Camera color vision for crop ripeness model.

Color is the main indicator used to recognize ripeness of the agricultural products and thus determine the best time to harvest the products. In this research, a Nikon coolpix 4500 digital camera (Nikon, Japan) was used to investigate the relationship between oil content in oil palm fruit and its surface color distribution. The relationship of between oil content with optical properties for fruit color of hue was illustrated using trend line analysis of polynomial second order method. The results showed that the hue value of FFB image was highly significant in determining the oil content of oil palm fruit: Y= -0.0116x² -I- 5.2376x - 514.88; R² 0.884 where y = mesocarp oil content, x :=; hue value, R = coefficient of determination. The oil content of fruits increased with increasing hue value of fruit skin image. Apart from that, the method may include a step of acquiring predicted number of days left for optimum harvesting of the oil palm fruits by associating the predicted oil content to another model of relative ripeness of oil palm fruits correlated to oil content. To determine the best harvesting time, the method may use a triangulation method which can be deemed as the model of relative ripeness of oil palm fruits correlated to oil content. Entering the predicted oil content from the above mentioned two approaches into this model, the number of days left for optimum harvesting is predicted. The advantage of predicting the oil palm fruit maturity in real time oil palm plantation will help harvesters to immediately harvest the oil palm FFB at the correct maturity stage. Harvesting oil palm fresh fruit bunches (FFB) at the right stage of ripeness is critical to ensure optimum quality and quantity.

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