Computer vision and agriculture to develop a practical solution for African breeding program

Dr Mbaye Modou is presenting his research on computer vision for counting sorghum grains using a mobile phone. Dr. Mbaye’s work combines the fields of computer vision and agriculture to develop a practical solution for African breeding program.
Accurately counting sorghum grains manually can be a time-consuming and labor-intensive task.
By leveraging the power of mobile phone cameras and sophisticated image processing algorithms, Dr. Mbaye has developed a system that can accurately count sorghum grains within seconds. This technology has the potential to revolutionize the way breeders and researchers manage and analyze their crops.
The system utilizes advanced computer vision techniques, including image segmentation, feature extraction, and machine learning algorithms, to efficiently identify and count individual sorghum grains in an image. By simply taking a photo of a sorghum sample using a mobile phone, breeders can obtain accurate grain counts, eliminating the need for manual counting.

The technology is not only capable of counting the number of grains but can also provide additional data, such as size distribution and grain density by sorghum genotype.

The benefits of this computer vision system are numerous. It saves significant time and effort ,enabling breedera to make informed decisions about crop management and yield estimation. Additionally, researchers can collect large-scale data on sorghum grains more efficiently, facilitating breeding programs, yield improvement, and agronomic studies.