Influence of age, body weight, parity and morphometric traits on litter size in prolific Black Bengal goats

Abstract

Data on some linear traits along with age, body weight (BW) at breeding, parity and previous litter size (LZ) of 1008 pregnant Black Bengal goats were analysed using one-way Analysis of Variance. Higher age, heavier BW at breeding, higher parity order resulted more (P < 0.01) chance of triplet or quadruplet births as compared to that of single birth. Larger previous LZ resulted larger (P < 0.01) LZ in subsequent kidding. Most of the linear traits were higher (P < 0.01 or P < 0.05) in goats bearing multiple foetuses than in the goats bearing single foetus. The results of stepwise discriminant function suggested that heart girth, punch girth, BW, distance between trochanter major and pelvic triangle area might be the predictive indices for higher LZ.

Keywords:

• goat
• phenotypic descriptors
• prolificacy
• number of foetuses
• pregnancy

1. Introduction

India is a vast reserve of 20 goat breeds with 15.6% and 24.6% of world (807 million) and Asian (511.3 million) populations, respectively. It ranks second in goat population (125.7 million) after China (149.3 million) in the world (FAO 2008). Goat production is an attractive livestock enterprise particularly for small and marginal farmers and landless labourers in India and in other developing countries like Bangladesh, Nepal and Pakistan. High kid production is essential to meet the huge demand of goat meat in India as well as in other Asian countries (Argüello 2011). Increased kid production is of great significance to the goat producers. Linear traits are currently included in the genetic evaluations of a variety of breeds of goats in the USA (Wiggans & Hubbard 2001). There is paucity of information on the association between linear traits and fertility traits in goats (Mellado et al. 2008), sheep (Gaskins et al. 2005) and cattle (Royal et al. 2002). Where genetic evaluation has still limited use as in developing countries, identification of descriptive linear traits and farmers' friendly tools for selecting goats with high reproduction potential may be useful for realising higher economic returns. A clear knowledge on phenotypic descriptors for the prediction of foetal number during pregnancy is essential for preventing pregnancy toxaemia, reducing dystocia, optimising birth weights and increasing the survivability of newborns (Karen et al. 2006; Moallem et al. 2012). Despite the use of ultrasonographic scanning for the prediction of foetal number mostly at organised farms in goats (Abdelgafar et al. 2007) and sheep (Karen et al. 2006), there is a dearth of information on phenotypic descriptors to differentiate the pregnant goats bearing single or multiple foetuses under field conditions. Therefore, our objectives were (1) to assess the effect of age, body weight (BW) at breeding, parity, previous litter size (LZ) and days open on LZ of does, (2) to study the changes in linear type traits in does during pregnancy and (3) to explore which traits would influence the LZ of does.

2. Materials and methods

2.1. Study area

Two-stage stratified random sample survey (consisting of village as strata-1 and animal within village as strata-2) based data were collected from 1008 goats during 5 months of pregnancy period from July 2007 to February 2011 for 3½ years in 45 villages located in four districts, viz. Nadia (23°4′N and 88°5′E), North 24 parganas (23°1′N and 88°5′E), Hooghly (22°5′N and 88°2′E) and Murshidabad (24°1′N and 88°2′E) in West Bengal, a state of Eastern India. These four districts are part of the main Bengal goat breeding tract in the country. Care was taken to select the villages which were located in isolation to minimise genetic linkage among animals. The annual rainfall for these areas varies from 1500 to 2000 mm. The climate is hot and humid, with temperature ranging from 9°C in winter to 40°C in summer.

2.2. Data collection procedure and description

The study commenced with primary visits to identify individual female goats involved in the study and their owners. Owners volunteered to participate in response to questionnaires at the start of the study. Herd details recorded on an individual data card consisted of number of females, kids, whether buck are maintained in the herd, hair coat colour, age of the female goats, parity, last date of kidding, previous LZ, days open, date of last breeding and management practices (e.g., feeding regimen, system of breeding). Sixteen phenotypic variables measured included ear length, neck length, head rump length (HRL), head rump curve length (HRCL), body length (BL), sacral length (SL), BW, heart girth (HG), punch girth (PG), pelvic triangle area (PtA), wither height (WH), croup height (CrH), clearance at sternum (CS), clearance at udder (CU), distance between tuber coxae bones (DTC) and distance between trochanter major bones (DTM). All measurements were recorded on an individual data sheet from the goats at the third week of each month during a five-month pregnancy period in the morning before the animals were released for grazing.

2.3. Experimental animals

A small-sized, meat-type, early-maturing, non-seasonal and prolific Black Bengal goat breed was the experimental animal used in the present study. This breed is available in a vast geographic area in the eastern and north eastern regions of India, Bangladesh and other Southeast Asian countries (Acharya 1982; Rahman et al. 2006; Khanum et al. 2007). Major physical characteristics of the breed are small size, deep body, straight, convex or concave head, short legs, thin and shiny hair coat of any single colour (black, white and brown) or mixed (combination of any two of the pure colours), erect or pendulous ears, curved or straight horn and short tail (Sahoo et al. 2005). Animals which were apparently free from diseases, experienced at least one kidding, but not completed their sixth kidding, were selected for the present investigation. Goats between their first and second month of pregnancy, as reported by the owners, were selected. One goat was sampled only once. The experimental goats were identified by a neck tag. The goats were reared in small numbers from 2 to 5 per household under the free-range system on natural vegetation and tree lopping without any supplementation. The female goats were bred naturally by the bucks available in the village. The animals were examined regularly by a veterinarian during the study period. Does that aborted during the study were excluded from the experiment. Finally, 1008 does completed the term and gave birth to live kid(s). The numbers of single, twin, triplet and quadruplet pregnancies were 289,584, 128 and 7, respectively. LZ was defined as the number of kid(s) born to each goat and considered at four levels: single, twin, triplet and quadruplet births. Prolificacy was calculated as the percentage of number of kids born to total number of does delivered.

2.4. Statistical analyses

Data are presented as the mean ± the standard error of the mean (SEM). The association between hair coat colour and goats belonging to different LZ groups was tested by a chi-square test. All the linear traits measured were considered independent group variables and the resultant LZs were the dependent group variables. A complete time-series data on 1008 pregnant goats were analysed using one-way Analysis of Variance (ANOVA) considering observed LZ as the only source of variation to investigate if linear phenotypic traits influenced the LZ of Black Bengal goats. Duncan's multiple range test was applied to compare pairwise mean difference probabilities using SPSS (1997), as and when necessary. Pearson correlation between different phenotypic traits and LZ was determined and tested for significance. The multivariate technique applied was stepwise discriminant function analysis using SPSS (1997) to build a predictive model of group membership based on the observed phenotypes of each case and thus recognise the most probable descriptors in pregnant Black Bengal goats for predicting LZ. The procedure generated a discriminant function (or, for more than two groups, a set of discriminant functions) based on linear combinations of the predictor variables that provided the best discrimination between the groups. The functions were generated from a sample of cases for which group membership was known; the functions could then be applied to new cases with measurements for the predictor variables but unknown group membership. The relative importance of the phenotypic variables in discriminating four goat groups was assessed using canonical discriminant function coefficients, canonical correlation, eigen value and % of variance. For all analyses, values were considered either at P < 0.01 or at P < 0.05.

3. Results and discussion

3.1. Prolificacy

The percentage of Black Bengal does showing different LZs is presented in Table 1. The LZ proportions for single, twin, triplet and quadruplet were 28.7%, 57.9%, 12.7% and 0.7%, respectively. The birth of 1869 kids was recorded from 1008 kidding does, averaging 1.8 kids per doe and the prolificacy rate was 185.4%. The record of 71.3% multiple births, of which 57.9% was twins, supports the previous findings of the incidence of 56.3% twinning in Black Bengal goats in Bangladesh (Hassan et al. 2007). Twinning was more frequent (46.2%) in Egyptian Nubian goats which gave 82.9% multiple births (Aboul-Naga et al. 2012). The average LZs for Nubian, Pygmy, American Alpine, French Alpine, Saanen and Toggenburg were 2.0, 1.9, 1.9, 1.7, 1.7 and 1.6 kids per doe, respectively (Amoah et al. 1996). Results of the present study reconfirm that Black Bengal goats are prolific, with the average LZ being 1.8.

Table 1. Hair coat colour of Black Bengal goats belonging to different LZ groups.

	LZ class of doe
Hair coat colour	Single	Twin	Triplet	Quadruplet	Total
Black	207	416	95	4	722 (71.7%)
White	7	18	1	–	26 (2.6%)
Brown	8	22	4	–	34 (3.3%)
Mixed	67	128	28	3	226 (22.4%)
	289 (28.7%)	584 (57.9%)	128 (12.7%)	7 (0.7%)	1008

3.2. Coat colour

The goats with different hair coat colour with different LZs are presented in Table 1. Interestingly, 71.7% of the randomly selected goats (722 out of 1008) were black in hair coat colour indicating why the breed was named as ‘Black Bengal’ goat (Bhattacharya 2000). The incidence of twin births was recorded in 416 (41.2%) goats with black hair coat colour; however, such an association was not significant (P > 0.05).

3.3. Age of does, BW, parity, previous LZ and days open

The influences of age, BW of does at breeding, parity, previous LZ and days open on LZ in experimental goats are documented in Table 2. Age at breeding (≤ 24.15 months) did not influence the birth of single or twin kids, but age (≥ 28.44 months) significantly influenced (P < 0.01) the triplet or quadruplet LZ, when compared with the single LZ at the age of ≤20.46 months. BW at breeding (≥21.00 kg) could increase (P < 0.01) the chance of quadruplet births as compared to that of single birth at the BW of ≤15.31 kg. However, BW (≤18.56 kg) did not have any influence on the incidence of single, twin or triplet births. Incidences of triplet and quadruplet kidding were more (P < 0.01) at higher parity (≥ 3.61) as compared to those of single and twin kidding at lower parity (≤ 3.00). The preceding LZ exhibited a strong (P < 0.0l) effect on the subsequent LZ. If the preceding LZ was large, there was a higher (P < 0.01) chance of getting larger LZ in subsequent kidding. These findings support the previous reports on does (Constantinou 1989; Mellado et al. 1991; Amoah et al. 1996) and on ewes (Laster et al. 1972; Smith 1985; Gaskins et al. 2005).

Table 2. Age of does at breeding, BW during the month of conception, parity, previous LZ and days open (± SEM) of the does belonging to different LZ classes.

	LZ class of doe
Parameter	Single (n = 289)	Twin (n = 584)	Triplet (n = 128)	Quadruplet (n = 7)
Age of does at breeding (months)	20.46^b ± 0.41	24.15^ab ± 0.33	28.44^a ± 0.70	30.00^a ± 2.34
BW during the month of conception (kg)	15.31^b ± 0.51	17.06^ab ± 0.32	18.56^ab ± 0.72	21.00^a ± 2.00
Parity	2.54^b ± 0.05	3.00^b ± 0.04	3.61^a ± 0.09	4.00^a ± 0.46
Previous kidding size	1.35^d ± 0.03	1.72^c ± 0.03	2.25^b ± 0.07	2.86^a ± 0.34
Days open	94.44 ± 2.93	103.95 ± 2.29	97.89 ± 5.22	79.71 ± 13.56

Note: Means for different groups with different superscript letters within a row differ (P < 0.01).

3.4. Ears and neck

The influence of ear length and neck length on LZ in Black Bengal goats is presented in Table 3. The goats with bigger (P < 0.01) ears, ranging from a mean of 13.59 cm to 14.14 cm in length, and longer (P < 0.01) necks, between a mean of 22.59 cm and 24.57 cm, gave birth to more triplet or quadruplet kids when compared to the goats that gave birth to single kids (average 12.42 cm ear length and 19.59 cm neck length). It is not known whether ear and neck lengths are adjusted with age or may be heritable characters for multiple births. The influence of ear and tail size on milk production in Spanish Assaf breed has been detected; however, no genetic reason has been concluded (Pérez-Cabal et al. 2013).

Table 3. Ear length and neck length (± SEM) of the does belonging to different LZ classes.

	LZ class of doe
Parameter	Single (n = 289)	Twin (n = 584)	Triplet (n = 128)	Quadruplet (n = 7)
Ear length (cm)	12.42^c ± 0.10	13.07^bc ± 0.06	13.59^ab ± 0.13	14.14^a ± 0.40
Neck length (cm)	19.59^c ± 0.23	21.30^bc ± 0.17	22.59^ab ± 0.28	24.57^a ± 0.92

Note: Means for different groups with different superscript letters within a row differ (P < 0.01).

3.5. Linear traits

The mean (± SEM) of different linear traits in pregnant goats carrying different number of foetuses is presented in Table 4. The measurements of most of the traits were significantly higher (P < 0.01 or P < 0.05) in goats bearing multiple foetuses than the goats bearing a single foetus during different months of pregnancy. Except CU, all these phenotypic descriptors were positively correlated (P < 0.01) with the LZ. An increase in measurement in various phenotypic traits in goats bearing multiple foetuses as compared to the goats bearing single foetus could be due to the enlargement of the body size anatomically to make room for more foetuses and provide more body strength to bear more foetuses by storage of more nutrients for mobilisation and meeting physiological demand of multiple foetuses during pregnancy. In previous study, strength was associated with an increased likelihood of multiple births and the strongest goats were 43% more likely to produce multiple births than medium to weak goats (Mellado et al. 2008). Likewise, strength has been implicated in the increment of multiple offsprings in ewes (Hall et al. 1994). Body volume traits like stature, size, body depth, etc. have been shown to be related to calving interval in dairy cattle (Haile- Mariam et al. 2004). There was no significant difference (P > 0.05) in CU throughout the pregnancy and CS during the first month of pregnancy. No change in CU measurement among different groups suggested the fact that Black Bengal goat breed was recognised as a poor milk producer (Husain et al. 1996) and as such there was no marked change in udder size approaching kidding. Indeed, supplemental milk feeding was recommended for saving more Black Bengal kids out of multiple births (Chowdhury & Faruque 2004). No significant change (P > 0.05) in CS during the first month of pregnancy suggested that the size and the growth of foetuses were not sufficient to bring about any significant change (P > 0.05) in measurement of those traits during the first month of pregnancy.

Table 4. Mean (± SEM) and correlation between linear traits and LZ.

		LZ
		Single (n = 289)		Twin (n = 584)		Triplet (n = 128)		Quadruplet (n = 7)
Parameter	Month of pregnancy	Mean	SEM	Mean	SEM	Mean	SEM	Mean	SEM	P value	r value	P value*
HRL (cm)	1	55.63^b	0.93	58.61^a ^b	0.51	62.81^a ^b	0.93	64.13^a	3.50	0.001	0.272	0.000
	2	55.83^b	0.53	58.79^b	0.31	63.10^a	0.66	64.27^a	1.29	0.000	0.368	0.000
	3	55.91^b	0.40	58.99^b	0.25	63.20^a	0.50	64.36^a	1.03	0.000	0.354	0.000
	4	56.20^b	0.38	59.33^b	0.23	63.38^a	0.48	64.57^a	1.19	0.000	0.354	0.000
	5	56.25^c	0.38	59.55^b	0.23	63.44^a	0.47	64.89^a	1.25	0.000	0.359	0.000
HRCL (cm)	1	59.65^b	0.89	63.43^a ^b	0.55	67.89^a ^b	0.98	69.90^a	3.50	0.000	0.278	0.000
	2	59.87^b	0.48	63.63^b	0.32	68.02^a	0.68	70.21^a	1.75	0.000	0.381	0.000
	3	60.47^d	0.38	63.89^c	0.26	68.17^b	0.53	71.52^a	1.86	0.000	0.375	0.000
	4	60.71^d	0.35	64.36^c	0.24	68.25^b	0.49	71.71^a	1.87	0.000	0.383	0.000
	5	60.88^b	0.35	64.43^a ^b	0.24	68.48^a ^b	0.49	71.77^a	1.85	0.000	0.386	0.000
BL (cm)	1	50.32^c	0.70	52.88^a ^b ^c	0.45	56.67^a ^b	0.98	57.31^a	1.00	0.000	0.357	0.000
	2	50.51^b	0.37	53.18^b	0.26	56.93^a	0.60	57.60^a	0.66	0.000	0.370	0.000
	3	50.97^c	0.30	53.37^b	0.21	57.55^a	0.46	58.29^a	0.81	0.000	0.394	0.000
	4	51.30^c	0.28	54.58^b	0.20	57.88^a	0.45	59.14^a	0.83	0.000	0.390	0.000
	5	51.73^c	0.28	54.75^b	0.20	58.54^a	0.46	59.71^a	0.92	0.000	0.401	0.000
SL (cm)	1	12.89^y	0.26	13.56^x ^y	0.16	14.11^x ^y	0.28	14.54^x	0.50	0.019	0.212	0.000
	2	12.95^b	0.13	13.56^a ^b	0.08	14.14^a ^b	0.18	14.55^a	0.55	0.000	0.236	0.000
	3	12.97^c	0.10	13.57^b ^c	0.06	14.16^a ^b	0.14	14.56^a	0.53	0.000	0.238	0.000
	4	13.00^c	0.09	13.59^b ^c	0.06	14.18^a ^b	0.14	14.56^a	0.55	0.000	0.236	0.000
	5	13.04^c	0.09	13.60^b ^c	0.06	14.15^a ^b	0.13	14.57^a	0.65	0.000	0.219	0.000
BW (kg)	1	14.31^b	0.51	17.06^a ^b	0.32	18.56^a ^b	0.72	21.00^a	2.00	0.001	0.275	0.000
	2	14.53^c	0.29	17.37^b	0.19	20.72^a ^b	0.45	21.40^a	1.78	0.000	0.448	0.000
	3	15.36^c	0.24	18.20^b	0.17	21.65^a ^b	0.37	23.00^a	1.45	0.000	0.447	0.000
	4	16.41^c	0.25	19.57^b	0.17	23.56^a ^b	0.37	25.00^a	1.80	0.000	0.474	0.000
	5	17.85^c	0.25	21.27^b	0.17	25.71^a ^b	0.37	27.93^a	2.02	0.000	0.503	0.000
HG (cm)	1	57.13^b	0.81	60.88^a ^b	0.44	65.97^a	1.42	67.00^a	1.00	0.000	0.362	0.000
	2	57.20^c	0.42	61.09^b	0.26	66.24^a	0.63	67.20^a	2.22	0.000	0.464	0.000
	3	57.67^c	0.33	61.56^b	0.21	66.64^a	0.48	67.71^a	1.60	0.000	0.480	0.000
	4	58.04^c	0.32	62.17^b	0.21	67.25^a	0.47	68.02^a	2.11	0.000	0.483	0.000
	5	58.43^c	0.32	62.54^b	0.21	67.81^a	0.47	68.29^a	1.77	0.000	0.480	0.000
PG (cm)	1	64.94^c	0.87	69.47^a ^b ^c	0.55	74.82^a ^b	1.70	76.50^a	4.50	0.000	0.298	0.000
	2	65.39^b	0.49	69.91^b	0.33	75.22^a	0.77	77.40^a	1.60	0.000	0.433	0.000
	3	66.38^c	0.40	71.56^b	0.28	76.33^a	0.64	79.29^a	1.21	0.000	0.447	0.000
	4	67.66^b	0.39	73.24^b	0.27	78.81^a	0.62	81.57^a	1.60	0.000	0.475	0.000
	5	69.24^c	0.40	75.23^b	0.28	81.80^a	0.62	83.57^a	1.63	0.000	0.501	0.000
WH (cm)	1	47.13^b	0.82	49.71^b	0.44	52.47^a	0.77	53.30^a	3.00	0.001	0.262	0.000
	2	47.50^b	0.37	49.75^a ^b	0.24	52.53^a	0.50	53.40^a	1.25	0.000	0.311	0.000
	3	48.10^b	0.30	49.97^b	0.19	52.66^a	0.39	53.57^a	1.25	0.000	0.298	0.000
	4	48.23^b	0.29	50.27^b	0.18	52.78^a	0.37	53.63^a	1.46	0.000	0.304	0.000
	5	48.33^b	0.29	50.33^b	0.18	52.81^a	0.37	53.69^a	1.51	0.000	0.296	0.000
CrH (cm)	1	50.11^y	0.79	52.46^y	0.42	54.48^x	0.79	55.00^x	3.00	0.012	0.213	0.002
	2	50.33^b	0.38	52.81^a ^b	0.24	55.19^a	0.50	55.40^a	1.29	0.000	0.316	0.000
	3	51.05^b	0.32	52.92^b	0.19	55.26^a	0.38	55.59^a	0.89	0.000	0.287	0.000
	4	51.11^b	0.30	53.14^a ^b	0.18	55.39^a	0.37	55.79^a	0.89	0.000	0.279	0.000
	5	51.22^b	0.30	53.20^a ^b	0.18	55.45^a	0.36	56.00^a	0.90	0.000	0.257	0.000
PtA (square cm)	1	410.61^b	9.15	454.02^b	8.33	528.53^a	9.83	532.17^a	6.02	0.003	0.243	0.000
	2	420.42^b	7.16	467.22^b	4.79	531.86^a	8.45	544.10^a	7.45	0.000	0.311	0.000
	3	437.47^b	5.98	470.55^b	3.98	539.25^a	9.69	551.92^a	9.71	0.000	0.297	0.000
	4	440.40^b	5.63	482.73^b	3.75	548.41^a	9.43	563.16^a	9.30	0.000	0.320	0.000
	5	448.00^b	5.72	490.84^b	3.78	556.56^a	9.45	579.53^a	8.70	0.000	0.318	0.000
CS (cm)	1	24.15	0.58	24.97	0.27	25.86	0.61	26.50	0.50	0.196	0.102	0.134
	2	24.28^b	0.26	25.06^a ^b	0.16	26.47^a	0.46	26.90^a	1.47	0.000	0.207	0.000
	3	24.48^b	0.20	25.14^a ^b	0.13	26.60^a	0.33	27.14^a	1.54	0.000	0.194	0.000
	4	24.53^b	0.19	25.16^a ^b	0.12	26.67^a	0.32	27.43^a	1.60	0.000	0.200	0.000
	5	24.62^b	0.19	25.09^a ^b	0.12	26.73^a	0.33	27.71^a	1.34	0.000	0.176	0.000
CU (cm)	1	24.74	0.58	24.80	0.31	25.85	0.60	26.80	1.00	0.644	0.053	0.439
	2	24.62	0.25	24.74	0.18	25.86	0.52	26.77	1.83	0.351	0.034	0.301
	3	24.34	0.20	24.68	0.14	25.64	0.36	26.57	1.36	0.354	0.017	0.330
	4	24.24	0.19	24.54	0.14	25.48	0.35	26.29	1.34	0.143	0.058	0.171
	5	24.12	0.20	24.23	0.14	24.98	0.34	25.29	1.41	0.287	0.068	0.231
DTC (cm)	1	10.19^y	0.19	10.77^y	0.12	11.44^x	0.21	12.38^x	0.50	0.039	0.179	0.008
	2	10.21^b	0.10	10.78^b	0.07	11.55^a	0.22	12.40^a	0.75	0.000	0.322	0.000
	3	10.20^c	0.07	10.81^c	0.05	11.60^b	0.16	12.43^a	0.61	0.000	0.325	0.000
	4	10.29^c	0.07	10.91^c	0.05	11.69^b	0.15	12.57^a	0.48	0.000	0.333	0.000
	5	10.34^b	0.07	10.99^b	0.05	11.81^a	0.14	12.63^a	0.53	0.000	0.346	0.000
DTM (cm)	1	11.63^y	0.16	11.99^y	0.09	12.86^x	0.17	13.32^x	1.00	0.043	0.162	0.017
	2	11.71^c	0.08	12.16^b ^c	0.06	12.94^a ^b	0.21	13.40^a	0.60	0.000	0.282	0.000
	3	11.71^c	0.06	12.19^b ^c	0.05	13.02^a ^b	0.15	13.57^a	0.53	0.000	0.291	0.000
	4	11.76^c	0.05	12.27^b ^c	0.05	13.06^a ^b	0.15	13.57^a	0.53	0.000	0.295	0.000
	5	11.80^c	0.06	12.29^b ^c	0.05	13.06^a ^b	0.15	13.69^a	0.47	0.000	0.275	0.000

^a,b,c Means for different groups with different superscript letters within a row differ (P < 0.01).

^x,y Means for different groups with different superscript letters within a row differ (P < 0.05).

* The P value is for the correlation.

The stepwise discriminant function as presented in Table 5 indicated that five linear traits (HG, BW, PG, DTM and PtA) were significant in discriminating the foetal numbers between groups. The standardised canonical discriminant function coefficients showed the multivariate discriminating power of the phenotypic traits. HG measurement might be considered as the best indicator for higher LZ from the first month to the fourth month of pregnancy. BW emerged as the second best indicator for higher LZ during second, fourth and fifth month of pregnancy. PG measurement was found to be the third best indicator for higher LZ from third month to fifth month of pregnancy. Besides, distance between trochanter major at third and fifth month of pregnancy and PtA at fifth month of pregnancy might be considered as indicators for higher LZ. Discriminant analysis allowed us to identify important and informative variables from a lot of traits. The pregnant does could be divided into classes carrying multiple foetuses and single foetus on the basis of HG, PG, BW, distance between trochanter major and PtA. Thus, a parsimonious discrimination between the goat groups may be achieved by using a few discriminant traits. Our results are in agreement with the previous finding of using phenotypic discriminate variables for classifying different goat breeds (Yakubu et al. 2010).

Table 5. Stepwise discriminant function results for month-wise discrimination of variables during pregnancy.

4. Conclusion

Higher prolificacy has been recorded in goats with the history of larger previous LZ (≥1.72) and higher parity (≥3.61). Multiple births are achieved due to breeding at higher age (≥28.44 months) and heavier BW (≥21.00 kg). The present study also reveals substantial phenotypic variations among the goats bearing single, twin, triplet or more foetus(s). HG, PG, BW, distance between trochanter major and PtA may be useful tools for the discrimination between the goats carrying multiple foetuses and the goats carrying single foetus and thus achieving more economic benefits out of multiple births by taking special care of does carrying multiple foetuses.

Acknowledgements

The necessary support and assistance during the project work extended by the Vice Chancellors of West Bengal University of Animal and Fishery Sciences and Bidhan Chandra Krishi Viswavidyalaya, West Bengal, India, are duly acknowledged. The authors wish to thank the farmers for their regular help and cooperation during the investigation in the field.

Funding

This work was supported by the National Fund for Basic, Strategic and Frontier Application Research in Agriculture (NFBSFARA) of Indian Council of Agricultural Research, New Delhi, India [grant number NFBSRA/PCN/AP-06/2006-07].

Additional information

Funding

Funding: This work was supported by the National Fund for Basic, Strategic and Frontier Application Research in Agriculture (NFBSFARA) of Indian Council of Agricultural Research, New Delhi, India [grant number NFBSRA/PCN/AP-06/2006-07].