quality control in boar semen production by use of the facscount af system

Quality control in boar semen production by useof the FACSCount AF system

Preben Christensena,*, Dorte B. Knudsena,Henrik Wachmannb, Mads T. Madsenb

aSection for Reproduction, Department of Large Animal Sciences, Royal Veterinary and

Agricultural University, Dyrlaegevej 68, 1870 Frederiksberg C, DenmarkbThe National Committee for Pig Production, Danish Bacon and Meat Council,

Axelborg, Copenhagen, Denmark

Received 8 July 2003; received in revised form 6 January 2004; accepted 15 January 2004

Abstract

A simple and rapid flow cytometric method has recently been developed for simultaneous

determination of sperm concentration and viability in semen from domestic animals.1 Use of

SYBR-14TM in combination with propidium iodide (PI) allows estimation of the proportion of live

sperm (viability). An internal standard of fluorescent microspheres (beads) makes it possible to

determine the sperm concentration during the same analysis. In the first experiment, the relationship

between sperm viability and litter size was investigated. The second experiment explored whether a

smaller variation in the number of motile sperm per insemination dose could be obtained using the

FACSCount AF flow cytometer than using a spectrophotometer. Results in the first experiment show

that sperm viability is closer related to litter size than is the traditionally used motility parameter.

Although the flow cytometer is precise and objective, a limited effect on litter size should be

anticipated if ejaculates are selected for insemination according to the percentage of viable sperm.

However, the present trial used large insemination doses (2:3 � 109 motile sperm/dose) which

partially compensate for the differences in motility and viability between boars and ejaculates. In the

second experiment it was found that variation in the number of motile sperm per insemination dose

could be reduced significantly if the FACSCount AF flow cytometer rather than the Corning 254

spectrophotometer was used for determination of sperm concentration in the raw semen. It is

concluded that the FACSCount AF flow cytometer is a strong tool for improvement of the quality

control in artificial insemination (AI) centres.

# 2004 Elsevier Inc. All rights reserved.

Keywords: Spermatozoa; Quality; Insemination; Litter size; Flow cytometry

Theriogenology 62 (2004) 1218–1228

* Corresponding author. Tel.: þ45-35-28-29-70, fax: þ45-35-28-29-72.

E-mail address: [email protected] (P. Christensen).1 Patent Pending, Int. Publication Number WO/00/54026.

0093-691X/$ – see front matter # 2004 Elsevier Inc. All rights reserved.

doi:10.1016/j.theriogenology.2004.01.015

1. Introduction

Routine assessment of boar semen in an AI centre includes estimation of semen

volume, microscopic assessment of sperm motility and determination of sperm con-

centration. The three measures together are necessary for calculation of the number of

insemination doses which can be produced from an ejaculate. Inaccuracy or lack of

precision for one or more of the measures is likely to result in insemination doses with

too few sperm (and reduced fertility after insemination) or doses which contain too many

sperm (and loss of possible revenue for the AI centre). Determination of the volume can

be based on the weight of the ejaculate. If an electronic scale with increments of 1 g is

used, this procedure is objective, accurate and precise. In contrast, assessment of sperm

motility is a subjective judgement of the proportion of motile cells. In addition, this

procedure is not particular precise due to evaluation of a limited number of sperm

(approximately 200 per sample) which may differ individually with regard to type of

movement and velocity [1]. A more objective and precise assessment of sperm motility

can be achieved using a computer-assisted semen analyzer (CASA), but bias due to

program settings, and differences between systems, as well as the time required for the

analysis make this method unsuitable for routine work [2,3]. Assessment of sperm

viability has been used for research purposes such as evaluation of freezing protocols [4]

or to compare different extenders [5]. Recently, Juonala et al. [6] showed that sperm

viability for liquid boar semen stored for 7 days correlated significantly with non-return

rates and litter size. Several different protocols for assessment of sperm viability have

been reported during recent years and some include centrifugation or other steps which

are time-consuming. Garner et al. [7] were the first to use the viability dye combination

of SYBR-14 and PI where both stains target the DNA, staining is rapid and almost no

background staining occurs.

For individual raw ejaculates of boar semen, differences in the amount of gel particles or

debris (cytoplasmic droplets, bacteria) can result in a inaccurate determination of the sperm

concentration when a spectrophotometer is used [1]. For satisfactory results, periodic

calibration of spectrophotometers against a haemocytometer is necessary [8]. For routine

assessment of ejaculates or for quality control, the haemocytometer is too slow since

multiple measurements of each sample are necessary to achieve acceptable precision [9].

Electronic particle counters provide rapid determinations of sperm concentration, but tend

to include in the count any debris in the size range of sperm and gel particles in boar semen

may block the aperture of the system [9,10]. A novel method based on the use of flow

cytometry and staining of sperm DNA with SYBR-14 and PI has been tested against

haemocytometer and was shown to be highly accurate and precise for determination of

sperm concentration [11]. With this method, which has been developed for routine use in

an AI centre, the percentage of viable sperm is determined simultaneously with high

precision [12].

The objective of the present paper is to describe the relationship between flow

cytometric determination of boar sperm viability and fertility after insemination, as

well as to investigate if flow cytometric determination of sperm concentration also could

result in production of more uniform insemination doses than possible with a spectro-

photometer.

P. Christensen et al. / Theriogenology 62 (2004) 1218–1228 1219

2. Materials and methods

2.1. Preparation of counting tubes

Sealed polyethylene counting tubes were provided by BD Biosciences Immunocyto-

metry Systems (San Jose, CA, USA). Each counting tube contains 400 mL of FACSCount

diluent with a predetermined number of fluorescent microspheres (beads). Prior to use,

tubes were vortexed 5 s in upright position and 5 s inverted. After opening and addition of

dyes, tubes were capped and vortexed briefly (<2 s) in upright position.

2.2. Semen dilution

Dilution of semen is necessary to achieve an appropriate ratio between sperm and beads.

Dilutions were in EDTA extender (glucosemonohydrate 302.7 mM, Na3Citrate 12.6 mM,

NaHCO3 14.3 mM, Na2EDTA, 2H2O 10 mM, pH 7.2 [13]). Raw semen was diluted 1:100

and insemination doses (Experiment 2) were diluted 1:10.

2.3. Fluorescent staining

SYBR-14 and PI (Molecular Probes, Eugene, OR) were dissolved respectively in

anhydrous DMSO (4 mM) or distilled water (1 mM). Aliquots of the two working solutions

were mixed to the appropriate concentration and 10 mL were added per counting tube,

resulting in a final concentration of 50 nM SYBR-14 and 12 mM PI. Prepared counting

tubes generally were used within 3 weeks. After dilution of the semen (see above), 40 mL of

the diluted semen were added to a prepared counting tube using a Finn Pipette (Labsys-

tems, Helsinki, Finland). The counting tube was vortexed briefly (<2 s) and incubated at

room temperature. After 4–5 min, the counting tube was vortexed briefly and subjected to

flow cytometric analysis.

In Experiment 2, the dye solution included in the Sperm Counting Reagent (BD

Biosciences Immunocytometry Systems) was used. To each counting tube, 20 mL of this

solution was added and resulted in the same concentrations of SYBR-14 and PI as

mentioned above. Addition of the diluted samples to counting tubes was made more

consistent by use of the electronic FACSCount pipette which dispenses 50 mL by reverse

pipetting (an excess of fluid is taken up automatically by the pipette and only 50 mL is

dispensed). In Experiment 2, all counting tubes were prepared less than 12 h prior to use.

2.4. Flow cytometry and attractor analysis

Analyses were performed on modified FACSCount flow cytometers with a fiber-coupled

488 nm external laser. This instrument collects two parameters of fluorescence and one

parameter of size data for each event. Emission signals were separated by a 620 short pass

dichroic mirror. The green fluorescence was collected through 515–545 nm a band pass

filter and the red fluorescence was collected through a 645 nm long pass filter. Data were

collected into 256 channels with logarithmic amplification covering four decades and

compensation was not used. In Experiment 1, analysis of quantitative data was performed

1220 P. Christensen et al. / Theriogenology 62 (2004) 1218–1228

on a Macintosh Quadra 650 computer using Attractors SoftwareTM (BD Biosciences

Immunocytometry Systems). In Experiment 2, the AF version of the FACSCount flow

cytometer was used. This flow cytometer performs the Attractors analysis as an automated

step in the data processing and results for sperm concentration and viability are presented

on a print-out.

2.5. Experimental design

2.5.1. Experiment 1: boar fertility trial

To assess the relation between boar semen quality and fertility, a field trial was

performed from June 1999 to June 2000. A total of 1648 ejaculates were collected from

170 Landrace and Yorkshire boars in two Danish AI centres. Semen volume was

determined from the weight of the ejaculates, and sperm concentration was determined

using a Corning 254 spectrophotometer (Sherwood Scientific Ltd, Manchester, UK). A

0.25 mL sample of the raw semen was diluted 1:40 in EDTA extender. The density of the

dilution was determined by the spectrophotometer and the result was read from a

calibration curve. Sperm motility was assessed microscopically under phase contrast

using 200� magnification. All ejaculates were subsequently diluted with EDTA extender

and insemination doses containing approximately 2:3 � 109 motile sperm were produced.

Flow cytometric analyses were performed by four technicians in two AI centres using the

modified FACSCount flow cytometers as described above. For practical reasons, dyes were

added to counting tubes up to 2–3 weeks prior to use at the Royal Veterinary and

Agricultural University (RVAU) and were transported to the two laboratories. All analyses

of flow cytometric data with Attractors SoftwareTM were performed at RVAU.

During edition of data, ejaculates without measurements by both spectrophotometer and

flow cytometer was excluded. Ejaculates where an outlier was observed for the flow

cytometric determination of sperm concentration and ejaculates with a sperm viability

below 75% or above 95% was removed from the data set to avoid that ‘extreme’ values

affected the statistical analyses. The editing procedure reduced the data set to 1246

ejaculates from 150 boars (70 Landrace and 80 Yorkshire boars). After experimental

inseminations, a total of 7786 litters were recorded from Landrace or Yorkshire gilts or

sows in Danish breeding herds. Return to service was recorded for 1883 sows/gilts. Effects

of the semen parameters on litter size were estimated in a mixed model using the race of the

sow and boar, the age of the insemination dose (production date to insemination date), the

previous number of litters for the sow and the calculated fertility-level of the sow as

systematic effects. The effect of boar and ejaculate were included in the model as random

effects. A bivariate analysis was performed to estimate the correlation between sperm

viability and litter size. Random effects of boar and ejaculate (nested within boar) on the

two traits were assumed to be correlated whereas residuals of the two traits were assumed

to be independent.

2.5.2. Experiment 2: production of insemination doses

2A: A small experiment was carried out to identify if the number of sperm per dose was

related to individual ejaculates (due to over- or underestimation of sperm concentration by

the spectrophotometer) or if the variation mainly was between doses within ejaculate


(random error in the filling of insemination doses). Sperm concentration in the raw semen

was determined with the Corning 254 spectrophotometer as described in Experiment 1, and

after motility assessments, semen was diluted in order to pack approximately 2:3 � 109

motile sperm in a insemination dose (approximate volume 81 mL). During the packing

procedure, one insemination dose was collected in the start, the middle and the end of the

packing procedure for each ejaculate. The content of the insemination doses were

determined on an electronic scales and the sperm concentration was determined with

the FACSCount AF flow cytometer after 1:10 dilution in EDTA extender. Fifty microliters

of the dilution was transferred to a counting tube using an electronic FACSCount pipette.

After a staining of 4–5 min, analysis was performed and the flow cytometer subsequently

printed the result. After calculation of the total number of motile sperm per dose, the results

were subjected to analysis of variance.

2B: This experiment was carried out over five days. Production of insemination doses

from 50 randomly selected ejaculates were based on assessment of sperm concentration

using the Corning 254 spectrophotometer as well as on determinations by the FACSCount

AF flow cytometer. Measurements for the spectrophotometer and microscopic assessment

of sperm motility were identical to Experiment 1. For flow cytometric analysis, the raw

semen was diluted 1:100 in EDTA extender while the remaining procedure was performed

as described in Experiment 2A. All the insemination doses produced according each of the

two methods (spectrophotometer and flow cytometer) were aimed at containing 2:3 � 109

motile sperm. Examination of insemination doses were identical to Experiment 2A. For a

random selection of 25 ejaculates, assessment of sperm concentration in the insemination

doses were also performed by microscopic counting using a Burker–Turk haemocytometer.

Samples from the insemination doses were diluted 1:20 in 5% (w/v) sodium chloride in

distilled water. From the diluted samples, two aliquots of 7 mL were withdrawn with a

FinnPipette (Labsystems, Helsinki, Finland) to fill the two counting areas of the Burker–

Turk haemocytometer. The filling procedure was always performed after the coverslip was

applied and fixed by the two clips. After approximately 1 to 2 min, the counting was carried

out using phase-contrast microscopy at 200� magnification. In each side of the haemo-

cytometer, 10 squares of 0:2 mm � 0:2 mm were counted. The counting procedure was

performed by two technicians in random order.

3. Results

3.1. Experiment 1: boar fertility study

The breed of the boar appeared to have a systematic effect on litter size and the estimate

was 0.66 piglets per litter higher for Landrace versus Yorkshire (P < 0:0001). A similar

effect was observed for the sows with an estimate of 0.87 piglets per litter higher for

Landrace versus Yorkshire (P < 0:0001). Litter size appeared to decrease with increasing

age of the insemination dose and when insemination doses used within 24 h semen

collection were compared against those used from 24 to 72 h, this effect was estimated to

0.69 piglets per litter (P < 0:0001). The previous number of litters for the sow significantly

affected the total number of piglets born. When gilts were compared with sows which were


having their third litter, the litter size was estimated to be 1.78 piglets higher for the sows

(P < 0:0001). A significant effect on litter size (0.43) was also observed for the two periods

of the trial, P < 0:0001 (the first half versus second half of the experiment). SUBFGK

(calculated fertility level for the sows) was also positively associated with the total number

of piglets per litter (estimate 1.21; P < 0:0001).

The random effects on litter size are shown in Table 1. It is shown that approximately

92.6% of the total variation was residual while 1.9% of the variation was due to herd

effects. Boars accounted for 3.5% of the variation in litter size (P < 0:0001) while

ejaculate variation explained the remaining 2.0% of the variation (P ¼ 0:0007). The

relationship between litter size and sperm motility was estimated to 0.021 piglet/%motility,

but this effect was only marginally significant (P ¼ 0:08). In contrast, the relationship

between litter size and flow cytometric assessment of sperm viability was found to be

significant (P ¼ 0:002) and was estimated to 0.037 piglet/%viability. The effect of sperm

viability or sperm motility on return to service was not significant (P > 0:05).

Bivariate analysis of the correlation between sperm viability and litter size are shown in

Table 2. The correlation (r) at boar level was 0.28 (95% confidence interval: 0.11–0.44)

while the correlation on ejaculate level was 0.24 (95% confidence interval: 0.11–0.37).

Bivariate analysis was not performed for the motility parameter. Expected increase in litter

size was calculated from the correlations and the amount of the proportion of the variation

explained by boar and ejaculate (Table 3). It appears that the average litter size would

increase to respectively 12.70, 12.71 and 12.74 with rejection of the 5, 10 and 20

percentage of ejaculates with poorest sperm viability. Rejection values were not calculated

for the motility parameter but if all ejaculates with motility below 90% are rejected (this

represents 18% of the ejaculates), the average litter size would be 12.78 (standard error for

this estimate was 3.49).

Table 1

Sources of variation with random effect on litter size

Random effects S.D.a Percentage of total variation in litter size

Boar 0.64 3.5

Ejaculate 0.49 2.0

Herd 0.47 1.9

Residual variation 3.29 92.6

Total variation 3.41 100

Standard deviation (S.D.) for the different effects are shown as well as the percentage of the total variation.a The unit for S.D. is piglet per litter.

Table 2

Estimated correlation and 95% confidence interval for the correlation between sperm viability assessed with the

FACSCount AF flow cytometer and the total number of piglets per litter

Effect Estimated correlation (r) 95% confidence interval

Boar 0.28 0.11–0.44

Ejaculate 0.24 0.11–0.37

Estimates are based on 7786 litters.


3.2. Experiment 2: production of insemination doses

Experiment 2A showed that 95.7% of the total variation in the number of motile sperm

per dose was related to the ejaculate and that the remaining 4.3% of the variation was

random. No significant difference in the number of motile sperm per dose was observed

between insemination doses from the start, the middle or the end of the packing procedure

for an ejaculate (P ¼ 0:20).

Results of Experiment 2B are summarized in Table 4. It appears that a small and

marginally significant difference in the average number of motile sperm was observed

between insemination doses packed according to spectrophotometer versus flow cyto-

metry. The standard deviations for insemination doses packed according to the spectro-

photometer were respectively 0:61 � 109 and 0:55 � 109 when sperm concentrations in the

insemination doses were determined by haemocytometer and flow cytometer. In compar-

ison, standard deviations were significantly lower when sperm concentration in the raw

semen was determined by the flow cytometer (P < 0:0001, standard deviations respec-

tively 0:22 � 109 and 0:14 � 109 for assessment of doses by haemocytometer and flow

Table 3

Rejection of the poorest ejaculates according to determination of sperm viability with the FACSCount AF flow

cytometer

Percentage of rejected ejaculates Calculated litter size for

Semen below threshold Semen above threshold

5 12.22 � 3.69 12.70 � 3.53

10 12.36 � 3.59 12.71 � 3.54

20 12.40 � 3.70 12.74 � 3.51

Calculated values for litter size are based on 7786 litters born after experimental inseminations (average litter

size 12.68 piglets per litter). For each threshold, average litter size are calculated for the ‘rejected ejaculates’

(semen below threshold) and for semen that would be used for inseminations (semen above threshold). The total

number of piglets per litter expressed as mean � S:D.

Table 4

Production of insemination doses after determination of sperm concentration in raw semen by the Corning 254

spectrophotometer and the FACSCount AF flow cytometer

Assessment of insemination doses by Determination of sperm concentration in raw semen by

Corning 254 FACSCount AF

FACSCount AFa 2.51 � 0.55 2.36 � 0.14

Haemocytometerb 2.46 � 0.61 2.23 � 0.22

Concentrations of sperm in the insemination doses were determined by the FACSCount AF (N ¼ 50) and

microscopic counting in a Burker–Turk haemocytometer (N ¼ 25). Numbers indicate motile sperm (�109) in

the doses as mean � S:D:a Means in the row do not differ significantly (P ¼ 0:07) while standard deviations differ significantly

(P < 0:0001).b Means in the row do not differ significantly (P ¼ 0:11) while standard deviations differ significantly

(P < 0:0001).


cytometer). The variation in the number of motile sperm per dose was 1:30 � 109 to

3:99 � 109 for spectrophotometer and 1:75 � 109 to 2:62 � 109 for flow cytometer.

4. Discussion

The total number of piglets born per litter was affected by several systematic and

random effects. The systematic effects include the breed of the boar and the sow. The age

of the insemination dose (<24 h versus 24 to 72 h) appeared to affect the litter size.

However, this observation could be biased since most experimental semen collections

were carried out on Sundays and Mondays. In Danish pig production, most sows are

weaned on Thursdays and would thus be inseminated the following Monday or Tuesday. It

is possible that sows inseminated on Wednesdays or later during the week represent a

group of animals with a higher frequency of reproductive disorders. Lower litter size for

semen collected on a Monday and used on a Wednesday or Thursday could thus be related

to both aging of the semen as well as poor reproductive health of the inseminated sows and

gilts. The previous number of litters born by the sow affected the litter size significantly

(P < 0:0001). The calculated fertility level for the sow (SUBFGK) was significantly

(P < 0:0001) higher than the expected value of 1.0. It is not clear if this is related to the

unballanced nature of this field trial or, if SUBFGK for some sows included the data from

the experimental litter. Since SUBFGK is updated weekly for all sows in Danish breeding

herds and old data is overwritten, it has not been possible to establish if all values for

SUBFGK are correct. A significantly (P < 0:0001) higher litter size was recorded in the

second half of the trial versus the first half of the trial. Apart from the different time periods

of the year (autumn versus spring) and genetic improvement, the reason for this

discrepancy is unclear. The random effects on litter size included the boar, the ejaculate,

herd effects as well as residual variation. The majority of the variation in litter size (94.5%,

Table 1) was explained by herd effects and residual variation. This is in agreement with our

recent trial with bull semen where it was observed that more than 99% of the total variation

was herd related or residual variation [14]. Also in agreement with the observations in the

bull semen field trial, the variation in fertility from one ejaculate to another within boar

was almost of the same magnitude as the variation between boars. Analysis of the 5.5% of

the variation in fertility explained by boar and ejaculate against the observed variations in

sperm viability for the 1246 ejaculates was carried out in a bivariate model [15]. The

correlation between sperm viability and litter size was respectively 0.28 at boar level and

0.24 on ejaculate level (Table 2). A bivariate analysis was not carried out for the motility

parameter and this parameter was only analyzed against the data for litter size in a mixed

model which included all random and systematic effects. Results of this analysis showed

that motility was marginally associated with litter size (estimate 0.021 piglet/%motility,

P ¼ 0:08) while a better relationship was observed for the viability parameter (estimate

0.037 piglet/%viability, P ¼ 0:002). Fertility studies with boar semen have often been

carried out on a limited scale due to the expenses and logistics involved in a major study

[16]. The relationship between sperm viability and litter size have recently been

investigated by Juonala and co-workers [6,17] who conducted a study with 106 AI boars

(23,972 first inseminations and 12,725 litters) and three methods for identification of


viable sperm. In the study by Juonala and co-workers [6,17] average values for sperm

viability and litter size were based on several ejaculates and semen evaluation was carried

out after 7 days of storage. Evaluation of semen after storage and obtaining data from

several ejaculates is an acceptable strategy if the aim only is to exclude some boars from

the breeding program. However, as indicated in Table 1, a significant amount of the

variation was caused by the quality of the individual ejaculates. If the aim is to assess

screen boars as well as individual ejaculates, a rapid, precise and objective method such as

flow cytometry is necessary in order to implement the technique in the routine work in an

AI centre.

The present insemination trial with boar semen and our recent trial with bull semen [14]

shows that the effect on the individual male and ejaculate on the overall fertility is limited

and that the major part of the variation is residual (Table 1). In addition, the correlation

between the observed fertility and sperm viability as well as motility appeared to be low

(Table 2) [14]. These observations are probably the result of the use of large insemination

doses (bull: 15 � 106 motile sperm/dose, boar 2:3 � 109 motile sperm/dose) which

compensates for most of the difference in semen quality (viability and motility) between

males and ejaculates [18]. Amann and Hammerstedt [19] stated that the number of sperm

per dose should be decreased in fertility trials in order to have more males with a relatively

low fertility and to provide the best possible basis for testing a diagnostic sperm assay. In

the present and our recent trial [14], reduction of the number of sperm per dose was not

possible, since this would require a consent from the participating farmers and possibly a

financial compensation. Decuadro-Hansen et al. [20] performed a low-dose trial (2.5 to

7:5 � 106 motile sperm/dose) to test the FACSCount AF flow cytometer on frozen semen

from top-bulls and observed correlations of respectively 0.49 and 0.83 between sperm

motility and sperm viability against non-return rates. The correlations reported by

Decuadro-Hansen et al. [20] are higher than in the recent trial with bull semen [14],

and it appears likely that a low-dose insemination trial with boar semen also would lead to

higher correlations than observed in the present study. The relatively low correlations

shown in Table 2 indicate that the impact of sperm viability on litter size is low when a

insemination dose of 2:3 � 109 motile sperm/dose is used. Calculation of the potential

increase in litter size by rejection of the poorest semen according to the viability parameter

is shown in Table 3. If, the 10% poorest ejaculates were rejected, the average litter size

would increase from 12.68 to 12.71. If used for inseminations, the average litter size for the

rejected ejaculates would be 12.36 and 0.32 piglets per litter lower than the average before

selection. Since only 10% of the ejaculates are rejected, the average for the remaining 90%

of the population will increase only 0.03 piglet per litter. It should be kept in mind that boar

and ejaculate effects only account for 5.5% of the variation in litter size when large

insemination doses are used. This limits the potential effect of semen rejection even for the

ideal method for assessment of semen quality with a correlation of 1.0. Rejection of the

poorest 10 or 20% of the ejaculates according to such a method (or combination of

methods) would only result in an increase in average litter size of respectively 0.15 and

0.28 piglets per litter. Although other methods such as the sperm chromatin structure assay

[21] appear to be able to detect uncompensable sperm defects, 92.6% of the total variation

would still be residual when large insemination doses are used and would be unaffected by

selection of the ejaculates.


In the present field trial, the variation in the flow cytometric determination of sperm

concentration was very high (CV was from 8 to 10%). Due to this high variation it was not

possible to establish if the number of viable sperm in the insemination doses had effect on

the observed fertility. Analysis of data from the flow cytometric analyses by the Attractors

Software was not performed in the two participating AI centres but RVAU, and during the

trial it was very difficult to identify the causes of the high variation. Accurate and precise

pipetting of samples as well as appropriate mixing of counting tubes have previously been

identified as a problem when beads are used for determination of sperm concentration [9].

After the field trial, we observed that addition of dyes to the counting tubes more than 12 h

prior to analysis could affect the precision in the determination of sperm concentration while

the precision in assessment of sperm viability is unchanged (Christensen, unpublished data).

It is possible that the dyes may cause the beads to stick together or to the inner sides of the

counting tube. When dyes are added to the counting tubes less than 12 h prior to analysis, the

coefficient of variation in the determination of sperm concentration generally is below 3.5%.

Experiment 2 was carried out to show if the FACSCount AF flow cytometer could be

used for production of insemination doses with a more uniform number of viable sperm

than possible with the spectrophotometer. Experiment 2A showed that 95.7% of the total

variation in the number of sperm per insemination dose was caused by ejaculate and that

the remaining variation was random. In Experiment 2B, insemination doses packed

according to determination of sperm concentration in the raw semen with FACSCount

AF flow cytometer and Corning 254 spectrophotometer resulted respectively

2:36 � 109 � 0:14 � 109 and 2:51 � 109 � 0:55 � 109 motile sperm per dose (Table 4).

The difference in the average number of motile sperm per dose was not statistically

different for the two methods (P > 0:05), but the standard deviation for the FACSCount AF

flow cytometer was significantly smaller than for the spectrophotometer (P < 0:0001). For

50% of the ejaculates, sperm count in the insemination doses were confirmed by

microscopic counting using a Burker–Turk haemocytometer. These results confirm the

results of the flow cytometric analyses of the insemination doses. The variation in the

number of motile sperm per dose ranged from 1.30 to 3:99 � 109 for the spectrophot-

ometer, but was only from 1.75 to 2:62 � 109 for the FACSCount AF flow cytometer.

Based on the results presented in the above we conclude that the FACSCount AF flow

cytometer can be used to improve the quality control in AI centres for boars. When a high

number of sperm is packed in each insemination dose, the effect of selecting the best

ejaculates according to the sperm viability in the raw semen appears to be limited.

However, this parameter may be of high significance in combination with low dose

inseminations. The FACSCount AF flow cytometer also determines sperm concentration

accurately and precisely. In comparison to spectrophotometers, the variation in the number

of sperm per insemination dose can be reduced significantly by use of the FACSCount AF

flow cytometer.

Acknowledgements

This work was supported by Danish AI societies for cattle and pigs and by The Danish

Directorate for Development (grants no. 93S-2465-A97-0705 and 93S-2465-A00-01120).


BD Biosciences Immunocytometry Systems is thanked for making flow cytometers for

these experiments available and for technical support.

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quality control in boar semen production by use of the facscount af system

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