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Estimates of Growth Curve, Carcass Characteristics and Determination of Production Environment for Philippine Swamp Buffalo (Bubalus bubalis) in Cagayan Province, Philippines
Thesis Abstract:
Four studies were conducted to determine the estimate growth curve, carcass characteristics, production environment, and use of principal component analysis of farmers’ profile and production environment of swamp buffalo in Cagayan province. For the first study, weight and height for the different age groups of Philippine carabao (PC) from birth to a 3-months interval up to 60 months were determined to come up with a growth curve model that best fits the data set with higher prediction accuracy. This was done to correlate meat characteristics from ultrasonography of 57 animals to weight and age and determine and apply principal component analysis (PCA) to the 120 farmers’ responses to production environment survey of PC in Cagayan. Data from 7,480 and 3,321 records of body weight for 2001 to 2017 and height for 2001 to 2015, respectively, were extracted and analyzed statistically and used in the development of growth curve models with estimation. Significant increase in body weight (P<0.05) of PC were observed from birth until 60 months for all animals but not in all ages. Significantly higher weights (P<0.05) were noted in female PC than male PC at ages 6, 12, and 15 months, and the reverse were found in ages 36, 39, 51, 57, and 60 months. There is significant increase in weight from birth until 60 months of age, whereas, the average daily gain (ADG) only increased from 3 months old (0.36 kg/day) to 9 months old (0.38 kg/day) PC, and then gradually slows down in 12 months up to 60 months. Height of PC increased significantly (P<0.05) as the animal grows observed from 0 (at birth) until 12 months old. The Brody growth curve model best fits the data set of weight and height for all male and female PC. The prediction equation for WT of all is given by W(t)=601.32[1+(30.02/601.32)-1] exp (-0.02(age (month)] and for HT of all by H(t)=119.46[1+(69.17/119.46)-1] exp (-0.07(age (month)].
Significant positive correlations were obtained between EMA and RFT-12 months old (r=0.63), EMA and WT-18 months (r=0.75), EMA and WT-30 months (r=0.625, and RFT and P8- 30 months (r=0.800) old PC. However, significantly negative correlations were found between EMA-12 month and EMA-36 months (r=-0.68), and WT-36 months and P8-12 months (r=-0.74) old PC.
Most (36%) of the respondents have landholding of 1.0-1.9 ha, while 13 percent have none. Majority (61%) of the respondents did not reach college level and/or finished college education; most of them were undergraduates of high school (34%). Family/relatives are the main sources of knowledge for most of the respondents (47%); respondents gained additional knowledge from friends, school, training/seminars, and from their own experience (48%).
The educational attainment, sources of knowledge in raising PC, problems encountered in PC production, and farmland area were the variables identified in components 1 and 2, respectively. The two components have an opposite effect to each other. Farmland area and source of additional knowledge in raising PC are interrelated and correlated positively.
In conclusion, among nonlinear models, the Brody model was found to best fit the PC growth data. The Brody model can predict the weight and height of PC using age. RFT and EMA are positively correlated with age. PCA can be applied to survey data.
