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The objective of this study was to investigate growth patterns of goats utilizing data from a crossbreeding program involving the exotic German Fawn (GF) and the indigenous Kambing Katjang (KK) goats. Growth curve models and growth curve parameters were compared and analyzed for different genotypes and litter types. A total of 20,393 weight-age data from 208 female goats belonging to various crossbreeding genotypes were individually fitted to four growth curve models (Brody, Bertalanffy, Gompertz and Logistic). The goodness of fit was highest in the Brody model in most cases. A comparison of R2 among genotypes showed that they were highest for KK. There were no significant differences of genotypes for estimated mature weight in the Brody model. The estimated mature weights for KK were significantly lower (P < 0.05) than for GF × KK (F1), backcrosses with 75% GF genes (BC) and F1 × F1 (F2) in the other models. The correlations between estimated mature weights and the maturing rates were lowest for BC. The genotype significantly (P < 0.01) affected the age at the constant degree of maturity (67% and 90% of mature weight) in all models. The BC genotype was the youngest at maturity and KK the oldest. All models well expressed the growth pattern of the target animals when they were older than 2.5 years of age. The results from the present study showed that the growth pattern may be altered by crossbreeding of KK with the GF breed.

In order to solve serious problem on the lack of job opportunity and poverty in Indonesia, oil palm expansion driven by smallholders have been taken into the economic development agenda. The evidence shows that oil palm expansion by smallholders have a great performance for improving livelihood of rural community. Thus, this study aims to estimate the causal effect of oil palm expansion on farmers' livelihoods in Indonesia. Using cross-sectional data from 271 households in Riau Province, the determinants of farmers' decisions to expand oil palm farm size and the impacts of expansion are analyzed. Propensity Score Matching was employed in order to deal with self-selection biased in the evaluation of oil palm expansion impact. In the first step, logit model was applied to analyze the determinant of oil palm expansion. In the second step, each observation is matched with a similar propensity score value in order estimate the average treatment effect for the treated (ATT). Empirical results show that number of family members actively involved in oil palm cultivation, farmers' financial assets, contract farming, and distance to the market are significantly associated with likelihood for expanding farm size. Positive and significant impacts of crop income from oil palm and per capita expenditures, confirms that oil palm expansion help reducing the problem of job opportunity and poverty in Indonesia. This study implicates that, to improve oil palm expansion practice in Indonesia, several schemes must be considered: enhancing human resources development, integrating oil palm marketing schemes, and improving infrastructure facilities.

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