New management practices must be developed to improve yam productivity. By allowing non-destructive analyses of important plant traits, image-based phenotyping techniques could help developing such practices. Our objective was to determine the potential of image-based phenotyping methods to assess traits relevant for tuber yield formation in yam grown in the glasshouse and in the field. We took plant and leaf pictures with consumer cameras. We used the numbers of image pixels to derive the shoot biomass and the total leaf surface and calculated the ‘triangular greenness index’ (TGI) which is an indicator of the leaf chlorophyll content. Under glasshouse conditions, the number of pixels obtained from nadir view (view from the top) was positively correlated to shoot biomass, and total leaf surface, while the TGI was negatively correlated to the SPAD values and nitrogen (N) content of diagnostic leaves. Pictures taken from nadir view in the field showed an increase in soil surface cover and a decrease in TGI with time. TGI was negatively correlated to SPAD values measured on diagnostic leaves but was not correlated to leaf N content. In conclusion, these phenotyping techniques deliver relevant results but need to be further developed and validated for application in yam.