WHEATS QUALITY PREDICTION BY MACHINE LEARNING

WHEAT'S QUALITY PREDICTION USING MACHINE LEARNING

CIMMYT ( http://www.cimmyt.org) works under a very noble objective: eradicate global starving. They expect to reach such objective using natural sciences in order to make essential crops to produce more and better under the most difficul circumstances.

Quality of products is measured using long test on the results of flour processes of grains.

In this project we used data of 5 years of complete tests on quality on products of wheat's flour, and using Self Organized Maps, a kind of statistical artificial neural networks, we did predictions on the quality of products of wheat from the DNA lectures of grain.

This kind of work promises to be useful in order to save time when long quality test are necessary to perform predicting quality from genotypical lectures.

This research was accepted as poster in IWC 2015, Australia.

The draft of the poster introduced there is attached.

https://www.researchgate.net/profile/Hafeez_Rehman/publication/293823628_Phenotyping_wheat_germplasm_for_terminal_heat_stress/links/56bc60f808aef29efca4c5d1.pdf