Correlation between dry matter intake and weight gain in bali cattle

Authors

  • Hamdi Mayulu Animal Husbandry Department of Agricultural Faculty, Mulawarman University Author
  • Ika Wahyuningsih Animal Husbandry Department of Agricultural Faculty, Mulawarman University, Kampus Gunung Kelua Jalan Pasir Belengkong Samarinda 75123, East Kalimantan, Indonesia Author

DOI:

https://doi.org/10.30872/jtpc.v9i2.308

Keywords:

Bali cattle; dry matter intake; body weight; livestock growth; productivity

Abstract

Beef cattle productivity is strongly influenced by the quality and quantity of feed provided. Dry matter intake (DMI) is a key indicator of nutritional adequacy. Previous studies have been largely descriptive and have not emphasized the quantitative relationship between DMI and growth performance of Bali cattle under intensive smallholder farming systems.

This study analyzed the correlation between dry matter intake and body weight gain in male Bali cattle raised intensive management. The research was conducted in Kutai Kartanegara Regency, East Kalimantan Province, involving 45 respondents, with a total of 180 male Bali cattle. Data were collected through field surveys, body weight measurements, and laboratory analyses of the feed dry matter content. Statistical analyses were performed using Pearson’s correlation and simple linear regression.

The results indicated that the average daily body weight gain of the Bali cattle reached 0.48 kg/head/day. Dry matter intake was positively and significantly correlated with body weight gain (r= 0.777; p < 0.01) using the regression equation Y= 8.159 + 0.483X. These findings confirm that increasing the DMI directly enhances the growth performance of Bali cattle.

The study concluded that feed management emphasizing dry matter intake optimization is essential to support the productivity of local beef cattle.

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References

[1] FAO. (2021). The state of food and agriculture 2021. Food and Agriculture Organization of the United Nations, Rome.

[2] Rojas-Downing, M.M., Knapp, J.R. and Parsons, J.E. (2022). Sustainable beef production and nutritional efficiency: A review. Sustainability, 14(2), 854. https://doi.org/10.3390/su14020854

[3] Tedeschi, L.O., Fox, D.G. and Fonseca, M.A. (2021). Evaluating beef cattle nutrition and dry matter intake prediction models. Animal, 15(3), 100203. https://doi.org/10.1016/j.animal.2021.100203

[4] Almeida, D.M., Paulino, M.F., Rennó, L.N., Marcondes, M.I. and Valadares Filho, S.C. (2021). Dry matter intake and performance of beef cattle under tropical conditions. Journal of Animal Science, 99(3), 1-12. https://doi.org/10.1093/jas/skab056

[5] Suryani, A., Widi, T.S.M. and Yani, A. (2022). Productivity and genetic potential of Bali cattle under smallholder farming systems. Tropical Animal Health and Production, 54(5), 287. https://doi.org/10.1007/s11250-022-03126-2

[6] Liu, J., Zhang, R. and Xu, G. (2022). Dry matter intake and nutrient utilization in beef cattle: A meta-analysis. Animal Feed Science and Technology, 289, 115317. https://doi.org/10.1016/j.anifeedsci.2022.115317

[7] Puspitasari, N., Widjaja, E.A. and Santoso, B. (2023). Local feed resources and dry matter intake in smallholder beef cattle systems. Tropical Animal Health and Production, 55(4), 189. https://doi.org/10.1007/s11250-023-03562-5

[8] Tedeschi, L.O., et al. (2023). Harnessing extant energy and protein requirement systems to improve efficiency. Animal, 17(8), 101010. https://doi.org/10.1016/j.animal.2023.101010

[9] Zhang, H., Li, X. and Chen, Y. (2023). Big data-based prediction of dry matter intake in beef cattle. Frontiers in Animal Science, 4, 112233. https://doi.org/10.3389/fanim.2023.112233

[10] Xu, T., Li, Y. and Wang, J. (2022). Precision nutrition approaches in beef cattle production systems. Frontiers in Veterinary Science, 9, 932877. https://doi.org/10.3389/fvets.2022.932877

[11] AOAC. (2019). Official Methods of Analysis (21st ed.). Association of Official Analytical Chemists, Arlington.

[12] Wei L., W., B. Ye, B. Wu, X. Yi, X. Li, R, X. Cui, Z. Zhou, Y. Cheng, X. Zhu, X. Tang, X. Fu, N. Li, H. Wu, and Z. Zhou. 2024. Effect of Total Mixed Ration on Growth Performance, Rumen Fermentation, Nutrient Digestion, and Rumen Microbiome in Angus Beef Cattle during the Growing and Fattening Phases. Fermentation 10, 205. https://doi.org/10.3390/fermentation10040205

[13] Hidayat, J., Panjaitan, T., Dahlanuddin, P., Halliday, M.J. and Shelton, H.M. (2024). Utilising locally based energy supplements in leucaena and corn stover diets to increase growth rate and profitability of Bali cattle. Animal Production Science, 64(6), AN23217. https://doi.org/10.1071/AN23217

[14] Abu Tani, S.A., Putra, A.R., Sari, D.N. and Wibowo, H. (2025). Indonesian herbal mixture improves dry matter intake and growth performance of transported Bali cattle. American Journal of Animal and Veterinary Sciences, 20(2), 145-152. https://doi.org/10.3844/ajavsp.2025.145.152

[15] Fernandes, L.D., Silva, R.C. and Gomes, M.A. (2024). Effects of different additives on cattle feed intake and performance: A systematic review and meta-analysis. Anais da Academia Brasileira de Ciências, 96(1),e20231234.https://doi.org/10.1590/0001-3765202496123

[16] Sutaryono, Y.A., Gunawan, A., Prasetyo, R. and Putri, E.D. (2025). Nutrient-rich feed supplementation accelerates recovery of Bali cattle affected by foot-and-mouth disease. Journal of Advanced Veterinary and Animal Research, 12(1), 106–116. https://doi.org/10.5455/javar.2025.i12

[17] Shaffer, W.R., McCabe, B.E. and Brown, E.G. (2025). Phenotypic plasticity and genotype-by-environment interactions for dry matter intake and respiration across temperature-humidity gradients. Journal of Animal Science, 103(4), skaf115. https://doi.org/10.1093/jas/skaf115

[18] Duan, H., Zhao, Y., Wang, L. and Chen, J. (2025). Anti-heat stress supplementation increased dry matter intake and alleviated heat stress in beef cattle. Frontiers in Veterinary Science, 12, 1562964. https://doi.org/10.3389/fvets.2025.1562964

[19] Blake, N.E., Smith, J.R. and Thompson, P. (2023). Predicting dry matter intake in beef cattle using machine learning approaches. Animals, 13(17), 2772. https://doi.org/10.3390/ani13172772

[20] Maciel, A.S. and Duff, G.C. (2025). Integrating precision technologies in beef cattle production systems. Frontiers in Veterinary Science, 12, 13391906. https://doi.org/10.3389/fvets.2025.13391906

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Published

2025-12-16

How to Cite

Correlation between dry matter intake and weight gain in bali cattle. (2025). Journal of Tropical Pharmacy and Chemistry , 9(2). https://doi.org/10.30872/jtpc.v9i2.308

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