The Research Center for Agricultural Information Technology is pursuing research using artificial intelligence (AI) and the agricultural data collaboration platform, to facilitate the realization of smart agriculture, and contribute in the realization of a super-smart society, "Society 5.0", in the field of agriculture and food.

RCAIT News

Development of "Pedigree Finder", a web-based crop family tree creation tool

National Agriculture and Food Research Organization (NARO), in collaboration with Research Organization of Information and Systems (ROIS), has developed a database "Pedigree Finder" that allows users to freely create a family tree (pedigree chart) of crops. This database has a user-friendly interface to display a pedigree chart including cultivars and lines of interest in a visible format. Crop characteristics they exhibit can also be indicated. Therefore, breeders can use this to efficiently select the optimal combination of parents for breeding cultivars with desired traits. In addition, since it can be used in the same way for multiple crop species, it is expected to be widely used as a tool for pedigree information utilization, such as for agricultural producers and consumers to understand the characteristics of cultivars. Read more


Automatic counting of planthoppers in surveys of the occurrence of rice pests by the specialized AI

The National Agricultural Food Research Organization (NARO) has developed an AI system that can automatically count rice planthoppers from pictorial images of survey boards. By automatically recognizing and counting rice planthopper individuals with an accuracy of more than 90%, the inspection time, which may take more than an hour per survey board by visual inspection, can be reduced to 3-4 minutes. This AI system will be useful for the accurate prediction of crop damage due to pests and their control. Read more


Launch of AI-based pest image diagnostic system via WAGRI

NARO, Hosei university, and Northern System Service will start providing AI based pest image diagnostic system via WAGRI intended for agricultural information service providers. Each service provider can build and provide the pest image diagnosis service for general users by utilizing this system. This system accumulates and utilizes images sent from general users thereby it aims for the continuous improvement of diagnostic accuracy. As the first step, leaf surface disease discriminator was published for four types of vegetables & fruits such as tomato, cucumber, strawberry, and eggplant. Read more


Development of new AI that can visualize image features

National Agricultural Food Research Organization (NARO), has developed an AI that can visualize the features of images that are the basis of judgment. When this AI is utilized in potato leaf disease diagnosis, it was found that we could diagnosis whether the leaf is healthy or diseased with an accuracy of 95% or more, based on the characteristics of the disease. Since this AI can clarify the basis of judgment, it is safe and reliable for the user. The developed AI is expected to be used in various fields ranging from agriculture, where AI that can explain the basis is required.Read more.

Establishment of a research center for integrating AI and big data infrastructure

As part of a structural reorganization of the National Agriculture and Food Research Organization (NARO), the Research Center for Agricultural Information Technology was established on October 1, 2018. With the aim of promoting the 'smartization' of agriculture and the food industry, external personnel with expertise in artificial intelligence (AI) will be appointed to train human resources who will be at the forefront in conduct extensive research towards the realization of smart agriculture using AI technology and big data. Read more.

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