The objective of this study was to understand the associations of calf growth traits with subsequent milk yield and body weight (BW). Data were collected for 281 Holstein heifer calves from 6 different calf trials of varying lengths (4 to 8 wk) conducted at Pennsylvania State University between 2003 and 2010. Calves were classified as high, medium, or low for hip height, starter feed intake, BW, and growth rate. Milk yield and cow BW were recorded during subsequent lactations. In total, there were 169,734 daily milk records and 136,153 cow BW records available. Data were evaluated using mixed model equations. Separate models were used for each calf growth trait initially, followed by models that considered multiple growth measures. Each model included age at calving, treatment within trial, parity, days in milk, lactation, and one of the calf growth traits as well as the interaction between lactation and days in milk as fixed effects. Cow and calendar week by year were fitted as random effects. Heifers from the low hip height classification as calves produced less milk across lactations after accounting for BW differences. Cows from the medium BW classification as calves produced more milk in early lactation than cows from the high BW classification as calves after accounting for differences in height. Calves that grew more quickly, ate more, and weighed more were heavier as first-lactation heifers and as mature cows. Our results suggest that the type of preweaning growth is an important consideration for future milk yield. Calves that were the shortest had the lowest milk production potential and were the least likely to remain in the herd until first lactation.

Transportation losses of market-weight pigs are an animal welfare concern, and result in direct economic impact for producers and abattoirs. Such losses are related to multiple factors including pig genetics, human handling, management, and weather conditions. Understanding the factors associated with total transport losses (TTL) is important to the swine industry because it can aid decision-making, and help in the development of transportation strategies to minimize the risk of losses. Hence, the objective of this study was to investigate factors associated with TTL on market-weight pigs in typically field conditions for Midwestern United States using a generalized additive mixed model (GAMM). The final quasi-binomial GAMM included the fixed (main and interactions) effects of abattoir of destination, type of driver, average market weight, distance traveled, wind speed, precipitation, and temperature-humidity index (THI), as well as the random effects of truck companies and the combination of site of origin and period of the year. Results indicate significant associations between TTL and the main effect of all explanatory variables (P < 0.05), except for wind speed and precipitation. Interactions of average market weight × abattoir, and wind speed × precipitation were also significant. A complex nonlinear relationship between TTL and model covariates were observed for distance traveled, THI, and interaction terms. This study showed that TTL of market-weight pigs are caused by a complex system involving multiple interacting factors, which can be potentially managed to mitigate the risk of losses. In addition, the GAMM showed to be a simple and flexible approach to model TTL because it can capture nonlinear relationships, handle non-normal data, and can potentially accommodate data structure.

Objective: Determine seasonal patterns of nursery and finisher growth performance in 3 commercial US production systems located in the midwest. Materials and methods: Five years of production records, including 5039 nursery and 5354 finisher production batches, were collected from 3 production systems. Explanatory variables include system, site, pig-flow type, feeder type, batch size, week of placement, average days-on-feed, fill length, number of sow farm sources, dietary energy, mortality, and initial body weight. Week of placement served as the unit for seasonal patterns. Nursery and finisher performance (average daily gain [ADG], average daily feed intake [ADFI], and gain to feed ratio [G:F]) were analyzed in separate datasets using multi-level linear mixed models. A guided stepwise selection approach was used to select fixed variables and their interactions. Seasonality curves were generated using rolling averages of least squares means with a 5-week window and 1-week step-size. Results: For nursery, the seasonality effect was significant (P < .001) for ADG, ADFI, but not for G:F. Nursery ADG and ADFI decreased as week of placement progressed from the 1st to 20th week of a year but increased thereafter. All finisher growth responses were affected by week of placement (P < .001) but the pattern and magnitude of seasonal variability differed among systems (system × week interactions, P < .02). Implications: Seasonal variability of nursery and finisher performance can be quantified using production records in a multi-level linear mixed model. Seasonality effects on finisher performance were system dependent, while nursery seasonality shared more similarity among investigated systems.