Pengembangan Sensor Warna Daun untuk Menduga Kebutuhan Pupuk pada Tanaman Padi
Abstract
Leaf colour is an indicator of plant fertility level which can be used for predicting fertilizer need of the paddy plants. The use of leaf colour chart (LCC) is one of instruments to measure greenness level. This research used image processing technology for analysing leaf colour level according to the IRRI-LCC standard. Taking the image of paddy leaves used a cart which is equiped with a proximity sensor and a CCD camera. Proximity sensor functions sending a signal to the camera to capture an image at every certain travelling distance. The captured images were then saved in the hard disk memory. Furthermore, those images were processed with Visual Basic program for analysing leaves area and greenness level. Then, the results were transformed into an area colour map, where each patch of land contains information about fertilizer need. Beside analysing with image processing, the measurement of leaf colour level was also done manually. The result of the manual measurement was also translated into an area colour map. The results of the manual and image processing measurement were then compared for determining the accuracy level. Accuracy at the colour level 2 was 38%, the colour level 3 was 69%, and the colour level 4 was 75%. The correlation between leaf colour level and nutrient content of soil was observed by comparing the result of soil nutrient content test and leaf colour level. It was found that both averages show a strong correlation