Biomedical subjects

B A Shalev

Publications and source records attributed to B A Shalev.

9 recordsLinked to original sources

PubMed1999

Genetic-economic evaluation of traits in a goose meat enterprise.

1. Goose can be considered as an additional and inexpensive meat source, provided that the marketing age does not exceed 8 weeks. Using the ability of geese to eat grass may reduce the intake of concentrated food up to 30%. 2. According to an equation developed, growth rate accounts for about 58% of the annual breeding gains, egg number 28%, feather yield 10%, fertility and mortality about 2%. These values are about the same for a wide range of food prices. 3. Employing realistic values for expected annual genetic gains reveals that the customary practice of keeping breeders for 5 to 6 years should be replaced by a much shorter cycle of 3 years because the economic gain from the shorter generation interval of selection exceeds the replacement costs.

Animals↗

PubMed1998

The relative energy requirement of male vs female broilers and turkeys.

Three models to estimate energy requirement as a function of growth curve pattern were applied to controlled experimental data of male vs female of broilers and turkeys. The share of maintenance out of total feed requirement was 55% for the average of the three models with major divergence due to age. Comparison of the ratio between actual and estimated feed consumption reveals that the relative energy requirement was always lower in females than in males in the range of 5 to 10% for the three models, with an average of 7.7%. It appears, therefore, that in estimating the energy requirement for use in practical feeding, specific models should be assigned for males and females in both broilers and turkeys.

Animal Feed↗

PubMed1995

Incremental changes in and distribution of chick weight with hen age in four poultry species.

1. It is proposed that a general biological pattern exists for chick weight increase with hen age for the various commercial species of poultry and that one general equation can be used for the estimation of chick weight increment. 2. The parameters estimated for this equation are based on (a) chick weights as a percentage of annual mean chick weight, and (b) age, from onset of lay, as a percentage of maximum age of the hen; both serving as common denominators. Hence, if the annual mean chick weight is known for any species, breed or strain, then the increase in chick weight can be predicted for the whole season, or for any particular hen age. 3. For early prediction, first-month chick weight can be used to estimate the annual mean weight and consequently the chick weight curve for the full season. Although such prediction will be somewhat less accurate, it still can be used for general planning. 4. Results indicate that chick weights of various avian species are normally distributed. Therefore, at each point of hen age, the chick weight distribution can be estimated by employing the computerised Burr's (1967) equation. This may be useful for segregating chicks by size, thus improving uniformity and reducing competition within the flock. 5. Computation results show that coefficient of variation (CV) of chick weights, originating from 22 and 62 week dam ages, is increased by up to about 75%. The CV may thus be used as a quality indicator.

Aging↗

PubMed1994

The effect of a feature of regression disturbance on the efficiency of fitting growth curves.

Growth curve parameters are usually estimated by employing non-linear regression. In the present study this method was found to be inefficient for fitting growth curves, since the magnitude of random deviations of body weight greatly increases with age (heteroskedastic regression disturbance). Simulated samples of broiler body weights at different ages were generated and the associated Gompertz growth curve parameters were estimated employing three methods. Comparison of the efficiency of these methods in fitting Gompertz growth curve under this regression disturbance were performed. The results indicate that the most efficient method to estimate growth curve parameters is "weighted non-linear regression". The efficiency of this method was found to be much higher than that of conventional non-linear regression. These findings should be taken into consideration when fitting growth curves, in general, as well as for the Gompertz equation.

Age Factors↗

PubMed1993

Increment of egg weight with hen age in various commercial avian species.

1. The present study indicates that a common biological pattern exists for egg weight increase with hen age for the various commercial avian species, breeds and strains at their first laying cycle. Therefore, one common equation can be used for the estimation of egg weight increase. 2. The parameters estimated for this equation are based on (a) egg weights in terms of percentage of seasonal mean egg weight, and (b) age as percentage of maximum age of the hen. Therefore, if the season's mean egg weight is known for any species, breed or strain, the increase in egg weight can be easily predicted for the whole season, or for any particular hen age. For early prediction, egg weight expressed as a percentage of initial egg weight can be used, although such prediction will be somewhat less accurate. 3. The use of egg weight as a percentage of seasonal mean egg weight, and age as a percentage of maximum age, was found to overcome the differences between strains, breeds and even species, by applying the same denominators for egg weights and periods of lay. 4. At each point of hen age (mean egg weight), the egg weight grades can be easily estimated by employing the computerised Burr's (1967) equation. These values showed excellent fit with extensive field data, provided that only normal eggs and those originating from a single flock and from no more than two weeks of collection are counted.

Animals↗

PubMed1992

An algorithm to fit the Gompertz function to growth curves.

An algorithm to fit the Gompertz growth function is presented. This algorithm is easy to program on a microcomputer. The algorithm is based on employing a searching technique to solve a set of equations derived from the Gompertz function. Its application may prove valuable when access to a computer mainframe is difficult. Such a method may be useful in construction of a specific growth curve in biology, or as a managerial tool in livestock enterprise, as well as in the clinical treatment of tumors. Demonstration of the successful application of this algorithm in experimental livestock growth data are presented.

Algorithms↗

PubMed1991

Long-term goose breeding for egg production and crammed liver weight.

1. Results of an 8-year (1981 to 1988) period of breeding geese for egg production and crammed liver weight, including phenotypic and/or genetic parameters for various traits (1982 to 1985), as well as line tests (1987 to 1988), are summarised for two lines. 2. The regressed annual genetic gains over years were 2.7 eggs and 30.8 g crammed liver. However, there was a decline in the rate of genetic progress after 4 years of selection. 3. Heritability estimates were found to be relatively high for most traits, whereas phenotypic and genetic correlation coefficients between traits were rather low, as would be expected from lines not previously subjected to an intense selection programme. 4. Phenotypic correlation coefficients between part-period records and full-period egg production, suggest that 3-month (October to December) records may be adequate to identify most of the best first-year layers. However, sexual maturity should be treated as a separate trait. 5. The cross between the 'Grey' (male) line, superior in crammed liver weight, and the 'White' (female) line, excelling in egg production, seems to be superior to the pure lines, in a fully-integrated enterprise.

Analysis of Variance↗

PubMed1983

Genetic-economic evaluation of traits in a broiler enterprise: the relative genetic-economic values.

Selection for growth rate and food utilisation (assuming annual genetic gains of 3 and 1.5% respectively) have about the same economic value and account for 94.3% of the annual potential economic savings in the production costs of an integrated broiler enterprise. Selection for more hatching eggs (annual genetic gain of 1.7 eggs) accounts for only 4.2% and selection for fertility, hatchability and reduced mortality have a value of less than 1% each. The introduction of the dwarf gene (dw) has a questionable economic value. Even if growth rate and fertility are not reduced by using dwarf females, the economic importance will equal no more than two generations of selection for growth rate. As egg production increases, the relative economic value of growth rate and food utilisation will increase, while the advantage of using dwarf females will decrease. Both body weight and body fat content (which are correlated with food utilisation) are moderately heritable and if body fat can be measured reliably in live birds, this may aid breeding for economic advantage.

Adipose Tissue↗

PubMed1983

Genetic-economic evaluation of traits in a broiler enterprise: reduction of food intake due to increased growth rate.

Separate mathematical models for food consumption and growth pattern of broilers were used to derive a combined model to estimate food consumption during the growth period. The model was used to show that each reduction of one day in reaching a fixed body weight would reduce food consumption per bird by 50 to 60 g. Broiler lines with a slow growth rate at an early age and rapid growth rate near market age require appreciably less food overall. This feature should be considered in breeding and feeding programmes.

Animal Husbandry↗