Add to ORKGPheno i has successfully been used and validated to classify the rice Hoja Blanca virus in collaboration between CIAT and FLAR breeders and also by using this application for precision agriculture in a project funded by the UK Space Agency
This tool is available on GitHub. The users can calculate vegetation indexes, apply different traine...
Sustainable, high-yield production of crops requires transitioning from conventional agricultural me...
The underlying machine learning technology has been tested, developed and proven. A successful pilot...
The image analysis software ( Pheno-i) can be widely applicable to any other crop to extract phenoty...
The drone operated by the CIAT Phenomics Platform can take an image of 10,000 breeding lines within ...
The system is going to be tested in the next screening season. Using drones can standardize screenin...
Training materials including classroom and hands-on field exercises for drone phenotyping were devel...
Proof of concept delivered. Three machine learning methods based on multivariable linear regressions...
New HTP platforms and facilities were deployed in the reference panel evaluation in Raipur, Titabar ...
Using e-kakashi sensor platforms to monitor conditions such as temperature, humidity and soil satura...
This study has proposed a methodology to generate maps for rice zones which detailed the crop growth...
Piloted, with some study limitations identified that need to be addressed in future
Data was gatherer by the end of 2020 for CIAT PAlmira, and Saldana (Colombia) and under current anal...
Filed experiments were concluded to provide proof of concept. Accurate plot segmentation results ena...
The introduction of precision farming technologies using hightech equipment will increase the produc...
This tool is available on GitHub. The users can calculate vegetation indexes, apply different traine...
Sustainable, high-yield production of crops requires transitioning from conventional agricultural me...
The underlying machine learning technology has been tested, developed and proven. A successful pilot...
The image analysis software ( Pheno-i) can be widely applicable to any other crop to extract phenoty...
The drone operated by the CIAT Phenomics Platform can take an image of 10,000 breeding lines within ...
The system is going to be tested in the next screening season. Using drones can standardize screenin...
Training materials including classroom and hands-on field exercises for drone phenotyping were devel...
Proof of concept delivered. Three machine learning methods based on multivariable linear regressions...
New HTP platforms and facilities were deployed in the reference panel evaluation in Raipur, Titabar ...
Using e-kakashi sensor platforms to monitor conditions such as temperature, humidity and soil satura...
This study has proposed a methodology to generate maps for rice zones which detailed the crop growth...
Piloted, with some study limitations identified that need to be addressed in future
Data was gatherer by the end of 2020 for CIAT PAlmira, and Saldana (Colombia) and under current anal...
Filed experiments were concluded to provide proof of concept. Accurate plot segmentation results ena...
The introduction of precision farming technologies using hightech equipment will increase the produc...
This tool is available on GitHub. The users can calculate vegetation indexes, apply different traine...
Sustainable, high-yield production of crops requires transitioning from conventional agricultural me...
The underlying machine learning technology has been tested, developed and proven. A successful pilot...