Institute of Crop Science, NARO

Development of Method for evaluating vegetation fraction for rice plants using UAV imagery

Along with DNA analysis genes involved in vegetation fraction are identified

National Agriculture and Food Research Organization (NARO) has developed a method for evaluating the vegetation fraction for rice plant using images captured by Unmanned Aerial Vehicle (UAV). This method can give more objective results within 1/20 of the working time compared to conventional visual inspection. Vegetation fraction is one of the important characteristics of crop productivity, but it is easily influenced by the environment and difficult to measure objectively and efficiently. Until now, accurate selection has not been possible, which has been a bottleneck for breeding. By combining the data collected by the developed method and DNA analysis, we identified genes related to the vegetation fraction at four locations on the chromosome. With the help of these genes, it is expected that the cultivation of highly productive rice varieties will become more efficient in the future.


NARO has developed a method to quantify and evaluate the difference in the vegetation fraction in the early stage of growth of rice plants from aerial images by drones. In this survey method, sufficient images for the survey can be obtained by means of shooting images of 400 types of rice cultivated in the field of 10a in a span of about 10 minutes by drone. We can obtain more objective results in 1/20 of the working time by this method compared to the conventional visual survey method.

By combining the developed survey method and DNA analysis for about 3,000 rice plants which were bred for the study, genes related to vegetation fraction were identified at four locations on the chromosome. Further analysis revealed that rice with genes that increased vegetation fraction also increased biomass, and some genes also increased grain (brown rice) yields. The identified genes are expected to be used in the selection of DNA markers for highly productive Japanese-type rice varieties, and to help improve their efficiency.

Reference Information

Daisuke Ogawa, Toshihiro Sakamoto, Hiroshi Tsunematsu, Noriko Kanno, Yasunori Nonoue, Jun-ichi Yonemaru. Haplotype analysis from UAV imagery of rice MAGIC population for the trait dissection of biomass and plant architecture. Journal of Experimental Botany URL: