IDEAS home Printed from https://ideas.repec.org/a/gam/jagris/v15y2025i4p357-d1585522.html
   My bibliography  Save this article

Estimation of Genetic Parameters for Milk Urea Nitrogen in Iranian Holstein Cattle Using Random Regression Models

Author

Listed:
  • Mehridokht Mortazavi

    (Department of Animal Science, University of Zanjan, Zanjan 45371-38111, Iran)

  • Mohammad Bagher Zandi

    (Department of Animal Science, University of Zanjan, Zanjan 45371-38111, Iran)

  • Rostam Pahlavan

    (Animal Breeding Centre and Promotion of Animal Products, Karaj 3158-5963, Iran)

  • Moradpasha Eskandari Nasab

    (Department of Animal Science, University of Zanjan, Zanjan 45371-38111, Iran)

  • Hinayah Rojas de Oliveira

    (Department of Animal Sciences, Purdue University, 270 S. Russell St., Room 3034, West Lafayette, IN 47907-2041, USA)

Abstract

Reducing nitrogen excretion in dairy cattle is a critical factor for improving the environmental sustainability of the livestock industry. This research aimed to estimate the genetic parameters over time for the milk urea nitrogen (MUN) trait in Iranian Holstein dairy cattle. Data from 347,639 test-day records of 52,219 first-parity Iranian Holstein dairy cows (spanning 2018 to 2023), were sourced from the Iranian National Animal Breeding Center. A single-trait random regression test-day animal model was used for the genetic evaluation of MUN. Three orders of Legendre orthogonal polynomials (ranging from 1 to 3) were tested to fit the fixed curve, additive genetic effects, and permanent environmental effects. Based on the AIC, BIC, and residual variances to compare the models, the third order was considered as the appropriate order for this dataset. The average heritability and repeatability of the MUN trait were estimated to be 0.027 and 0.081, respectively. The average estimates for additive genetic variance, permanent environmental variance, and phenotypic variance were 0.14, 0.28, and 5.17, respectively. The genetic trend analysis revealed that the MUN trait exhibited fluctuations across birth years (2016–2021), with an overall negative trend. Importantly, the average MUN levels remained within the desirable range of 13–16 mg/dL for Iranian Holstein cows across calving years from 2019 to 2023. Despite the low heritability estimates, the genetic parameters obtained in this study are valuable for improving MUN in Iranian dairy cattle. These findings provide critical insights for designing effective breeding programs aimed at reducing nitrogen excretion and promoting environmental sustainability in the dairy industry.

Suggested Citation

  • Mehridokht Mortazavi & Mohammad Bagher Zandi & Rostam Pahlavan & Moradpasha Eskandari Nasab & Hinayah Rojas de Oliveira, 2025. "Estimation of Genetic Parameters for Milk Urea Nitrogen in Iranian Holstein Cattle Using Random Regression Models," Agriculture, MDPI, vol. 15(4), pages 1-16, February.
  • Handle: RePEc:gam:jagris:v:15:y:2025:i:4:p:357-:d:1585522
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2077-0472/15/4/357/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2077-0472/15/4/357/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. ChaoQing Yu & Xiao Huang & Han Chen & H. Charles J. Godfray & Jonathon S. Wright & Jim W. Hall & Peng Gong & ShaoQiang Ni & ShengChao Qiao & GuoRui Huang & YuChen Xiao & Jie Zhang & Zhao Feng & XiaoTa, 2019. "Managing nitrogen to restore water quality in China," Nature, Nature, vol. 567(7749), pages 516-520, March.
    2. Evan Perrault, 2011. "E. Melanie DuPuis: Nature’s perfect food: how milk became America’s drink," Agriculture and Human Values, Springer;The Agriculture, Food, & Human Values Society (AFHVS), vol. 28(4), pages 583-584, December.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Heng Liu & Caizhu Huang & Heng Lian & Xia Cui, 2023. "Hierarchical Spatially Varying Coefficient Process Regression for Modeling Net Anthropogenic Nitrogen Inputs (NANI) from the Watershed of the Yangtze River, China," Sustainability, MDPI, vol. 15(16), pages 1-15, August.
    2. Jianqin Ma & Yongqing Wang & Lei Liu & Bifeng Cui & Yu Ding & Lansong Liu, 2025. "Research on Summer Maize Irrigation and Fertilization Strategy in Henan Province Based on Multi-Objective Optimization Model," Sustainability, MDPI, vol. 17(5), pages 1-13, February.
    3. Li Wang & Siyuan Liu & Wendi Xuan & Shaopeng Li & Anlei Wei, 2022. "Efficient Nitrate Adsorption from Groundwater by Biochar-Supported Al-Substituted Goethite," Sustainability, MDPI, vol. 14(13), pages 1-24, June.
    4. Mingqing Liu & Yuncheng Wu & Sijie Huang & Yuwen Yang & Yan Li & Lei Wang & Yunguan Xi & Jibing Zhang & Qiuhui Chen, 2022. "Effects of Organic Fertilization Rates on Surface Water Nitrogen and Phosphorus Concentrations in Paddy Fields," Agriculture, MDPI, vol. 12(9), pages 1-12, September.
    5. Mengru Wang & Benjamin Leon Bodirsky & Rhodé Rijneveld & Felicitas Beier & Mirjam P. Bak & Masooma Batool & Bram Droppers & Alexander Popp & Michelle T. H. Vliet & Maryna Strokal, 2024. "A triple increase in global river basins with water scarcity due to future pollution," Nature Communications, Nature, vol. 15(1), pages 1-13, December.
    6. Wang, Zhong-Jun & Yue, Fu-Jun & Wang, Yu-Chun & Qin, Cai-Qing & Ding, Hu & Xue, Li-Li & Li, Si-Liang, 2022. "The effect of heavy rainfall events on nitrogen patterns in agricultural surface and underground streams and the implications for karst water quality protection," Agricultural Water Management, Elsevier, vol. 266(C).
    7. Duan, Chenxiao & Li, Jiabei & Zhang, Binbin & Wu, Shufang & Fan, Junliang & Feng, Hao & He, Jianqiang & Siddique, Kadambot H.M., 2023. "Effect of bio-organic fertilizer derived from agricultural waste resources on soil properties and winter wheat (Triticum aestivum L.) yield in semi-humid drought-prone regions," Agricultural Water Management, Elsevier, vol. 289(C).
    8. Kiyotaka Tsunemi & Tohru Kawamoto & Hideyuki Matsumoto, 2023. "Estimation of the Potential Global Nitrogen Flow in a Nitrogen Recycling System with Industrial Countermeasures," Sustainability, MDPI, vol. 15(7), pages 1-12, March.
    9. Panpan Ji & Jianhui Chen & Ruijin Chen & Jianbao Liu & Chaoqing Yu & Fahu Chen, 2024. "Nitrogen and phosphorus trends in lake sediments of China may diverge," Nature Communications, Nature, vol. 15(1), pages 1-9, December.
    10. Qinyi Huang & Yu Zhang, 2021. "Decoupling and Decomposition Analysis of Agricultural Carbon Emissions: Evidence from Heilongjiang Province, China," IJERPH, MDPI, vol. 19(1), pages 1-16, December.
    11. Taotao Chen & Erping Cui & Yanbo Zhang & Ge Gao & Hao You & Yurun Tian & Chao Hu & Yuan Liu & Tao Fan & Xiangyang Fan, 2024. "Microbial Network Complexity Helps to Reduce the Deep Migration of Chemical Fertilizer Nitrogen Under the Combined Application of Varying Irrigation Amounts and Multiple Nitrogen Sources," Agriculture, MDPI, vol. 14(12), pages 1-18, December.
    12. Ouping Deng & Sitong Wang & Jiangyou Ran & Shuai Huang & Xiuming Zhang & Jiakun Duan & Lin Zhang & Yongqiu Xia & Stefan Reis & Jiayu Xu & Jianming Xu & Wim Vries & Mark A. Sutton & Baojing Gu, 2024. "Managing urban development could halve nitrogen pollution in China," Nature Communications, Nature, vol. 15(1), pages 1-16, December.
    13. Richard W. McDowell & Dongwen Luo & Peter Pletnyakov & Martin Upsdell & Walter K. Dodds, 2025. "Anthropogenic nutrient inputs cause excessive algal growth for nearly half the world’s population," Nature Communications, Nature, vol. 16(1), pages 1-15, December.
    14. Wang, Tian & Xiao, Wenfa & Huang, Zhilin & Zeng, Lixiong, 2022. "Interflow pattern govern nitrogen loss from tea orchard slopes in response to rainfall pattern in Three Gorges Reservoir Area," Agricultural Water Management, Elsevier, vol. 269(C).
    15. Kolluru, Venkatesh & John, Ranjeet & Saraf, Sakshi & Chen, Jiquan & Hankerson, Brett & Robinson, Sarah & Kussainova, Maira & Jain, Khushboo, 2023. "Gridded livestock density database and spatial trends for Kazakhstan," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 10, pages 1-15.
    16. Yixuan Yang & Tongqian Zhao & Huazhe Jiao & Li Wu & Chunyan Xiao & Xiaoming Guo, 2022. "Types and Distribution of Organic Amines in Organic Nitrogen Deposition in Strategic Water Sources," IJERPH, MDPI, vol. 19(7), pages 1-17, March.
    17. Binhui Chen & Xiuming Zhang & Baojing Gu, 2025. "Managing nitrogen to achieve sustainable food-energy-water nexus in China," Nature Communications, Nature, vol. 16(1), pages 1-14, December.
    18. Wang, Hongzhang & Ren, Hao & Zhang, Lihua & Zhao, Yali & Liu, Yuee & He, Qijin & Li, Geng & Han, Kun & Zhang, Jiwang & Zhao, Bin & Ren, Baizhao & Liu, Peng, 2023. "A sustainable approach to narrowing the summer maize yield gap experienced by smallholders in the North China Plain," Agricultural Systems, Elsevier, vol. 204(C).
    19. Xing Yan & Yongqiu Xia & Xu Zhao & Chaopu Ti & Longlong Xia & Scott X. Chang & Xiaoyuan Yan, 2025. "Coupling nitrogen removal and watershed management to improve global lake water quality," Nature Communications, Nature, vol. 16(1), pages 1-9, December.
    20. Hou, Peng & Liu, Lu & Tahir, Muhammad & Li, Yan & Wang, Xuejun & Shi, Ning & Xiao, Yang & Ma, Changjian & Li, Yunkai, 2024. "Effect of fertilization on emitter clogging in drip irrigation using high sediment water: Perspective of sediment discharge capacity," Agricultural Water Management, Elsevier, vol. 294(C).

    More about this item

    Keywords

    ;
    ;
    ;
    ;

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jagris:v:15:y:2025:i:4:p:357-:d:1585522. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.