Quality assessment of lettuce using artificial neural network

• Main Authors: Valenzuela, Ira C., Puno, John Carlo V., Bandala, Argel A., Baldovino, Renann G., De Luna, Robert G., De Ocampo, Anton Louise, Cuello, Joel, Dadios, Elmer P.
• Format: text
• Published: Animo Repository 2018
• Subjects: Lettuce—Quality; Neural networks (Computer science); Manufacturing
• Online Access: https://animorepository.dlsu.edu.ph/faculty_research/1733; https://animorepository.dlsu.edu.ph/context/faculty_research/article/2732/type/native/viewcontent
• Institution: De La Salle University

The critical features in yield forecasts determination are crop health and seasonal progress. These serve as an indicator for the success of farming. Visual inspection often produces a false assumption on the quality of the lettuce crop health. To address this problem, a proposed solution is the dev...