Next Article in Journal
3Rs-Related and Objective Indicators to Help Assess the Culture of Care
Next Article in Special Issue
Towards Improving the Outcomes of Assisted Reproductive Technologies of Cattle and Sheep, with Particular Focus on Recipient Management
Previous Article in Journal
Performance and Ruminal Parameters of Boer Crossbred Goats Fed Diets that Contain Crude Glycerin
Previous Article in Special Issue
Genetic Effects of Single Nucleotide Polymorphisms in the Goat GDF9 Gene on Prolificacy: True or False Positive?
 
 
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

The Effects of Reproductive Disorders, Parity, and Litter Size on Milk Yield of Serrana Goats

by
Gisele Margatho
1,
Vicente Rodríguez-Estévez
2,
Hélder Quintas
3 and
João Simões
1,*
1
Animal and Veterinary Research Centre (CECAV), University of Trás-os-Montes e Alto Douro, Quinta de Prados, 5370-801 Vila Real, Portugal
2
Department of Animal Production, University of Córdoba, Campus de Rabanales, 14071 Córdoba, Spain
3
Mountain Research Centre (CIMO), School of Agriculture, Polytechnic Institute of Bragança (IPB), Campus de Santa Apolónia, 5300-253 Bragança, Portugal
*
Author to whom correspondence should be addressed.
Animals 2019, 9(11), 968; https://doi.org/10.3390/ani9110968
Submission received: 21 October 2019 / Revised: 8 November 2019 / Accepted: 11 November 2019 / Published: 13 November 2019
(This article belongs to the Collection Reproductive Management of Sheep and Goats)

Abstract

:

Simple Summary

This study aimed to evaluate the effects of reproductive disorders, parity, and litter size on a 150-day standardized milk yield of the Transmontano ecotype of the Serrana goat breed (a dual purpose breed) over a three decade period. The 150-day standardized milk yield was significantly influenced by all studied factors and their interactions. The milk yield reduction due to reproductive disorders was more intense in primiparous than multiparous goats, and in primiparous or multiparous goats of the Transmontano ecotype presenting multiple fetuses, than in those presenting singletons. This milk production pattern proves that the lactation following abortion is viable for production purposes and an improvement of production system management can play an important role in mitigating milk yield losses.

Abstract

Several reproductive factors may affect milk yield in goats. The main aim of this study was to evaluate the influence of reproductive disorders, parity, and litter size, and their interactions on the 150-day standardized milk yield (SMY150) of low-producing dairy goats extensively raised. A total of 148,084 lactations between 1993 and 2015 were obtained from data of the Genpro pedigree records of the Transmontano ecotype of Serrana goat breed. The presence or absence of reproductive disorders (RD) from late (>half) pregnancy (abortions followed by lactation) or at kidding, number of fetuses (single vs. multiple), and parity (primiparous vs. multiparous) of the Transmontano ecotype of Serrana goat were used as fixed effects to fit a general linear model for a SMY150 output. A significant effect (p < 0.001) of all factors on SMY150, as well as three-way interactions, were observed. The SMY150 reduction subsequent to RD was 3.7% for multiparous and 9.6% for primiparous goats carrying singletons, and 14.1% for multiparous and 18.8% primiparous goats carrying multiple fetuses. It was concluded that a new lactation following abortion occurrence is viable for production purpose in low-producing dairy goats under pastoralism. Nevertheless, the impact of RD on SMY150 varied according to the number of fetuses and the parity of the Transmontano ecotype of Serrana goats. This information should be used in decision-making practices regarding reproductive and herd health management.

1. Introduction

Livestock benchmarking calculates data surrounding production, the resource base, costs, and other factors associated with the farming business to deduce effects from farm-recorded data. This is a useful and common management technique for livestock systems [1,2]. However, inferring causal effects between variables from farm data is challenging, as the association between them may arise not only from the effect of one on another but also from confounding background factors [3].
In dairy production, many factors may affect the overall milk yield (MY) and composition [4,5]. It is crucial to understand which factors directly affect MY and quality, such as diet [6], management [7], udder health, and somatic cell counts [8]. The influence of the number of fetuses or offspring and parity on MY is not straightforward in ruminants, and somewhat controversial in dairy versus meat goats. Ewes giving birth to more than one lamb produce more milk per lactation [3]; and those nursing twins produce more milk than those nursing single lambs [9,10].
There are different animal-dependent factors which affect goat prolificacy [11]. Morantes et al. [12] indicated a significantly higher prolificacy for dairy goat farms using assisted reproductive techniques compared to unassisted farms. In goats, multiple births have a higher mean MY in spite of having longer lactations than single births [13,14,15]. Thomas et al. [16] showed increases of 27% in the MY of goats producing twins over those producing single kids and of 16% in goats producing triplets over those with twins, with no indication that this trend was affected by age or lactation number. However, Carnicella et al. [15] observed that goats with higher parities, in particular goats in greater than or equal to the fourth parity, had a longer lactation and consequently a higher total MY; in addition, goats kidding twins yielded more milk and had longer lactation.
Nevertheless, the influence of reproductive disorders (RD) such as abortion, parity, and litter size on MY, especially focused in 150-day standardized milk yield (SMY150), and their interactions, have not yet been fully studied in low-producing dairy goats with dual purpose (meat and milk). Increasing kid production is of great interest to goat farmers, especially in traditional systems; and thus, prolificacy is an economically important trait and the most important reproductive parameter in determining the efficiency of the system and the economic viability of the flock [17].
Recently, Simões and Pires [18] observed that the SMY150 in low-producing goats was negatively influenced by RD in late pregnancy (abortions) or at kidding (stillbirths and other perinatal mortality). In that same study, preliminary data showed a higher frequency of RD in primiparous versus multiparous goats, and in single pregnancies versus pregnancies with multiple fetuses. Therefore, a more thorough evaluation also involving the number of fetuses is needed to address the best goat production management. Management and decision-making practices that aim to increase prolificacy could positively affect MY. This would be very useful knowledge at the farm level, especially for traditional grazing systems where MY is key to food production and economic security of farmers.
This is a retrospective study aiming to determine the relationship between RD, parity, and litter size on the SMY150 of the ecotype Transmontano of Serrana goats, a Portuguese local breed reared in extensive systems. The ultimate goal is to improve benchmarking knowledge in these low-producing dairy goats.

2. Materials and Methods

2.1. Animals and Records

A total of 148,084 lactations were obtained, between 1993 and 2015, from data of the pedigree records of Serrana goats breed (Genpro, Ruralbit, Portugal). For a description of this breed see Sociedade Portuguesa de Ovinotecnia e Caprinotecnia [19]. The Transmontano ecotype of this breed spread over northern Portugal and was considered for this study.
These regions are included in the temperate Mediterranean climate region, classified as Csa (dry and hot-summer climate) or Csb (dry and warm-summer climate) according to the Köppen climate classification [20]; Overall, and considering the data reported between 1971 and 2000, accessible at [21], the annual rainfall varies from 144.1 mm per month in winter (December) reaching a tenfold decrease, 13.7 mm, in summer (August). Inversely, the minimum, maximum, and average temperature is low in January (4.5, 13.1, and 8.8 °C, respectively), and increases gradually reaching the highest values in August (15.5, 28.8, and 22.2 °C, respectively), followed by a gradual decrease until the next winter. In mountain zones, these temperatures have a much wider range. Most recent climatic data can be found at the Portuguese Institute for Sea and Atmosphere site [22].
The production system was described by Simões and Bauer [23] and by Margatho et al. [24]. Briefly, these goats were reared under daytime pastoralism, mainly in mountain regions, in herds normally up to 100 adult animals. The feeding varies according to the seasonal biomass and goats can move several kilometers per day during grazing, mainly in mountain zones. The natural potential vegetation from both regions was included in a spatial model reported by Capelo et al. [25]. Nevertheless, some forages (e.g., rye grass and sorghum) are cultivated in few herds. The stocking rate is estimated 0.2–0.3 goats per hectare. Normally, rye grass and salt are fully available in stable areas. A concentrated feed, normally between 0.25 and 0.75 kg, is individually supplemented to each lactating female at milking time, which is normally performed by hand once a day. The prevalent practice is milking goats after a sucking period up to 75 days. Natural mating, keeping bucks together with does, is the common practice, without artificial insemination, and genetic improvement remains incipient. The fertility rate can reach 95% in herds and the first kidding occurs approximately at 15 months of age. In the reproductive season, some goats are simultaneously pregnant and lactating. The annual replacement rate varied approximately by 20% throughout the period studied. Sanitary measures include de-worming and vaccination programs, such as enterotoxaemia, as well as against brucellosis in some cases and in some areas. Similar to other worldwide regions [26], milking goats after abortion is a recurrent practice.
For the present study, each record included ecotype, number of fetuses, parity (1 to ≥14) or lactation number, month of kidding or abortion, RD data as independent variables, and SMY150 as a dependent variable. The RD mainly included abortion from late (>half) pregnancy with a subsequent new lactation. Abortion was defined as the delivery of one dead fetus or fetuses before day 140 of pregnancy. However, throughout the three decades studied, due to the practical difficulty in classifying the exact time of mating, RD occurring in the last two weeks of pregnancy, such as stillbirth occurrence, mummified fetus, and other perinatal mortality were also considered. Stillbirths were defined as premature or at term fetuses (≥140 days) born dead or dead within 24 h after birth, while abortions are early or late pregnancy dead fetuses without possibilities of survival. Mummified fetus was defined as (aseptic) dead fetus with reabsorption of body and fetal fluids. These abnormalities were registered by farmers and supervised by technicians during their periodical interventions in herds and transferred to the Genpro database.
The data, milk measurements, and milk samples (for milk composition evaluation) regarding one-day milk production were collected monthly from the ≤52nd (goats without suckling period) or ≤97th (after suckling period) day on lactation to the end of lactation [27]. Each lactation was only considered for at least three and four successive evaluations in primiparous and multiparous lactating goats, respectively. The Fleischmann’s method [28] was used to estimate the 150-day standardized milk yield (SMY150).

2.2. Statistical Analysis

The means of SMY150 by parity/lactation number were tested by ANOVA and the Tukey test.
Univariable logistic regression models were made to test the effects between each parity or number of fetuses and RD occurrence. The Wald test was also used a posteriori and the odd ratios calculated.
An analysis of mean for proportions was made for the RD estimation according to the month in order to determine which proportions are significantly different from the overall average. For this purpose, the likelihood ratio test was used and upper and low decision lines (α = 0.05) were estimated according to Nelson et al. [29].
To build the general linear model, parity was classified as primiparous or multiparous goat, the number of fetuses/kids as single or multiple (two or more) and the RD as presence or absence.
The three fixed effects and their interactions were fitted by the following equation:
Yijkl= u + Fi + Pj + Rk + (FP)ij + (FR)ik + (PR)jk + (FPR)ijk + eijkl
where
Yijkl = 150-day standardized milk production,
u = Overall mean,
Fi = fixed effect due to ith number of fetuses /kids (i = 1, 2),
Pj= fixed effect due to jth parity (j = 1, 2),
Rk = fixed effect due to kth RD (k = 1, 2),
(FP)ij, (FR)ik and (PR)jk = two-way interactions between F, P and R factors,
(FPR)ijk = three-way interactions between F, P and R factors,
eijkl = random error.
The Tukey–Kramer test was used to compare differences between pairs.
The JMP11 program from SAS [30] was used for all evaluations, and p < 0.05 was considered significant.
The results are show used a posteriori as mean ± standard deviation (±SD).

3. Results

3.1. Milk Yield, Prolificacy, and Reproductive Disorder Incidence

The mean SMY150 observed was 96.6 ± 39.8 L (mean ± SD) with a 95% confidence interval (95% CI) between 96.4 and 96.8 L (n = 148,084). The mean SMY150 was 90.1 ± 32.2 L (n = 35,283) at the first lactation and reached a maximum of 100.2 ± 40.7 L (n = 22,362; p < 0.001) at the third lactation, decreasing gradually in the following lactations. However, SMY150 remains higher than the first lactation until to the 10th lactation (93.8 ± 39.4 L; n = 2317).
The prolificacy was 1.43 ± 0.55 (95% CI: 1.43 to 1.44). The frequency of singleton, twins and triplets was 58.9% (n = 87,229), 38.5% (n = 57,018), and 2.6% (n = 3837), respectively.
The overall incidence of RD was 9.4% (n = 13,882; 95% CI: 9.2 to 9.5) of the lactations. The RD were approximately twice (odds ratio = 1.87; 95% CI: 1.81 to 1.94) as likely to occur in primiparous (13.9%; n = 4914) than in multiparous goats (8.0%; n = 8968; p < 0.001). The incidence of RD also is higher in goats carrying singletons (15.0%; n = 13,056) than goats carrying twins (4.6%; n = 636) or triplets (5.0%; n = 190).
The incidence of RD also varied according to month (p < 0.001). September (6.3%; n = 7845), October (4.4%; n = 17,178), November (6.8%; n = 10,494) and December (8.1%; n = 15,977) were outside the lower decision line. Inversely, February (12.4%; n = 19,441), March (11.4%; n = 23,161), April (11.3%; n = 15,544), May (10.8%; n = 6686), June (12.6%; n = 2738), and July (12.1%; n = 1585) were outside the respective upper decision lines.

3.2. Effects of Litter Size, Parity, and Reproductive Disorders on Milk Yield

The general linear model reported significant effects (p < 0.001) of RD, number of fetuses, parity and their interactions on SMY150, as shown in Table 1.
Significant SMY150 differences (p < 0.001) were more pronounced in primiparous than multiparous goats and in goats carrying singletons than multiple fetuses (Table 2).

4. Discussion

4.1. Milk Yield

Similar to previous studies in ruminant species a higher total MY was achieved in Transmontano ecotype of Serrana goats with multiple parity (p < 0.001). Parity plays an important role affecting milk production. In the present study, an increase of SMY150 was observed from the first to the third lactation, and persisted higher than the first lactation until the 10th lactation. An increasing MY as parity increased from first to third was also described by Salama et al. [31] for the Murciano-Granadina breed and Ciappesoni et al. [5] for Czech White Shorthaired breed. However, although most goat breeds reach maximum MY at the third or, less frequently, at the fourth lactation, Crepaldi et al. [32] found that MY showed a steady growing trend from first to fifth lactation in Alpine goats. Exceptionally, Vecerova and Krizek [33] found increasing MY until the 10th lactation in Czech White Short-hair goats. Carnicella et al. [15] observed that animals with higher parities, in particular goats of greater than or equal to the fourth parity, had a longer lactation and consequently a higher MY. In a recent study involving more than 300,000 lactations, Arnal et al. [34] observed a significant and progressive decrease in MY after the fourth lactation in French goat breeds.
In other species, such as sheep, the effect of parity on MY is controversial. Different authors observed significant increases on MY as the number of lactations advanced [35,36], while others observed that parity had no significant effect on MY [37,38,39]. Inconsistent findings may be due to factors such as the number of lambs suckled, which can play a role when different parities are compared [38].

4.2. Prolificacy

The average prolificacy of 1.43 we observed in Transmontano ecotype of Serrana goats is similar to that observed in other breeds such as 1.41 in Nubian breed in India [40], 1.45 in Alpine breed in Egypt [41], 1.49 in crossbred dairy goats of the Brazilian northeastern [42] and 1.51 in Florida breed in Spain [12]. Dickson-Urdaneta et al. [43] found a close prolificacy in Nubian does, with 1.38 kids. According to Sacoto and Simões [44] prolificacy of the Serrana goats (p < 0.001) depends on parity, reaching its maximum around the 5th kidding. Other authors reported that prolificacy is affected by the year of kidding [43,45]. Prolificacy of Portuguese Serrana goats has been shown to be influenced by the month of kidding, decreasing from December onwards and until a minimum in April [44].

4.3. Incidence of Reproductive Disorders

The proportion of RD (9.4%) found in this study is higher than the values previously reported by other authors, even more so considering that only the failures that precede lactations are included. In this regard, Menzies [46] and Braun [47] suggested 5% as a critical level of incidence of abortion and dystocia. Simões and Pires [18] noticed the risk for misclassification of abortion, especially for stillbirths due to dystocia at kidding time. A higher incidence of RD in first parity females has been reported in most herds and also in small ruminant species [48,49].
The occurrence of abortions also appears to be influenced by parity. Mellado et al. [50] showed that goats of different breeds in Mexico of parity groups two to five were half as likely to abort as primiparous or older goats. In that study, the oldest does were 90% more likely to have stillbirths than the younger goats, and the risk of stillbirth was lowest for goats of the fifth parity or less [50].
In the present study, primiparous goats had approximately twice the chance of presenting RD than all other parities. This fact could be justified, at least partly, by abortions caused by the presence of brucellosis during these three studied decades [51,52,53] and dystocia, which are more frequent in primiparous goats [54,55,56]. Currently, brucellosis can be considered eradicated in Portuguese goat farms and only few numbers of seropositive animals to Brucella can be detected in circumscribed zones [57]. Other infectious diseases, such as chlamydiosis, campylobacteriosis, Q fever, toxoplasmosis and leptospirosis, and even non-infectious causes of abortions probably played an important role in RD occurrence and should be monitored at the farm level [54].
In the present study, the proportion of RD varied seasonally, with the lowest proportions observed between September and November (4.4% to 6.8%). During fall, only a low number of goats are pregnant due to the natural breeding seasonality. This probably explains the relative low proportion of RD during this period. Inversely, in late winter, the great concentration of goats presenting advanced pregnancy and the high number of parturitions favor a higher circulation of infectious agents potentially causing abnormal parturitions which increase RD. Heat stress during hot months between spring and summer, can also influence the occurrence of RD. For example, in a hot arid environment in Mexico, Mellado et al. [50] described a low frequency of stillbirths in goats bred in the fall. In Spain, Morantes et al. [12] also observed an influence of month on abortion in Florida breed goats from 51 farms in 2010, and where about 75% of farmers used hormonal protocols to change the reproductive seasonality. Still, the lowest frequency for the whole set of abortions (<2.5%) was observed from May to July. These findings indicate the possible influence of other infectious and non-infectious factors such as heat stress on the occurrence of abortion in extensive production systems.

4.4. Effect of Reproductive Disorders, Parity, and Number of Fetuses on Milk Yield and Their Interactions

In the present study, we observed significant effects of RD, parity and No. of fetuses on SMY150 in Tansmontano ecotype of Serrana goats. All groups consistently displayed a decrease in SMY150 due to RD, but at different degree due to interactions between the studied factors. In a previous study, Simões and Pires [18] also observed a significant negative effect of RD on the subsequent lactations in both, primiparous and multiparous, goats of the Transmontano ecotype. Further, they observed similar values of SMY150 in primiparous goats carrying either single or multiple fetuses in presence of RD. This suggested the presence of interactions, which were included as a whole model in the present study.
In the present study, the overall effect of the number of fetuses on SMY150 is in agreement with other reported findings. For example, in Murciano-Granadina dairy goats [58] the MY increased up to the lactation peak for more prolific goats; and in Zaraibi goats [59] the litter size was positively related with an increase in MY in early lactation. In fact, MY is proportional to the mammary alveolar surface area which is positively correlated with fetal number. This relation may be due to the high levels of the hormonal placental lactogen produced by fetuses during the final phase of gestation [13,60]. Placental lactogen has a significant role in the control of normal mammary development and function in dairy goats. It provides prolactin hormone-like and growth hormone-like activities required for udder growth [60]. Multiple gestations are associated with more placental tissue and, hence, with elevated placental lactogen, suggesting that the extent of mammogenesis depends in part on the number of feto-placental units or placental mass [16]. Hayden el al. [13] emphasize the influence of the placental mass on the growth of mammary gland by the fact that in hand-milked goats, MY was related to the number of kids born by goat, implying that the kids in utero actively affect their chance of survival by regulating their food supply. We think that hormonal and mammary gland differences between primiparous and multiparous could partly explain the variation of SMY150 in the presence of RD.
Ferreira et al. [3] also observed a positive influence of prolificacy on MY in dairy sheep. Lactating ewes lambing multiple kids produced 12.62 L of milk during whole lactation more than ewes lambing singletons. Moreover, to reinforce the influence of prolificacy on MY, Delgado-Pertíñez et al. [61] found greater MY in the first to fifth weeks of lactation with two kids vs. one regardless of type of milking, i.e., machine-milking or natural suckling. Contrarily, MY did not differ during the post-weaning period (after the sixth week). Equally, Crepaldi et al. [32] found less effect of prolificacy on MY in late lactation. Peris et al. [62] showed the effect of prolificacy on udder volume, goats with twins having the largest volume and this was positively correlated with MY (r = 0.69). Therefore, it is likely that the occurrence of a fetal death, or abortion, would have a major impact on post-partum lactational performance, since it is related to pre-partum mammary gland development.
It is well-known in goats, that multiple births have higher (total) mean MY in consequence of longer lactations [5,13−15,61]. In hand-milked goats and after correction for lactation number, Hayden et al. [13] observed that dams kidding twins and triplets had an increase of 27% and 47% MY, respectively, than dams kidding singletons. In Alpine goats, Crepaldi et al. [32], found that the difference in MY due to prolificacy was greater for first compared to third parity dams kidding twin kids than single kids (i.e., 63.2 vs. 15.02 kg of milk). Likewise, in sheep, the number of lambs is also a major factor influencing MY. Ewes nursing twins produce more milk than those nursing single lambs [9,10].
In the present study, the effect of the number of fetuses was observed considering SMY150. The standardization of lactation, and its evaluation instead of total MY, is very important due to the implications of the reproductive management to shorten the interval between kidding in seasonal species, such as small ruminants. Dairy goat farms using any reproductive technique obtain a significant higher prolificacy [12,63] hence, these techniques should be considered as an indirect method to achieve a higher total MY and SMY150.
Suckling induces prolactin secretion which is essential for maintaining lactation [13]. The effect of prolificacy on MY is likely larger in farms where kids are raised by their does. A similar practice is prevalent in the Transmontano ecotype of Serrana goat breed. The appearance of reproductive disorders, may interrupt prolactin stimulation of the udder, since it depends on the intensity of the suckling stimulus produced by different size litters, which may be the cause of the differences observed in mean MY. In spite of the negative effects of RD on MY, it is advantageous to have multiple fetuses in the herds. Prolificacy can be promoted using reproductive techniques [12]. Due to the inherent risk of RD when using these, any misclassification between abortion and dystocia should be avoided in order to improve benchmarking analysis of reproductive performance and of subsequent MY.
The interactions between the number of fetuses, parity, and RD on SMY150 observed in the present study suggest that the different management practices and environmental conditions can have a significant impact on MY and should be taken in consideration in herd health management. Transmontano ecotype of Serrana goats are normally reared for dual purpose and produce low MY under pastoralism. Hence, greater attention should be paid to this ecotype at a nutritional and milking (once vs. twice a day) level to improve the lactation following RD.
In further studies, the exact moment of abortion should be considered mainly for primiparous goats, in which the mammary development occurs for the first time, in order to evaluate its influence on MY.

5. Conclusions

We conclude that RD interacted with number of fetuses and parity in low-producing dairy goats modifying the SMY150.
A negative effect of RD on SMY150 was more pronounced for primiparous than multiparous goats and for goats carrying multiple fetuses than singletons, likely due to endogenous hormonal influence.
The goat lactation following abortion or stillbirths at kidding is viable under pastoralism and the improvement of production system management can play an important role in mitigating MY losses.

Author Contributions

Conceptualization, data analysis and writing of the study was performed by G.M., V.R.-E., H.Q. and J.S.

Funding

This work was funded by the project UID/CVT/00772/2019 supported by the Portuguese Science and Technology Foundation (FCT).

Acknowledgments

The authors thank the Associação Nacional de Caprinicultores da Raça Serrana (ANCRAS) for the data collection.

Conflicts of Interest

The authors declare no conflict of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, or in the decision to publish the results.

References

  1. Koketsu, Y.; Tani, S.; Iida, R. Factors for improving reproductive performance of sows and herd productivity in commercial breeding herd. Porc. Health Manag. 2017, 3, 1. [Google Scholar] [CrossRef]
  2. Crowe, M.A.; Hostens, M.; Opsomer, G. Reproductive management in dairy cows—The future. Ir. Vet. J. 2018, 71, 1. [Google Scholar] [CrossRef]
  3. Ferreira, V.C.; Thomas, D.L.; Valente, B.D.; Rosa, G.J.M. Causal effect of prolificacy on milk yield in dairy sheep using propensity score. J. Dairy Sci. 2017, 100, 8443–8450. [Google Scholar] [CrossRef] [PubMed]
  4. Gipson, T.A.; Grossman, M. Lactation curves in dairy goats: A review. Small Rumin. Res. 1990, 3, 383–396. [Google Scholar] [CrossRef]
  5. Ciappesoni, G.; Přibyl, J.; Milerski, M.; Mares, V. Factors affecting goat milk yield and its composition. Czech J. Anim. Sci. 2004, 11, 465–473. [Google Scholar] [CrossRef]
  6. Goetsch, A.L.; Zeng, S.S.; Gipson, T.A. Factors affecting goat milk production and quality. Small Rumin. Res. 2011, 101, 55–63. [Google Scholar] [CrossRef]
  7. Sandrucci, A.; Bava, L.; Tamburini, A.; Gislon, J.; Zucali, M. Management practices and milk quality in dairy goat farms in Northern Italy. Ital. J. Anim. Sci. 2019, 18, 1–2. [Google Scholar] [CrossRef]
  8. Jiménez-Granado, R.; Sánchez-Rodríguez, M.; Arce, C.; Rodríguez-Estévez, V. Factors affecting somatic cell count in dairy goats: A review. Span. J. Agric. Res. 2014, 12, 133–150. [Google Scholar] [CrossRef]
  9. Slen, S.B.; Clark, R.D.; Hironaka, R. A comparison of milk production and its relation to lamb growth in five breeds of sheep. Can. J. Anim. Sci. 1963, 43, 16–21. [Google Scholar] [CrossRef]
  10. Snowder, G.D.; Glimp, H.A. Influence of breed, number of suckling lambs, and stage of lactation on ewe milk production and lamb growth under range conditions. J. Anim. Sci. 1991, 69, 923–930. [Google Scholar] [CrossRef]
  11. Haldar, A.; Pal, P.; Datta, M.; Paul, R.; Pal, S.K.; Majumdar, D.; Biswas, C.K.; Pan, S. Prolificacy and its relationship with age, body weight, parity, previous litter size and body linear type traits in meat-type goats. Asian-Australas. J. Anim. Sci. 2014, 27, 628–634. [Google Scholar] [CrossRef] [PubMed]
  12. Morantes, M.; Rodríguez-Estévez, V.; Arce, C.; Jiménez-Granado, R.; López-Fariña, M.; Rodríguez-Zarco, M.; Sánchez-Rodríguez, M. Distribución de partos, prolificidad y porcentaje de abortos en explotaciones de caprino lechero de raza Florida. In Proceedings of the XXXVII Congreso SEOC, Ciudad Real, Spain, 17–21 September 2012; pp. 373–377. (In Spanish). [Google Scholar]
  13. Hayden, T.J.; Thomas, C.R.; Forsyth, I.A. Effect of number of young born (litter size) on milk yield of goats: Role for placental lactogen. J. Dairy Sci. 1979, 66, 2426–2433. [Google Scholar] [CrossRef]
  14. Browning, R., Jr.; Leite-Browning, M.L.; Sahlu, T. Factors affecting standardized milk and fat yields in Alpine goats. Small Rumin. Res. 1995, 18, 173–178. [Google Scholar] [CrossRef]
  15. Carnicella, D.; Dario, M.; Ayres, M.; Laudadio, V.; Dario, C. The effect of diet, parity, year and number of kids on milk yield and milk composition in Maltese goat. Small Rumin. Res. 2008, 77, 71–74. [Google Scholar] [CrossRef]
  16. Thomas, C.R.; Forsyth, A.; Hart, C. Goat placental lactogen: Levels through pregnancy and variation over 24 hour periods. J. Endocrinol. 1977, 75, 51P–52P. [Google Scholar]
  17. Hoque, M.A.; Amin, M.R.; Baik, D.H. Genetic and non-genetic causes of variation in gestation length, litter size and litter weight in goats. Asian-Australas. J. Anim. Sci. 2002, 15, 772–776. [Google Scholar] [CrossRef]
  18. Simões, J.; Pires, A.F.A. Reproductive disorders in Portuguese Serrana goats and its effects on milk production. Rev. Colomb. Cienc. Pec. 2018, 31, 64–71. [Google Scholar] [CrossRef]
  19. SPOC. Sociedade Portuguesa de Ovinotecnia e Caprinotecnia. Cabra Serrana. Available online: http://www.ovinosecaprinos.com/serrana.html (accessed on 29 May 2019).
  20. Kottek, M.; Grieser, J.; Beck, C.; Rudolf, B.; Rubel, F. World Map of the Köppen-Geiger climate classification updated. Meteorol. Z. 2006, 15, 259–263. [Google Scholar] [CrossRef]
  21. Portal do Clima. Available online: http://portaldoclima.pt/pt/ (accessed on 08 November 2019).
  22. Instituto Português do Mar e da Atmosfera. Available online: https://www.ipma.pt/pt/index.html (accessed on 8 November 2019).
  23. Simões, J.; Bauer, A. Reproductive and Milk Production Profiles in Serrana Goats. In Sustainable Goat Production in Adverse Environments: Local Goat Breeds; Simões, J., Gutiérrez, C., Eds.; Springer: Cham, Switzerland, 2018; Volume II, pp. 233–243. [Google Scholar]
  24. Margatho, G.; Rodríguez-Estévez, V.; Medeiros, L.; Simões, J. Seasonal variation of Serrana goat milk contents in mountain grazing system for cheese manufacture. Rev. Med. Vet. 2018, 169, 157–165. [Google Scholar]
  25. Capelo, J.; Mesquita, S.; Costa, J.C.; Ribeiro, S.; Arsénio, P.; Neto, C.; Monteiro-Henriques, T.; Aguiar, C.; Honrado, J.; Espírito-Santo, D.; et al. A methodological approach to potential vegetation modeling using GIS techniques and phytosociological expert-knowledge: Application to mainland Portugal. Phytocoenologia 2007, 37, 399–415. [Google Scholar] [CrossRef]
  26. Mellado, M.; Garcia, E. Effects of abortion and stage of lactation on chemical composition and mineral content of goat milk from mixed-breed goat on rangeland. APCBEE Procedia 2014, 8, 1–5. [Google Scholar] [CrossRef]
  27. ICAR. Guidelines for Dairy Goats. Available online: http://www.icar.org/index.php/icar-recording-guidelines (accessed on 29 May 2019).
  28. Berger, Y.M.; Thomas, D.L. Milk testing, calculation of milk production and adjustment factors. In Proceedings of the 10th Great Lakes Dairy Sheep Symposium, Hudson, WI, USA, 4–6 November 2004; pp. 55–63. [Google Scholar]
  29. Nelson., P.R.; Wludyka, P.S.; Copeland, K.A.F. The Analysis of Means: A Graphical Method for Comparing Means, Rates, and Proportions; SIAM: Philadelphia, PA, USA; ASA: Alexandria, VA, USA, 2005; p. 184. [Google Scholar]
  30. SAS. Using JMP 11, 2nd ed.; SAS Institute Inc.: Cary, NC, USA, 2014; p. 530. [Google Scholar]
  31. Salama, A.A.K.; Such, X.; Caja, G.; Rovai, M.; Casals, R.; Albanell, E.; Marín, M.P.; Martí, A. Effects of one versus twice daily milking throughout lactation on milk yield and milk composition in dairy goats. J. Dairy Sci. 2003, 86, 1673–1680. [Google Scholar] [CrossRef]
  32. Crepaldi, P.; Corti, M.; Cicogna, M. Factors affecting milk production and prolificacy of Alpine goats in Lombardy (Italy). Small Rumin. Res. 1999, 32, 83–88. [Google Scholar] [CrossRef]
  33. Vecerova, D.; Krizek, J. Analýza variance mléčné užitkovosti koz bílého krátkosrstého plemene. Živočisna Výroba 1993, 38, 961–969. (In Czech) [Google Scholar]
  34. Arnal, M.; Robert-Granié, C.; Larroque, H. Diversity of dairy goat lactation curves in France. J. Dairy Sci. 2018, 101, 11040–11051. [Google Scholar] [CrossRef]
  35. Casoli, C.; Duranti, E.; Morbidini, L.; Panella, F.; Vizioli, V. Quantitative and compositional variations of Massases sheep milk by parity and stage of lactation. Small Rumin. Res. 1989, 2, 47–62. [Google Scholar] [CrossRef]
  36. Hatziminaoglou, I.; Geogordiudis, A.; Karalazos, A. Factors affecting milk yield and prolificacy of Karagouniko sheep in West Thessaly (Greece). Livest. Sci. 1990, 24, 181–186. [Google Scholar] [CrossRef]
  37. Dell’Aquila, S.; Pilla, A.M.; Catillo, G.; Scardella, G.; Taibi, L. Milk yield of Comisana, Delle Langhe, Massese, Sarda and crossbred ewes. Zootec. Nutr. Anim. 1993, 14, 95–102. [Google Scholar]
  38. Sevi, A.; Taibi, L.; Albenzio, M.; Muscio, A.; Annicchiarico, G. Effect of parity on milk yield, composition, somatic cell count, renneting parameters and bacteria counts of Comisana ewes. Small Rumin. Res. 1999, 37, 99–107. [Google Scholar] [CrossRef]
  39. KrálíčKová, Š.; Pokorná, M.; Kuchtík, J.; Filipčík, R. Effect of parity and stage of lactation on milk yield, composition and quality of organic sheep milk. Acta Univ. Agric. Silvic. Mendel. Brun. 2012, 60, 71–78. [Google Scholar] [CrossRef]
  40. Jan, I.A.; Gupta, S.C. Performance of goats under intensive management system. In Proceedings of the V International Conference on Goats, New Delhi, India, 2–8 March 1981; pp. 550–552. [Google Scholar]
  41. Mourad, M. Reproductive performance of Alpine and Zaraibi goats and growth of their first cross in Egypt. Small Rumin. Res. 1993, 12, 379–384. [Google Scholar] [CrossRef]
  42. Sarmento, J.L.R.; Pimenta-Filho, E.C.; Abreu, U.G.P.; Ribeiro, M.N.; Sousa, J.E.R. Litter size of crossbreed dairy goats in the northeastern semi-arid. Rev. Bras. Zootec. 2010, 39, 1471–1476. [Google Scholar] [CrossRef]
  43. Dickson-Urdaneta, L.; Torres-Hernández, G.; Becerril-Pérez, C.; González-Cossio, F.; Osorio-Arce, F.; García-Betancourt, O. Comparison of Alpine and Nubian goats for some reproductive traits under dry tropical conditions. Small Rumin. Res. 2000, 36, 91–95. [Google Scholar] [CrossRef]
  44. Sacoto, S.; Simões, J. Prolificity of Portuguese Serrana Goats between 1987 and 2015. Asian Pac. J. Reprod. 2016, 5, 519–523. [Google Scholar] [CrossRef]
  45. Odubote, I.K. Genetic parameters for litter size at birth and kidding interval in the West African Dwarf Goats. Small Rumin. Res. 1996, 20, 261–265. [Google Scholar] [CrossRef]
  46. Menzies, P.I. Control of important causes of infectious abortion in sheep and goats. Vet. Clin. North Am. Food Anim. Pract. 2011, 27, 81–93. [Google Scholar] [CrossRef]
  47. Braun, W. Parturition and dystocia in the goat. In Current Therapy in Theriogenology 2; Younquist, R.S., Threlfall, W.R., Eds.; Saunders: St. Louis, MO, USA, 2007; pp. 555–558. [Google Scholar]
  48. Majeed, A.F.; Taha, M.B. Dystocia in local goats in Iraq. Small Rumin. Res. 1989, 2, 375–381. [Google Scholar] [CrossRef]
  49. Dwyer, C.M.; Conington, J.; Corbiere, F.; Holmøy, I.H.; Muri, K.; Nowak, R.; Rooke, J.; Vipond, J.; Gautier, J.M. Invited review: Improving neonatal survival in small ruminants: Science into practice. Animal 2016, 10, 449–459. [Google Scholar] [CrossRef] [Green Version]
  50. Mellado, M.; Valdez, R.; Garcia, J.E.; López, R.; Rodríguez, A. Factors affecting the reproductive performance of goats under intensive conditions in a hot arid environment. Small Rumin. Res. 2006, 63, 110–118. [Google Scholar] [CrossRef]
  51. Coelho, A.M.; Coelho, A.C.; Roboredo, M.; Rodrigues, J.A. A case-control study of risk factors for brucellosis seropositivity in Portuguese small ruminants herds. Prev. Vet. Med. 2007, 82, 291–301. [Google Scholar] [CrossRef]
  52. Coelho, A.M.; Pinto, M.L.; García-Díez, J.; Coelho, A.C. Impact of B. melitensis Rev-1 vaccination on brucellosis prevalence. Turk. J. Vet. Anim. Sci. 2015, 39, 261–270. [Google Scholar] [CrossRef]
  53. García-Díez, J.; Coelho, A.D.; Pinto, M.L.; Coelho, A.C. Evaluation of Brucellosis from 2001 to 2007 in a Small Ruminant Population Vaccinated with a Live Freeze-dried B. melitensis Rev-1 Vaccine in Northeast Portugal. Philipp. J. Vet. Anim. Sci. 2015, 52, 21–29. [Google Scholar]
  54. Edmondson, M.A.; Roberts, J.F.; Baird, A.N.; Bychawski, S.; Pugh, D.G. Theriogenology of Sheep and Goats. In Sheep and Goat Medicine, 2nd ed.; Pugh, D.G., Baird, A.N., Eds.; Saunders: St. Louis, MO, USA, 2012; pp. 129–186. [Google Scholar]
  55. Kumar, V.; Talekar, S.H.; Ahmad, R.A.; Mathew, D.D.; Zama, M.M.S. Delayed cases of dystocia in small ruminants—Etiology and surgical management. Indian J. Anim. Sci. 2013, 1, 47–54. [Google Scholar]
  56. Ismail, Z.B. Dystocia in sheep and goats: Outcome and fertility following surgical and non-surgical management. Mac. Vet. Rev. 2017, 40, 91–96. [Google Scholar] [CrossRef] [Green Version]
  57. Castelo, C.; Simões, J. Risk factors of brucellosis (re-)incidence in sheep and goat flocks in an endemic area of Portugal. Trop. Anim. Health Prod. 2019, 51, 487–490. [Google Scholar] [CrossRef]
  58. León, J.M.; Macciotta, N.P.P.; Gama, L.T.; Barba, C.; Delgado, J.V. Characterization of the lactation curve in Murciano-Granadina dairy goats. Small Rumin. Res. 2012, 107, 76–84. [Google Scholar] [CrossRef]
  59. Shaat, I. Application of the Wood lactation curve in analysing the variation of daily milk yield in the Zaraibi goats in Egypt. Small Rumin. Res. 2014, 117, 25–33. [Google Scholar] [CrossRef]
  60. Buttle, H.L.; Cowie, A.T.; Jones, E.A.; Turvey, A. The contribution of placental hormones to the development of the mammary glands in goats. J. Endocrinol. 1978, 77, 59p. [Google Scholar]
  61. Delgado-Pertíñez, M.; Guzmán-Guerrero, J.L.; Caravaca, F.P.; Castel, J.M.; Ruiz, F.A.; González-Redondo, P.; Alcalde, M.J. Effect of artificial vs. natural rearing on milk yield, kid growth and cost in Payoya autochthonous dairy goats. Small Rumin. Res. 2009, 84, 108–115. [Google Scholar] [CrossRef]
  62. Peris, S.; Caja, G.; Such, X. Relationships between udder and milking traits in Murciano-Granadina dairy goats. Small Rumin. Res. 1999, 33, 171–179. [Google Scholar] [CrossRef]
  63. Muayad, M.T.A.; Haniza, M.Z.H.; Husni, I. Reproductive performance of different goat breeds in Malaysia. Indian J. Anim. Res. 2019, 53, 24–27. [Google Scholar] [CrossRef]
Table 1. Effect of number of fetuses, parity, and reproductive disorders (RD), and their interactions, in Transmontano ecotype of Serrana goats 150-day standardized milk yield (SMY150).
Table 1. Effect of number of fetuses, parity, and reproductive disorders (RD), and their interactions, in Transmontano ecotype of Serrana goats 150-day standardized milk yield (SMY150).
Transmontano Ecotype of Serrana Goatsp Values
FetusesParityParturitionSMY150 (n)
SingleMultiparousNormal97.5 ± 39.7 a (53,125)No. of fetuses
Parity
RD
<0.05<
0.001<
0.001
RD93.9 ± 40.3 b (8278)
PrimiparousNormal88.7 ± 32.7 c (21,048)No. of fetuses × Parity
No. of fetuses × RD
Parity × RD
<0.001<
0.001
0.01
RD80.2 ± 31.5 d (4778)
MultipleMultiparousNormal100.9 ± 42.0 e (50,708)No. of fetuses × Parity × RD<0.05
RD86.7 ± 39.7 f (690)
PrimiparousNormal98.3 ± 40.4 g (9321)
RD79.8 ± 31.2 d,h (136)
a–h different superscript letters within the same column are significant at p < 0.05.
Table 2. Percentage variation of 150-day standardized milk yield in Transmontano ecotype of Serrana goats presenting reproductive disorders.
Table 2. Percentage variation of 150-day standardized milk yield in Transmontano ecotype of Serrana goats presenting reproductive disorders.
Transmontano Ecotype Of Serrana Goats (1)
ParitySingletonMultiple fetuses
Multiparous goats−3.7%−14.1%
Primiparous goats−9.6%−18.8%
(1) Milk yield variation (%) = [SMY150 (RD) / SMY150 (normal) −1] * 100. SMY150 (RD): 150-day standardized milk yield from goats with reproductive disorders. SMY150 (normal): 150-day standardized milk yield from goats with normal parturition.

Share and Cite

MDPI and ACS Style

Margatho, G.; Rodríguez-Estévez, V.; Quintas, H.; Simões, J. The Effects of Reproductive Disorders, Parity, and Litter Size on Milk Yield of Serrana Goats. Animals 2019, 9, 968. https://doi.org/10.3390/ani9110968

AMA Style

Margatho G, Rodríguez-Estévez V, Quintas H, Simões J. The Effects of Reproductive Disorders, Parity, and Litter Size on Milk Yield of Serrana Goats. Animals. 2019; 9(11):968. https://doi.org/10.3390/ani9110968

Chicago/Turabian Style

Margatho, Gisele, Vicente Rodríguez-Estévez, Hélder Quintas, and João Simões. 2019. "The Effects of Reproductive Disorders, Parity, and Litter Size on Milk Yield of Serrana Goats" Animals 9, no. 11: 968. https://doi.org/10.3390/ani9110968

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop