The objectives of this study were to establish a pattern for the seasonality of days open (DO) by state and region within the United States and to present statistics on regional trends for DO. Data included 8,676,915 records on DO for Holsteins from 1997 to 2002 covering all regions of the United States. Fixed effects in the model included herd, parity, milk-class, state x month of calving (MOC), year of calving x MOC, and parity x MOC. Least squares means of DO were highest for calvings in March and lowest for calvings in September. The highest mean DO of 155 d was recorded in the Southeast, while the mean DO for the Midwest, Northeast, Northwest, and Southwest were 142, 141, 140, and 137 d, respectively. Variation in monthly averages of DO was highest in Southeast with a range of 51 d, and less than 25 d in all the other regions. Seasonality of calving was defined as the ratio of the fewest to the most calvings in months. The SOC was > or = 60% in Southeast and < or = 23% in the other regions. Selected states: Texas, Oklahoma, and Arizona in the Southwest and Missouri, Kansas, and Kentucky in the Midwest showed patterns of variation in monthly averages and seasonality of calving similar to those of Southeast. Distributions of DO were bimodal for some months of calving due to postponed breeding during the hot season or depressed fertility as a result of thermal stress; the second mode at > 200 d was highest in the Southeast but also could be observed in Texas, Wisconsin, and California. High level of heat stress for DO exists in the Southeast and in selected states of the Midwest and the Southwest; these regions contribute less than 10% of national records. A methodology for analyzing DO especially under heat stress needs to consider effects of intentionally delayed breeding--by using a model that accounts for bimodality, for example.

A reaction norm approach was used to estimate the genetic parameters of days open (DO) with a model that accounted for heat stress. Data included DO records for Georgia, Tennessee, and North Carolina in the Southeastern United States. A fixed effect model included herd-year, month of calving (MOC), age of cow, and a regression on 305-d milk yield. The reaction norm model additionally included the effect of animal with random regression on a heat stress index (HI), calculated as the standardized solutions to MOC derived from the fixed effect model; the residual variance was assumed to be a function of the HI. The shape of the distribution of the HI was close to a sinusoidal function with the highest value in March/April and the lowest value in September. Genetic and residual variances and heritabilities were highest for spring calvings and lowest for fall calvings. The variance associated with the random regression of the highest level of HI was 33% of the genetic variance of the regular animal genetic effect. Genetic correlation between these effects was 0.67. As a validation, DO data were grouped into 4 seasons of calving and treated as different traits. A 4-trait mixed linear model that included the fixed effects listed above except MOC, was used to analyze the grouped data. In general, the estimates of genetic and residual variances of the multiple trait analyses followed those of the reaction norm model. Genetic correlations of spring with summer, and fall with winter were both 0.90. Genetic correlations between spring/summer and fall/winter were around 0.80. The reaction norm model for DO allows inexpensive genetic evaluation of fertility under heat stress. Results of such an evaluation may strongly depend on editing criteria and model specifications.

High poverty levels continue to plague much of Africa despite several intervention strategies aimed to stem the tide. The role of small livestock like rabbits as a tool in poverty alleviation programmes has been acknowledged for decades and successful national rabbit projects have clearly been demonstrated in Africa. With rising poverty levels across Africa, the need to rejuvenate such national rabbit projects for long-term sustainability becomes apparent. This presentation focuses on the status of rabbit production in Africa, with special attention to smallholder rabbit project development and its connection with poverty alleviation issues in the continent and with an emphasis on the strengths, weaknesses, opportunities and barriers to the system. A special case is made for the sustainable development of smallholder, low-input rabbit production systems in Africa on account of their popularity, low investment requirements and low economic risks, as well as their contributions to family nutrition, income generation and gender empowerment. Successful rabbit projects in several countries across Africa were identified and the reasons for success, as well as lessons learned, are discussed. In all, several cases standout: the National Rabbit Project of Ghana, the Heifer Project International Rabbit Project in Cameroon, and CECURI Rabbit Project in Benin Republic. Other fast-paced and moderately developed rabbit industries (e.g. in Egypt, Tunisia and Algeria) are recognised. Critical constraints to rabbit project development (e.g. non-implementation of sustainable models for low-input rabbit units and absence of client-focused research and development programmes) are noted. Prospects for the development of sustainable smallholder rabbit production models are discussed, which include the following: a paradigm shift among researchers to focus on innovative research related to the development of sustainable backyard rabbit production systems; upscaling of sound practices in smallholder rabbit units across regions; use of local value chains in smallholder rabbit development and setting up regional networks of smallholder family rabbit projects. The actualisation of these goals requires a sustainability research agenda that focuses more on backyard rabbit farmers as the primary beneficiaries. Overall, the need for a poverty focus and a pro-poor research agenda involving owners of backyard rabbits are emphasised.

We sought to determine morphological descriptors of Nigerian indigenous pigs (NIP) and crossbred pigs (CBP) based on relationships among live weight (LW) and a suite of 18 morphometric measurements plus the number of teats. We sampled four locations in southwestern Nigeria and obtained data for a total of 120 NIP and CBP. More female pigs (61.7%) than males (38.3%) were sampled, and they had a mean live weight of 19.9 ± 6.10 kg (range 9 - 32 kg) and 20.1 ± 6.08 kg (range 8 - 37 kg), respectively. The NIP had a longer snout, wider head and longer erect ears than CBP (P < 0.0001). Morphological variables that were highly correlated with LW included neck circumference (NC), breast height (BH), rump height (RH), body length (BL), interorbital width (IW), paunch girth (PG), hearth girth (HG), tail length (TL) and length of snout (LS) with Spearman correlation coefficients (R²) of 0.97, 0.92, 0.96, 0.97, 0.91, 0.97, 0.97, 0.90, and 0.93, respectively (all P < 0.0001). Teat number for NIP ranged from 5 to 14 while the CBP had a range of 10 to 16 teats. For male NIP, HG and TL best-fit in the model for body weight prediction (LW = ﹣25.71 + 0.43 HG + 2.21 TL; R² = 0.93; P < 0.0001), while HG and IW had the best-fit for the female NIP (LW = ﹣28.27 + 0.50 HG + 2.22 IW; R² = 0.96; P < 0.0001). Models for male and female CBP were LW = ﹣8.89 + 0.32 RH + 0.34 BL (R² = 0.84; P < 0.0001) and LW = ﹣13.01 + 0.44 RH+0.27 BL (R² = 0.94; P < 0.0001), respectively. Thus, for these populations of pigs, LS and TN differentiated NIP from CBP, because the NIP consistently recorded longer LS and lesser TN.

The influence of various editing criteria for days open (DO) records on genetic parameter estimates of DO and pregnancy rates (PR) in US Holsteins was investigated. Data included first parity 305-d milk yield and DO records from 8 states: Georgia (GA), Florida (FL), North Carolina (NC), Texas (TX), Arizona (AZ), California (CA), New York (NY), and Wisconsin (WI). The pregnancy rate was computed as 1/[(DO - VWP)/HI + 1)], where VWP was the approximate voluntary waiting period and HI was the heat interval set as 21 d. The upper limit for PR was set to 1.0. A bivariate animal model for DO (or PR) and 305-d milk yield was fit separately for each state. The model included fixed effects of herd-year, month of calving, and age of cow, as well as random animal and residual effects. In separate analyses, maximum DO records were limited to 150, 200, 250, 300, and 365 d. Analyses for PR used values of 50, 80, and 120 d for the VWP. Genetic and residual variances for DO were strongly dependent on the upper limit; both variances were 8 times larger as the upper bound increased from 150 to 365 d. Estimates of heritability for DO varied between 0.03 and 0.06. There was a 30% increase in the heritability estimate as the upper limit increased from 150 to 250 d for FL and NC, and small or no increases for the other states. The increase of the upper limit from 250 to 365 d resulted in little change. The genetic correlation between milk and DO was the highest for FL (0.6) and the lowest for GA (0.12 to 0.23). For PR with VWP=50, the heritability was higher than the corresponding estimate for DO in GA, equal to that in AZ, and lower in the remaining states. Heritabilities of PR also varied by the length of VWP; highest heritabilities were obtained at VWP=50 d for GA and AZ; at VWP=80 d for NY and WI; at VWP=120 d for FL, NC, and CA. Increase of genetic variation for records of DO < 250 d was small. Days open and PR are strongly influenced by differences in management protocols among states.