Linear or nonlinear genetic relationships between productive life and functional productive life at 72 mo, with final score (SCO), stature, strength, dairyness (DAI), teat diameter, rear legs (side view), rump angle, rump width (RUW), fore udder attachment (FUA), rear udder height, rear udder arch, udder depth (UDD), suspensory ligament (SUS), and teat placement, as well as heritabilities and correlations were estimated from multibreed US dairy goat records. Productive life was defined as the total days in production until 72 mo of age (PL72) for goats having the opportunity to express the trait. Functional productive life (FPL72) was analyzed by incorporating first lactation milk yield, fat yield, protein yield, and SCO in the statistical model. Heritabilities and correlations were estimated using linear mixed models with pedigree additive genetic relationships and ASReml software. Nonlinearity of genetic relationships was assessed based on second-degree polynomial (quadratic) regression models, with the breeding values of PL72 or FPL72 as responses and the breeding values for each type trait (linear and quadratic) as predictor variables. Heritability estimates were 0.19, 0.14, 0.18, 0.20, 0.14, 0.07, 0.28, 0.20, 0.15, 0.13, 0.25, 0.18, 0.20, 0.21, 0.21, and 0.32 for PL72, FPL72, SCO, stature, strength, DAI, teat diameter, rear legs, rump angle, RUW, FUA, rear udder height, rear udder arch, UDD, SUS, and teat placement, respectively. The type traits SCO, RUW, and FUA were the most correlated with PL72 and FPL72, so these may be used as selection criteria to increase longevity in dairy goats. An increase in the coefficient of determination >1% for the second degree, compared with that for the linear model for either PL72 or FPL72, was taken as evidence of a nonlinear genetic relationship. Using this criterion, PL72 showed maximum values at intermediate scores in DAI, UDD, and RUW, and maximum values at extreme scores in FUA and SUS, whereas FPL72 showed maximum values at intermediate scores in DAI and UDD, and maximum values at extreme scores in FUA, RUW, and SUS. Selecting for increased SCO, RUW, and FUA will lead to an increase of FPL72 in goats. Consideration of nonlinear relationships between DAI, FUA, RUW, SUS, and UDD may help in the design of more efficient breeding programs for dairy goats using conformation traits.

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Summary Parasitic diseases of sheep involving gastrointestinal nematodes (GIN) are one of the main problems that affect fl ock productivity, especially during the peripartum period. Around lambing, the ewes are immunosuppressed and the nematode faecal egg count (FEC) increases at four weeks before lambing, reaching a peak between the fourth and sixth week postpartum and subsequently decreasing towards weaning. Prolactin has been credited with a suppressive effect on immune system, along with other hormones that intervene in metabolism, such as leptin, which has an important role in the activation of other hormones. Cortisol has also been included; this is stimulated by any stressful event and inhibits the proliferation of T-cells and alters the function of immunoglobulins. Another related hormone is pepsinogen, which is considered a marker of the integrity of the abomasum mucosa, as well as the albumin concentration that increases in the presence of a GIN infection. The humoral and cellular immune response, as well as inflammatory reactions, are the main mechanisms of action against GIN. Lymphocytes direct the effector mechanisms in a Th2 cell response, including interleukins (IL-4, IL-5, IL-9, IL-10) and transforming growth factor beta (TGF-β) together with immunoglobulins (IgA, IgG, IgM and IgE), which prevent the invasion of pathogens. Eosinophils with a cytotoxic effect are indicators of a parasitic infection, with importance in the immune protection of infected individuals. The genetic selection of resistant individuals measured by FEC is dependent on the heritability (h2), which is moderately inheritable and highly repeatable. Effects that influence the resistance or susceptibility of sheep to GIN infections in the peripartum period are determined by the interaction of various factors, such as genotype or breed, nutrition, age, type of birth, season and production system, etc., which are studied in this review.