Comparing quality parameters obtained using destructive and optical methods in grading tomatoes

• Published in: Ciência agronômica Vol. 52; no. 3
• Main Authors: Silva, Thainara Rebelo da, Costa, Anderson Gomide, Paes, Juliana Lobo, Oliveira, Marcus Vinícius Morais de, Pinto, Francisco de Assis de Carvalho
• Format: Journal Article
• Language: English; Portuguese
• Published: Universidade Federal do Ceará 01.01.2021
• Subjects: AGRONOMY; Artificial neural networks; Biospeckle laser; Fruit ripening; Physico-chemical variables; Redes neurais artificias; Artificial neural networks; Physico-chemical variables; Maturação de frutos; Fruit ripening; Variáveis físico-químicas; Biospeckle laser

ABSTRACT Optical methods for analysing fruit quality have various advantages compared to conventional methods, including not destroying the sample and the possibility of automating the quality control process. The aim of this study was to compare artificial neural networks developed from biological...