Yield prediction with machine learning algorithms and satellite images.
Journal:
Journal of the science of food and agriculture
PMID:
32755005
Abstract
BACKGROUND: Barley is one of the strategic agricultural products available in the world, and yield prediction is important for ensuring food security. One way of estimating a product is to use remote sensing data in conjunction with field data and meteorological data. One of the main issues surrounding this comprises the use of machine learning techniques to create a multi-resource data-based estimation model. Many studies have been conducted on barley yield prediction from planting to harvest. Still, the effect of different time intervals on yield prediction has not been investigated. Furthermore, the effect of different periods on yield prediction has not been investigated.