Toward Global Agricultural Cloud Masayuki HIRAFUJI* ** Yasuyuki HAMADA* Tomokazu YOSHIDA* Atsushi ITOH * Takuji KIURA * * NARO National Agriculture and Food Research Organization ** University of Tsukuba

“Big Data” Has Been Dream in Agriculture Plant growth is complex system. Environment is complex system. Maximization of income Minimization of pollution Maximization of plant growth Modeling by learning Analysis between genome and phonotype

Nonlinear Regression Models Using Artificial Neural Networks (studied since 20 years ago) Predicted Yield Recommendation of fertilizer … Last year’s application of fertilizer Accumulated air temperature. Accumulated soil temperature Accumulated soil moisture Last year’s yield

Field Servers for Continuous Data Collection

Low-cost USB DNA Sequencer

Nanopore Technology

More phenotypic data is needed for breeding.

Phenomics vs. Genomics Gene + ome = Genome Genome + ics = Genomics Phenotype + ome = Phenome Phenome + ics = Phenomics

Genome Data >> Phenome Data by High-throughput Phenotyping Nanopore Sequencer Sensors in Fields Genotypic Data << Phenome Data Environment Data Genome Data >> Phenome Data Environment Data

by Open Field Server (Open-FS) Massive Deployment by Open Field Server (Open-FS) Wi-Fi LED garden light with IR sensor Solar panel Photo sensors Inside temperature sensor Soil temperature sensor Soil moisture sensor

Field Twitter (Open-FS) Has Been Improved. 樹体水分センサ

Towards A Field Phenomics Center Wi-Fi Router 1km Phenotype data Calibration data for remote sensing Memuro Campus of HARC, NARO

Tweeting data

Tweeting data

Tweeting data

Collecting Microscopic Data by A Smartphone with A Macro Lens A macro lens for iPhone Stomata on beet leaves can be measured.

Products with Twitter

Plant Sensor

Data of Agricultural Machinery

Data stream on agricultural machinery Petition (GPS) Speed Power Fuel consumption Steering Vibration Yield Fertilizer Chemical

Reprinted from the Proceeding of AgEng 2011 , pp.294, 2011 XML by iGreen Project for Agricultural Machine EU (Germany) leading. USA has a same project (AgGateway) ・ Reprinted from the Proceeding of AgEng 2011 , pp.294, 2011

Farm management data

Contents of FIX-pms Common Data Format for Farm Management Data

How Can We Combine Data? API of Cloud Services Can Be A Method.

Let’s Make Big Data for Agriculture! Applicayions Developing New Businesses Decision Support System Precision Farming GAP Models API （Application Interface） New Apps and Businesses CLOP: CLoud Open Platform in agriculture API API API API Consortium Faming Data Field Data Sensor data of Agr-Machines Others 移動監視 SNS Smartphones UAV Satellites etc. Sensor Networks Such As Field Server ISO11783

All Data Provided As API API of Cloud Services Satellites UAV Smartphone Variable rate fertilization Harvester equipped with yield sensor Sensor data

Mashape: Cloud API Hub https://www.mashape.com/

Mash-Up Using API for Agricultural Data (FIX-pms) on CLOP FIX FARMS APRAS

Big Data Will Be Created by Using API of Apps FIX FARMS APRAS

The Best Condition Can Be Found on Nonlinear Models Predicted yield Big data Yield Fertilizer Soil temperature Soil moisture : … Last year’s yield Last year’s application of fertilizer This year’s application of fertilizer Accumulated soil moisture

Conclusion CLOP is conceptual framework for API mash-up. CLOP must be flexible, and will include all. ANN can utilize big data. ICT companies should provide open API. Let’s make big data together. Let’s make API of agricultural apps. Let’s open “How to use API”.