Review: Teknologi Simple Phenotyping sebagai Database Pengembangan Robot Pendeteksi dan Pemupuk Nitrogen Padi

Abstract

Rice is one of the most important staple food consumed by more than half of the world population, especially in Indonesia where majority of the people consumed rice as daily intake. Precision agriculture is needed to boost production to meet the demand. As limiting factor for plant growth, huge doses of nitrogen fertilizer are deployed, in fact the absorbtion rate of plant was only about 50%. Developing vision-control based robot for fertilizing plant need proper database so that false positive and negative could be avoided. Several previous methods that were available to assest nitrogen status in plant such as a color chart, spectrometer, SPAD-502, and kjedahl. Plant phenotyping is often used for plant breeding, but also very useful in determining nutrient status in plants. Cheap and simple phenotyping using digital camera followed by extracting data through open source platform such as ImageJ can be very useful to generate data for building the database. Here we presented the current progress on plant phenotyping for nitrogen assessment in plant as well as an ImageJ in phenomic era. We also highlight some robotic progress especially vision-based robot, who rely on proper imaging data for their training.