Body weight prediction of Belgian Blue crossbred using random forest.

Objective: The aim of this study was to predict the body weight (BW) of a Belgian Blue X Friesian Holstein (BB X FH) crossbred in Indonesia based on morphometrics using random forest. Materials and Methods: A total of 26 BB X FH crossbreds were observed for BW, chest weight (CW), body length (BL), hip height (HH), wither height (WH), and chest girth (CG) from 0, 30, 60, 90, 120, 150, 180, 210, 240, 270, and 300 days of age. Stepwise regression and random forest were performed using R 3.6.1. Results: The random forest results show that CG is an important variable in estimating BW, with an important variable value of 24.49%. Likewise, the results obtained by stepwise regression show that CG can be an indicator of selection for the BB X FH crossbred. The R squared value obtained from the regression is 0.83, while the R squared value obtained from the random forest (0.86) is greater than the regression. Conclusion: In conclusion, random forest produces a better model than stepwise regression. However, a good simple equation to use to estimate BW is CG.

Evaluation of potential genetic marker for growth and carcass traits in Sumba Ongole (Bos indicus) cattle.

Objective: This study was conducted to investigate the variants of the growth hormone receptor (GHR), growth hormone-releasing hormone (GHRH), pituitary-specific transcription factor-1 (PIT1), and signal transducer and activator of transcription 5A (STAT5) genes and their effect on growth performance and dressing percentage (DP) parameters. Materials and Methods: A total of 401 DNA samples from Sumba Ongole (SO) cattle were utilized for the polymerase chain reaction-restriction fragment length polymorphism method, of which 200 samples were used for the study of DP association and 74 samples were used to investigate growth performance. The SO cattle growth performance includes the following: birth weight, weaning weight at 205 days of age, weaning average daily gain (ADG), yearling weight at 365 days of age, and post-weaning ADG. Results: The GHR, GHRH, PIT1, and STAT5A genes showed polymorphism. The highest polymorphism information content value was shown in the STAT5A gene. The highest DP value was found in the SO cattle population with the CC genotype (STAT5A), and the lowest DP value was found in the SO cattle population with the GG genotype (GHR). The GHR and STAT5A genotypes were highly associated (p < 0.05) with the DP parameter. Based on locus combination analysis, the highest DP value was found in the SO cattle population with AG|CC genotype (GHR|STAT5A) (57.85%), AG|BB|CC genotype (GHR|GHRH|STAT5A) (57.85%), and AA|BB|BB|CC genotype 18 (GHR|GHRH|PIT1|STAT5A) (56.02%). Conclusion: All investigated genes in this study were polymorphic but were not associated with several growth parameters. The GHR and STAT5A genes can be proposed as genetic markers for the high DP trait in SO cattle in Indonesia, especially the AA genotype (GHR) and CC genotype (STAT5A).

A review of dairy cattle heat stress mitigation in Indonesia.

Indonesia is a tropical country with a hot climate. In tropical nations such as Indonesia, heat stress is a key reason for the reduced productivity of dairy cattle. Heat stress is a combination of internal and external stimuli that affects an animal, raises its body temperature, and causes it to react physiologically. Most Indonesian dairy cattle are Friesian Holstein (FH), imported from European nations with a temperate environment with low temperatures in the range of 5°C-25°C. Indonesia has a tropical climate with a high ambient temperature that can reach 34°C during the day and the local relative humidity varies between 70% and 90%. Temperature and humidity are two microenvironment factors that may impact the production and heat release in FH cattle. More than 98% of the entire dairy cattle population in Indonesia is found on Java Island. On Java Island, there are between 534.22 and 543.55 thousand heads of cattle, while the dairy cattle population outside Java Island is just 6.59 thousand heads of cattle. The milk output climbs by an average of 3.34% per year, or approximately 909.64 thousand tons and the average annual growth in whole milk consumption was 0.19 L/capita. Indonesian cow milk output has been unable to keep pace with the country's increasing demand. This study aimed to review the strategies to mitigate heat stress in FH dairy cattle in Indonesia.

Genetic diversity of Gallus sp. in Southeast Asia based on d-lopp: In silico study.

Objective: This study was conducted to analyze the matrilineal structure of Gallus sp. in Southeast Asia, especially in the D-loop region. Materials and Method: A total of 563 sequences from eight countries (Laos, Myanmar, Vietnam, Malaysia, Indonesia, Cambodia, the Philippines, and Thailand) in Southeast Asia are used in this study. Data collected from National Center for Biotechnology Information (NCBI) regarding the genus Gallus sp. in a Southeast Asian country. Data analysis was performed using MEGA 7.2 and DnaSP v6. Results: In the haplotype found in Gallus sp. in Southeast Asia, there are 89 haplotypes. Using a neighbor-joining (Nj) analysis, 89 haplotypes found three haplogroups for Gallus sp. in Southeast Asia. In Southeast Asia, the genetic diversity of the d-loop is exceptionally high, with a haplotype diversity value of 0.524 to 1. Conclusion: D-loop cannot be used as a specific marker for breeds or country-specifics.

Genetic diversity of Indonesian cattle breeds based on microsatellite markers.

OBJECTIVE: This research was conducted to study the genetic diversity in several Indonesian cattle breeds using microsatellite markers to classify the Indonesian cattle breeds. METHODS: A total of 229 DNA samples from of 10 cattle breeds were used in this study. The polymerase chain reaction process was conducted using 12 labeled primers. The size of allele was generated using the multiplex DNA fragment analysis. The POPGEN and CERVUS programs were used to obtain the observed number of alleles, effective number of alleles, observed heterozygosity value, expected heterozygosity value, allele frequency, genetic differentiation, the global heterozygote deficit among breeds, and the heterozygote deficit within the breed, gene flow, Hardy-Weinberg equilibrium, and polymorphism information content values. The MEGA program was used to generate a dendrogram that illustrates the relationship among cattle population. Bayesian clustering assignments were analyzed using STRUCTURE program. The GENETIX program was used to perform the correspondence factorial analysis (CFA). The GENALEX program was used to perform the principal coordinates analysis (PCoA) and analysis of molecular variance. The principal component analysis (PCA) was performed using adegenet package of R program. RESULTS: A total of 862 alleles were detected in this study. The INRA23 allele 205 is a specific allele candidate for the Sumba Ongole cattle, while the allele 219 is a specific allele candidate for Ongole Grade. This study revealed a very close genetic relationship between the Ongole Grade and Sumba Ongole cattle and between the Madura and Pasundan cattle. The results from the CFA, PCoA, and PCA analysis in this study provide scientific evidence regarding the genetic relationship between Banteng and Bali cattle. According to the genetic relationship, the Pesisir cattle were classified as Bos indicus cattle. CONCLUSION: All identified alleles in this study were able to classify the cattle population into three clusters i.e. Bos taurus cluster (Simmental Purebred, Simmental Crossbred, and Holstein Friesian cattle); Bos indicus cluster (Sumba Ongole, Ongole Grade, Madura, Pasundan, and Pesisir cattle); and Bos javanicus cluster (Banteng and Bali cattle).

Study of Genetic Diversity among Simmental Cross Cattle in West Sumatra Based on Microsatellite Markers.

A study was conducted to assess the genetic diversity among Simmental Cross cattle in West Sumatra using microsatellite DNA markers. A total of 176 individual cattle blood samples was used for obtaining DNA samples. Twelve primers of microsatellite loci as recommended by FAO were used to identify the genetic diversity of the Simmental Cross cattle population. Multiplex DNA fragment analysis method was used for allele identification. All the microsatellite loci in this study were highly polymorphic and all of the identified alleles were able to classify the cattle population into several groups based on their genetic distance. The heterozygosity values of microsatellite loci in this study ranged from 0.556 to 0.782. The polymorphism information content (PIC) value of the 12 observed loci is high (PIC>0.5). The highest PIC value in the Simmental cattle population was 0.893 (locus TGLA53), while the lowest value was 0.529 (locus BM1818). Based on the genetic distance value, the subpopulation of the Simmental Cross-Agam and the Simmental Cross-Limapuluh Kota was exceptionally close to the Simmental Purebred thus indicating that a grading-up process has taken place with the Simmental Purebred. In view of the advantages possessed by the Simmental Cross cattle and the evaluation of the genetic diversity results, a number of subpopulations in this study can be considered as the initial (base) population for the Simmental Cross cattle breeding programs in West Sumatra, Indonesia.