A preliminary study on digital quantification of ocular attributes in cattle as potential non-invasive indicators of anemia

初步研究牛眼部特征的数字化量化作为潜在的非侵入性贫血指标

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Abstract

BACKGROUND: Various non-invasive indicators such as ocular attributes have been tested and validated for the assessment of anemia and vitamin A deficiency in human medical sciences with promising results. However, regarding veterinary diagnostics/prognostics, there is limited literature for photometric assessment of anemia in cattle. The present preliminary study is the first account of digital quantification of various ocular attributes in cattle (n = 36) carried out with an objective to unearth the potential of these attributes (RGB analysis and morphometry of eyeballs, and color of palpebral conjunctiva) as non-invasive predictors of RBC count, hemoglobin (Hb) and packed cell volume (PCV). RESULTS: The results showed that green (r = 0.571), blue (r = 0.706), yellow (r = 0.624), black (r = 0.712) and whiteness (r = 0.778) of cattle eye were positively and significantly (P ≤ 0.05) correlated with Hb with 67.0% predictability for overall model. Similarly, red (r= -0.536), green (r= -0.565), magenta (r= -0.409), yellow (r= -0.563), black (r = 0.700) and whiteness (r= -0.805) were highly correlated (P ≤ 0.05) with Hb with a strong overall model predictability of 67.6%. The associations with RBC count were, however, weaker and non-significant (23% predictability). CONCLUSIONS: It is concluded that various ocular attributes of cattle, particularly blue, yellow, black, whiteness and lightness, could serve as non-invasive indicators of Hb and PCV, assisting in detecting of anemia. The palpebral conjunctiva color chart developed through this preliminary data could function as an on-field point-of-care testing (POCT) tool to predict Hb and PCV levels in cattle.

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