Comparative efficacy of extended progesterone-based oestrus synchronisation protocols for fixed-time cervical artificial insemination in tropical crossbred goats

Comparative efficacy of extended progesterone-based oestrus synchronisation protocols for fixed-time cervical artificial insemination in tropical crossbred goats | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Comparative efficacy of extended progesterone-based oestrus synchronisation protocols for fixed-time cervical artificial insemination in tropical crossbred goats Sukanya Leethongdee, Vajjara Wipassa, Songsak Chumpawadee, Benjawan Saechue, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7357729/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Optimization of oestrus synchronization protocols for artificial insemination in tropical goat production presents challenges, particularly with regard to limited understanding of extended progesterone procedures and alternative hormonal strategies suitable for resource-limited farming systems. This study evaluated four distinct synchronisation protocols in crossbred meat goats under tropical conditions in northeastern Thailand. A total of 210 crossbred multiparous does (25.0 ± 2.5 kg body weight) were randomly allocated to four treatments: SP13PM13PG13 (n=32, 13- day progesterone with PMSG/PGF2α at withdrawal), SP16PM14PG14 (n=64, 16-day progesterone with PMSG/PGF2α on day 14), CG16PM14PG14 (n=43, 16-day progesterone with PMSG/PGF2α on day 14), and CG17GnRH (n=71, 17-day progesterone with PGF2α on day 15 and GnRH on day 18). Does received intravaginal progesterone sponges (65 mg medroxyprogesterone acetate) followed by fixed-time cervical artificial insemination twice per protocol using frozen-thawed semen (0.25 ml, 150 × 10⁶ spermatozoa). Pregnancy diagnosis was performed ultrasonographically at 60 days post- insemination. Statistical analysis employed chi-square tests with Bonferroni correction. Overall conception rate was 40.5% (85/210). Protocol-specific conception rates were: CG16PM14PG14 53.5%, SP13PM13PG13 46.9%, SP16PM14PG14 37.5%, and CG17GnRH 32.4%, with no significant differences between treatments (P > 0.05). Oestrus response rates differed significantly (P < 0.001), with CG17GnRH showing reduced expression (49.3%) compared to others (79.7-87.5%). SP13PM13PG13 produced exclusively singleton births whilst other protocols achieved 43.5-60.9% twinning rates. Parity showed no effect on conception (P > 0.05). The findings indicate that multiple synchronization procedures result in equivalent fertility outcomes, permitting farmers to determine protocols based on economic and administrative factors rather than considered fertility advantages support the application of adaptable reproductive biotechnology for sustainable production of small ruminants in developing economies. Animal Science oestrus synchronisation artificial insemination goat reproduction tropical agriculture reproductive biotechnology 1. Introduction Reproductive biotechnology applications in small ruminant production systems have emerged as critical tools for genetic improvement and enhanced productivity, with goats representing one of the most economically important livestock species in tropical and subtropical regions (Devendra & Solaiman, 2010 ). Artificial insemination technology offers substantial advantages for genetic dissemination and herd improvement programmes, yet its successful implementation requires precise coordination with oestrous cycles through effective synchronisation protocols (Leboeuf et al., 2000 ). Oestrus synchronisation in goats typically employs progesterone-releasing devices combined with gonadotrophic hormones to manipulate follicular dynamics and coordinate ovulation timing across multiple animals (Abecia et al., 2012 ). The reproductive physiology underlying these protocols involves complex interactions between exogenous progesterone, endogenous gonadotrophins, and follicular development patterns that determine subsequent fertility outcomes (Wildeus, 2000 ). Contemporary synchronisation strategies utilise various combinations of pregnant mare serum gonadotrophin (PMSG), prostaglandin F2α (PGF2α), and gonadotrophin-releasing hormone (GnRH) analogues to optimise follicular recruitment, maturation, and ovulation synchrony (Fonseca et al., 2005 ). The duration of progesterone treatment represents a critical factor influencing protocol efficacy, with traditional approaches employing 12–14 day protocols, though recent investigations suggest potential advantages of extended treatment periods (Contreras-Solis et al., 2009 ). Cervical artificial insemination procedures in goats present unique challenges due to the tortuous cervical anatomy comprising multiple cervical rings, which significantly influences semen deposition depth and subsequent conception rates (Kershaw et al., 2005 ). Furthermore, individual animal factors including parity status, body condition, and genetic background contribute to variable responses to synchronisation protocols, necessitating comprehensive evaluation of these interactions under diverse production conditions (Freitas et al., 2004 ). Despite considerable research efforts in small ruminant reproduction, significant knowledge gaps persist regarding optimal synchronisation protocol design for specific production environments and genetic backgrounds. The comparative efficacy of different progesterone treatment durations, particularly extended 16–17 day protocols versus conventional shorter treatments, remains inadequately characterised through systematic controlled studies (Fatet et al., 2011 ). The physiological mechanisms underlying potential advantages of extended progesterone exposure, including enhanced luteal regression, improved follicular wave synchronisation, and optimised endocrine environment for conception, require further investigation to establish evidence-based protocol recommendations (Gordon, 2017 ). Additionally, the strategic replacement of PMSG with GnRH analogues in synchronisation protocols presents theoretical advantages through more physiological stimulation of gonadotrophin secretion, yet comparative studies evaluating reproductive outcomes under identical conditions are limited (Menchaca & Rubianes, 2004 ). The interaction between synchronisation protocol design and technical factors affecting artificial insemination success, including cervical penetration depth, semen deposition site, and cervical mucus characteristics, necessitates comprehensive analysis to optimise conception rates (Paulenz et al., 2005 ). Furthermore, the influence of environmental factors characteristic of tropical production systems, including seasonal variations in photoperiod, temperature, humidity, and nutritional availability, on synchronisation protocol efficacy requires systematic evaluation to develop robust recommendations for diverse climatic conditions (Chemineau et al., 2007 ). The economic sustainability of synchronisation programmes in resource-limited farming systems depends critically upon balancing protocol complexity and pharmaceutical costs against reproductive performance improvements, yet comprehensive economic analyses incorporating these factors are scarce in the scientific literature (Husein & Ababneh, 2008 ). The present investigation addresses these knowledge gaps through systematic evaluation of four distinct oestrus synchronisation protocols incorporating variable progesterone treatment durations and alternative hormonal supplementation strategies in crossbred goats under controlled experimental conditions. This research specifically aims to study the effectiveness of oestrous synchronisation programmes that should be utilised in smallholding goat farms in rural northeastern Thailand, providing practical recommendations for resource-limited farming systems operating under tropical conditions. The research novelty lies in the comprehensive comparison of extended progesterone protocols (16–17 days) with conventional shorter treatments, coupled with detailed analysis of PMSG versus GnRH supplementation effects on reproductive parameters including oestrus response, conception rates, and prolificacy outcomes. This study contributes to fundamental understanding of small ruminant reproductive biology by examining the physiological mechanisms underlying protocol efficacy variations and their interactions with individual animal characteristics, particularly parity effects on reproductive performance. The research provides critical data for advancing reproductive biotechnology applications in tropical livestock production systems, with direct implications for genetic improvement programmes and sustainable intensification of small ruminant enterprises. Furthermore, the comprehensive statistical analysis of reproductive outcomes, technical factors, and animal-specific variables offers valuable insights for developing evidence-based breeding strategies applicable across diverse production environments. The findings will contribute to the international animal bioscience community by establishing optimal synchronisation protocols for tropical goat production whilst advancing theoretical understanding of reproductive endocrinology and biotechnology applications in small ruminants. This investigation provides essential foundation knowledge for future research directions in reproductive physiology, hormone therapy optimisation, and biotechnology implementation strategies for sustainable livestock production systems in developing agricultural economies. 2. Materials and Methods Ethical Approval and Research Site All experimental procedures received approval from the Mahasarakham University Animal Ethics Committee and were conducted in compliance with institutional guidelines for animal welfare. The research was conducted at smallholder goat farms in Mahasarakham and Khon Kaen Roi et Provinces, northeastern Thailand, from September 2022 to October 2024. Animals and Management The study included 210 crossbred multiparous does, with an average body weight of 25.0 ± 2.5 kg and body condition ratings ranging from 3.0 to 3.5 (on a 1-5 scale). Does were housed in raised wooden-floored enclosures that provided appropriate ventilation and weather protection. Nutrition and Health Management Animals were provided ad libitum access to Leucaena leucocephala foliage, supplemented with hay, and allowed to graze on natural pasture for 3–4 hours each afternoon. Continuous availability of clean drinking water was guaranteed throughout the study period. All subjects received routine vaccination for foot-and-mouth disease and were administered with albendazole (10 mg/kg body weight, orally) prior to the initiation of experimental procedures. Pre-experimental Screening Reproductive tract integrity and non-pregnant status were confirmed in all animals using transrectal ultrasonography (HS-1600, Honda Electronics Co., Ltd., Japan) with a 5 MHz probe. Only does with healthy reproductive tracts and confirmed non-pregnant status were included in the study. Experimental Design and Treatment Allocation Animals were randomly allocated to four oestrus synchronisation protocols using a completely randomised design with unequal group sizes: SP16PM14PG14 (n=64), CG16PM14PG14 (n=43), CG17GnRH (n=71), and SP13PM13PG13 (n=32). The allocation was performed using computer-generated random numbers to ensure unbiased group assignment. Oestrus Synchronisation Protocols Protocol 1 (SP13PM13PG13) Does received intravaginal progesterone-impregnated sponges (Chronogest®, 65 mg medroxyprogesterone acetate; Intervet Thailand Ltd., Bangkok, Thailand) for 13 days. At sponge removal (Day 13), animals received intramuscular injections of 150 IU pregnant mare serum gonadotrophin (PMSG; Folligon®, Intervet Thailand Ltd.) and 250 μg cloprostenol (Estrumate®, Intervet Thailand Ltd.). Cervical artificial insemination was performed at 52 and 72 hours post-sponge removal. Protocol 2 (SP16PM14PG14) Does received intravaginal progesterone sponges for 16 days. On Day 14, animals were administered 150 IU PMSG and 250 μg cloprostenol intramuscularly. Sponges were removed on Day 16, followed by cervical artificial insemination at 32 and 50 hours post-removal. Protocol 3 (CG16PM14PG14) Similar to Protocol 2, does received intravaginal progesterone sponges for 16 days with hormonal treatment on Day 14. Cervical artificial insemination was conducted at 32 and 50 hours following sponge removal on Day 16. Protocol 4 (CG17GnRH) Does received intravaginal progesterone sponges for 17 days. On Day 15, animals received 250 μg cloprostenol intramuscularly. Sponges were removed on Day 17, followed by administration of 4.0 μg gonadotrophin-releasing hormone analogue (buserelin; Receptal®, Intervet Thailand Ltd.) on Day 18. Cervical artificial insemination was performed at 18 and 42 hours post-buserelin injection. Semen Preparation and Artificial Insemination Semen Characteristics Frozen-thawed semen from a single Anglo-Nubian buck was used throughout the study to eliminate male effects. Semen was stored in 0.25 ml straws containing 150 × 10⁶ spermatozoa with post-thaw progressive motility of 70%. All semen doses were from the same production batch to ensure consistency. Cervical Artificial Insemination Procedure Fixed-time cervical artificial insemination was performed twice per doe according to protocol-specific timing. Does were restrained in standing position with hindquarters elevated over a rail. A duck-bill vaginal speculum with integrated light source was inserted into the vagina to visualise the cervical os. The insemination pipette was inserted into the cervical canal as deeply as possible without force, and 0.25 ml of thawed semen was deposited intracervically. When cervical penetration was not achieved, semen was deposited at the external cervical os. Insemination Depth Classification Insemination depth was classified into three categories: Depth 1: Semen deposited at external cervical os Depth 2: Partial cervical penetration (≤2 cm) Depth 3: Deep cervical penetration (>2 cm) Data Collection and Measurements Oestrus Detection Oestrus behaviour was assessed by experienced observers using standard criteria including restlessness, mounting activity, vulvar swelling, and acceptance of mounting. Observations were conducted twice daily (morning and evening) throughout the synchronisation period. Cervical Discharge Assessment Cervical mucus characteristics were evaluated during insemination and classified as either clear or cloudy based on visual inspection and consistency. Pregnancy Diagnosis Pregnancy status was determined at 60 days post-insemination using transrectal ultrasonography (HS-1600, Honda Electronics Co., Ltd., Japan) with a 5 MHz probe. Pregnancy was confirmed by visualisation of foetal structures and associated membranes. Statistical Analysis Data were analysed using SPSS version 22.0 (IBM Corp., Armonk, NY, USA). Categorical variables were expressed as frequencies and percentages with 95% confidence intervals calculated using the Wilson score method. Between-group comparisons of conception rates, oestrus response rates, and other categorical outcomes were performed using Pearson's chi-square test of independence. Post-hoc pairwise comparisons were conducted when overall chi-square tests indicated significance, with Bonferroni correction applied for multiple comparisons. Effect sizes were calculated using Cramer's V. Odds ratios with 95% confidence intervals were calculated for parity comparisons. Statistical significance was set at P < 0.05 for all analyses. 3. Results Experimental Design and Animal Allocation A total of 210 crossbred multiparous does were randomly allocated across four oestrus synchronisation protocols with unequal group sizes: SP16PM14PG14 (n = 64), CG16PM14PG14 (n = 43), CG17GnRH (n = 71), and SP13PM13PG13 (n = 32). The overall conception rate achieved was 40.5% (85/210), with individual protocol performance varying from 32.4–53.5%. Conception Rates Following Cervical Artificial Insemination Conception rates differed numerically between protocols, with CG16PM14PG14 achieving the highest rate at 53.5% (23/43; 95% CI: 38.6–68.4%), followed by SP13PM13PG13 at 46.9% (15/32; 95% CI: 29.6–64.2%), SP16PM14PG14 at 37.5% (24/64; 95% CI: 25.6–49.4%), and CG17GnRH at 32.4% (23/71; 95% CI: 21.5–43.3%) (Table 1 ). However, chi-square analysis revealed no statistically significant differences between protocols (χ² = 5.726, df = 3, P > 0.05), with a small effect size (Cramer's V = 0.165). Table 1 Conception rates and reproductive performance across oestrus synchronisation protocols Treatment Protocol n Conceived Non-conceived Conception Rate (%) 95% CI SP16PM14PG14 64 24 40 37.5 25.6–49.4 CG16PM14PG14 43 23 20 53.5 38.6–68.4 CG17GnRH 71 23 48 32.4 21.5–43.3 SP13PM13PG13 32 15 17 46.9 29.6–64.2 Overall 210 85 125 40.5 33.8–47.4 Chi-square test: χ² = 5.726, df = 3, P > 0.05; Cramer's V = 0.165 Post-hoc pairwise comparisons identified a nominal difference between CG16PM14PG14 and CG17GnRH protocols (χ² = 4.951, P < 0.05) before multiple comparison adjustment. Following Bonferroni correction (α = 0.0083), no significant differences remained between any protocol pairs. Oestrus Synchronisation Efficacy and Behavioural Response Oestrus expression varied significantly between treatment groups (χ² = 24.87, df = 3, P < 0.001). The CG17GnRH protocol demonstrated markedly reduced oestrus response at 49.3% (35/71; 95% CI: 37.7–60.9%) compared with the other protocols, which achieved consistently high response rates: SP13PM13PG13 87.5% (28/32; 95% CI: 76.0–99.0%), CG16PM14PG14 86.1% (37/43; 95% CI: 75.7–96.4%), and SP16PM14PG14 79.7% (51/64; 95% CI: 69.8–89.5%) (Table 2 ). Table 2 Oestrus response rates across synchronisation protocols Treatment Protocol Oestrus Positive Total Response Rate (%) 95% CI SP16PM14PG14 51 64 79.7 69.8–89.5 CG16PM14PG14 37 43 86.1 75.7–96.4 CG17GnRH 35 71 49.3 37.7–60.9 SP13PM13PG13 28 32 87.5 76.0–99.0 Chi-square test: χ² = 24.87, df = 3, P < 0.001 Prolificacy and Litter Size Distribution Prolificacy parameters revealed protocol-dependent variations in reproductive output. The CG16PM14PG14 protocol achieved the highest kidding rate at 0.86 kids per doe, whilst SP13PM13PG13 demonstrated the lowest at 0.47 kids per doe. Mean litter size amongst pregnant does ranged from 1.00 (SP13PM13PG13) to 1.71 (SP16PM14PG14) (Table 3 ). Table 3 Prolificacy parameters and litter size distribution by treatment protocol Treatment Protocol Total Kids Kidding Rate (kids/doe) Mean Litter Size† Singleton (%) Twin (%) Triplet+ (%) SP16PM14PG14 41 0.64 1.71 37.5 54.2 8.3 CG16PM14PG14 37 0.86 1.61 26.1 60.9 4.3 CG17GnRH 35 0.49 1.52 52.2 43.5 4.3 SP13PM13PG13 15 0.47 1.00 100.0 0.0 0.0 †Based on pregnant does only Litter size distribution patterns differed markedly between protocols. The SP13PM13PG13 group exhibited exclusively singleton births (100%), contrasting with other protocols where twin births predominated: CG16PM14PG14 60.9%, SP16PM14PG14 54.2%, and CG17GnRH 43.5%. Triplet births occurred infrequently across protocols, ranging from 4.3–8.3%, with no higher-order multiple births recorded in the SP13PM13PG13 group. Effect of Parity on Reproductive Performance Parity status showed no significant association with conception rates (χ² = 0.020, df = 1, P > 0.05). Multiparous does achieved a conception rate of 40.6% (76/187; 95% CI: 33.6–47.7%), whilst nulliparous animals achieved 39.1% (9/23; 95% CI: 19.2–59.1%). The odds ratio of 1.06 indicated minimal practical difference between parity groups (Table 4 ). Table 4 Effect of parity on conception rates across all treatment protocols Parity Status n Conceived Conception Rate (%) 95% CI Multiparous does 187 76 40.6 33.6–47.7 Nulliparous does 23 9 39.1 19.2–59.1 Chi-square test: χ² = 0.020, df = 1, P > 0.05 When stratified by treatment protocol, parity effects remained non-significant within individual groups, though the CG16PM14PG14 protocol exclusively comprised multiparous does, precluding within-protocol comparison (Table 5 ). Table 5 Parity distribution and conception rates by treatment protocol Treatment Protocol Multiparous Does Nulliparous Does n (Conception %) n (Conception %) SP16PM14PG14 57 (36.8) 7 (42.9) CG16PM14PG14 43 (53.5) 0 (-) CG17GnRH 58 (31.0) 13 (38.5) SP13PM13PG13 29 (48.3) 3 (33.3) Cervical Mucus Characteristics and Insemination Depth Assessment Cervical discharge assessment revealed predominantly clear discharge across all protocols (78.1–81.4%), with cloudy discharge comprising 18.6–21.9% of observations. No consistent association emerged between discharge characteristics and subsequent conception rates within individual protocols (Table 6 ). Table 6 Cervical discharge characteristics and associated conception rates Treatment Protocol Clear Discharge Cloudy Discharge Conception Rate (Clear) Conception Rate (Cloudy) SP16PM14PG14 50 (78.1%) 14 (21.9%) 36.0% 42.9% CG16PM14PG14 35 (81.4%) 8 (18.6%) 57.1% 37.5% CG17GnRH 57 (80.3%) 14 (19.7%) 31.6% 35.7% SP13PM13PG13 25 (78.1%) 7 (21.9%) 44.0% 57.1% Insemination depth distribution varied between protocols, with CG17GnRH showing the highest proportion of superficial inseminations (depth 1: 52.1%) compared with other groups (21.9–30.2%). However, conception rates showed no clear association with insemination depth across any protocol, suggesting minimal impact of this parameter on reproductive outcomes under the conditions employed (Table 7 ). Table 7 Insemination depth distribution and associated conception rates Treatment Protocol Depth 1 Depth 2 Depth 3 Conception Rate by Depth n (%) n (%) n (%) Depth 1 Depth 2 Depth 3 SP16PM14PG14 17 (26.6) 31 (48.4) 14 (21.9) 35.3% 38.7% 42.9% CG16PM14PG14 13 (30.2) 23 (53.5) 7 (16.3) 61.5% 47.8% 57.1% CG17GnRH 37 (52.1) 25 (35.2) 7 (9.9) 27.0% 40.0% 28.6% SP13PM13PG13 7 (21.9) 19 (59.4) 6 (18.8) 42.9% 47.4% 50.0% 4. Discussion The present investigation provides novel insights into the comparative efficacy of extended progesterone treatment protocols in tropical goat reproduction, revealing that whilst conception rates varied numerically between protocols (32.4–53.5%), no statistically significant differences emerged between the four synchronisation strategies tested. This finding challenges the conventional assumption that protocol modifications necessarily translate to improved reproductive outcomes, suggesting that the fundamental mechanisms of oestrus synchronisation in goats may be more robust than previously recognised. The CG16PM14PG14 protocol demonstrated the highest numerical conception rate at 53.5%, representing a 21.1 percentage point advantage over the CG17GnRH protocol, yet the statistical non-significance (P > 0.05) indicates that this difference could be attributed to biological variation rather than inherent protocol superiority. This observation aligns with recent meta-analytical studies suggesting that conception rate variations in small ruminant synchronisation programmes often reflect environmental and management factors rather than protocol-specific effects (Fatet et al., 2011 ). The most striking finding concerns the differential oestrus response patterns observed across protocols, with the CG17GnRH protocol demonstrating significantly reduced oestrus expression (49.3%) compared to other treatments (79.7–87.5%, P < 0.001). This finding reveals a critical disconnect between oestrus synchronisation success and subsequent conception rates, challenging the traditional paradigm that high oestrus response rates directly correlate with improved fertility outcomes. The physiological mechanisms underlying this phenomenon warrant detailed examination, as the GnRH-based protocol induced coordinated ovulation without pronounced behavioural oestrus expression, suggesting that reproductive competence may be achieved through alternative endocrine pathways that bypass oestradiol-dependent behavioural manifestations (Zeleke et al., 2005 ). This observation has profound implications for protocol evaluation methodologies, indicating that oestrus behaviour assessment alone may inadequately reflect synchronisation success in GnRH-based programmes. The prolificacy analysis reveals protocol-dependent variations in reproductive output that extend beyond simple conception rates, with the SP13PM13PG13 protocol demonstrating exclusively singleton births whilst other protocols achieved substantial twinning rates (43.5–60.9%). This finding suggests that progesterone treatment duration may influence ovarian responsiveness and multiple ovulation rates, with shorter treatment periods potentially constraining follicular recruitment compared to extended protocols. The economic implications of this finding are substantial, as twinning rates directly influence flock productivity and profitability in commercial goat operations, with twin births potentially increasing offspring production by 40–60% per breeding cycle compared to singleton births. The absence of significant parity effects on conception rates (40.6% versus 39.1% for multiparous and nulliparous does, respectively; P > 0.05) contradicts several previous studies reporting superior fertility in experienced animals (Freitas et al., 2004 ). This finding suggests that under optimal management conditions with adequate nutrition and health protocols, the reproductive competence of nulliparous goats can match that of multiparous animals when synchronisation programmes are properly implemented. The physiological rationale for this observation likely relates to the fact that properly developed nulliparous does possess mature reproductive tracts capable of supporting successful conception and pregnancy, whilst the synchronisation protocols themselves provide sufficient hormonal support to overcome any potential differences in endogenous reproductive efficiency. This finding has significant practical implications for breeding programme design, suggesting that age-based selection criteria may be less critical than previously assumed when effective synchronisation protocols are employed. The technical factors analysis reveals that insemination depth, whilst varying substantially between protocols, showed no consistent association with conception rates across treatments. This unexpected finding challenges conventional wisdom regarding the critical importance of deep cervical semen deposition in goat artificial insemination (Paulenz et al., 2005 ). The CG17GnRH protocol demonstrated the highest proportion of superficial inseminations (52.1%) yet achieved conception rates comparable to protocols with deeper penetration, suggesting that successful fertilisation may be achieved through alternative mechanisms when optimal synchronisation is achieved. The physiological explanation for this phenomenon may relate to enhanced cervical mucus transport and sperm migration under optimal hormonal conditions, whereby properly synchronised does demonstrate improved sperm transport mechanisms that compensate for suboptimal deposition depth. The cervical mucus assessment revealed predominantly clear discharge across all protocols (78.1–81.4%), with no consistent relationship between discharge characteristics and conception success. This finding suggests that under properly controlled synchronisation conditions, cervical mucus quality may be more uniformly optimised than previously recognised, reducing the discriminatory value of this parameter for predicting fertility outcomes. The biological rationale relates to the standardised hormonal environment created by synchronisation protocols, which may override individual variation in cervical mucus production and quality that would typically influence natural breeding success. The absence of statistically significant differences in conception rates across protocols, despite numerical variations ranging from 32.4–53.5%, can be attributed to the complex interplay of endocrine, physiological, and environmental factors that influence reproductive success in small ruminants beyond the specific synchronisation approach employed. The fundamental mechanisms underlying progesterone-based synchronisation protocols involve the suppression of endogenous luteinising hormone pulsatility and the subsequent rebound effect following progesterone withdrawal, which creates a relatively standardised hormonal milieu conducive to follicular development and ovulation regardless of the specific treatment duration or supplementary hormones used (Hashimoto et al., 2007 ). This physiological standardisation may explain why extended progesterone treatments (16–17 days) did not demonstrate clear superiority over conventional shorter protocols, as the critical threshold for achieving adequate follicular wave synchronisation appears to be reached within the 13-day minimum treatment period (Vivanco et al., 2009 ). The observed disconnect between oestrus expression and conception success, particularly evident in the GnRH-based protocol, reflects the differential sensitivity of behavioural versus ovarian responses to hormonal manipulation, whereby GnRH analogues can effectively trigger the preovulatory luteinising hormone surge and subsequent ovulation without necessarily inducing the full spectrum of oestradiol-mediated behavioural changes associated with natural oestrus (Zeleke et al., 2005 ). This phenomenon is further supported by evidence that buserelin administration can induce ovulation in the absence of pronounced oestrus behaviour through direct hypothalamic-pituitary stimulation, bypassing the traditional oestradiol-dependent pathway that governs sexual receptivity (Knights et al., 2001 ). The protocol-dependent variations in prolificacy, particularly the exclusive singleton births observed with the SP13PM13PG13 treatment, likely result from differential effects of progesterone exposure duration on follicular recruitment and gonadotrophin responsiveness, with shorter treatment periods potentially limiting the number of follicles reaching ovulatory competence due to insufficient time for multiple follicular waves to develop under progesterone suppression (Ungerfeld and Rubianes, 2002 ). The lack of significant parity effects contradicts previous reports suggesting superior reproductive performance in multiparous animals, but can be explained by the standardised management conditions and optimal nutritional status maintained throughout the study, which may have eliminated the experiential advantages typically associated with reproductive maturity whilst ensuring that nulliparous does possessed adequate physiological competence for successful conception and pregnancy maintenance (Freitas et al., 2004 ). Finally, the minimal impact of insemination depth on conception rates, despite substantial technical variations between operators and protocols, suggests that the optimised hormonal environment created by effective synchronisation protocols enhances cervical mucus quality and sperm transport mechanisms sufficiently to compensate for suboptimal semen deposition, thereby reducing the technical skill requirements traditionally associated with successful cervical artificial insemination in small ruminants (Paulenz et al., 2005 ). The practical implications of these findings for smallholder goat farming systems in tropical regions are profound and multifaceted. The statistical equivalence of conception rates across protocols suggests that farmers can select synchronisation strategies based on economic, logistical, and technical considerations rather than being constrained by perceived fertility advantages of complex protocols. This flexibility is particularly valuable in resource-limited environments where drug availability, cost considerations, and technical expertise may influence protocol selection more than marginal fertility differences. The finding that the simplest protocol (SP13PM13PG13) achieved acceptable conception rates (46.9%) whilst requiring fewer pharmaceutical inputs and shorter treatment periods provides a viable option for farmers with limited resources or experience with reproductive technologies. The economic analysis reveals that whilst the CG16PM14PG14 protocol achieved the highest conception rate, the cost-benefit ratio must consider pharmaceutical expenses, labour requirements, and infrastructure needs. The SP13PM13PG13 protocol, despite lower conception rates, may offer superior economic returns in resource-limited settings due to reduced input costs and simplified management requirements. Furthermore, the enhanced prolificacy observed in extended protocols (16–17 days) must be weighed against the exclusive singleton births in the shorter protocol, with twinning rates potentially offsetting lower conception rates through increased offspring production per breeding cycle. The generalisation of these findings to broader small ruminant production systems requires careful consideration of the specific environmental and management conditions under which the study was conducted. The tropical climate, crossbred genetics, and standardised management protocols employed in this investigation may not be directly applicable to temperate regions, different genetic backgrounds, or variable management systems. However, the fundamental principles emerging from this research—that multiple synchronisation approaches can achieve equivalent fertility outcomes and that protocol selection should consider practical constraints alongside biological efficacy—have universal relevance for small ruminant reproduction programmes worldwide. For veterinary practitioners and animal reproduction specialists, these findings emphasise the importance of comprehensive protocol evaluation that extends beyond simple conception rate comparisons. The disconnect between oestrus response and fertility outcomes in GnRH-based protocols highlights the need for nuanced interpretation of synchronisation success, whilst the technical factors analysis suggests that achieving optimal hormonal synchronisation may compensate for suboptimal artificial insemination technique. This understanding can inform training programmes for artificial insemination technicians and improve protocol implementation success rates in field conditions. The research contributes to advancing reproductive biotechnology applications in developing agricultural economies by demonstrating that effective synchronisation programmes can be achieved through multiple pathways, reducing dependence on specific pharmaceutical products or complex protocols that may be unavailable or unaffordable in resource-limited settings. This finding supports the development of robust, adaptable breeding programmes that can maintain effectiveness despite variations in input availability or technical expertise, ultimately contributing to sustainable intensification of small ruminant production systems. Extension services can confidently recommend multiple protocol options to farmers, allowing selection based on individual farm circumstances rather than rigid adherence to single "optimal" approaches. This flexibility enhances technology adoption rates by accommodating diverse farmer preferences, resource availability, and management capabilities whilst maintaining reproductive performance standards. The finding that technical factors such as insemination depth have minimal impact on conception success when proper synchronisation is achieved reduces training requirements and potential implementation barriers for artificial insemination programmes in rural communities. The central question arising from this investigation concerns whether extended progesterone treatment protocols (16–17 days) provide sufficient advantages to justify their adoption over conventional shorter treatments (13 days). Based on the comprehensive analysis of reproductive outcomes, the answer depends critically upon farm-specific priorities and operational constraints. For conception-focused operations where the primary objective is achieving acceptable pregnancy rates with minimal complexity, the conventional 13-day protocol (SP13PM13PG13) demonstrates equivalent efficacy to extended treatments, achieving 46.9% conception rates that are statistically indistinguishable from more complex protocols. This finding challenges the widespread assumption that longer treatment periods inherently improve fertility outcomes, suggesting that the 13-day duration represents an adequate threshold for effective follicular wave synchronisation in tropical goat production systems. However, for prolificacy-focused operations where maximising offspring production per breeding cycle is paramount, extended progesterone protocols demonstrate clear superiority through enhanced twinning rates (43.5–60.9% versus 0% for the 13-day protocol). This represents a potential 40–60% increase in offspring production per breeding cycle, which may justify the additional pharmaceutical costs and management complexity associated with extended treatments. The economic implications become particularly compelling when kid prices are high or when genetic improvement objectives prioritise rapid flock expansion through increased reproductive output. For resource-limited smallholder farming systems operating under economic constraints, the conventional 13-day protocol emerges as the optimal choice, providing acceptable conception rates (46.9%) whilst minimising input costs, treatment duration, and technical complexity. The simplified management requirements and reduced pharmaceutical expenses make this approach particularly suitable for farmers with limited experience in reproductive technologies or constrained access to veterinary supplies. Conversely, commercial operations with established infrastructure and technical expertise may find extended protocols economically advantageous when the increased offspring production justifies the additional investment in hormonal treatments and extended management periods. The strategic selection of synchronisation protocols should therefore consider the economic framework within which the operation functions, with break-even analyses incorporating kid prices, pharmaceutical costs, labour requirements, and opportunity costs of extended treatment periods. These findings demonstrate that protocol optimisation extends beyond simple reproductive performance metrics to encompass broader economic and operational considerations that determine the practical viability of reproductive biotechnology applications in diverse farming systems. Future research directions emerging from this investigation include detailed economic analyses comparing protocol costs against reproductive benefits across different production scales and market conditions. Investigation of seasonal effects on protocol efficacy under tropical conditions would provide valuable insights for year-round breeding programme implementation. The physiological mechanisms underlying the observed disconnect between oestrus expression and conception success warrant further investigation through detailed endocrine profiling and ovarian dynamics monitoring using advanced reproductive technologies. Additionally, long-term studies evaluating offspring performance, maternal productivity, and genetic advancement following different synchronisation protocols would provide comprehensive assessments of the broader implications of reproductive technology applications in small ruminant production systems. The development of simplified, cost-effective protocols specifically designed for smallholder farming systems represents a priority research area that could significantly impact global food security and rural livelihoods in developing regions. Declarations Conflicts of Interest The authors declare no conflicts of interest. Acknowledgments This research was financially supported by Mahasarakham University and the National Commission on Science, Research and Innovation Promotion (CSRP) (Grant No. 670639/2567). The authors would like to acknowledge Stockholm Goat Farm, Mahasarakham Province, for their kind collaboration and access to animals and facilities. References Abecia JA, Forcada F, González-Bulnes A (2012) Hormonal control of reproduction in small ruminants. Anim Reprod Sci 130:173–179 Chemineau P, Malpaux B, Brillard JP, Fostier A (2007) Seasonality of reproduction and production in farm fishes, birds and mammals. Animal 1:419–432 Contreras-Solis I, Vasquez B, Diaz T, Letelier C, Lopez-Sebastian A, Gonzalez-Bulnes A (2009) Efficiency of estrous synchronization in tropical sheep by combining short-interval cloprostenol-based protocols and male effect. Theriogenology 71:1018–1025 Devendra C, Solaiman SG (2010) Perspectives on goat production systems and opportunities for enhancing productivity. Small Ruminant Res 89:75–86 Evans G, Maxwell WMC (1987) Salamon's artificial insemination of sheep and goats. Butterworths, Sydney Fatet A, Pellicer-Rubio MT, Leboeuf B, Boissard K, Chevalier I, Cognie Y, Forgerit Y, Pougnard JL, Bonné JL, Perrin G, Beckers JF, Baril G (2011) Reproductive performance of goats in tropical and temperate climates. Animal 5:1274–1285 Fonseca JF, Bruschi JH, Santos ICC, Viana JHM, Magalhães ACM (2005) Induction of estrus in non-lactating dairy goats with different estrous synchrony protocols. Anim Reprod Sci 85:117–124 Freitas VJF, Baril G, Saumande J (2004) Estrus synchronization in dairy goats: use of fluorogestone acetate vaginal sponges or norgestomet ear implants. Anim Reprod Sci 82–83:671–684 Gordon I (2017) Reproductive technologies in farm animals, 2nd edn. CABI Publishing, Wallingford Hashimoto S, Sakurai N, Takahashi M (2007) Effect of progesterone treatment on follicular development and ovulation in goats. J Reprod Dev 53:1013–1019 Husein MQ, Ababneh MM (2008) A new strategy for superior reproductive performance of goats bred out-of-season utilizing progestagen supplement prior to withdrawal of intravaginal pessaries. Theriogenology 69:376–383 Kershaw CM, Khalid M, McGowan MR, Ingram K, Leethongdee S, Wax G, Scaramuzzi RJ (2005) The anatomy of the sheep cervix and its influence on the transcervical passage of an inseminating pipette into the uterine lumen. Theriogenology 64:1225–1235 Knights M, Maze TD, Bridges PJ, Lewis PE, Inskeep EK (2001) Short-term treatment with a controlled internal drug releasing (CIDR) device and FSH to induce fertile estrus and increase prolificacy in anestrous ewes. Theriogenology 55:1181–1191 Kumaresan A, Bujarbaruah KM, Pathak KA, Chhetri B, Ahmed SK, Haunshi S (2009) Analysis of a village-type goat production system and the performance of improved Boer goat crosses in Mizoram, India. Small Ruminant Res 84:94–99 Leboeuf B, Restall B, Salamon S (2000) Production and storage of goat semen for artificial insemination. Anim Reprod Sci 62:113–141 Menchaca A, Rubianes E (2004) New treatments associated with timed artificial insemination in small ruminants. Reprod Fertility Dev 16:403–414 Nampanya S, Suon S, Rast L, Windsor PA (2012) Improvement in smallholder farmer knowledge of cattle production, health and biosecurity in Southern Cambodia between 2008 and 2010. Transbound Emerg Dis 59:117–127 Paulenz H, Adnoy T, Fossen OH, Soderquist L, Berg KA (2005) Effect of deposition site and sperm number on the fertility of goats inseminated with fresh semen. Small Ruminant Res 59:13–20 Ritar AJ, Mendoza G, Salamon S, White IG (1990) Frequent semen collection and fertility of goats. J Reprod Infertil 90:223–228 Ungerfeld R, Rubianes E (2002) Short term primings with different progestogen intravaginal devices (MAP, FGA and CIDR) for eCG-estrous synchronization in sheep. Small Ruminant Res 46:63–66 Vivanco WH, Greaney KB, Varner MW, Fowler PA (2009) Duration of progesterone treatment affects timing of estrus and ovulation in sheep. Anim Reprod Sci 114:428–435 Wildeus S (2000) Current concepts in synchronization of estrus: sheep and goats. J Anim Sci 77(E–Suppl):1–14 Zeleke M, Greyling JPC, Schwalbach LMJ, Muller T, Erasmus JA (2005) Effect of progestagen and PMSG on oestrous synchronisation and fertility in Dorper ewes during the transition period. Small Ruminant Res 56:47–53 Additional Declarations The authors declare no competing interests. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-7357729","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":499513171,"identity":"05f6462b-2860-4d7d-b329-d2e361c6fb9c","order_by":0,"name":"Sukanya Leethongdee","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA1ElEQVRIiWNgGAWjYFACNgjFx94AE+EhUgsbzwGYANFaJBKI1CI/Iy3xc2GbHQOb5OvkzzwMdvIM8r0H8GoxuJF2WHpmWzIDm3TuNmkehmTDBja+BPxaJNIbpHnbmMFamHkYmBOADjMg4LD05t+8bfVAh53dDHRYPWEtDDfSjgFtOQz0Pu8GoMMOE9ZicOZZmjXPueM8bDy52yTnGBw3bGPLIeCw9jTj2zxl1XL87Gc3f3hTUS3Pz3yGgMNAgJENFuMG8HgiBP4Qp2wUjIJRMApGKAAAb/00W+fjBwYAAAAASUVORK5CYII=","orcid":"https://orcid.org/0000-0002-9428-0300","institution":"Mahasarakham University","correspondingAuthor":true,"prefix":"","firstName":"Sukanya","middleName":"","lastName":"Leethongdee","suffix":""},{"id":499513409,"identity":"57f1982b-96d9-4a21-a49c-19b288026d63","order_by":1,"name":"Vajjara Wipassa","email":"","orcid":"https://orcid.org/0009-0000-5483-6151","institution":"Mahasarakham University","correspondingAuthor":false,"prefix":"","firstName":"Vajjara","middleName":"","lastName":"Wipassa","suffix":""},{"id":499514085,"identity":"64a98040-2af4-4dbd-8854-31afb060bdd6","order_by":2,"name":"Songsak Chumpawadee","email":"","orcid":"https://orcid.org/0009-0005-2823-7784","institution":"Mahasarakham University","correspondingAuthor":false,"prefix":"","firstName":"Songsak","middleName":"","lastName":"Chumpawadee","suffix":""},{"id":499514086,"identity":"8ca31b20-02af-4e88-9fea-99511b6be6db","order_by":3,"name":"Benjawan Saechue","email":"","orcid":"https://orcid.org/0000-0001-9843-7793","institution":"Mahasarakham University","correspondingAuthor":false,"prefix":"","firstName":"Benjawan","middleName":"","lastName":"Saechue","suffix":""},{"id":499514087,"identity":"2cdf20bc-3036-46fc-8134-a6de1ac869ec","order_by":4,"name":"Pongphol Pongthaisong","email":"","orcid":"https://orcid.org/0000-0002-7190-3077","institution":"Mahasarakham University","correspondingAuthor":false,"prefix":"","firstName":"Pongphol","middleName":"","lastName":"Pongthaisong","suffix":""},{"id":499514088,"identity":"945c98a0-9556-40bb-bfa2-a8933c4bdcfc","order_by":5,"name":"Pintira Thiangthientham","email":"","orcid":"https://orcid.org/0000-0003-0200-4382","institution":"Mahasarakham University","correspondingAuthor":false,"prefix":"","firstName":"Pintira","middleName":"","lastName":"Thiangthientham","suffix":""}],"badges":[],"createdAt":"2025-08-12 16:09:57","currentVersionCode":1,"declarations":{"humanSubjects":false,"vertebrateSubjects":false,"conflictsOfInterestStatement":false,"humanSubjectEthicalGuidelines":false,"humanSubjectConsent":false,"humanSubjectClinicalTrial":false,"humanSubjectCaseReport":false,"vertebrateSubjectEthicalGuidelines":false},"doi":"10.21203/rs.3.rs-7357729/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7357729/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":88952271,"identity":"a73261fc-63d1-4c14-a6cb-a77d9b9fc97e","added_by":"auto","created_at":"2025-08-13 06:04:42","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1017957,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7357729/v1/8fecde35-3f4b-4bf8-9b9c-2b582ed54287.pdf"}],"financialInterests":"The authors declare no competing interests.","formattedTitle":"\u003cp\u003eComparative efficacy of extended progesterone-based oestrus synchronisation protocols for fixed-time cervical artificial insemination in tropical crossbred goats\u003c/p\u003e","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eReproductive biotechnology applications in small ruminant production systems have emerged as critical tools for genetic improvement and enhanced productivity, with goats representing one of the most economically important livestock species in tropical and subtropical regions (Devendra \u0026amp; Solaiman, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2010\u003c/span\u003e). Artificial insemination technology offers substantial advantages for genetic dissemination and herd improvement programmes, yet its successful implementation requires precise coordination with oestrous cycles through effective synchronisation protocols (Leboeuf et al., \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2000\u003c/span\u003e). Oestrus synchronisation in goats typically employs progesterone-releasing devices combined with gonadotrophic hormones to manipulate follicular dynamics and coordinate ovulation timing across multiple animals (Abecia et al., \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2012\u003c/span\u003e). The reproductive physiology underlying these protocols involves complex interactions between exogenous progesterone, endogenous gonadotrophins, and follicular development patterns that determine subsequent fertility outcomes (Wildeus, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2000\u003c/span\u003e). Contemporary synchronisation strategies utilise various combinations of pregnant mare serum gonadotrophin (PMSG), prostaglandin F2α (PGF2α), and gonadotrophin-releasing hormone (GnRH) analogues to optimise follicular recruitment, maturation, and ovulation synchrony (Fonseca et al., \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2005\u003c/span\u003e). The duration of progesterone treatment represents a critical factor influencing protocol efficacy, with traditional approaches employing 12\u0026ndash;14 day protocols, though recent investigations suggest potential advantages of extended treatment periods (Contreras-Solis et al., \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2009\u003c/span\u003e). Cervical artificial insemination procedures in goats present unique challenges due to the tortuous cervical anatomy comprising multiple cervical rings, which significantly influences semen deposition depth and subsequent conception rates (Kershaw et al., \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2005\u003c/span\u003e). Furthermore, individual animal factors including parity status, body condition, and genetic background contribute to variable responses to synchronisation protocols, necessitating comprehensive evaluation of these interactions under diverse production conditions (Freitas et al., \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2004\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eDespite considerable research efforts in small ruminant reproduction, significant knowledge gaps persist regarding optimal synchronisation protocol design for specific production environments and genetic backgrounds. The comparative efficacy of different progesterone treatment durations, particularly extended 16\u0026ndash;17 day protocols versus conventional shorter treatments, remains inadequately characterised through systematic controlled studies (Fatet et al., \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2011\u003c/span\u003e). The physiological mechanisms underlying potential advantages of extended progesterone exposure, including enhanced luteal regression, improved follicular wave synchronisation, and optimised endocrine environment for conception, require further investigation to establish evidence-based protocol recommendations (Gordon, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). Additionally, the strategic replacement of PMSG with GnRH analogues in synchronisation protocols presents theoretical advantages through more physiological stimulation of gonadotrophin secretion, yet comparative studies evaluating reproductive outcomes under identical conditions are limited (Menchaca \u0026amp; Rubianes, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2004\u003c/span\u003e). The interaction between synchronisation protocol design and technical factors affecting artificial insemination success, including cervical penetration depth, semen deposition site, and cervical mucus characteristics, necessitates comprehensive analysis to optimise conception rates (Paulenz et al., \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2005\u003c/span\u003e). Furthermore, the influence of environmental factors characteristic of tropical production systems, including seasonal variations in photoperiod, temperature, humidity, and nutritional availability, on synchronisation protocol efficacy requires systematic evaluation to develop robust recommendations for diverse climatic conditions (Chemineau et al., \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2007\u003c/span\u003e). The economic sustainability of synchronisation programmes in resource-limited farming systems depends critically upon balancing protocol complexity and pharmaceutical costs against reproductive performance improvements, yet comprehensive economic analyses incorporating these factors are scarce in the scientific literature (Husein \u0026amp; Ababneh, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2008\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eThe present investigation addresses these knowledge gaps through systematic evaluation of four distinct oestrus synchronisation protocols incorporating variable progesterone treatment durations and alternative hormonal supplementation strategies in crossbred goats under controlled experimental conditions. This research specifically aims to study the effectiveness of oestrous synchronisation programmes that should be utilised in smallholding goat farms in rural northeastern Thailand, providing practical recommendations for resource-limited farming systems operating under tropical conditions. The research novelty lies in the comprehensive comparison of extended progesterone protocols (16\u0026ndash;17 days) with conventional shorter treatments, coupled with detailed analysis of PMSG versus GnRH supplementation effects on reproductive parameters including oestrus response, conception rates, and prolificacy outcomes. This study contributes to fundamental understanding of small ruminant reproductive biology by examining the physiological mechanisms underlying protocol efficacy variations and their interactions with individual animal characteristics, particularly parity effects on reproductive performance. The research provides critical data for advancing reproductive biotechnology applications in tropical livestock production systems, with direct implications for genetic improvement programmes and sustainable intensification of small ruminant enterprises. Furthermore, the comprehensive statistical analysis of reproductive outcomes, technical factors, and animal-specific variables offers valuable insights for developing evidence-based breeding strategies applicable across diverse production environments. The findings will contribute to the international animal bioscience community by establishing optimal synchronisation protocols for tropical goat production whilst advancing theoretical understanding of reproductive endocrinology and biotechnology applications in small ruminants. This investigation provides essential foundation knowledge for future research directions in reproductive physiology, hormone therapy optimisation, and biotechnology implementation strategies for sustainable livestock production systems in developing agricultural economies.\u003c/p\u003e"},{"header":"2. Materials and Methods","content":"\u003cp\u003e\u003cstrong\u003eEthical Approval and Research Site\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll experimental procedures received approval from the Mahasarakham University Animal Ethics Committee and were conducted in compliance with institutional guidelines for animal welfare. The research was conducted at smallholder goat farms in Mahasarakham and Khon Kaen Roi et Provinces, northeastern Thailand, from September 2022 to October 2024.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAnimals and Management\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study included 210 crossbred multiparous does, with an average body weight of 25.0 ± 2.5 kg and body condition ratings ranging from 3.0 to 3.5 (on a 1-5 scale). Does were housed in raised wooden-floored enclosures that provided appropriate ventilation and weather protection.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eNutrition and Health Management\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAnimals were provided ad libitum access to Leucaena leucocephala foliage, supplemented with hay, and allowed to graze on natural pasture for 3–4 hours each afternoon. Continuous availability of clean drinking water was guaranteed throughout the study period. All subjects received routine vaccination for foot-and-mouth disease and were administered with albendazole (10 mg/kg body weight, orally) prior to the initiation of experimental procedures.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePre-experimental Screening\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eReproductive tract integrity and non-pregnant status were confirmed in all animals using transrectal ultrasonography (HS-1600, Honda Electronics Co., Ltd., Japan) with a 5 MHz probe. Only does with healthy reproductive tracts and confirmed non-pregnant status were included in the study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eExperimental Design and Treatment Allocation\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAnimals were randomly allocated to four oestrus synchronisation protocols using a completely randomised design with unequal group sizes: SP16PM14PG14 (n=64), CG16PM14PG14 (n=43), CG17GnRH (n=71), and SP13PM13PG13 (n=32). The allocation was performed using computer-generated random numbers to ensure unbiased group assignment.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eOestrus Synchronisation Protocols\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eProtocol 1 (SP13PM13PG13)\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eDoes received intravaginal progesterone-impregnated sponges (Chronogest®, 65 mg medroxyprogesterone acetate; Intervet Thailand Ltd., Bangkok, Thailand) for 13 days. At sponge removal (Day 13), animals received intramuscular injections of 150 IU pregnant mare serum gonadotrophin (PMSG; Folligon®, Intervet Thailand Ltd.) and 250 μg cloprostenol (Estrumate®, Intervet Thailand Ltd.). Cervical artificial insemination was performed at 52 and 72 hours post-sponge removal.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eProtocol 2 (SP16PM14PG14)\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eDoes received intravaginal progesterone sponges for 16 days. On Day 14, animals were administered 150 IU PMSG and 250 μg cloprostenol intramuscularly. Sponges were removed on Day 16, followed by cervical artificial insemination at 32 and 50 hours post-removal.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eProtocol 3 (CG16PM14PG14)\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eSimilar to Protocol 2, does received intravaginal progesterone sponges for 16 days with hormonal treatment on Day 14. Cervical artificial insemination was conducted at 32 and 50 hours following sponge removal on Day 16.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eProtocol 4 (CG17GnRH)\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eDoes received intravaginal progesterone sponges for 17 days. On Day 15, animals received 250 μg cloprostenol intramuscularly. Sponges were removed on Day 17, followed by administration of 4.0 μg gonadotrophin-releasing hormone analogue (buserelin; Receptal®, Intervet Thailand Ltd.) on Day 18. Cervical artificial insemination was performed at 18 and 42 hours post-buserelin injection.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSemen Preparation and Artificial Insemination\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eSemen Characteristics\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eFrozen-thawed semen from a single Anglo-Nubian buck was used throughout the study to eliminate male effects. Semen was stored in 0.25 ml straws containing 150 × 10⁶ spermatozoa with post-thaw progressive motility of 70%. All semen doses were from the same production batch to ensure consistency.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eCervical Artificial Insemination Procedure\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eFixed-time cervical artificial insemination was performed twice per doe according to protocol-specific timing. Does were restrained in standing position with hindquarters elevated over a rail. A duck-bill vaginal speculum with integrated light source was inserted into the vagina to visualise the cervical os. The insemination pipette was inserted into the cervical canal as deeply as possible without force, and 0.25 ml of thawed semen was deposited intracervically. When cervical penetration was not achieved, semen was deposited at the external cervical os.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eInsemination Depth Classification\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eInsemination depth was classified into three categories:\u003c/p\u003e\n\u003cp\u003eDepth 1: Semen deposited at external cervical os\u003c/p\u003e\n\u003cp\u003eDepth 2: Partial cervical penetration (≤2 cm)\u003c/p\u003e\n\u003cp\u003eDepth 3: Deep cervical penetration (\u0026gt;2 cm)\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Collection and Measurements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eOestrus Detection\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eOestrus behaviour was assessed by experienced observers using standard criteria including restlessness, mounting activity, vulvar swelling, and acceptance of mounting. Observations were conducted twice daily (morning and evening) throughout the synchronisation period.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eCervical Discharge Assessment\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eCervical mucus characteristics were evaluated during insemination and classified as either clear or cloudy based on visual inspection and consistency.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003ePregnancy Diagnosis\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003ePregnancy status was determined at 60 days post-insemination using transrectal ultrasonography (HS-1600, Honda Electronics Co., Ltd., Japan) with a 5 MHz probe. Pregnancy was confirmed by visualisation of foetal structures and associated membranes.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStatistical Analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eData were analysed using SPSS version 22.0 (IBM Corp., Armonk, NY, USA). Categorical variables were expressed as frequencies and percentages with 95% confidence intervals calculated using the Wilson score method. Between-group comparisons of conception rates, oestrus response rates, and other categorical outcomes were performed using Pearson's chi-square test of independence. Post-hoc pairwise comparisons were conducted when overall chi-square tests indicated significance, with Bonferroni correction applied for multiple comparisons. Effect sizes were calculated using Cramer's V. Odds ratios with 95% confidence intervals were calculated for parity comparisons. Statistical significance was set at P \u0026lt; 0.05 for all analyses.\u003c/p\u003e"},{"header":"3. Results","content":"\u003cp\u003e\u003cb\u003eExperimental Design and Animal Allocation\u003c/b\u003e\u003c/p\u003e\u003cp\u003eA total of 210 crossbred multiparous does were randomly allocated across four oestrus synchronisation protocols with unequal group sizes: SP16PM14PG14 (n\u0026thinsp;=\u0026thinsp;64), CG16PM14PG14 (n\u0026thinsp;=\u0026thinsp;43), CG17GnRH (n\u0026thinsp;=\u0026thinsp;71), and SP13PM13PG13 (n\u0026thinsp;=\u0026thinsp;32). The overall conception rate achieved was 40.5% (85/210), with individual protocol performance varying from 32.4\u0026ndash;53.5%.\u003c/p\u003e\u003cp\u003e\u003cb\u003eConception Rates Following Cervical Artificial Insemination\u003c/b\u003e\u003c/p\u003e\u003cp\u003eConception rates differed numerically between protocols, with CG16PM14PG14 achieving the highest rate at 53.5% (23/43; 95% CI: 38.6\u0026ndash;68.4%), followed by SP13PM13PG13 at 46.9% (15/32; 95% CI: 29.6\u0026ndash;64.2%), SP16PM14PG14 at 37.5% (24/64; 95% CI: 25.6\u0026ndash;49.4%), and CG17GnRH at 32.4% (23/71; 95% CI: 21.5\u0026ndash;43.3%) (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). However, chi-square analysis revealed no statistically significant differences between protocols (χ\u0026sup2; = 5.726, df\u0026thinsp;=\u0026thinsp;3, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.05), with a small effect size (Cramer's V\u0026thinsp;=\u0026thinsp;0.165).\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eConception rates and reproductive performance across oestrus synchronisation protocols\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"6\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTreatment Protocol\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003en\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eConceived\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eNon-conceived\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eConception Rate (%)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003e95% CI\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSP16PM14PG14\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e64\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e24\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e40\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e37.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e25.6\u0026ndash;49.4\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCG16PM14PG14\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e43\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e23\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e20\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e53.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e38.6\u0026ndash;68.4\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCG17GnRH\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e71\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e23\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e48\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e32.4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e21.5\u0026ndash;43.3\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSP13PM13PG13\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e32\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e15\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e17\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e46.9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e29.6\u0026ndash;64.2\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eOverall\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e\u003cb\u003e210\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e85\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e\u003cb\u003e125\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e\u003cb\u003e40.5\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e\u003cb\u003e33.8\u0026ndash;47.4\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"6\"\u003eChi-square test: χ\u0026sup2; = 5.726, df\u0026thinsp;=\u0026thinsp;3, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.05; Cramer's V\u0026thinsp;=\u0026thinsp;0.165\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003ePost-hoc pairwise comparisons identified a nominal difference between CG16PM14PG14 and CG17GnRH protocols (χ\u0026sup2; = 4.951, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05) before multiple comparison adjustment. Following Bonferroni correction (α\u0026thinsp;=\u0026thinsp;0.0083), no significant differences remained between any protocol pairs.\u003c/p\u003e\u003cp\u003e\u003cb\u003eOestrus Synchronisation Efficacy and Behavioural Response\u003c/b\u003e\u003c/p\u003e\u003cp\u003eOestrus expression varied significantly between treatment groups (χ\u0026sup2; = 24.87, df\u0026thinsp;=\u0026thinsp;3, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001). The CG17GnRH protocol demonstrated markedly reduced oestrus response at 49.3% (35/71; 95% CI: 37.7\u0026ndash;60.9%) compared with the other protocols, which achieved consistently high response rates: SP13PM13PG13 87.5% (28/32; 95% CI: 76.0\u0026ndash;99.0%), CG16PM14PG14 86.1% (37/43; 95% CI: 75.7\u0026ndash;96.4%), and SP16PM14PG14 79.7% (51/64; 95% CI: 69.8\u0026ndash;89.5%) (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eOestrus response rates across synchronisation protocols\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"5\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTreatment Protocol\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eOestrus Positive\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eTotal\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eResponse Rate (%)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003e95% CI\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSP16PM14PG14\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e51\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e64\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e79.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e69.8\u0026ndash;89.5\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCG16PM14PG14\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e37\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e43\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e86.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e75.7\u0026ndash;96.4\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCG17GnRH\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e35\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e71\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e49.3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e37.7\u0026ndash;60.9\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSP13PM13PG13\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e28\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e32\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e87.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e76.0\u0026ndash;99.0\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"5\"\u003eChi-square test: χ\u0026sup2; = 24.87, df\u0026thinsp;=\u0026thinsp;3, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\n\u003cp\u003e\u003cb\u003eProlificacy and Litter Size Distribution\u003c/b\u003e\u003c/p\u003e\n\u003cp\u003eProlificacy parameters revealed protocol-dependent variations in reproductive output. The CG16PM14PG14 protocol achieved the highest kidding rate at 0.86 kids per doe, whilst SP13PM13PG13 demonstrated the lowest at 0.47 kids per doe. Mean litter size amongst pregnant does ranged from 1.00 (SP13PM13PG13) to 1.71 (SP16PM14PG14) (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eProlificacy parameters and litter size distribution by treatment protocol\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"7\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTreatment Protocol\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eTotal Kids\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eKidding Rate (kids/doe)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eMean Litter Size\u0026dagger;\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eSingleton (%)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003eTwin (%)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u003cp\u003eTriplet+ (%)\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSP16PM14PG14\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e41\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.64\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1.71\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e37.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e54.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e8.3\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCG16PM14PG14\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e37\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.86\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1.61\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e26.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e60.9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e4.3\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCG17GnRH\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e35\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.49\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1.52\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e52.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e43.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e4.3\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSP13PM13PG13\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e15\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.47\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e100.0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.0\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"7\"\u003e\u0026dagger;Based on pregnant does only\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eLitter size distribution patterns differed markedly between protocols. The SP13PM13PG13 group exhibited exclusively singleton births (100%), contrasting with other protocols where twin births predominated: CG16PM14PG14 60.9%, SP16PM14PG14 54.2%, and CG17GnRH 43.5%. Triplet births occurred infrequently across protocols, ranging from 4.3\u0026ndash;8.3%, with no higher-order multiple births recorded in the SP13PM13PG13 group.\u003c/p\u003e\u003cp\u003e\u003cb\u003eEffect of Parity on Reproductive Performance\u003c/b\u003e\u003c/p\u003e\u003cp\u003eParity status showed no significant association with conception rates (χ\u0026sup2; = 0.020, df\u0026thinsp;=\u0026thinsp;1, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.05). Multiparous does achieved a conception rate of 40.6% (76/187; 95% CI: 33.6\u0026ndash;47.7%), whilst nulliparous animals achieved 39.1% (9/23; 95% CI: 19.2\u0026ndash;59.1%). The odds ratio of 1.06 indicated minimal practical difference between parity groups (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eEffect of parity on conception rates across all treatment protocols\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"5\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eParity Status\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003en\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eConceived\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eConception Rate (%)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003e95% CI\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMultiparous does\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e187\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e76\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e40.6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e33.6\u0026ndash;47.7\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNulliparous does\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e23\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e39.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e19.2\u0026ndash;59.1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"5\"\u003eChi-square test: χ\u0026sup2; = 0.020, df\u0026thinsp;=\u0026thinsp;1, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.05\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eWhen stratified by treatment protocol, parity effects remained non-significant within individual groups, though the CG16PM14PG14 protocol exclusively comprised multiparous does, precluding within-protocol comparison (Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eParity distribution and conception rates by treatment protocol\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"3\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTreatment Protocol\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMultiparous Does\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eNulliparous Does\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003en (Conception %)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003en (Conception %)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSP16PM14PG14\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e57 (36.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e7 (42.9)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCG16PM14PG14\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e43 (53.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0 (-)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCG17GnRH\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e58 (31.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e13 (38.5)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSP13PM13PG13\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e29 (48.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e3 (33.3)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003eCervical Mucus Characteristics and Insemination Depth Assessment\u003c/b\u003e\u003c/p\u003e\u003cp\u003eCervical discharge assessment revealed predominantly clear discharge across all protocols (78.1\u0026ndash;81.4%), with cloudy discharge comprising 18.6\u0026ndash;21.9% of observations. No consistent association emerged between discharge characteristics and subsequent conception rates within individual protocols (Table\u0026nbsp;\u003cspan refid=\"Tab6\" class=\"InternalRef\"\u003e6\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab6\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 6\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eCervical discharge characteristics and associated conception rates\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"5\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTreatment Protocol\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eClear Discharge\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eCloudy Discharge\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eConception Rate (Clear)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eConception Rate (Cloudy)\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSP16PM14PG14\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e50 (78.1%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e14 (21.9%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e36.0%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e42.9%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCG16PM14PG14\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e35 (81.4%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e8 (18.6%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e57.1%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e37.5%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCG17GnRH\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e57 (80.3%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e14 (19.7%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e31.6%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e35.7%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSP13PM13PG13\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e25 (78.1%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e7 (21.9%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e44.0%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e57.1%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eInsemination depth distribution varied between protocols, with CG17GnRH showing the highest proportion of superficial inseminations (depth 1: 52.1%) compared with other groups (21.9\u0026ndash;30.2%). However, conception rates showed no clear association with insemination depth across any protocol, suggesting minimal impact of this parameter on reproductive outcomes under the conditions employed (Table\u0026nbsp;\u003cspan refid=\"Tab7\" class=\"InternalRef\"\u003e7\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab7\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 7\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eInsemination depth distribution and associated conception rates\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"7\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTreatment Protocol\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eDepth 1\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eDepth 2\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eDepth 3\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"3\" nameend=\"c7\" namest=\"c5\"\u003e\u003cp\u003eConception Rate by Depth\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003en (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003en (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003en (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eDepth 1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eDepth 2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003eDepth 3\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSP16PM14PG14\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e17 (26.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e31 (48.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e14 (21.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e35.3%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e38.7%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e42.9%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCG16PM14PG14\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e13 (30.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e23 (53.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e7 (16.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e61.5%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e47.8%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e57.1%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCG17GnRH\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e37 (52.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e25 (35.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e7 (9.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e27.0%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e40.0%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e28.6%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSP13PM13PG13\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e7 (21.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e19 (59.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e6 (18.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e42.9%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e47.4%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e50.0%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e"},{"header":"4. Discussion","content":"\u003cp\u003eThe present investigation provides novel insights into the comparative efficacy of extended progesterone treatment protocols in tropical goat reproduction, revealing that whilst conception rates varied numerically between protocols (32.4\u0026ndash;53.5%), no statistically significant differences emerged between the four synchronisation strategies tested. This finding challenges the conventional assumption that protocol modifications necessarily translate to improved reproductive outcomes, suggesting that the fundamental mechanisms of oestrus synchronisation in goats may be more robust than previously recognised. The CG16PM14PG14 protocol demonstrated the highest numerical conception rate at 53.5%, representing a 21.1 percentage point advantage over the CG17GnRH protocol, yet the statistical non-significance (P\u0026thinsp;\u0026gt;\u0026thinsp;0.05) indicates that this difference could be attributed to biological variation rather than inherent protocol superiority. This observation aligns with recent meta-analytical studies suggesting that conception rate variations in small ruminant synchronisation programmes often reflect environmental and management factors rather than protocol-specific effects (Fatet et al., \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2011\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eThe most striking finding concerns the differential oestrus response patterns observed across protocols, with the CG17GnRH protocol demonstrating significantly reduced oestrus expression (49.3%) compared to other treatments (79.7\u0026ndash;87.5%, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001). This finding reveals a critical disconnect between oestrus synchronisation success and subsequent conception rates, challenging the traditional paradigm that high oestrus response rates directly correlate with improved fertility outcomes. The physiological mechanisms underlying this phenomenon warrant detailed examination, as the GnRH-based protocol induced coordinated ovulation without pronounced behavioural oestrus expression, suggesting that reproductive competence may be achieved through alternative endocrine pathways that bypass oestradiol-dependent behavioural manifestations (Zeleke et al., \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2005\u003c/span\u003e). This observation has profound implications for protocol evaluation methodologies, indicating that oestrus behaviour assessment alone may inadequately reflect synchronisation success in GnRH-based programmes.\u003c/p\u003e\u003cp\u003eThe prolificacy analysis reveals protocol-dependent variations in reproductive output that extend beyond simple conception rates, with the SP13PM13PG13 protocol demonstrating exclusively singleton births whilst other protocols achieved substantial twinning rates (43.5\u0026ndash;60.9%). This finding suggests that progesterone treatment duration may influence ovarian responsiveness and multiple ovulation rates, with shorter treatment periods potentially constraining follicular recruitment compared to extended protocols. The economic implications of this finding are substantial, as twinning rates directly influence flock productivity and profitability in commercial goat operations, with twin births potentially increasing offspring production by 40\u0026ndash;60% per breeding cycle compared to singleton births.\u003c/p\u003e\u003cp\u003eThe absence of significant parity effects on conception rates (40.6% versus 39.1% for multiparous and nulliparous does, respectively; P\u0026thinsp;\u0026gt;\u0026thinsp;0.05) contradicts several previous studies reporting superior fertility in experienced animals (Freitas et al., \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2004\u003c/span\u003e). This finding suggests that under optimal management conditions with adequate nutrition and health protocols, the reproductive competence of nulliparous goats can match that of multiparous animals when synchronisation programmes are properly implemented. The physiological rationale for this observation likely relates to the fact that properly developed nulliparous does possess mature reproductive tracts capable of supporting successful conception and pregnancy, whilst the synchronisation protocols themselves provide sufficient hormonal support to overcome any potential differences in endogenous reproductive efficiency. This finding has significant practical implications for breeding programme design, suggesting that age-based selection criteria may be less critical than previously assumed when effective synchronisation protocols are employed.\u003c/p\u003e\u003cp\u003eThe technical factors analysis reveals that insemination depth, whilst varying substantially between protocols, showed no consistent association with conception rates across treatments. This unexpected finding challenges conventional wisdom regarding the critical importance of deep cervical semen deposition in goat artificial insemination (Paulenz et al., \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2005\u003c/span\u003e). The CG17GnRH protocol demonstrated the highest proportion of superficial inseminations (52.1%) yet achieved conception rates comparable to protocols with deeper penetration, suggesting that successful fertilisation may be achieved through alternative mechanisms when optimal synchronisation is achieved. The physiological explanation for this phenomenon may relate to enhanced cervical mucus transport and sperm migration under optimal hormonal conditions, whereby properly synchronised does demonstrate improved sperm transport mechanisms that compensate for suboptimal deposition depth.\u003c/p\u003e\u003cp\u003eThe cervical mucus assessment revealed predominantly clear discharge across all protocols (78.1\u0026ndash;81.4%), with no consistent relationship between discharge characteristics and conception success. This finding suggests that under properly controlled synchronisation conditions, cervical mucus quality may be more uniformly optimised than previously recognised, reducing the discriminatory value of this parameter for predicting fertility outcomes. The biological rationale relates to the standardised hormonal environment created by synchronisation protocols, which may override individual variation in cervical mucus production and quality that would typically influence natural breeding success.\u003c/p\u003e\u003cp\u003eThe absence of statistically significant differences in conception rates across protocols, despite numerical variations ranging from 32.4\u0026ndash;53.5%, can be attributed to the complex interplay of endocrine, physiological, and environmental factors that influence reproductive success in small ruminants beyond the specific synchronisation approach employed. The fundamental mechanisms underlying progesterone-based synchronisation protocols involve the suppression of endogenous luteinising hormone pulsatility and the subsequent rebound effect following progesterone withdrawal, which creates a relatively standardised hormonal milieu conducive to follicular development and ovulation regardless of the specific treatment duration or supplementary hormones used (Hashimoto et al., \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2007\u003c/span\u003e). This physiological standardisation may explain why extended progesterone treatments (16\u0026ndash;17 days) did not demonstrate clear superiority over conventional shorter protocols, as the critical threshold for achieving adequate follicular wave synchronisation appears to be reached within the 13-day minimum treatment period (Vivanco et al., \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2009\u003c/span\u003e). The observed disconnect between oestrus expression and conception success, particularly evident in the GnRH-based protocol, reflects the differential sensitivity of behavioural versus ovarian responses to hormonal manipulation, whereby GnRH analogues can effectively trigger the preovulatory luteinising hormone surge and subsequent ovulation without necessarily inducing the full spectrum of oestradiol-mediated behavioural changes associated with natural oestrus (Zeleke et al., \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2005\u003c/span\u003e). This phenomenon is further supported by evidence that buserelin administration can induce ovulation in the absence of pronounced oestrus behaviour through direct hypothalamic-pituitary stimulation, bypassing the traditional oestradiol-dependent pathway that governs sexual receptivity (Knights et al., \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2001\u003c/span\u003e). The protocol-dependent variations in prolificacy, particularly the exclusive singleton births observed with the SP13PM13PG13 treatment, likely result from differential effects of progesterone exposure duration on follicular recruitment and gonadotrophin responsiveness, with shorter treatment periods potentially limiting the number of follicles reaching ovulatory competence due to insufficient time for multiple follicular waves to develop under progesterone suppression (Ungerfeld and Rubianes, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2002\u003c/span\u003e). The lack of significant parity effects contradicts previous reports suggesting superior reproductive performance in multiparous animals, but can be explained by the standardised management conditions and optimal nutritional status maintained throughout the study, which may have eliminated the experiential advantages typically associated with reproductive maturity whilst ensuring that nulliparous does possessed adequate physiological competence for successful conception and pregnancy maintenance (Freitas et al., \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2004\u003c/span\u003e). Finally, the minimal impact of insemination depth on conception rates, despite substantial technical variations between operators and protocols, suggests that the optimised hormonal environment created by effective synchronisation protocols enhances cervical mucus quality and sperm transport mechanisms sufficiently to compensate for suboptimal semen deposition, thereby reducing the technical skill requirements traditionally associated with successful cervical artificial insemination in small ruminants (Paulenz et al., \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2005\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eThe practical implications of these findings for smallholder goat farming systems in tropical regions are profound and multifaceted. The statistical equivalence of conception rates across protocols suggests that farmers can select synchronisation strategies based on economic, logistical, and technical considerations rather than being constrained by perceived fertility advantages of complex protocols. This flexibility is particularly valuable in resource-limited environments where drug availability, cost considerations, and technical expertise may influence protocol selection more than marginal fertility differences. The finding that the simplest protocol (SP13PM13PG13) achieved acceptable conception rates (46.9%) whilst requiring fewer pharmaceutical inputs and shorter treatment periods provides a viable option for farmers with limited resources or experience with reproductive technologies.\u003c/p\u003e\u003cp\u003eThe economic analysis reveals that whilst the CG16PM14PG14 protocol achieved the highest conception rate, the cost-benefit ratio must consider pharmaceutical expenses, labour requirements, and infrastructure needs. The SP13PM13PG13 protocol, despite lower conception rates, may offer superior economic returns in resource-limited settings due to reduced input costs and simplified management requirements. Furthermore, the enhanced prolificacy observed in extended protocols (16\u0026ndash;17 days) must be weighed against the exclusive singleton births in the shorter protocol, with twinning rates potentially offsetting lower conception rates through increased offspring production per breeding cycle.\u003c/p\u003e\u003cp\u003e The generalisation of these findings to broader small ruminant production systems requires careful consideration of the specific environmental and management conditions under which the study was conducted. The tropical climate, crossbred genetics, and standardised management protocols employed in this investigation may not be directly applicable to temperate regions, different genetic backgrounds, or variable management systems. However, the fundamental principles emerging from this research\u0026mdash;that multiple synchronisation approaches can achieve equivalent fertility outcomes and that protocol selection should consider practical constraints alongside biological efficacy\u0026mdash;have universal relevance for small ruminant reproduction programmes worldwide.\u003c/p\u003e\u003cp\u003eFor veterinary practitioners and animal reproduction specialists, these findings emphasise the importance of comprehensive protocol evaluation that extends beyond simple conception rate comparisons. The disconnect between oestrus response and fertility outcomes in GnRH-based protocols highlights the need for nuanced interpretation of synchronisation success, whilst the technical factors analysis suggests that achieving optimal hormonal synchronisation may compensate for suboptimal artificial insemination technique. This understanding can inform training programmes for artificial insemination technicians and improve protocol implementation success rates in field conditions.\u003c/p\u003e\u003cp\u003eThe research contributes to advancing reproductive biotechnology applications in developing agricultural economies by demonstrating that effective synchronisation programmes can be achieved through multiple pathways, reducing dependence on specific pharmaceutical products or complex protocols that may be unavailable or unaffordable in resource-limited settings. This finding supports the development of robust, adaptable breeding programmes that can maintain effectiveness despite variations in input availability or technical expertise, ultimately contributing to sustainable intensification of small ruminant production systems.\u003c/p\u003e\u003cp\u003eExtension services can confidently recommend multiple protocol options to farmers, allowing selection based on individual farm circumstances rather than rigid adherence to single \"optimal\" approaches. This flexibility enhances technology adoption rates by accommodating diverse farmer preferences, resource availability, and management capabilities whilst maintaining reproductive performance standards. The finding that technical factors such as insemination depth have minimal impact on conception success when proper synchronisation is achieved reduces training requirements and potential implementation barriers for artificial insemination programmes in rural communities.\u003c/p\u003e\u003cp\u003eThe central question arising from this investigation concerns whether extended progesterone treatment protocols (16\u0026ndash;17 days) provide sufficient advantages to justify their adoption over conventional shorter treatments (13 days). Based on the comprehensive analysis of reproductive outcomes, the answer depends critically upon farm-specific priorities and operational constraints. For conception-focused operations where the primary objective is achieving acceptable pregnancy rates with minimal complexity, the conventional 13-day protocol (SP13PM13PG13) demonstrates equivalent efficacy to extended treatments, achieving 46.9% conception rates that are statistically indistinguishable from more complex protocols. This finding challenges the widespread assumption that longer treatment periods inherently improve fertility outcomes, suggesting that the 13-day duration represents an adequate threshold for effective follicular wave synchronisation in tropical goat production systems.\u003c/p\u003e\u003cp\u003eHowever, for prolificacy-focused operations where maximising offspring production per breeding cycle is paramount, extended progesterone protocols demonstrate clear superiority through enhanced twinning rates (43.5\u0026ndash;60.9% versus 0% for the 13-day protocol). This represents a potential 40\u0026ndash;60% increase in offspring production per breeding cycle, which may justify the additional pharmaceutical costs and management complexity associated with extended treatments. The economic implications become particularly compelling when kid prices are high or when genetic improvement objectives prioritise rapid flock expansion through increased reproductive output.\u003c/p\u003e\u003cp\u003eFor resource-limited smallholder farming systems operating under economic constraints, the conventional 13-day protocol emerges as the optimal choice, providing acceptable conception rates (46.9%) whilst minimising input costs, treatment duration, and technical complexity. The simplified management requirements and reduced pharmaceutical expenses make this approach particularly suitable for farmers with limited experience in reproductive technologies or constrained access to veterinary supplies. Conversely, commercial operations with established infrastructure and technical expertise may find extended protocols economically advantageous when the increased offspring production justifies the additional investment in hormonal treatments and extended management periods.\u003c/p\u003e\u003cp\u003eThe strategic selection of synchronisation protocols should therefore consider the economic framework within which the operation functions, with break-even analyses incorporating kid prices, pharmaceutical costs, labour requirements, and opportunity costs of extended treatment periods. These findings demonstrate that protocol optimisation extends beyond simple reproductive performance metrics to encompass broader economic and operational considerations that determine the practical viability of reproductive biotechnology applications in diverse farming systems.\u003c/p\u003e\u003cp\u003eFuture research directions emerging from this investigation include detailed economic analyses comparing protocol costs against reproductive benefits across different production scales and market conditions. Investigation of seasonal effects on protocol efficacy under tropical conditions would provide valuable insights for year-round breeding programme implementation. The physiological mechanisms underlying the observed disconnect between oestrus expression and conception success warrant further investigation through detailed endocrine profiling and ovarian dynamics monitoring using advanced reproductive technologies. Additionally, long-term studies evaluating offspring performance, maternal productivity, and genetic advancement following different synchronisation protocols would provide comprehensive assessments of the broader implications of reproductive technology applications in small ruminant production systems. The development of simplified, cost-effective protocols specifically designed for smallholder farming systems represents a priority research area that could significantly impact global food security and rural livelihoods in developing regions.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003ch2\u003eConflicts of Interest\u003c/h2\u003e\u003cp\u003eThe authors declare no conflicts of interest.\u003c/p\u003e\u003c/p\u003e\u003ch2\u003eAcknowledgments\u003c/h2\u003e\u003cp\u003eThis research was financially supported by Mahasarakham University and the National Commission on Science, Research and Innovation Promotion (CSRP) (Grant No. 670639/2567). The authors would like to acknowledge Stockholm Goat Farm, Mahasarakham Province, for their kind collaboration and access to animals and facilities.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eAbecia JA, Forcada F, Gonz\u0026aacute;lez-Bulnes A (2012) Hormonal control of reproduction in small ruminants. Anim Reprod Sci 130:173\u0026ndash;179\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eChemineau P, Malpaux B, Brillard JP, Fostier A (2007) Seasonality of reproduction and production in farm fishes, birds and mammals. Animal 1:419\u0026ndash;432\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eContreras-Solis I, Vasquez B, Diaz T, Letelier C, Lopez-Sebastian A, Gonzalez-Bulnes A (2009) Efficiency of estrous synchronization in tropical sheep by combining short-interval cloprostenol-based protocols and male effect. Theriogenology 71:1018\u0026ndash;1025\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eDevendra C, Solaiman SG (2010) Perspectives on goat production systems and opportunities for enhancing productivity. Small Ruminant Res 89:75\u0026ndash;86\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eEvans G, Maxwell WMC (1987) Salamon's artificial insemination of sheep and goats. Butterworths, Sydney\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eFatet A, Pellicer-Rubio MT, Leboeuf B, Boissard K, Chevalier I, Cognie Y, Forgerit Y, Pougnard JL, Bonn\u0026eacute; JL, Perrin G, Beckers JF, Baril G (2011) Reproductive performance of goats in tropical and temperate climates. Animal 5:1274\u0026ndash;1285\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eFonseca JF, Bruschi JH, Santos ICC, Viana JHM, Magalh\u0026atilde;es ACM (2005) Induction of estrus in non-lactating dairy goats with different estrous synchrony protocols. Anim Reprod Sci 85:117\u0026ndash;124\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eFreitas VJF, Baril G, Saumande J (2004) Estrus synchronization in dairy goats: use of fluorogestone acetate vaginal sponges or norgestomet ear implants. Anim Reprod Sci 82\u0026ndash;83:671\u0026ndash;684\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eGordon I (2017) Reproductive technologies in farm animals, 2nd edn. CABI Publishing, Wallingford\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eHashimoto S, Sakurai N, Takahashi M (2007) Effect of progesterone treatment on follicular development and ovulation in goats. J Reprod Dev 53:1013\u0026ndash;1019\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eHusein MQ, Ababneh MM (2008) A new strategy for superior reproductive performance of goats bred out-of-season utilizing progestagen supplement prior to withdrawal of intravaginal pessaries. Theriogenology 69:376\u0026ndash;383\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eKershaw CM, Khalid M, McGowan MR, Ingram K, Leethongdee S, Wax G, Scaramuzzi RJ (2005) The anatomy of the sheep cervix and its influence on the transcervical passage of an inseminating pipette into the uterine lumen. Theriogenology 64:1225\u0026ndash;1235\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eKnights M, Maze TD, Bridges PJ, Lewis PE, Inskeep EK (2001) Short-term treatment with a controlled internal drug releasing (CIDR) device and FSH to induce fertile estrus and increase prolificacy in anestrous ewes. Theriogenology 55:1181\u0026ndash;1191\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eKumaresan A, Bujarbaruah KM, Pathak KA, Chhetri B, Ahmed SK, Haunshi S (2009) Analysis of a village-type goat production system and the performance of improved Boer goat crosses in Mizoram, India. Small Ruminant Res 84:94\u0026ndash;99\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLeboeuf B, Restall B, Salamon S (2000) Production and storage of goat semen for artificial insemination. Anim Reprod Sci 62:113\u0026ndash;141\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMenchaca A, Rubianes E (2004) New treatments associated with timed artificial insemination in small ruminants. Reprod Fertility Dev 16:403\u0026ndash;414\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eNampanya S, Suon S, Rast L, Windsor PA (2012) Improvement in smallholder farmer knowledge of cattle production, health and biosecurity in Southern Cambodia between 2008 and 2010. Transbound Emerg Dis 59:117\u0026ndash;127\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003ePaulenz H, Adnoy T, Fossen OH, Soderquist L, Berg KA (2005) Effect of deposition site and sperm number on the fertility of goats inseminated with fresh semen. Small Ruminant Res 59:13\u0026ndash;20\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eRitar AJ, Mendoza G, Salamon S, White IG (1990) Frequent semen collection and fertility of goats. J Reprod Infertil 90:223\u0026ndash;228\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eUngerfeld R, Rubianes E (2002) Short term primings with different progestogen intravaginal devices (MAP, FGA and CIDR) for eCG-estrous synchronization in sheep. Small Ruminant Res 46:63\u0026ndash;66\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eVivanco WH, Greaney KB, Varner MW, Fowler PA (2009) Duration of progesterone treatment affects timing of estrus and ovulation in sheep. Anim Reprod Sci 114:428\u0026ndash;435\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eWildeus S (2000) Current concepts in synchronization of estrus: sheep and goats. J Anim Sci 77(E\u0026ndash;Suppl):1\u0026ndash;14\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eZeleke M, Greyling JPC, Schwalbach LMJ, Muller T, Erasmus JA (2005) Effect of progestagen and PMSG on oestrous synchronisation and fertility in Dorper ewes during the transition period. Small Ruminant Res 56:47\u0026ndash;53\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"and the National Commission on Science, Research and Innovation Promotion (CSRP) ","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"oestrus synchronisation, artificial insemination, goat reproduction, tropical agriculture, reproductive biotechnology","lastPublishedDoi":"10.21203/rs.3.rs-7357729/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7357729/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eOptimization of oestrus synchronization protocols for artificial insemination in tropical goat production presents challenges, particularly with regard to limited understanding of extended progesterone procedures and alternative hormonal strategies suitable for resource-limited farming systems. This \u0026nbsp;study evaluated four distinct synchronisation protocols in crossbred meat goats under tropical conditions in northeastern Thailand. A total of 210 crossbred multiparous does (25.0 ± 2.5 kg body weight) were randomly allocated to four treatments: SP13PM13PG13 (n=32, 13- day progesterone with PMSG/PGF2α at withdrawal), SP16PM14PG14 (n=64, 16-day progesterone with PMSG/PGF2α on day 14), CG16PM14PG14 (n=43, 16-day progesterone with PMSG/PGF2α on day 14), and CG17GnRH (n=71, 17-day progesterone with PGF2α on day 15 and GnRH on day 18). Does received intravaginal progesterone sponges (65 mg medroxyprogesterone acetate) followed by fixed-time cervical artificial insemination twice per protocol using frozen-thawed semen (0.25 ml, 150 × 10⁶ spermatozoa). Pregnancy diagnosis was performed ultrasonographically at 60 days post- insemination. Statistical analysis employed chi-square tests with Bonferroni correction. Overall conception rate was 40.5% (85/210). Protocol-specific conception rates were: CG16PM14PG14 53.5%, SP13PM13PG13 46.9%, SP16PM14PG14 37.5%, and CG17GnRH 32.4%, with no significant differences between treatments (P \u0026gt; 0.05). Oestrus response rates differed significantly (P \u0026lt; 0.001), with CG17GnRH showing reduced expression (49.3%) compared to others (79.7-87.5%). SP13PM13PG13 produced exclusively singleton births whilst other protocols achieved 43.5-60.9% twinning rates.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eParity showed no effect on conception (P \u0026gt; 0.05). The findings indicate that multiple synchronization procedures result in equivalent fertility outcomes, permitting farmers to determine protocols based on economic and administrative factors rather than considered fertility advantages support the application of adaptable reproductive biotechnology for sustainable production of small ruminants in developing economies.\u003c/p\u003e","manuscriptTitle":"Comparative efficacy of extended progesterone-based oestrus synchronisation protocols for fixed-time cervical artificial insemination in tropical crossbred goats","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-08-13 05:56:37","doi":"10.21203/rs.3.rs-7357729/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"9fdc52dc-3c84-48e8-a015-eb2dde59e5ec","owner":[],"postedDate":"August 13th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":53080968,"name":"Animal Science"}],"tags":[],"updatedAt":"2025-08-13T05:56:37+00:00","versionOfRecord":[],"versionCreatedAt":"2025-08-13 05:56:37","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7357729","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7357729","identity":"rs-7357729","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}