<![CDATA[Chicken eggs are a widely consumed animal food commodity, along with other products such as chicken meat, beef, and milk. Chicken eggs are produced by laying hens, scientifically known as Gallus gallus domesticus. Manual grading of chicken eggs in West Sumatra relies on subjective sensory assessment, resulting in inconsistent classification outcomes. The development of a chicken egg grading application using Android-based digital images is a solution to this problem. This study presents the development and validation of an Android-based digital image processing system for automated mass-based grading of chicken eggs using the five-grade local classification system in Payakumbuh (pelor, bujang, remban, super, and jumbo). The image processing pipeline employed Otsu thresholding for segmentation, mean filtering for noise removal, and eccentricity-based shape determination to calculate egg volume, which was subsequently converted to Mass using a density constant of 1.0801 g/cm³. A total of 100 eggs were tested: 67 for correlation analysis and 33 for validation. The system achieved a mass correlation coefficient of r = 0.9986, a volume correlation of r = 0.9976, a mass RMSE of 0.4486 g, and a volume RMSE of 0.3972 ml. Out of 67 tested samples, 64 were correctly classified (95.5% accuracy). These results confirm that the developed application can reliably replace manual grading for small-scale poultry farmers, providing a practical and measurable digital innovation for the agricultural sector. These results indicate that Android-based image processing applications exhibit small errors, enabling the designed application to be implemented. Contribution to Sustainable Development Goals (SDGs):SDG 2 (Zero Hunger)SDG 8 (Decent Work and Economic Growth).SDG 9 (Industry, Innovation and Infrastructure)SDG 12 (Responsible Consumption and Production)]]>
Copyrights © 2026
