<![CDATA[This study presents the design and performance evaluation of a low-cost automated egg sorting system utilizing a TCS34725 color sensor and Arduino Uno microcontroller for small-scale poultry operations. The system classifies chicken and duck eggs based on real-time RGB value measurements integrated with servo motor actuators and conveyor mechanisms for automated separation. Experimental testing was conducted on 12 samples comprising 6 chicken eggs and 6 duck eggs under variable ambient lighting conditions. The TCS34725 sensor successfully differentiated eggshell colors based on RGB value variations, with chicken eggs exhibiting higher values due to lighter coloration compared to darker duck eggs. System performance achieved classification accuracy ranging from 90% to 95%, with a mean sorting time of 4 to 8 seconds per egg and an operational cost of approximately Rp2–3 per egg. Primary classification errors were attributed to misaligned egg positioning and ambient lighting variations. Despite these limitations, the system demonstrated reliable automated operation suitable for resource-constrained agricultural contexts. The findings validate the feasibility of employing low-cost RGB sensors as viable alternatives to expensive industrial vision systems for species-based egg classification. This research contributes practical insights for implementing affordable automation technologies in small to medium-scale poultry farms, supporting the broader adoption of smart farming practices in developing agricultural economies.]]>
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