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Smartphone photos may be able to predict rice

Rice provides 20% of the world’s food energy, with expected demand rising by 60% by 2050, but climate change, more extreme weather and evolving pathogens threaten farmers’ ability to produce enough of the crop. To help better predict crop yield and how interventions may improve yield an international research team has developed an approach that farmers may be able to implement using just a smartphone. ....

Yu Tanaka , Japan General , United States , Keisuke Katsura , Eisuke Takeuchi , Kokou Ahouanton , Yu Iwahashi , Toshiyuki Takahiro , Kensuke Kawamura , Norvie Manigbas , Tomoya Watanabe , Vimal Kumamoto Semwal , Yashuhiro Tsujimoto , Kazuki Saito , Edgar Corredor , Eduardo Jose Graterol Matute , Takashi Sonam Tashi Tanaka , Raafat El Namaky , Koki Houma , Takeshita Sonam Tashi Tanaka , Salifou Goube Mairoua , Eduard Jippy , Kalimuthu Senthilkumar , Ali Ibrahim , School Of Mathematics , Japan International Research Center ,

Estimating Rice Yield with a Convolutional Neural Network Model

The demand for rice across the world has been projected to increase considerably by 2050, thereby needing viable intensification of present croplands. ....

Yu Tanaka , Kazuki Saito , Megan Craig , Convolutional Neural Network Model , School Of Environmental , Africa Rice Center , Okayama University , International Rice Research Institute , Price Yield , Study Lead Author , Associate Professor , Graduate School , Natural Science , Automation Industry Focus , Deep Learning Enables Instant , Versatile Estimation , Rice Yield Using Ground Based ,

Artificial intelligence can now estimate rice

The global demand for rice is projected to rise significantly by 2050, necessitating sustainable intensification of existing croplands. Now, Japanese researchers have made significant progress by developing deep-learning algorithms that can rapidly estimate rice yield through the analysis of thousands of photographs. The model exhibited high precision across diverse conditions and cultivars, surpassing previous methods, while effectively detecting yield differences between cultivars and also with different water management practices. ....

Yu Tanaka , Kazuki Saito , Okayama University , International Rice Research Institute , School Of Environmental , Africa Rice Center , Method Of Research , Associate Professor , Graduate School , Natural Science , Associate Professor Yu Tanaka , Learning Enables Instant , Versatile Estimation , Rice Yield Using Ground Based ,

Artificial intelligence can now estimate rice yields, according to new study

Artificial intelligence can now estimate rice yields, according to new study
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Yu Tanaka , Kazuki Saito , School Of Environmental , Africa Rice Center , Okayama University , International Rice Research Institute , Associate Professor , Graduate School , Natural Science , Deep Learning Enables Instant , Versatile Estimation , Rice Yield Using Ground Based , Plant Phenomics ,