Add to ORKGUsing e-kakashi sensor platforms to monitor conditions such as temperature, humidity and soil saturation. AI is applied to correlate that environmental data with the predefined ideal growing conditions for any particular crop
Proof of concept delivered. Three machine learning methods based on multivariable linear regressions...
International Center for Tropical Agriculture (CIAT) has a long history of collaboration with Japane...
This study has proposed a methodology to generate maps for rice zones which detailed the crop growth...
The image analysis software ( Pheno-i) can be widely applicable to any other crop to extract phenoty...
A calibration database permits an algorithme development for measurement of leaf Eh-pH-EC with porta...
Pheno i has successfully been used and validated to classify the rice Hoja Blanca virus in collabora...
We did field evaluations to determine the sensitivity of the cameras to phenological changes. Howeve...
Data collection in Bangladesh and Nepal, through government agencies, has been reached. Data analysi...
Partners network was key to the innovation. Sequenced Antenna panel distributed to Global Array site...
This technology was developed through on-station and on-farm experiments in Central Java, Indonesia ...
Proof of concept: the partners demonstrated a capability to detect crop onset in-season using remote...
The drone operated by the CIAT Phenomics Platform can take an image of 10,000 breeding lines within ...
Phenotyping and weather data from 10 locations available at project site. Other data sets are being ...
The MINCER is readily available for use and a network was established based on MINCER, called MINCER...
Data was gatherer by the end of 2020 for CIAT PAlmira, and Saldana (Colombia) and under current anal...
Proof of concept delivered. Three machine learning methods based on multivariable linear regressions...
International Center for Tropical Agriculture (CIAT) has a long history of collaboration with Japane...
This study has proposed a methodology to generate maps for rice zones which detailed the crop growth...
The image analysis software ( Pheno-i) can be widely applicable to any other crop to extract phenoty...
A calibration database permits an algorithme development for measurement of leaf Eh-pH-EC with porta...
Pheno i has successfully been used and validated to classify the rice Hoja Blanca virus in collabora...
We did field evaluations to determine the sensitivity of the cameras to phenological changes. Howeve...
Data collection in Bangladesh and Nepal, through government agencies, has been reached. Data analysi...
Partners network was key to the innovation. Sequenced Antenna panel distributed to Global Array site...
This technology was developed through on-station and on-farm experiments in Central Java, Indonesia ...
Proof of concept: the partners demonstrated a capability to detect crop onset in-season using remote...
The drone operated by the CIAT Phenomics Platform can take an image of 10,000 breeding lines within ...
Phenotyping and weather data from 10 locations available at project site. Other data sets are being ...
The MINCER is readily available for use and a network was established based on MINCER, called MINCER...
Data was gatherer by the end of 2020 for CIAT PAlmira, and Saldana (Colombia) and under current anal...
Proof of concept delivered. Three machine learning methods based on multivariable linear regressions...
International Center for Tropical Agriculture (CIAT) has a long history of collaboration with Japane...
This study has proposed a methodology to generate maps for rice zones which detailed the crop growth...