{
  "abstract": "In practical beef cattle monitoring scenarios, automated body condition scoring (BCS) based on single-frame visual information can be affected by posture variation, occlusion, and image quality changes. This study proposed an episode-level BCS assessment framework using synchronized RGB-D videos, integrating multi-frame visual information, attention-based multiple instance learning (Attention-MIL), and a dorsal geometry-based quality control mechanism to improve reliability under complex acquisition conditions. The publicly available Raramuri Criollo dataset was reorganized into a dataset containing 3815 RGB-D frame pairs, 52 animal identity groups, and 151 episodes, and evaluated using animal-wise three-fold cross-validation. Predictions were generated only when an episode contained at least three quality-filtered frames and reliable angle estimation. With an average coverage of 0.7345 after quality gating, the final model achieved 61.66% accuracy, a Macro-F1 score of 0.5680, and a quadratic weighted kappa (QWK) of 0.6339 for five-class BCS classification. Additionally, 89.71% of predictions were within one BCS category of the reference scores. Three-class management classification achieved a Macro-F1 score of 0.8059. Ablation experiments showed complementary contributions from RGB and depth information, and the combined angle and quality-statistic features improved several metrics in the original ablation. Additional matched experiments did not establish an independent angle benefit but supported multi-frame aggregation and within-Episode prediction consistency. The proposed RGB-D multi-frame fusion approach demonstrates potential for automated beef cattle body condition monitoring under controlled acquisition conditions.",
  "abstract_shown": true,
  "affiliations": [
    "College of Information Science and Engineering, Shanxi Agricultural University, Jinzhong 030801, China.",
    "Shanxi Province Science and Technology Information Research Center, Taiyuan 030027, China."
  ],
  "article_type": "research article",
  "arxiv": null,
  "author_total": 8,
  "authors": [
    {
      "affs": [
        0
      ],
      "name": "Zhen Hou",
      "orcid": "0000-0002-5476-1441"
    },
    {
      "affs": [
        0
      ],
      "name": "Weinan Cao",
      "orcid": "0009-0007-9595-5588"
    },
    {
      "affs": [
        0
      ],
      "name": "Wei He"
    },
    {
      "affs": [
        0
      ],
      "name": "Yanwen Li"
    },
    {
      "affs": [
        0
      ],
      "name": "Jiarui Li"
    },
    {
      "affs": [
        0
      ],
      "name": "Di Wu"
    },
    {
      "affs": [
        1
      ],
      "name": "Ruiping Wang"
    },
    {
      "affs": [
        0
      ],
      "name": "Hua Yang"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/0vk78q84p2kwd.bib",
  "cited_by": 0,
  "doi": "10.3390/ani16193040",
  "fulltext_url": "https://europepmc.org/articles/PMC13663532",
  "id": "0vk78q84p2kwd",
  "issns": [
    "2076-2615"
  ],
  "landing_url": "https://europepmc.org/article/MED/42883009",
  "language": "eng",
  "licence": "CC-BY",
  "licence_label": "CC BY",
  "licence_source": "article",
  "licence_url": "https://creativecommons.org/licenses/by/4.0/",
  "metadata_licence": null,
  "native_subjects": [
    [
      "openalex",
      "1110|Smart Agriculture and AI"
    ]
  ],
  "openalex": "W7214627099",
  "pdf_url": "https://europepmc.org/articles/PMC13663532?pdf=render",
  "pmcid": "PMC13663532",
  "pmid": "42883009",
  "published": "2026-09-27",
  "publisher": null,
  "ris": "https://research.draconitic.com/paper/0vk78q84p2kwd.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T12:19:16Z",
      "native_id": "MED:42883009",
      "source": "europepmc",
      "url": "https://europepmc.org/article/MED/42883009"
    }
  ],
  "subjects": [
    {
      "field": "biology",
      "origin": "openalex:1110|Smart Agriculture and AI",
      "subfield": "plant-biology"
    }
  ],
  "title": "Quality-Gated Episode-Level RGB-D Body Condition Scoring in Beef Cattle.",
  "title_text": "Quality-Gated Episode-Level RGB-D Body Condition Scoring in Beef Cattle.",
  "type": "peer-reviewed",
  "updated_at": "2026-10-30T12:19:16Z",
  "url": "https://research.draconitic.com/paper/0vk78q84p2kwd",
  "venue": "Animals : an open access journal from MDPI",
  "versions": []
}