An evaluation of visual assessment for fertility in Brahman cross cows using the Bonsma technique

UTTERWORTH EINEMANN

AN EVALUATION OF VISUAL ASSESSMENT FOR FERTILITY IN BRAHMAN CROSS COWS USING THE BONSMA TECHNIQUE G. Fordyce

and N.J. Cooper

Queensland Department of Primary Industries Swan’s Lagoon Beef Cattle Research Station Millaroo, Queensland 4807, Australia Received for publication: Accepted:

~zlne 21, November

I gg4 18, 1994

ABSTRACT A technique of visual assessment of cattle for reproductive efficiency, described by Professor Jan Bonsma of South Africa, was evaluated in two well-managed large herds of % to X Brahman cross heifers and cows located in the dry tropics of north Australia. Experienced Individual lifetime performance records were available for all animals. Higher scores were previously claimed to indicate cattlemen carried out the assessments. higher fertility. The technique had high repeatability (0.7) and was quickly learned by the assessors. Scores from visual assessment had no useful predictive value for either heifer or cow fertility or for growth rate up to 27 mo of age, although 2.5yr-old heifers which were scored as Scores subfertile matured into 4% smaller cows than heifers which had scored higher. decreased as fatness increased (P
cow, heifer, Brahman, fertility, growth, prediction, visual assessment of fertility

Acknowledgments We thank Mr. Rob Atkinson for participating as an assessor and for training the other assessors. We also thank the other assessors: Mr. John Andison, Mr. John Lyons and Mr. Warren West. The data analyses were carried out by Mr. Bob Mayer.

Theriogenology 43:495-507,1995 0 1995 by Elsevier Science Inc. 655 Avenue of the Americas, New York, NY 10010

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Theriogenology INTRODUCTION More than 80% of the herds in north Australia are made up of & indicus cattle and their crosses (1). Culling of Bos indicus cross cows with low fertility from breeding herds would raise the reproductive efficiency of both current and future generations, as fertility is both repeatable (14,6) and heritable (10). Fertility of individuals has not generally been economically viable to estimate in commercial herds because of the very extensive management, including continuous mating and infrequent handling, which is often of low efficiency. Therefore, cattlemen for generations have used various indirect visual indicators in the physique of cattle to estimate past and future performance when carrying out culling or selection. The phenotype of cattle is a function of their genotype, the environment and the interactions between these. Bonsma (2) suggests that important components in establishing phenotype and performance are 1) the endocrine system and physiological activity which can regulate. morphological attributes and 2) the skin and its adnexa which play a major role in environmental adaptation. In a further development of an earlier lecture series (2), Bonsma (3) outlined specific criteria for visual assessment of cattle to determine “functional efficiency.” Bonsma suggests that if the hormonal systems of a cow are suboptimal (i.e., she has “disturbed endocrine balance”), then she will be subfertile and will not display “femininity” as described by conformational traits; the converse is also claimed to be true. Parallel claims are made for Most aspects of the hypothesis appear to be based on a very small bulls and castrates. number of animals at the extremes of variation in cattle populations. There appears to be no reported data which validates the hypothesis. This paper reports an evaluation of Bonsma’s system of assessing cows as it relates to fertility and growth in 2 herds of Brahman cross cows in the dry tropics of north Queensland. This study was instigated as many beef producers in this region (as well as in many other parts of Australia and other countries) were placing considerable credence on Bonsma’s system and used it in the selection and culling of cattle. Several aspects have been incorporated into breed standards in many countries. In this environment, efficient breeding cattle reach puberty early (before 2 yr), and have high weaning rates (over 80X), high growth potential, low mortality risk and high salvage value with minimal inputs and management. Subfertile females reach puberty relatively late and raise no more than 1 calf every 2 yr under good management, i.e., where herd weaning rates are at least 70%. MATERIALS AND METHODS Environment Observation 1 was conducted at Swan’s Lagoon Beef Cattle Research Station (latitude 20” 05’S, longitude 147O 14’E) in the subcoastal black spear grass region of north Queensland,

497

Theriogenology

Australia (18). The climate is dry tropical and is characterized by a hot wet summer period (wet season) and a warm dry winter period followed by a hot dry period (dry season). Mean maximum and minimum temperatures for January (mid-summer) are 31°C and 23°C and for July (mid-winter) are 26°C and 9°C respectively. Distribution and amount of annual rainfall is highly variable. On average, 75% of the 919 mm of average (26-yr mean) annual rainfall occurs between December and March inclusive. The vegetation is open woodland (primarily Eucalctus spe3 with a native unimproved pasture which is predominantly black spear grass (Heteromn contortus) with tropical tall grasses and other medium grasses (e.g., Eulalia fulva, Themeda triandrq Bothriochloa Detusa). Soils are generally of low fertility with phosphorus levels at 6 to 8 pg/g and organic carbon at less than 0.5 to 1.5% (oven dry weight). A more detailed description of the site is provided by Holroyd et al. (12). The nearby La&own Research Station (CSIRO) was the site of Observation environment and climate is very similar to that in Observation 1.

2.

The

Animals and Management In Observation la, the heifers and cows used were %, % and j& F3 et seq. generation Brahman crosses with Beef Shorthorn aged from 2.5 to 8.5 yr. Date of birth was known for all r/z and 3k cross animals. All 6/8crosses were 2.5 yr of age. All females were mated each year to bulls of the same genotype for 12 wk commencing in mid-late January. All available 2-yr-old heifers had been included in the breeding herd each year with minimal culling only. Females were culled from these herds for very poor temperament, physical abnormality and very low fertility (failing to raise a calf to weaning following mating as a non-lactating animal). Calves were weaned each year approximately 7 wk after the end of the mating period, i.e., in the first week of June, which approximates the beginning of the dry season. As part of another experiment which utilized some of the cows earlier in the year of the study (1989), 49 cows aged 3.5 to 6.5 yr had their calves weaned at the start of mating or within 4 wk of that time. Observation lb used the 2.5-yr-old heifers in Observation la. At weaning, they were allocated to 3 nutritional treatments. From 12 mo of age, 2 of the treatments were managed as one group. The third treatment group was managed separately until 3 yr of age. This cohort of heifers was retained without culling (though mortalities did occur) until 6.5 yr of age. Management of 45% of them (rh and !4 Brahmans) was as for Observation la. The balance (% Brahmans) were continuously mated. All calves weighing 100 kg or more were weaned at 2 annual round ups in the late growing season (late April) and the mid-dry season (late August). In Observation 2, a herd of Droughtmaster cows (similar genetic origins to the herd in Observation 1) aged 3.5 to 5.5 yr was used. Management was very similar to that in Observation la.

498

Theriogenology

Measurements In Observation la, at the end of mating and at weaning, the day of conception was estimated for each heifer and cow by manual per rectum examination of the reproductive tract. Calf raising and losses were determined by assessing lactation status at the beginning and end of mating and at weaning. Weight and body condition were recorded each year at the beginning and end of mating, at weaning and prior to the commencement of calving. Body condition was assessed on a g-point scale as described by Holroyd (11). The hair color of Brahman cross cattle is highly variable. In this study, each was described as being in 1 of 4 classes: grey, black/brown, red or brindle. At the end of mating in April 1989, an assessor experienced with visual assessment of fertility as described by Bonsma (3), and who had received tuition from Professor Bonsma, scored 496 cows and heifers while they were held individually in a small yard immediately after weighing. Each was given a score between 1 and 10 based on traits which Bonsma suggests are desirable in cows for “functional efficiency” (Table 1). Scores of 1 to 2, 3 to 4, 5 to 6 and 7 to 10 indicated infertility, subfertility, average fertility and high fertility, respectively, as determined by the method of Bonsma (3). Later on the same day of visual assessment, 301 of the animals were presented for a second assessment in the same situation. In May 1989, 4 assessors were given 1 d of instruction by the experienced assessor at a different property. Each of the newly-trained assessors was an experienced practical cattleman and respected by his peers for his ability to assess cattle. At weaning in June 1989, each of the 5 assessors scored 496 cows and heifers, with a further 126 4/e Brahman cross heifers being scored by the experienced assessor and 1 of the 4 new assessors. Assessment was carried out at the same place using the same procedure as in April. At all times during scoring, the assessors were unaware of the reproductive records or management history of individual animals. Jn Observation lb, plasma progesterone was sampled every 2 mo (2 samples 10 d apart) between 12 and 24 mo. Concentrations > 1 nglml were taken to indicate puberty that had been reached; this overestimates age at puberty by an average of 1 mo. Following initial mating at 2 yr of age, the dates of all conceptions and the outcomes of these conceptions were recorded. First evidence of cycling was taken as the date of first conception if no evidence of cycling occurred prior to the first mating. Weights were recorded each 2 mo from 12 mo of age until the start of the first mating. Thereafter, they were weighed and body condition was assessed at routine management round ups. Observation 2 was conducted at weaning in May 1992, when 2 of the new assessors scored the cows as described in Observation 1. Age of cows was known. Estimated breeding values for pregnancy rates were available for ah cows. An estimated breeding value for a trait is the estimated deviation in genetic merit from an average animal within the original base herd (e.g., an estimated breeding value of +8% for pregnancy rate indicates that if mated to a bull with an estimated breeding value of O%, the average pregnancy rate of the female progeny will be 4% higher than for average heifers or for average cows in the herd).

Theriogenology Table 1.

Traits in cows which are considered by Bonsma (4) to indicate optimal potential nerformance Desirable

Undesirable

General structure

Nothing to impede locomotion Depth greater at the flank than at the heart girth, i.e., wedge-shaped outline

Low weight for age

Muscle

Lean, especially in forequarter

Fat

Even

Obvious (lumpy) depots, especially in the brisket, udder, vulva and hip

External genitalia

Smooth skin Vulva well developed and perpendicular Udder neatly attached Teats pigmented and even shape

Clitoris overdeveloped Vulva/udder with long coarse hairs Udder pendulous Teats wide at their base

Skin

Thick, pliable and pigmented Neat dewlap extending over brisket Neat navel flap

Hair

Short, sleek and difficult to felt White to red (in open range) Sheds winter coat early

Dry hair Black (in open range) Erect hairs on back line

Behaviour

Docile temperament

Nervous Social outcast

Head

Wide and wnvex Lean muscling of cheeks

Lips coarse Short ears

Neck

Long and slim Free from dark-colored hair

Shoulder

Dorsal aspect of scapula higher than dorsal processes of thoracic vertebrae

Body area

Sloping down and forward

Brisket Ribs and abdomen

Widest point

Back

Broad and straight

Rump

Rounded with moderate slope

Pelvis

Broad

Tail

Hangs perpendicular

High setting

Legs

Pigmented hooves

Straight hocks Very short or very long legs Relatively narrow (“light”) bone

500

Theriogenology

Hormone Analyses Plasma progesterone (P,) concentrations were measured by radioimmunoassay in unextracted plasma samples using a modification of the Danazol (R-004~RR; SterlingWinthrop Research Institute, NY) method described by McGinley and Casey (13). The assay used tritiated P, (1,2,6,7-‘H progesterone, 80-100 Ci/mmol; TRK413, Amersham Australia Pty Ltd, North Ryde, NSW) as tracer, P, (4-pregnene,3,20_dione; Sigma Chemical Co, St Louis, MO, USA: PO130) as standard, and antibody raised against progesterone-llhemisuccinate-bovine serum albumin in sheep (#9817, R.I. Cox, CSIRO, Prospect, NSW, All reagents were prepared in 0.1 M phosphate buffered saline (PH 7.0) Australia). containing 0.1% w/v gelatine. The sensitivity of the assay (90% zero-binding) was 0.10 nglml (10 pglassay tube), the intra-assay coefficient of variation (CV) was 4.72, and the inter-assay CV was 9.0%. Statistical Analyses For Observation la, the differences between assessors were tested by least squares analyses of variance. One analysis compared scores for the experienced assessor within the same day for 301 animals; the other compared all assessments for 496 animals. Using mean squares for animal variation and error derived from models comparing 2 assessors, repeatability of scores between assessors was estimated as described by Turner and Young (17). Least squares analyses of variance (9) of average Bonsma scores were carried out using a model which included the factors of age, Brahman genotype content, color, frame size, body condition score, weight per day of age at 27 mo, calf raising in 1989 and lifetime reproductive record. Separate analyses were carried out for heifers and cows because of the confounding between age and Brahman genotype content. Weight per day of age at 27 mo was calculated for each animal and classed as low, medium and high if CO.38, 0.38 to 0.42 and >0.42 kg/d, respectively. Full liveweights for all animals during 1988 and 1989 were initially adjusted for the products of conception using the method of Silvey and Haydock (15) assuming a calf birth weight of 27 kg (8). The ratios at each of six corrected weights to the average corrected weight of animals within the same body condition score were averaged to produce an estimate of relative size. Therefore, the relative size index of the average animal was 1.00; the range was 0.78 to 1.30. Frame size was then classed as small, medium, or large if the relative size index was <0.95, 0.95 to 1.06 and > 1.06 in cows and ~0.87, 0.87 to 0.92 and >0.92 in heifers, respectively. Lifetime reproductive record was calculated as the ratio of number of calves raised to weaning to the number of matings to fertile bulls and was classed as low, medium or high if it was 0.8, respectively. Calving date in the year of the study (1989) was split into 4 levels: did not calve; early calf (before 26 November); mid-season calf (26

Theriogenology

501

November to 25 December); and late calf (after 25 December). Calf raising was at 3 levels for cows: failed to raise a calf to weaning; early-weaned calf; and late-weaned calf. Because of the very high conception rates in 1989 (91%), conception in that year was classed on a scale of 1 to 5: the first 4 values corresponded to conception within successive 3-wk periods during the 12-wk mating period; Level 5 included those animals which did not conceive. For all animals in the study, this variable was then analyzed by least squares analysis of variance (9) using a model including age, Brahman genotype content, color, condition score and calving date as factors and the Bonsma score as a covariate. Factors excluded from this model in preliminary analyses, because of no significant effect, were the weaning date and frame size. In each analysis of variance, 2-way interactions between factors were fitted and then excluded if not significant. Least squares means were estimated for all factors within final models. Where a factor was significant, pair-wise comparisons between levels were tested using the protected least significant difference procedure (16). For Observation lb, each fertility parameter was variance (9) based on models which always included Bonsma score (average of the experienced assessor’s levels based on increments of 2 scores; e.g., Level 3

analyzed using least squares analysis of the genotype, nutritional treatment and scores in April and June) reduced to 3 = 4.5 to 6.0.

Weight was included in analyses as a factor with 25 kg increments. In analyses of cumulative percentage which had reached puberty, weight at the time of assessment was used. For analysis of first evidence of cycling, weaning weight was used, as well as growth rate from weaning to first mating which had been factorized into 0.05 kg/d increments. All other analyses of fertility parameters, excluding calving to conception interval, included weight at 27 mo of age (start of first mating). Relative size index was recalculated using weights and body conditions scores up to August 1993 and was included as a covariate in analyses of calving to conception interval and total calves raised. First evidence of cycling was also included as a covariate in these analyses. Analysis of relative size index used the same base model as for fertility parameters and included total calves raised as a covariate. Least squares analysis of variance (9) of estimated breeding values for pregnancy rate from Observation 2 used a model including cow age and Bonsma score reduced to 3 levels, as described above.

502 RESULTS Observation la Bonsma scores were moderately repeatable (range: 0.66 to 0.75), even for inexperienced assessors. The repeatability of scores across all assessors at the June assessment was 0.69. This was only marginally lower than repeatability within assessor on a single day (75%) and marginally higher than repeatability within assessor over 2 mo (66%). At the June assessment, any 2 assessors scored an average of 37% of the animals the same (range: 33% to 42%), and an average of 84% of the animals within 1 point of each other (range: 80% to 90%). Again, this was only marginally different from the consistency of scoring within a single day and across 2 mo by the experienced assessor. Small differences occurred in average scores between assessors (4.90 to 5.22; P
503

Theriogenology Table 2.

Effects (least squares means) on Bonsma scores (average of the experienced assessor’s first (of 2) score in April and all June scores) in Brahman cross cows

Factor

Number of cows

Bonsma score (range: 1 to 10)

386

4.60 .-&0.09

3.5 4.5 5.5 6.5 7.5 8.5

115 74 41 83 39 34

4.76a 4.68’” 4.33bc 4.28’ 4.67ak 4.84ab

‘/2 w

171 215

4.68 4.51

Level of factor

Mean + SEM Age (yrs)

Brahman genotype content (%) Color

Frame size

Body condition score

Weight per day of age at 27 mo

Weaning

Calves raised/matings

Grey Black/Brown Red Brindle

40 68 198 80

Small Medium Larse

67 116 203

4.47 4.56 4.76

4 to 6 7 8

144 118 124

5. 15a 4.54b 4. loc

LOW

Medium High

152 131 103

4.41 4.66 4.72

No calf Early Late

86 49 251

LOW

23 162 201

Medium High

a,b,CMean~ with different superscripts differ significantly (P< 0.05).

4.63 4.64 4.52

Theriogenology

504 Observation lb

Heifers which had high Bonsma scores at 2.5 yr of age reached puberty later than heifers which had lower Bonsma scores (PO.O5) for slower attainment of the initial pregnancy, although there was only a few weeks delay (Table 3). The lack of a significant relationship between Bonsma score and calving to conception interval, was reflected in the lack of relationship of score with total calves raised (Table 3). Average scores (using the mean of the experienced assessor’s scores in April and June) of cows raising 0, 1, 2, 3 and 4 calves were 5.1, 5.1, 4.5, 4.9 and 4.7, respectively. Parallel outcomes were seen when the Bonsma score of the new assessor was used in the analyses. Cows that were smaller mature size 1.029), with cows (relative size index:

Table 3.

scored as being subfertile (2.5 to 4) according to Bonsma’s criteria had a than the fertile (score >6) cows (P
Relationships of fertility traits in a cohort of Brahman cross cows with Bonsma scores (average of the experienced assessor’s scores in April and June) at 2.5 yr of age

Fertility uarameter

1

Unit of measurine fertihty-

Mean of fertilitv paramefer

SEM

Number

Bonsma score Subfertile

Average fertility

Fertile

66

117

14

First evidence of cycling

Days after 31 De-c 1986

552

12

508’

558b

591b

Conception within 3 months of mating

Percent

92

3

97

91

88

First contirmed pregnancy

Days after 31 Dee 1988

60

8

49

57

74

Average calving to conception interval

Days

471

10

473

478

462

Calves raised to 6.5 vr

Number

3.0

0.1

2.9

2.9

3.0

8*sMeans within row with different postscripts differ significantly (P < 0.05).

Theriogenology Observation 2 Eonsma scores were unrelated to the estimated breeding value for pregnancy rate (mean + SEM: +3.0% + 0.7). DISCUSSION For a efficiency production under the

cattle evaluation method to be of practical use by cattlemen in predicting the of breeding animals, it must accurately rank animals on 1 of more of the principle parameters of weaning rate, growth potential, mortality risk and salvage value management system and the environmental conditions in which the cattle are run.

Our study demonstrates clearly that the visual assessment criteria for “functional efficiency” as described by Bonsma (3) have no useful predictive value for heifer or cow fertility in a well-managed herd. In our observations, the only significant relationship was that heifers which were scored as subfertile reached puberty earlier than those. scored as being of average or higher fertility; this is contrary to Honsma’s hypothesis. Average Honsma scores would suggest that the herds used had low fertility. However, reproductive records showed that the average weaning rate was approximately 75%, which is highly fertile for the region under study, especially for cows restricted to a 12-wk annual mating period. As shown in Observation lb, Bonsma’s technique could not even identify individuals with very low fertility. There was a slight trend for cows that received higher Bonsma scores to have higher weight per day of age at 27 mo, although there was no significant relationship to frame size in the initial observation. However, in Observation lb, heifers scored as subfertile matured to be 4% smaller than heifers which received the higher scores. The overall relationship between Bonsma scores and growth was weak, In a dry tropical environment, fatter cows have a lower risk of dying during a dry season or a drought (7). &cause cows are scored lower using Bonsma’s technique if they show obvious fat depots, Bonsma scores decreased with increasing level of fatness independently of fertility. This appears to be contrary to F3onsma’s objective of determining “functional efficiency” which should favor a low mortality risk. The lack of useful relationships between Eonsma scores and both the reproductive and growth parameters occurred despite high repeatability (0.7) of scoring. The ease with which experienced cattlemen learned the technique would have been a positive factor had the technique been effective. Cattlemen traditionally use various physical attributes as indicators of production potential rather than direct measurements or complex records. Although simple, accurate methods have been developed to directly monitor fertility, even in continuously-mated herds (5), no reliable method is available to predict lifetime performance prior to initial mating, other than the use of detailed records to estimate breeding values.

506

Theriogenology

Prior to this study, the cattlemen who carried out the assessments, as well as other proponents of the Bonsma technique, believed that the Bonsma criteria would rank heifers and cows on reproductive and growth potential. However, follow-up observations in this study convincingly demonstrated to them that this technique is not efficacious. Since visual assessment will remain an important component of selection and culling of breeding animals, criteria that reflect reliable relationships with economically-important traits should be used. Crister et al. (4) related a wide range of conformational traits, including some of those described by Bonsma (3), to several superovulatory response parameters in cows. The primary predictor variables were clitoris score, cervix score, head cleanness and correctness and rump cleanness. The R* values of predictive equations were low (34, 15 and 21% for ovarian size, number of corpora lutea and number of fertilized ova, respectively), thus being of little practical value. Biases due to lactation status and color occurred in scoring. Independently of reproductive records and body condition, lactating cows scored higher than nonlactating cows. The bias was clearly indicated where the early-weaned cows scored lower than other cows which had raised a calf in the same year and which were lactating at the time of assessment. Cattlemen traditionally prefer even coloring, especially red and grey, of Brahman cattle and their crosses. This was evident in our study, since the red and grey cows scored marginally higher than the brindle and black/brown cows. No reason could crosses which failed differences between likely due to random

be found for the lower scores for !4 Brahman cross cows than for $5 to raise a calf in the year of the study. The small but significant cows of different ages were probably not due to bias and were most variation.

The conclusion of this work is that the femininity factor expressed through conformational traits such as wedge-shaped outline, long slim neck, broad pelvis, even fat depots, short sleek hair, and thick pliable skin is not a useful predictor of the major production indices of weaning rate, growth, mortality risk and salvage value in well-managed Brahman cross cattle in the dry tropics. REFERENCES 1. 2. 3.

Anonymous. Cattle Breeds, Queensland. Australian Bureau of Statistics, Queensland Office, Brisbane, 1985. Bonsma JC. Wortham Lectures in Animal Science. Texas A&M University Press, College Station, 1956. Bonsma JC. Livestock Production. A Global Approach. Tafelberg Publishers, Capetown, 1980.

Theriogenology

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Crister JK, Gunsett FC, Rowe RF, Rutledge JJ, Ginther OJ. Femininity in cattle and sdperovulatory response. Theriogen 1979; 11:94 abstr. Fordyce G. Management of beef cattle for optimum fertility. Proceedings of the Australian Veterinary Association PANSIG Conference, Townsville, 20-26 May 1990. Fordyce G, Saithanoo S, Goddard ME. Factors affecting mature size and dry-seasons weight loss in Bos indicus cross cows in north Queensland. Aust J Agric Res 1988;39: 1169-l 180. Fordyce G, Tyler R, Anderson VJ. The effect of reproductive status, body condition and age of Bps indicus cross cows early in a drought on survival and subsequent reproductive performance. Aust J Exp Agric 1990;30:315-322. Fordyce G, James TA, Holroyd RG, Beaman NJ, Mayer RJ, O’Rourke PK. The performance of B&man-Shorthorn and Sahiwal-Shorthorn cattle in the dry tropics of northern Queensland. 3. Birth weights and growth to weaning. Aust J Exp Agric 1993;33: 119-127. Harvey WR. Least squares analysis of data with unequal subclass numbers. United States Department of Agriculture, Agricultural Research Service, No. ARS-20-8, 1960. Hetzel DJS, MacKinnon MJ, Dixon R, Entwistle KW. Fertility in a tropical beef herd divergently selected for pregnancy rate. Anim Prod 1989;49:73-81. Holroyd RG. Methods of investigating beef cattle infertility. In: Murray RM, Entwistle KW James Cook University Press, Townsville, (eds), Beef Cattle Production in the Tropics. 1978;233-246. The performance of Holroyd RG, James TA, Doogan VJ, Fordyce G, O’Rourke PK. Brahman-Shorthorn and Sahiwal-Shorthorn cattle in the dry tropics of northern Queensland. 1. Aust J Exp Agric Reproductive rates and liveweights of F, and backcross females. 1990;30:717-725. McGinley R, Casey JH. Analysis of progesterone in unextracted serum: a method using danazol [17a-pregn-4-en-20-yno(2,3-d)isoxazol-l7-o1], a blocker of steroid binding to proteins. Steroids 1979;33:127-138. Seifert GW, Bean KG, Christensen HR. Calving performance of reciprocally mated Africander and Brahman cattle in Belmont. Proc Aust Sot Anim Prod 1980;13:62-64. Silvey MW, Haydock KP. A note on live-weight adjustment for pregnancy in cows. Anim Prod 1978;27:113-116. Snedecor GW, Cochran WG. Statistical methods, 6th edition. Iowa State University Press, 1974. Turner HN, Young SSY. Quantitative genetics in sheep breeding. MacMillan, Melbourne, 1969. Weston ET, Harbison J, Leslie JK, Rosenthal KM, Mayer RJ. Assessment of the agricultural Agriculture Branch Technical Report No. 27, and pastoral potential of Queensland. Queensland Department of Primary Industries, Brisbane, Australia, 1981.