Determination of the olive maturity index of intact fruits using image analysis.
In this work, the maturity index of different samples of olives was objectively assessed by image analysis obtained through machine vision, in which algorithms of color-based segmentation and operators to detect edges were used. This method allows a fast, automatic and objective prediction of olive maturity index. This prediction value was compared to maturity index (MI), generally used by olive oil industry, based on the subjective visual determination of color of fruit skin and flesh. Machine vision was also applied to the automatic estimation of size and weight of olive fruits. The proposed system was tested to obtain a good performance in the classification of the fruit in batches. When applied to several olive samples, the maturity index predicted by machine vision was in close agreement with the maturity index of fruits visually estimated, values that are currently used as standards. The evaluation of weight of fruit also provided good results (R(2) = 0.91). These results obtained by image analysis can be used as a useful method for the classification of olives at the reception in olive mill, allowing a better quality control of the production process.
IFAPA 'Venta del Llano', Crta. Nacional Bailén-Motril Km 18.5, 23620 Mengíbar, Jaén Spain.
Elena
E
Guzmán
Valorisation of Agricultural Products Department, Food and Feed Quality Unit, Walloon Agricultural Research Centre, Henseval Building, 24 Chaussée de Namur, 5030 Gembloux, Belgium.
Vincent
V
Baeten
Valorisation of Agricultural Products Department, Food and Feed Quality Unit, Walloon Agricultural Research Centre, Henseval Building, 24 Chaussée de Namur, 5030 Gembloux, Belgium.
Juan Antonio Fernández
JA
Pierna
IFAPA 'Venta del Llano', Crta. Nacional Bailén-Motril Km 18.5, 23620 Mengíbar, Jaén Spain.
José A
JA
García-Mesa
Algorithm; Image analysis; Maturity index; Olive fruit