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Lactoperoxidase potential in diagnosing subclinical mastitis in cows via image processing
Emmanuelle P E Silva1, Edgar P Moraes2, Katya Anaya3
1Postgraduate Program in Animal Production, Federal University of Rio Grande do Norte, Macaíba, Rio Grande do Norte, Brazil.
Plos One
|February 17, 2022
Summary
This study introduces a novel bio-analytical tool for cow mastitis screening using image processing and multivariate analysis. The method accurately correlates lactoperoxidase activity and somatic cell count, offering a low-cost, high-frequency diagnostic approach.
Area of Science:
- Veterinary Medicine
- Biotechnology
- Analytical Chemistry
Background:
- Mastitis is a significant concern in dairy farming, impacting animal health and milk quality.
- Accurate and efficient diagnostic tools are crucial for timely intervention and herd management.
- Current mastitis screening methods can be costly and time-consuming.
Purpose of the Study:
- To develop and validate an image processing-based bio-analytical tool for mastitis screening in cows.
- To assess the correlation between lactoperoxidase activity, somatic cell count, and image analysis data.
- To explore the potential of this method for cost-effective and high-frequency dairy chain quality control.
Main Methods:
- Collected milk samples from 48 cows across three breeds (Jersey, Gir, Guzerat).
- Utilized image processing techniques on sequential images of milk samples undergoing a lactoperoxidase activity assay.
- Applied multivariate analysis, including Principal Component Analysis (PCA), Multiple Linear Regression (MLR), and Second-Order Regression (SO), using an R statistics platform.
Main Results:
- Achieved high correlation coefficients for enzymatic activity (R2 = 0.96 by MLR, R2 = 0.98 by SO).
- Demonstrated strong correlation with somatic cell count (R2 = 0.97 by MLR, R2 = 0.99 by SO), a key mastitis indicator.
- The color change of the milk sample (white to brown) due to lactoperoxidase activity was quantitatively analyzed.
Conclusions:
- Image processing combined with multivariate analysis provides a reliable bio-analytical tool for mastitis screening.
- This method offers a low-cost, high-frequency alternative for assessing mammary gland health.
- Potential applications include dairy chain quality control and improved bovine mastitis prognosis.
