Modelling of Apple Fruit Growth by Application of Image Analysis

The possibility of RGB image processing and analysis for modelling of the development and growth of apple fruits was investigated during the two seasons under the orchards experiment in the four-years old ‘Golden Delicious’ and ‘Gala’ variety. The fruit detection depended significantly on the size and fruit’s colour of each growing stage, thus the correlation coefficients were continuously increasing from r=0.71 (2001) and r=0.73 (2002) after fruit tinning in June, up to r=0.88 (2001) and r=0.89 (2002) at harvesting in September respectively. The yield at harvest was estimated with the accuracy of 94% and 101% for ‘Golden Delicious’ and with 106% and 92% for ‘Gala’ respectively, whenever based on images captured on June 22 2001 and June 26 2002. Therefore, the image algorithm was proved to be equal or even better method for estimating the yield at harvest than the common ‘Prognosefruit’ method (accuracy 101% and 77% for ‘Golden Delicious’ and 72% and 63% for ‘Gala’ respectively