This article reports genetic and phenotypic parameters of monthly egg production and the influence of Box-Cox transformation on the parameters from a population of White Leghorns, selected for feed efficiency. A total of 6450 daughters of 180 sires and 1335 dams were analysed by restricted maximum likelihood (REML) using a multivariate animal model. The traits considered were monthly egg productions, cumulative production of the first 5 months (S5), cumulative production of first 10 months (S10), and survivor egg production in the first cycle (S12). Two sets of data were analysed: the original data and with the Box-Cox method transformed data. The results indicated that there were no great differences in the estimates between untransformed and transformed data. The estimates of heritability for monthly egg production were high for the first period, decreased to reach the lowest during peak production, and increased to the end of lay. The estimates of heritability for cumulative records were generally higher than monthly records. Genetic and phenotypic correlations among monthly egg production totals were generally high for contiguous periods and then decreased as the interval between months increased. The highest genetic correlation between monthly records and S5 was for the second month of production, whereas the correlations between monthly production totals and S10 and S12 reached their peak at the sixth and eighth months of production, respectively. Zusammenfassung Genetische und phä notypische Parameter fü r die monatliche Legeleistung der Rasse Weißes LeghornDas Ziel der Untersuchung bestand in der Schätzung genetischer und phänotypischer Parameter fü r die monatliche Legeleistung bei Legehennen. Insgesamt 6450 Hennen der Rasse Weißes Leghorn, selektiert auf Futterverzehr, welche von 180 Vätern und 1335 Mü ttern abstammen, wurden mit einem Tiermodell unter Verwendung der REML-Methode analysiert. In die Auswertung gingen folgende Merkmale ein: monatliche Legeleistungen, akkumulierte Legeleistungen vom ersten bis fü nften Monat (S5), vom ersten bis zehnten Monat (S10), und eine Gesamtleistung (S12) im ersten Zyklus der Legephase. Zwei Datensätze wurden analysiert: die Originaldaten und die mit der Box-Cox-Methode transformierten Daten. Die Ergebnisse zeigten nur geringfü gige Differenzen zwischen den Schätzungen mit untransformierten und transformierten Daten. Die Heritabilität war im ersten Monat hoch, verringerte sich bis zum dritten Monat und stieg zum Ende der Eiproduktion wieder an. Die Heritabilitäten der kumulativen Leistungen waren hö her als die der monatlichen Leistungen. Die genetischen und phänotypischen Korrelationen zwischen benachbarten monatlichen Legeleistungen waren generell hoch. Die hö chsten genetischen Korrelationen zwischen den monatlichen und den kumulativen Legeleistungen S5, S10 bzw. S12 ergaben sich im zweiten, im siebenten bzw. im achten Monat. U.S.

1. We investigated the use of monthly production records for genetic evaluation of laying hens, derived from a test day model with random regression in dairy cattle and compared it with other models. 2. Records of 6450 hens, daughters of 180 sires and 1335 dams, were analysed using a model with restricted maximum likelihood (REML): traits considered were monthly and cumulative egg production. Five models were studied: (1) random regression with covariates derived from the regression of Ali and Schaeffer (Canadian Journal of Animal Science, 67: 637-644, 1987) (RRMAS), (2) random regression with covariates derived from quartic polynomial (RRMP4), (3) fixed regression with covariates derived from Ali and Schaeffer (FRM), (4) multiple trait (MTM) and (5) cumulative (CM). 3. The models were compared on the basis of Spearman rank correlations of individual breeding values and sire breeding values estimated from subsets of full-sib split data. The hens (about 10% per generation) which ranked highest on their estimated breeding values from different models were compared phenotypically with their full records. 4. The estimates of heritability resulting from RRMP4 were biased upward from the estimates obtained from MTM, so this model was discarded. The heritabilities for monthly productions from RRMAS and MTM showed a similar pattern. They were high for the 1st month of production, decreased to their lowest value at about month 5 of production and increased again to the end of lay. 5. Spearman rank correlations between animal breeding values estimated by monthly models (RRMAS, FRM and MTM) were high, between 0.91 and 0.98, whereas those between estimates of monthly models and CM were lower, from 0.85 to 0.87. The correlations estimated either from intermittent months of measurements (odd vs even months) or full records were generally high, from 0.93 to 0.99. Information from odd months of production could be sufficient for cost-efficient recording schemes. The RRMAS generally had the highest correlation of sire breeding values between subsets of full-sib records, followed by MTM, RM and CM. Monthly models selected hens with higher productivity than the cumulative model. 6. In conclusion, genetic evaluation based on monthly production may be better than using cumulative production and RRMAS appeared to be the best among the models tested here.

1. This paper addresses the possibility of using a monthly model for the genetic evaluation of laying hens, based on the definition of a test day model with fixed regression as used in dairy cattle, in which monthly records were treated as repeated measurements of the same trait. 2. Production records of 6450 hens, daughters of 180 sires and 1335 dams were analysed using an animal model with restricted maximum likelihood (REML). The traits considered were individual monthly egg production and cumulative egg production in 11 months. Four different models were fitted to various combinations of monthly and cumulative records. The covariates were derived from the regression of Ali and Schaeffer (1987). 3. Spearman rank correlations were computed to compare breeding values from different models. Two types of correlations were computed: between individual breeding values and between sire breeding values based on subsets of full-sib records. 4. The results indicated that a monthly model with nested covariates produced higher heritability and permanent environmental variance than the models with non-nested or without covariates. The estimates of heritability obtained from monthly model were lower than the estimates from the cumulative model. The monthly model resulted in higher correlations of sire breeding values between two subsets of full-sib records than those from cumulative models. 5. In conclusion, the monthly model with nested covariates appears to be better than the model with non-nested covariates or without covariate. Although the heritability estimates obtained from the monthly model were lower, the monthly model with nested covariates could be better than the cumulative model for genetic evaluation of laying hens in the 1st cycle of laying period when using either full or part records. The use of information from odd months of production could be of interest for the evaluation of full records.

A research was conducted at Quail Breeding Centre of Padjadjaran University.  A hundred quails of female black and brown color of each line was observed from hatch to age of six weeks. Four growth models were compared: Gompertz, Logistic, Richards, and MMF. The best fit was measured with Coefficient of determination (R2) and standard error of prediction (se). The results showed that all observed models have high accuracy with R2 ranging from 0.9950 to 0.9988 for black color, and 0.9984 to 0.9992 for brown color respectively. Standard errors of prediction (SE) ranged from 1.99 g to 4.01 g for black, and from 1.92 g to 2.52 g for brown, respectively. Gompertz model was more favorable with R2 and SE of 0.9988 and 1.99 g for black, and 0.9991 and 1.92 g for brown, respectively. Age at inflection, maximum average daily gains and weights at inflection were 4.18 week, 27.87 g and 100.23 g for black line and 3.38 week, 25.05 g and 75.34 g for brown line, respectively.

Purpose : This research aims to study the technical characteristics of Muscovy duck in Ciayumajakuning. Research Method : The study uses a survey method and applies a purposive sampling to take samples by observing 22 farmers. Data analysis used in this study is a descriptive exploratory method. Findings : The results show that 95.5% of pens are in postal shape; 50% of the pen material is made from bamboo, wood, and roof tile while the other 50% is made from bamboo and roof tile; 72.7% of observed farmers have size of pens of 1-100; 95.5% of feed is in pasta-shaped and 4.5% is in flour; the frequency of 2 times feeding is 86.4%; mostly-used (54.5%) feed ingredient is in the form of Aking rice bran and 18.2% use pur bran; 9.1% farmers apply traditional raising management, 81.8% is semiintensive, and 9.1% is intensive; lastly, sex ratio of 1: 1 reaches 18.2%. Conclusion that the technical characteristics of Muscovy duck in Ciayumajakuning have not yet been standardized. It is expected that the farmers, relevant agencies, and other related parties can overcome the problem and seek for better and optimal management. Limitations : Research includes feed, pen, and raising management of Muscovy Duck. Value : The basis for establishing national standards for Muscovy Duck production and development.

The development of local genetic resources is important to meet the need of high demand of lamb meat in Indonesia, especially in West Java, through the selection of superior breeds of Garut sheep. The selection has to be initiated by studying the Garut sheep performances to determine the environmental factors affecting the preweaning performances of the sheep and involving those factors in the analysis of genetic parameters. The study was held on the Unit Pelayanan Teknis Dasar Balai Pengembangan Perbibitan Ternak Domba dan Kambing (UPTD-BPPTDK) Margawati Garut from August 21st to September 18th, 2019. The purpose of this experiment was to study the effect of sex and litter size on preweaning weight, i.e birth weight, weight on 30, 60, 90 days, and weaning weight (100 days). The traits were analyzed on 6.349 heads, 3.214 rams, and 3.135 ewes, from 2012 to 2019 using the General Linear Model (GLM) and Duncan multiple range test of SAS 9.0 software. The fixed effects used in the analysis were the sex and the birth type. The results showed that the performance of Garut Sheep based on the preweaning weight was affected significantly (P<0.05) by the sex, with the average of birth weight, 30, 60, 90 days weight and weaning weight (100 days) were 2.46 kg, 5.64 kg, 7.73 kg, 9.92 kg, 10.97 kg (rams) and 2.33 kg, 5.42 kg, 7.34 kg, 9.36 kg, and 10.28 kg (ewes). The pre-weaning weight was also significantly affected (P<0.05) by the birth type, in which  the average of birth weight, 30, 60, 90 days weight and weaning weight (100 days) were 2.96 kg, 6.49 kg, 8.98 kg, 11.29 kg, 12.52 kg (single), 2.25 kg, 5.09 kg, 6.78 kg, 8.71 kg, 9.52 kg (twin), 1.79 kg, 4.62 kg, 6.24 kg, 8.09 kg, 8.92 kg (triplet), 1.54 kg, 4.53 kg, 5.89 kg, 7.15 kg, 8.03 kg (quadruplet), and 1.51 kg, 3.84 kg, 5.23 kg, 6.58 kg, 7.15 kg (quintuplet). Based on the results, preweaning weight must be corrected by the sex and the birth type before the genetic parameters are analyzed to avoid bias of selection results.

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Salman LB, Djaja W, Anang A, Indrijani H, Partasasmita R. 2017. Birth weight of a Holstein calf based on forefoot circumference. Nusantara Bioscience 9: 367-370. Record of birth weight of Holstein calf can be used as consideration for selection. The purpose of this study is to determine the accuracy of birth weight based on regular measuring tape compared to Calf scale BW Tape. The records of calf’s birth weight were collected from 1370 female calf birth records from PT Taurus Dairy Farm, Sukabumi. Birth weight measurements were performed by (i) measuring birth weight using Calf scale BW Tape (Nasco, Fort Atkinson, WI); (ii) predicting birth weight with regression based on the circumference of the right front toenails using regular measuring tape a day after the calf was born; (iii) weighing the calf with the scales. The results showed that the predicted birth weight of dairy cow’s calves can be done by regular measuring tape with a polynomial regression equation, Y=(-6288,6)+(1378.8X)-(113.0X2)+(4.1X3)-(0.056X4), which has a deviation 0.5%, and 7.4% using Calfscale BW Tape. Conclusion of this research is that predicting birth weight of dairy cow’s calves using regular measuring tape is more accurate than using Calfscale BW Tape