PubMed Health⌕ Search

Biomedical subjects

W J Koops

Publications and source records attributed to W J Koops.

11 recordsLinked to original sources
PubMed1992

Characterization of poultry egg production using a multiphasic approach.

Egg production for an individual hen is described by a multiphasic model in which each phase is determined by number of eggs within a clutch, including internally laid eggs, and pause between clutches. Number of eggs in a clutch is determined by circadian rhythm, which consists of a daily rhythm and lag. Internal laying is a result of asynchrony in the development of the oviduct and the ovary. Pause consists of a circadian rhythm and a period called delay. It is expected that lag and internal laying are determined genetically, whereas delay is determined by the environment, especially by photoperiod. A multiphasic model was developed to characterize egg production by lag and delay, expressing cumulative egg number in terms of time. Data need to be adjusted for internal laying prior to the analysis. The inverse function, expressing time in terms of cumulative egg number, was used to estimate average lag and delay for individual hens. Hourly data from four hens over a 16-day period were analyzed to estimate parameters for lag and delay. Data were preadjusted for internal laying and for pause. Lag ranged from -.08 to 2.11 h, and was related positively to number of clutches and, consequently, related negatively to average length of clutch and total number of eggs over the period. Average delay was about 16 h, which may be determined by the light:dark ratio.

Animals↗
PubMed1991

Applications of a multiphasic growth function to body composition in pigs.

A multiphasic growth function was used to relate growth of body components to phases of total growth for pigs. Each phase of growth was characterized by asymptotic weight, age at maximum gain, and duration. Age at maximum gain and duration were expressed as a ratio and assumed constant for all phases. One application involved weights of total DM predicted directly with a diphasic function and indirectly with monophasic functions of fat-free DM and fat. Another involved weights of carcass side predicted directly with a diphasic function and indirectly with monophasic functions of offal + muscle + bone and fat + skin. Components were grouped on age at maximum gain. There was good agreement for asymptotic weight between body components and phases, and general agreement for age at maximum gain and for duration, except for carcass weights. A multiphasic growth function may provide a way to examine fat-adjusted weight in living animals because growth of fat appears as a late phase in a multiphasic description of total body growth.

Age Factors↗
PubMed1991

Multiphasic analysis of growth curves for progeny of a somatotropin transgenic male mouse.

Diphasic functions were applied to growth curves for body weight and for tail length of mice that were progeny of a transgenic male mated to random-bred NMRI females. A group of 20 female and male mice with high (H) body weight at week 12, assumed to be transgenic, and a group of 20 with normal (N) body weight, assumed to be non-transgenic, were selected for comparison. Body weight and tail length were measured about weekly from 3 to 26 weeks of age. Body weight for H mice at week 26 averaged 1.6 (females) times and 1.9 (males) times that of N littermates. The H mice averaged 1.3 times the gain in weight in first phase for N mice; H mice averaged 2.0 times the gain in second phase for N mice. Tail length for H mice at week 26 averaged 1.1 times that of N littermates. The H mice averaged .9 times the gain in length in first phase for N mice; H mice averaged 1.5 times the gain in second phase for N mice. For H mice, larger tail-length gain in second phase more than compensated for smaller gain in first phase. The transgenic effect may be different for body weight than for tail length. For body weight, the effect was continuous over the entire 26 weeks. For tail length, however, the effect was to delay growth of the tail.

Animals↗
PubMed1991

Multiphasic growth and allometry.

Multiphasic growth assumes increase in body weight, or in other body measures, to be a result of more than one growth phase. Therefore, the concept of allometry can be extended from relation between body measures to relation between phases of growth. For two phases of growth, body weight (W) and tail length (L) can be partitioned into W1 + W2 and L1 + L2. Here, W1 and W2 correspond to phases 1 and 2 of weight and L1 and L2 to phases 1 and 2 of length, where each phase is described by a logistic function. Diphasic functions were applied to growth curves for body weight and for tail length of mice that were progeny of a transgenic male mated to random-bred NMRI females. A group of 20 female and male mice with high body weight at week 12, assumed to be transgenic, and a group of 20 with normal body weight, assumed to be non-transgenic, were selected for comparison. Body weight and tail length were measured about weekly from 3 to 26 weeks of age. Allometric relations between phases for weight (W1 and W2) and tail length (L1 and L2) are presented using predicted values based on estimated parameters of the diphasic growth functions. Differences between ages at maximum gain and ratios of duration of phases were analyzed. Growth in second phase of body weight appeared to be unrelated to growth in first phase of body weight and unrelated to growth in tail length. Growth in each phase of tail length appeared to be close to a simple allometric relation with growth in first phase of body weight. It is now feasible to study multiphasic allometric relations of growth between phases of one body measure and between phases of different body measures by comparing estimates of parameters of the multiphasic growth function.

Animals↗
PubMed1988

Multiphasic analysis of growth curves in chickens.

A multiphasic function that considers body weight to result from an accumulation from more than one phase of growth was used to describe growth curves for Rhode Island Red (RIR) and White Leghorn (WL) males and females, from hatching to 45 wk of age. Mean body weight gains were fitted by iteratively reweighted nonlinear regression using the multiphasic function: (formula; see text) where yt is mean gain (grams) at age t; n is number of phases; tanh is hyperbolic tangent; for each phase i, ai is half asymptotic weight; bi is growth rate relative to ai (weeks-1) and ci is age at maximum gain (weeks). For each phase, maximum gain is aibi and duration (days required to attain about 75% of asymptotic yield during that phase) is 2bi-1. Estimates of parameters clearly point to the diphasic nature of growth and to differences between phases of sexes. First and second phases accounted for 97% of total asymptotic weight. For the first phase, males attained 70% of their asymptotic weight, whereas females attained 85%. Duration of the first phase was 15 wk. For the second phase, it was 12.5 wk for RIR and 10 for WL males, whereas it was 5 wk for RIR and 6 for WL females. Maximum gain during the first phase averaged 144.4 g for males, 108.8 g for females, 156.2 g for RIR, and 97.0 g for WL. During the second phase, it was 68.0 g for RIR males and females but 71.5 and 55.9 g for WL males and females, respectively. Age at maximum gain during the first phase was 12.0 wk. During the second phase, it was 24.2 wk for RIR females, 2.6 wk later than for males, whereas it was 27.3 wk for WL females, 8.3 wk later than for males. For a fixed total asymptotic weight, partitioned between two phases of growth, a higher, longer, and later first phase was associated with a lower, shorter, and later second phase; the association was greater for males than for females.

Age Factors↗
PubMed1987

Multiphasic growth curve analysis in mice.

Growth curves of mean body weights were compared to those of individual weights when fitted to data of male and female mice using monophasic (logistic) and triphasic growth functions. Goodness-of-fit was determined by residual variances and Durbin-Watson statistics. These criteria suggest that the triphasic function, with smaller and less correlated residuals, describes the data better than the monophasic function. For the triphasic function, residual variances were higher when fitting individual weights than mean weights. Males had higher residual variances than females. Auto-correlation was negligible when fitting individual weights for males and for females. Parameters of the triphasic function were higher when fitting curves of individual weights than curves of mean weights; differences between curves within sex were small. Parameters were similar for males and females, especially in the first phase of growth. Half asymptotic weights for the second and third phases were higher for males than for females. From these results, it should be clear that using a multiphasic function to describe growth curves in mice provides greater insight for understanding the biology of growth.

Aging↗
PubMed1986

Multiphasic growth curve analysis.

Application of a multiphasic growth curve is demonstrated with 4 data sets, adopted from literature. The growth curve used is a summation of n logistic growth functions. Human height growth curves of this type are known as "double logistic" (n = 2) and "triple logistic" (n = 3) growth curves (Bock and Thissen, 1976). In the literature there is also some evidence for the existence of growth phases in weight growth curves of animals. The fit of the multiphasic growth curve, applied to pika, mice and rabbit weights, was superior to the monophasic model in terms of residual variances and absence of autocorrelation of residuals.

Adolescent↗
PubMed1985

Effect of bull selection for somatic cell count in first lactation on cell counts and pathogens in later lactations.

Somatic cell counts were measured one time on Meuse-Rhine-Ijssel cattle in The Netherlands. Experiment 1 involved 1,741 first lactation daughters of 31 bulls. Eleven bulls with daughters with either high or low average cell count were selected for further study of their daughters in third and fourth lactation. Cell counts and bacteriological tests were performed on 684 of the older daughters. A second experiment was conducted to measure daughters in second lactation and to obtain additional daughters in first lactation. This experiment recorded cell counts of 1,071 daughters of 10 of the bulls selected in Experiment 1. Heritability of the natural logarithm of cell count in first lactation was .081 based on daughters of 31 bulls in Experiment 1. Geometric daughter averages ranged from 206 to 700 X 10(3) cells/ml. Transmitting ability of bulls was estimated by the regressed least squares method. Ranking of bulls on first lactation cell count was different between the two experiments. Management factors and stage of lactation effects could be responsible for these differences. Within Experiment 2, the ranking of bulls on cell counts was nearly identical between first and second lactation. Daughter groups with low average cell count in first lactation in Experiment 2 had low averages in third and fourth lactation although some changes in ranking did occur. These results are consistent with a low to moderate genetic correlation between lactations for cell count. In general, daughter groups with higher average cell count had higher percentage of quarters with mastitis pathogens.

Animals↗