidity Index (THI) inside the shed. Available space and volume per animal, frequency of bedding renewal, access to a yard, and indoor light were also recorded in each farm. Binary logistic regression of data records showed that temperature and THI increases at days −15 to +4 around AI (day 0) had a negative effect on pregnancy rates (reducing the likelihood of pregnancy by 3–6% and 7%, respectively). The latter also decreased significantly (p < 0.05) in farms with high stocking density, non-frequent bedding renewal, and outdoor access by ewes (by 30%, 34%, and 44%, respectively). Overall, the results indicate that appropriate housing conditions are warranted to increase the success of AI in dairy ewes during the summer months. Full article

(This article belongs to the Special Issue Modern Technology in Farm Animals’ Reproductive Services)

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11 pages, 3351 KiB

Open AccessArticle

The Role of Ewes’ Udder Health on Echotexture and Blood Flow Changes during the Dry and Lactation Periods

by Aikaterini Ntemka, Ioannis Tsakmakidis, Constantin Boscos, Alexandros Theodoridis and Evangelos Kiossis

Animals 2022, 12(17), 2230; https://0-doi-org.brum.beds.ac.uk/10.3390/ani12172230 - 30 Aug 2022

Cited by 2 | Viewed by 1449

Abstract

The objective of the current study was to investigate the echotextural and hemodynamic changes of ewes entering the dry period with or without subclinical mastitis. B-mode and color Doppler ultrasonography were applied to 12 Chios ewes (6 with healthy udders (group A) and 6 with subclinical mastitis (group B)) before the dry period, during the dry period (the involution phase, steady state, and transition phase), and postpartum. The color Doppler of the mammary arteries was used to evaluate them according to the pulsatility index (PI), resistive index (RI), end-diastolic velocity (EDV), time-averaged maximum velocity (TAMV), blood flow volume (BFV), and artery diameter (D). Udder parenchyma images, analyzed by Echovet v2.0, were used to evaluate the mean value (MV), standard deviation (SD), gradient mean value (GMV), gradient variance (GV), contrast (Con), entropy (Ent), gray value distribution (GVD), run length distribution (RunLD), and long run emphasis (LRunEm). In the involution phase, the PI was higher in group B compared to group A (p ≤ 0.05). The PI and RI were higher postpartum, whereas the EDV, TAVM, and D were higher in the transition phase (p ≤ 0.05). Neither the period nor the ewe group affected the MV, SD, GMV, GV, Con, and GVD values (p ≤ 0.05). In the steady state, the LRunEm was higher in group B, but postpartum, it was higher in group A (p ≤ 0.05). In conclusion, B-mode and Doppler can reveal differences (i) between healthy ewes and ewes with subclinical mastitis and (ii) among the different periods studied. Further research is needed on the blood flow and echotexture indices of the udders of ewes with unilateral subclinical mastitis. Full article

(This article belongs to the Special Issue Modern Technology in Farm Animals’ Reproductive Services)

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13 pages, 2132 KiB

Open AccessArticle

Boar Semen Shipping for Artificial Insemination: Current Status and Analysis of Transport Conditions with a Major Focus on Vibration Emissions

by Tim Hafemeister, Paul Schulze, Ralf Bortfeldt, Christian Simmet, Markus Jung, Frank Fuchs-Kittowski and Martin Schulze

Animals 2022, 12(10), 1331; https://0-doi-org.brum.beds.ac.uk/10.3390/ani12101331 - 23 May 2022

Cited by 8 | Viewed by 2853

Abstract

In the modern pig reproduction system, artificial insemination (AI) doses are delivered from AI centers to sow farms via logistics vehicles. In this study, six breeding companies in three countries (Brazil, Germany, and the USA) were interviewed about their delivery process. It was found that there is currently no comprehensive monitoring system for the delivery of semen. The entire process “shipping of boar semen” was documented using Business Process Model and Notation (BPMN). Although it is not currently known which vibrations occur at all, it is suspected that vibration emissions affect the quality of boar semen. For this reason, a prototype of a measuring system was developed to calculate a displacement index (D_i), representing vibration intensities. Vibrations were analyzed in standardized road trials (n = 120) on several road types (A: smooth asphalt pavement, B: rough asphalt pavement, C: cobblestone, and D: dirt road) with different speeds (30, 60, 90, 120, and 150 km/h). A two-way ANOVA showed significant differences in mean D_i, depending on road surface and speed as well as an interaction of both factors (p < 0.001). A field study on a reference delivery from a German AI center to several sow farms indicated that 33% of the observed roads are in good quality and generate only a few vibrations (D_i ≤ 1), while 40% are of a moderate quality with interrupted surfaces (D_i = 1–1.5). However, 25% of the roads show markedly increased vibrations (D_i ≥ 1.5), as a consequence of bad conditions on cobblestones or unpaved roads. Overall, more attention should be paid to factors affecting sperm quality during transport. In the future, an Internet of Things (IoT) based solution could enable complete monitoring of the entire transport process in real time, which could influence the courier’s driving behavior based on road conditions in order to maintain the quality of the transported AI doses. Full article

(This article belongs to the Special Issue Modern Technology in Farm Animals’ Reproductive Services)

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11 pages, 1535 KiB

Open AccessArticle

Effect of an Antioxidant Supplement Combination on Boar Sperm

by Ivan Galić, Saša Dragin, Ivan Stančić, Milan Maletić, Jelena Apić, Nebojša Kladar, Jovan Spasojević, Jovana Grba and Zorana Kovačević

Animals 2022, 12(10), 1301; https://0-doi-org.brum.beds.ac.uk/10.3390/ani12101301 - 18 May 2022

Viewed by 2019

Abstract

The study was conducted on a commercial pig farm located in Serbia. Thirty Duroc or Landrace breed boars were randomly selected for this study. The experimental group was fed a compound feed with added organic selenium and Oxynat 3D. The antioxidant status parameters of boar seminal plasma were evaluated using a biochemical analyzer and commercial Randox kits. The sperm chromatin structure assay (SCSA) using flow cytometry (FC) provided information about spermatozoa’s DNA status. Additionally, the total number of motile spermatozoa and spermatozoa kinematic parameters were measured using the computer-assisted sperm analysis (CASA) system. The aim of this study was to improve the parameters of semen by combining two preparations that have a potential antioxidant effect, but also to establish the level of various antioxidant enzymes in native sperm. There was no statistically significant difference in total antioxidant capacity and glutathione peroxidase activity in the seminal plasma obtained from the experimental and control groups of boars. Regarding the superoxide dismutase activity, the research results showed a difference in the control group compared to the experimental one. Moreover, spermatozoa DNA fragmentation and the total number of motile spermatozoa showed statistically significant lower and higher values, respectively, in experimental compared to the control groups. The combination of these two preparations shows significantly enhanced vital parameters of semen. To the best of our knowledge, this study is the first in which the ejaculate parameters were examined after the application of a combination of these two antioxidant supplements. Full article

(This article belongs to the Special Issue Modern Technology in Farm Animals’ Reproductive Services)

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11 pages, 1176 KiB

Open AccessArticle

The Use of Animal’s Body, Scrotal Temperature and Motion Monitoring in Evaluating Boar Semen Production Capacity

by Vasiliki Stravogianni, Theodoros Samaras, Constantin M. Boscos, John Markakis, Evdokia Krystallidou, Athina Basioura and Ioannis A. Tsakmakidis

Animals 2022, 12(7), 829; https://0-doi-org.brum.beds.ac.uk/10.3390/ani12070829 - 24 Mar 2022

Cited by 2 | Viewed by 2351

Abstract

Biomedical measurements by specialized technological equipment have been used in farm animals to collect information about nutrition, behavior and welfare. This study investigates the relation of semen quality (CASA analysis, viability, morphology, membrane biochemical activity and DNA fragmentation) with boar behavior during ejaculation. Sensors were placed on the boar’s body. Movement features were collected using an inertial measurement unit (IMU), comprising an accelerometer, a gyroscope and a magnetometer. Boar, scrotal and dummy temperatures were measured by an infrared (IR) camera and an IR thermometer, while the face salivation of the boar was recorded by a moisture meter (also based on IR technology). All signals and images were logged on a mobile device (smartphone or tablet) using a Bluetooth connection and then transferred wirelessly to the cloud. The data files were then processed using scripts in MATLAB 2021a (MathWorks, Natick, Massachusetts) to derive the necessary indices. Ninety-four ejaculates from five boars were analyzed in this study. The statistical analysis was performed in the Statistics and Machine Learning Toolbox of MATLAB 2021a using a linear mixed effects model. Significant and strong negative correlations (R² > 0.5, p ≤ 0.05) were observed between boar, dummy and scrotal temperature with the progressive, rapid and slow movement of spermatozoa, VCL (curvilinear velocity), VSL (straight line velocity) and ALH (amplitude of lateral head displacement) kinematics. The volume of the ejaculate was correlated with the scrotal and dummy temperature. Dummy’s temperature was negatively correlated with BCF (beat/cross-frequency), viability and total time of ejaculation, while it was positively correlated with abnormal morphology. Body temperature was negatively correlated with BCF. Positive correlations were noticed between VAP (average path velocity) and total time of ejaculation with body acceleration features, as well as between the overall dynamic body acceleration (ODBA) and total time of ejaculation. In conclusion, the use of biomedical sensors can support the evaluation of boar sperm production capacity, providing valuable information about semen quality. Full article

(This article belongs to the Special Issue Modern Technology in Farm Animals’ Reproductive Services)

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