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Biomedical subjects

W J Koops

Publications and source records attributed to W J Koops.

18 recordsLinked to original sources
PubMed1997

Nutrient flows in agriculture in The Netherlands with special emphasis on pig production.

Annual nitrogen (N), phosphorus (P), and potassium (K) flows in agriculture in The Netherlands were identified and quantified in 1990, with special emphasis on pig production. Also, the effects that various management strategies in pig production have on NPK emission in 1990 were compared using a static deterministic simulation model. Ammonia emission from pig production in 1990 (60.9 Gg N) exceeded the defined target for the year 2000 (12.7 Gg N). Measures that affect volatilization of ammonia directly (i.e., introduction of low-emission stables, manure storage facilities, or manure application techniques) reduced ammonia emission most effectively. These measures, however, should be combined with a reduction in application of artificial N fertilizer to avoid an increase in N losses through leaching, run-off, or denitrification. Targets for ammonia emission in the year 2010 require a reduction in the pig population of 24 to 62%, in addition to implications of measures described in this article. National NPK losses in 1990 through leaching, run-off, or denitrification, predicted at 223.5 kg/ha for N, 32.7 kg/ha for P, and 67 kg/ha for K, exceeded government targets for the year 2010 (185 kg N/ha; 8.7 kg P/ha; norm not set for K). Reducing application of artificial NPK fertilizer reduced national NPK losses most effectively. For P, use of phytase and feeding pigs in accordance with their P requirements is required, in addition to limited use of artificial P fertilizer to meet targets for the year 2010. Hence, from an environmental point of view, pig production in The Netherlands is limited primarily by ammonia emission targets for the year 2010.

Ammonia↗
PubMed1996

Multiphasic analysis of embryonic mortality in chickens.

Infertility and embryonic mortality are economically important for the commercial broiler industry because they are components of hatchability. Embryonic mortality in chickens is not uniformly distributed over the course of incubation; two phases of embryonic mortality are characteristic of chicken development. The objective of this paper was to develop a mathematical model to assess infertility and to characterize the distribution over time of embryonic mortality in chickens. A model was constructed based on evidence in the literature for multiple phases of embryonic mortality before and during incubation. A multiphasic model, with two phases, included parameters for the proportion of eggs that were infertile and the proportion that were fertile but the embryo died before or during incubation. For those eggs that were fertile but the embryo died, the model included the proportion of embryonic mortality during each phase, day of peak mortality, and duration of phase. Data on embryonic mortality for white Cornish chickens were used to illustrate the multiphasic model. Model parameters could be estimated easily and interpreted with clear biological meaning. Estimates of parameters, in general, were reasonably precise and consistent with the literature. With multiphasic analysis, one can assess infertility and characterize the distribution of embryonic mortality in chickens, which can lead to a useful understanding of management and genetic aspects of these components of hatchability.

Animals↗
PubMed1995

A model for reproductive efficiency of dairy bulls.

Reproductive efficiency of bulls is usually measured by nonreturn rate, which is commonly defined as the proportion of cows that were inseminated and did not return for another service within a specified number of days. The AI organizations use nonreturn rate to evaluate fertility of a bull or performance of a technician. Measures derived from nonreturn rate, such as conception rate and calving rate, might be more reliable for evaluation than nonreturn rate itself. Estimated conception rate is a better early measure of efficiency than nonreturn rate, because conception rate depends on the population of spermatozoa at insemination and not on developmental potential of the conceptus after insemination. A mathematical function is presented to model reproductive efficiency of bulls by estimation of the probability of conception at time of insemination (conception rate) and the probability of completing gestation after insemination (calving rate) through the relationship of nonreturn rate to the concentration of spermatozoa at insemination and the time after insemination. The model is illustrated with three bulls, using nonreturn rates by 28, 56, and 84 d after insemination.

Animals↗
PubMed1995

Multiphasic analysis of reproductive efficiency of dairy bulls.

Reproductive efficiency of dairy bulls is usually measured by nonreturn rate. Nonreturn is a compound trait that is a result of two events, conception and gestation, that lead to calving. Nonreturn rates can be used to derive more elementary biological measures for reproductive efficiency, such as conception rate and calving rate, which separately might be more reliable than nonreturn rate itself to evaluate the fertility of a bull or the performance of an AI technician. The challenge of this study was to examine the decline in nonreturn rate in light of the theory of multiphasic analysis. A multiphasic logistic function was developed to model decline in nonreturn rate by estimating conception rate, calving rate, and characteristics of the first two estrous cycles. The model is illustrated with data on daily nonreturn rates to 120 d. From the proportion of cows that conceived but failed to complete gestation because postsignal embryonic death, the model estimates conception rate and calving rate. From the proportion of cows that failed to conceive or that conceived but failed to complete gestation because of presignal embryonic death, the model estimates the proportion of returns, or probability of detecting estrus, duration of nonreturns, and time of maximum decline in nonreturn rate for the first two cycles. Using the proposed model, conception rate and calving rate estimated from daily nonreturn rates might be more reliable for evaluation of performance of an AI technician and fertility of a bull than nonreturn rates at arbitrarily chosen days after insemination.

Animals↗
PubMed1995

Onset of lay related to multiphasic growth and body composition in White Leghorn pullets provided ad libitum and restricted diets.

Growth of the body as a whole and of parts of the reproductive tract of White Leghorn pullets that ate ad libitum and restricted diets were analyzed by a multiphasic growth function. Parameter estimates were related to onset of lay. Chemical body compositions at defined stages of pubertal growth were related to the development of the reproductive organs. Data of pullets that had been restricted in one of two rearing periods (0 to 6 and 7 to 18 wk of age) were used. In each period, pullets were fed a low-lysine diet or a daily restricted amount of feed, on a pair-gain basis. In all mathematical fits, a well distinguishable "pubertal body growth spurt" at around 19 wk of age was found. About 40 to 70% of total growth within this phase consisted of growth of the reproductive tract (the ovary covered 19 to 35%, the oviduct 15 to 23%, and the uterus 7 to 11% of total growth). Age at maximum gain of the pubertal body growth spurt was 20.1 wk for lysine-restricted pullets and 19.6 wk for feed-restricted pullets. This difference reflected differences in onset of lay (50% rate of lay) between lysine- and feed-restricted birds (22.3 and 21.6 wk, respectively). An interval of 14 to 15 d existed between maximum gain of the pubertal body growth spurt and onset of lay. It was suggested that the occurrence of the pubertal body growth spurt can serve as a predictor for subsequent onset of lay. Body composition at defined moments during the pubertal body growth spurt was calculated by interpolation from chemical analyses of Weeks 15, 18, 20, 22, and 24. Crude fat content in the body at start of the pubertal body growth spurt varied considerably between the feeding regimens (112 to 179 g). The fat-free body (consisting of CP, ash, and water) showed less variation between the treatments at this stage (807 to 870 g). It is concluded that a particular amount of fat-free tissue is critical in pullet development and may be required before sexual organ development starts.

Age Factors↗
PubMed1993

Multiphasic analysis of growth of the body and its chemical components in White Leghorn pullets.

Data of White Leghorn pullets consuming feed ad libitum were used to study multiphasic growth during rearing and early lay. Two mathematical functions were used. Body weight gain and growth of the chemical components DM, CP, crude fat (Cfat), and ash (Ash) were described as a function of age, using a multiphasic growth function. To describe relative growth between CP and DM, Cfat and DM, and Ash and DM, a multiphasic allometric function was applied. Body weight gain from hatching to 24 wk of age was estimated most accurately by a tetraphasic growth function. The first two growth spurts represented 82% of mature BW. Growth in these two phases seemed to be related to the development of bones, muscles, and essential metabolic organs. Body growth was further characterized by a third phase at 19 wk of age, which was related to growth of the reproductive tract. The fourth phase consisted mainly of body fat deposition. Both multiphasic functions showed that the nature of component growth was diphasic, with a transition area between the two phases at around 11 wk of age. On the basis of the duration of growth and of allometric growth coefficients, growth of CP, Cfat, and Ash in the first phase seemed to be functionally related to each other and consisted of muscle growth, intermuscular fat deposition, and skeletal growth, respectively. After 11 wk of age, protein deposition is presumably a function of sexual maturity, i.e., the development of the reproductive tract; whereas fat growth is mainly abdominal fat deposition. The observed relationships indicate that the use of multiphasic functions might be helpful in the interpretation of changes in body growth and development of pullets.

Animals↗
PubMed1993

Multiphasic allometry.

A multiphasic linear model is presented that describes the allometric relation between body components and permits a smooth transition from one linear segment to the next. Three applications of a diphasic linear model to allometric growth problems were used to illustrate the model. The data sets were selected because a breakpoint exists in the allometric relation. Relations between growth of the alimentary tract and of empty body weight in rabbits, growth of length and of body weight in larval-carp and growth of protein and of fat in pullets were described by a diphasic allometric model. For rabbits and larval-carp, relations were described significantly better by a diphasic instead of a monophasic (simple) allometric model. For situations where response is expected to consist of more than one linear segment, the multiphasic model is recommended.

Animals↗
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↗