Animals (Dec 2024)

Predicting Body Weight from Birth to Old Age in Giant Pandas Using Machine Learning

  • Xingyong Zhu,
  • Jiaheng Li,
  • Jie Gao,
  • Jingchao Lan,
  • Mingxi Li,
  • Jue Deng,
  • Wenpei Peng,
  • Yongyou Feng,
  • Bi Li,
  • Huizhong Pang,
  • Jiawen Liu,
  • Jie Kou,
  • Ye Wang

DOI
https://doi.org/10.3390/ani14243694
Journal volume & issue
Vol. 14, no. 24
p. 3694

Abstract

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The giant panda (Ailuropoda melanoleuca) is one of the animals with the largest body weight differences between its birth and adult stages, where the newborn cub is 0.1% the size of its mother. The rapid growth of panda cubs has been reported previously, but little is known about the growth pattern of their entire lifetime. In this study, we analyzed body weight records from 206 captive giant pandas collected between 2000 and 2022. The dataset comprised 26,340 measurements, including 12,314 records from 98 males and 14,026 from 108 females, with the oldest male and female being 32 and 37 years old, respectively. Utilizing machine learning, we predicted daily body weights throughout the pandas’ lifespan, allowing us to establish detailed daily normative body weight ranges from birth to advanced age. This study presents the first comprehensive analysis of lifetime body weight distribution in giant pandas, enhancing our understanding of their developmental biology and informing improved body weight management strategies for captive populations.

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