Add to ORKGWe did field evaluations to determine the sensitivity of the cameras to phenological changes. However, the camera has not yet been calibrated with commercial sensors. There is also an app that is programing to automate the capture of images, processing them and transforming them to Kc and visualize the data
A proof of concept prototype has been developed as an open-source tool and tested for sorghum in Ind...
Filed experiments were concluded to provide proof of concept. Accurate plot segmentation results ena...
All the input variables needed for the calculation of farms' tri- dimensional performance (in terms ...
The image analysis software ( Pheno-i) can be widely applicable to any other crop to extract phenoty...
The underlying machine learning technology has been tested, developed and proven. A successful pilot...
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...
The CSA farm calculator (data capture and automatic calculations of the 7 core indicators is avaible...
Plant growth and fruiting development monitoring is required for horticulture crop and irrigation ma...
Proof of concept: the partners demonstrated a capability to detect crop onset in-season using remote...
The methodology was developed and tested at sub-national level; now a software-based tool is being d...
To strengthen the quantitative assessment of CSA effect on farm level performance, the tool was adju...
The tool is available in GitHub, it has several examples and its functions are documented for going ...
Proof of concept delivered. Three machine learning methods based on multivariable linear regressions...
Initial comparison between ground- and aerial-based tools made. Further multi-location validation re...
A proof of concept prototype has been developed as an open-source tool and tested for sorghum in Ind...
Filed experiments were concluded to provide proof of concept. Accurate plot segmentation results ena...
All the input variables needed for the calculation of farms' tri- dimensional performance (in terms ...
The image analysis software ( Pheno-i) can be widely applicable to any other crop to extract phenoty...
The underlying machine learning technology has been tested, developed and proven. A successful pilot...
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...
The CSA farm calculator (data capture and automatic calculations of the 7 core indicators is avaible...
Plant growth and fruiting development monitoring is required for horticulture crop and irrigation ma...
Proof of concept: the partners demonstrated a capability to detect crop onset in-season using remote...
The methodology was developed and tested at sub-national level; now a software-based tool is being d...
To strengthen the quantitative assessment of CSA effect on farm level performance, the tool was adju...
The tool is available in GitHub, it has several examples and its functions are documented for going ...
Proof of concept delivered. Three machine learning methods based on multivariable linear regressions...
Initial comparison between ground- and aerial-based tools made. Further multi-location validation re...
A proof of concept prototype has been developed as an open-source tool and tested for sorghum in Ind...
Filed experiments were concluded to provide proof of concept. Accurate plot segmentation results ena...
All the input variables needed for the calculation of farms' tri- dimensional performance (in terms ...