precision agriculture through the eye of a plant breeder...plant growth and biomass yidd. digital...

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Photo from T. Rocheford Michael Gore Plant Breeding and Genetics Section School of Integrative Plant Science Cornell University Precision agriculture through the eye of a plant breeder

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Page 1: Precision agriculture through the eye of a plant breeder...plant growth and biomass yidd. DIGITAL PHENOTYPE and microclimate ænsor will be aged to construct a 3D image of ach plant,

Photo from T. Rocheford

Michael GorePlant Breeding and Genetics SectionSchool of Integrative Plant Science

Cornell University

Precision agriculture through the eye of a plant breeder

Page 2: Precision agriculture through the eye of a plant breeder...plant growth and biomass yidd. DIGITAL PHENOTYPE and microclimate ænsor will be aged to construct a 3D image of ach plant,

Infrared thermometer

High-clearance tractor

Multi-spectral crop canopy sensor

Apogee

ACS-470 3-band

Ultrasonic Transducer

Pulsar db 3-m

Canopy Tm

Canopy height

Canopy reflectance

Average speed of 2.82 km/h1 data point/meter (1 Hz)

GPS-RTK (antenna)

Data loggers (CR1000 + CR3000)

GPS-RTK (receiver and radio)

Plant Phenotyping system: Cotton

Page 3: Precision agriculture through the eye of a plant breeder...plant growth and biomass yidd. DIGITAL PHENOTYPE and microclimate ænsor will be aged to construct a 3D image of ach plant,

ARPAE DOE TERRA-MEPP (Mobile Energy-crop Phenotyping Platform) University of Illinois, Urbana, IL; PI Stephen P. Long with several CoPIs including Cornell University

Page 4: Precision agriculture through the eye of a plant breeder...plant growth and biomass yidd. DIGITAL PHENOTYPE and microclimate ænsor will be aged to construct a 3D image of ach plant,

Artificial intelligence combined with small UAS: daily high-throughput phenotyping and monitoring of Northern corn leaf blight in maize

Autonomous robots work side-by-side with humans to enhance plant phenotyping, alert humans of suspected pathologies, and track disease spread dynamics

NSF National Robotics Initiative CoPIs: Hod Lipson, Columbia Univ. and Rebecca Nelson, Cornell Univ.

Page 5: Precision agriculture through the eye of a plant breeder...plant growth and biomass yidd. DIGITAL PHENOTYPE and microclimate ænsor will be aged to construct a 3D image of ach plant,

Software running on the mobile phone can process an image taken by the phone's camera and determine statistically the probability of different diseases. The diagnosis can be uploaded to a server where results can be seen in real-time on a map.

Automated detection of cassava mosaic disease with deep learning algorithms

Ernest Mwebaze, Makerere University in Uganda