Case study: cost-effective image analysis method to study drought stress of soybean in early vegetative stage

There are many applications of image-based analysis for phenotyping agronomic traits. However, they are inappropriate or difficult to operate due to lack of time, equipment, and financial limits. In this report, we demonstrate fast and reliable phenotyping methods to screen drought tolerance in soybeans (Glycine max L.) using the green area of the canopy from the image sensor. Vertical images obtained from the commercial digital camera and processed on free software called Canopeo were used for initial screening for drought stress evaluation. As a result, this method positively correlated with the number of nodes, which is the indicator of the yield components. It also showed that the green area of the canopy has significantly been affected by drought, and varieties than the number of nodes. This simple method using the digital images obtained in a cost-effective manner would be useful for initial drought evaluations.