Livestock Research for Rural Development 26 (6) 2014 Guide for preparation of papers LRRD Newsletter

Citation of this paper

Body parameters and prediction of body weight from linear body measurements in Coturnix quail

D Gambo, O M Momoh, N I Dim and A S Kosshak

Department of Animal Breeding and Physiology, College of Animal Science, University of Agriculture, Makurdi, Benue State, Nigeria
gambodauda21@gmail.com

Abstract

A study was conducted using one hundred and sixty nine day-old Japanese quail chicks to measure linear body parameters as well as to predict body weight from linear body measurements. Linear body measurements of shank length, breast girth, body length and wing length as well as body weight of each quail chick were measured on weekly basis until maturity at six weeks. The data obtained were subjected to analysis of variance and simple linear regression analysis using the restricted maximum likelihood (REML) procedure of SPSS Statistical software.

Shank length, breast girth, body length and wing length increased with age until maturity (week 6). Shank length demonstrated the highest coefficient of variation (CV %) at all stages except week 1 where wing length showed the highest CV (%). Shank length had the highest CV in week 2 but gradually reduced with age to a value of 43.6% at week 6. For breast girth, body and wing lengths, highest CV (%) occurred at week 1 and thereafter respectively decreased with age until week 6 (maturity). Estimates of coefficient of determination showed that shank length, which had highest value of R2 =0.84 and lowest variance inflation factor (VIF) value of 1.00, is the best single predictor of body weight. The predictive equation showed that body weight in Japanese quail is linearly related to body measurements especially shank length. It was concluded that body weight prediction in Japanese quail from linear body measurements is feasible using simple linear regression techniques. It is also possible for the breeder to use these easily measured parts as criteria for assessment and early selection for body weight.

Keywords: brooding, coefficient, guinea savannah, incubation, regression, variation


Introduction

It has been reported by FAO (1991) that the daily protein intake in many developing countries is still far below the recommended level of 67 g per head per day of which 58% must be of animal origin. Nigerians consume only 5.5 g of animal protein per person per day against 38.9 g per person per day recommended by FAO (1991). Protein intake, particularly of animal origin below recommended level has adverse consequences on health, productivity and development of the human being especially children, aged and pregnant women who are most susceptible to health challenges due to low protein intake.

Diversification into production of livestock species such as quail with short generation interval could be a viable option in ameliorating shortage of protein among the populace in developing countries (NVRI 1994; Muthukumar and Dev Roy 2005). Japanese quail is one of the poultry types with very short generation interval.

Quail farming serves as a form of alternate poultry production in many nations and is gaining attention from the farmers, entrepreneurs, and researchers. It is used for food, game, pet and also for research purposes (Muthukumar and Dev Roy 2005). Its consumption may be preferred by all, as it has no religious taboo. It has good nutritive value, amazing taste, gamy flavour, tender meat that are delicious with low caloric value and high dry matter. It is rich in protein, vitamins, essential amino acids, saturated fatty acids, unsaturated fatty acids and phospholipids (Muthukumar and Dev Roy 2005).

In view of the importance of this small stock, it is necessary to initiate improvement programs that can genetically improve the birds for efficient and effective productivity. Relationship existing among body traits (Oke et al 2004) provides useful information on the performance, productivity and carcass characteristics in animals. Most of the body linear measurements reflect primarily the length of the long bones of the animal and when taken sequentially over a period of time, they generally indicate the way in which the animal body is changing shape and have been useful as predictors of live weight and carcass composition (Oke et al 2004). Additionally, relationship between body weight and linear body measurements are important not only in predicting body weight but also useful in genetic improvement strategies.

In an organized livestock marketing system, weight is normally taken to determine the market prices of animals. This would normally require the use of weighing scales which, quite often may not be available to the rural livestock farmer/traders. Indirect methods of assessing body weights in animals without recourse to the use of weighing scales do exist such as the use of body measurements to predict body weight. A lot of works have been done in this regard in larger animals, particularly cattle, sheep and goats (Nwosu et al 1985; Attah et al 2004; Sowande and Sobola, 2008; Goe 2007). Few works have reported the use of linear body measurements to predict body weights in chickens (Gueye et al 1998; Momoh and Kershima 2008). In view of the small size of the quail bird with attendant consequence of difficulty in handling for taking body measurements, it is desired to examine the possibility of using body measurements to predict body weight as it has been done in other poultry types

The objective of the study was to examine progressive changes in linear body measurement with age as well as to predict body weight from linear body parameters in Japanese quail. The information to be gained in the study would be helpful especially in planning future breeding programmes and genetic improvement strategies.


Materials and methods

The experiment was carried out at Mundi’s Farm behind Livestock Teaching and Research Farm of the Faculty of Agriculture, Nasarawa State University Lafia, Nasarawa State, Nigeria. Nasarawa State falls within the Southern Guinea Savannah zone of Nigeria. The state lies between latitude 7 and 9 North and Longitude 7 and 10 East.

It has a climate typical of the tropical zone because of its location. It has a temperature ranging from 25C in October to 36C in March while monthly rainfall varies from 13.73 cm in some places to 14cm in others (Nasarawa State Ministry of Information 2006).

Experimental birds and their management

The base population (30 females and 10 males) of the Japanese quails for this experiment were procured at three weeks of age from a private farm in Tudun Amba, Lafia, Nasarawa State, which originally, was part of the procured parent stocks from the random bred Japanese quail population of the National Veterinary Research Institute (NVRI), Vom in Plateau State. This base population was housed in the same pen for two weeks for the purpose of acclimatization. However, the males were separated from the females when the quails were five weeks old to avoid indiscriminate mating. At the 6 th week of age, they were randomized into 10 breeding cages in the rearing house. A mating ratio of 1:3 (i.e. 1 cock to 3 hens) was used. Each breeding cage had a dimension of 47(length) x 40(width) x 36(height) cm as recommended by Daikwo (2011). The birds were fed formulated diets containing 18% crude protein and 2700 kcal/kg metabolizable energy as recommended by Dafwang (2006). Feed and water were provided ad libitum. Eggs for hatching were collected when the birds were at least 9 weeks of age. This is because higher rates of fertility and hatchability of Japanese quail eggs are achieved between 9 - 19 weeks of age (Daikwo 2011).

The eggs were accumulated for 6 days being held in egg crates under room temperature with good ventilation. At the end of 6 days of egg collection, the eggs were set for hatching in an automatic electric incubator. A total of 169 chicks were hatched and used for the study.

On hatching, chicks were weighed individually and were then taken to brooding room for brooding. The brooding house and experimental pens were thoroughly cleaned, scrubbed and disinfected using a disinfectant (Izal) and allowed to dry for two weeks before the arrival of the chicks. The brooding was carried out for a period of 21 days using stoves or electric bulbs as sources of heat and illumination. Wood shavings were used as litter materials. These were spread at a sufficient depth (5cm); and chicks guards were put in place to discourage chicks staying away from the heat sources. Feeders and drinkers were arranged to facilitate easy feeding both within and outside the brooder box. Stone pebbles were placed within the drinkers to discourage drowning and were removed after 2 weeks when the chicks have passed the stage when they can easily be drowned.

The quail chicks were brooded at a temperature of 35⁰C with adequate drinker and feeder spaces provided. Light was provided for 24 hours during brooding to avoid pilling and death. The temperature was reduced gradually at the rate of 3.50c on weekly basis as brooding progressed.

The chick’s phase of the study lasted for 3 weeks (21 days). During this phase, the birds were fed formulated chick mash which contained 24% crude protein (CP) and 2800Kcal/kg metabolizable energy. After the chick phase was the grower’s phase which lasted for another three weeks and the birds were fed growers mash containing 21% CP and 3000 kcal/kg metabolizable energy.

Though quail is known to be resistant to most viral diseases of poultry, anti-stress (vitalyte), antibiotics and coccidiostat were administered through water at various times to check against possible disease outbreak. Also, good hygiene, cleanliness and bio-security measures were ensured throughout the experimental period.

Measurement of traits

The linear body measurements such as body length, shank length, wing lengths and breast girth were measured at week 1, 2, 3, 4, 5 and 6 using measuring tape. Body weights were taken at hatch, week 1, 2, 3, 4, 5 and 6 using sensitive electronic scale.

Data analysis

Data collected were subjected to analysis of variance using the restricted maximum likelihood (REML) procedure of SPSS Statistical software (2011). The linear model fitted to the data is as shown below:

Yij = + +Ai +Eij

Where Yij =Single observation.

= Overall mean (constant).

Ai= Fixed effect of age

Eij = Random residual error

A simple linear regression was used to obtain equations for predicting body weight from the various linear body measurements.


Results

It was evident that shank length, breast girth, body length and wing length increased with age (Table 1). The coefficient of variation in shank length presented an interesting trend. It was highest in week 2 but gradually reduced with age to week 6. For wing lengths, breast girth and body length, highest CV values occurred at week 1 and also decreased to week 6 (maturity).

The effects of age on body weight and linear body measurements of Japanese quail are presented in Table 2. The coefficient of determination for prediction of body weight was highest for shank length, followed by wing length, breast girth and body length in that order (Table 3). Generally, coefficient of determination (R2) increased with decreasing variance inflation factor (VIF).

Table 1. Summary statistics of linear body measurement (cm) of Japanese quails reared in southern guinea savannah zone of Nigeria (n =169)

Age/Parameters

Mean

Min.

Max.

Range

Var.

SD

SEM

CV (%)

wk1 sl

1.39

1.00

1.90

0.90

0.38

0.62

0.14

44.63

bg

2.15

1.40

3.40

2.00

0.46

0.68

0.06

31.72

bl

5.78

4.50

9.00

4.50

3.11

1.76

0.15

30.46

wl

3.28

2.20

4.80

2.60

3.19

1.79

0.15

54.38

wk2 sl

2.19

1.80

2.60

0.80

2.90

1.70

0.15

77.75

bg

3.10

2.30

4.30

2.00

0.53

0.73

0.06

23.51

bl

9.24

6.80

12.30

5.50

3.52

1.88

0.16

20.30

wl

7.41

3.60

9.90

6.30

3.60

1.90

0.16

25.61

wk3 sl

2.50

2.00

3.10

1.10

2.86

1.69

0.15

67.49

bg

4.34

3.00

5.40

2.40

0.53

0.73

0.06

16.79

bl

11.49

7.60

14.50

6.90

3.47

1.86

0.16

16.22

wl

9.90

4.20

12.70

8.50

3.60

1.90

0.16

19.16

wk4 sl

2.91

2.20

3.50

1.30

2.90

1.70

0.15

58.43

bg

5.38

3.80

7.00

3.20

0.55

0.74

0.06

13.78

bl

14.50

10.00

18.00

8.00

3.52

1.88

0.16

12.93

wl

12.37

7.00

15.30

8.30

3.65

1.91

0.17

15.44

wk5 sl

3.21

2.70

3.70

1.00

2.93

1.71

0.15

53.32

bg

5.81

4.20

7.00

2.80

0.51

0.71

0.07

12.25

bl

16.84

12.80

19.00

6.20

3.55

1.88

0.16

11.19

wl

13.80

10.00

17.50

7.50

3.68

1.92

0.17

13.90

wk6 sl

3.93

2.90

3.70

0.80

2.93

1.71

0.15

43.57

bg

6.51

5.30

7.60

2.30

0.51

0.71

0.07

10.94

bl

17.99

14.60

20.50

5.90

3.55

1.88

0.16

10.47

wl

15.00

11.00

17.90

6.90

3.68

1.92

0.17

12.79

wk= week, SL= shank length, BG= breast girth, BL= body length, WL= wing length, Var. =variance, SD=standard error of the mean, SD= standard deviation, CV=coefficient of variation.n= number of observations.


Table 2. Effects of age on body weight and linear body measurement of Japanese quail (n= 169)

Age (weeks)

BW

SL

BG

BL

WL

Hatch

5.741.10a

ND

ND

ND

ND

1

10.91.10b

1.390.14a

2.150.06a

5.780.15a

3.280.15a

2

23.71.18c

2.190.15b

3.100.06b

9.240.16b

7.410.16b

3

34.71.18d

2.500.15b

4.340.06c

11.50.16c

9.900.16c

4

54.51.19e

2.910.15c

5.380.06d

14.50.16d

12.40.17d

5

76.11.20f

3.210.15c

5.810.07e

16.80.16e

13.80.17e

6

89.81.20g

3.930.15d

6.510.07f

18.00.16f

15.00.17f

BW= body weight, BL=body length, WL= wing length, SL= shank length and BG= breast girth, ND= not determine. n= no. of observations
abc
Means in the same row without common letter are different at P<0.05


Table 3. Regression equation and coefficient of determination (R2) for prediction of body weight from linear body measurements in Japanese quails

Regression Equation

SE

R2

VIF

BW=40.9+1.96bl

2.13

0.36

2.10

BW=40.9+3.980bg

4.36

0.36

1.70

BW=40.9-0.837wl

1.72

0.63

1.30

BW=40.9+0.112sl

0.55

0.84

1.00

BW= body weight, BL= body length, WL= wing length, BG= breast girth, SL = shank length, SE = standard error of the coefficient,
R2= coefficient of determination, VIF= variance inflation factor.


Discussion

Among the linear body measurements, shank length demonstrated the greatest variability at all ages except week 1. The high variability observed in shank length could be used for breed/strain characterization. The shank length values obtained at different ages in the present study agreed with findings of Adeogun and Adeoye (2004) who reported 1.47, 1.76, 2.18, 2.67, 3.05, 3.35 and 3.36 cm as average shank length of Japanese quail at hatch, 1, 2, 3, 4, 5, 6 and 7 weeks of age, respectively. Age had very highly significant effects on all linear body parameters as similarly reported by Daikwo (2011). Increase in body weight and most linear body measurements with age is expected as such changes are indicative of growth and development. Reported values for linear body measurements of quails are very scanty in literature as compared to other poultry types such as the chicken. This might be due to some practical problems associated with measurement of the traits such as the small size of the bird and the need for careful handling of birds to measure these traits.

Body weight prediction from linear body measurements

Shank length with the highest value of coefficient of determination (R2) and lower variance inflation factor (VIF) among the linear body parameters indicates that it is the best single predictor of body weight than the other body measurements in Japanese quail. Anebi (2010) had earlier reported a similar finding, although in the domestic pigeon, that shank length was the best predictor of body weight as compared with other body measurements. Bokhari (2002) reported that shank length serves as a reliable index of body weight during most of the pigeons’ growing period. Variance inflation factor (VIF) values for interrelationship between traits represent the increase in variance due to high correlation between predictors (Peter et al 2006). The VIF values obtained in the present study are within the range of 0.01-10.00 reported by Rook et al (1990). These authors pointed out that, VIF value less than 10.00 indicates good collinearity thereby rendering the reliability of the predictive equation effective.


Conclusion


References

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Received 7 January 2014; Accepted 7 May 2014; Published 1 June 2014

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