Using vegetation indices derived from conventional digital cameras as selection criteria for wheat breeding in water-limited environments

The ability to assess green biomass is of particular interest in a number of wheat breeding environments. However, the measurement of this and similar traits is either tedious and time-consuming or requires the use of expensive, sophisticated equipment, such as field-based spectroradiometers to measure vegetation indices (VIs). Here, conventional digital cameras are proposed as affordable and easy-to-use tools for gathering field data in wheat breeding programmes. Using appropriate software, a large set of images can be automatically processed to calculate a number of VIs, based on the performance of simple colour operations on each picture. The purpose of this study was to identify a set of picture-derived vegetation indices (picVIs) and to evaluate their performance in durum wheat trials growing under rainfed and supplementary irrigation conditions. Here, zenithal pictures of each plot were obtained roughly 2 weeks after anthesis, and the picVIs that were calculated were compared with the normalised difference vegetation index (NDVI), an index derived from spectroradiometrical measurements, and with the grain yield (GY) from the same plots. The picVIs that performed best were the Hue, CIE-Lab a* and CIE-Luv u* components of the average colour of each picture, the relative green area (GA) and the 'greener area', similar to GA but excluding the more yellowish-green pixels. Our results showed a high correlation between all these picVIs and the NDVI. Moreover, in rainfed conditions, each picVI provided an estimation of GY similar to or slightly better than that provided by the NDVI. However, in irrigated conditions during anthesis, neither these picVIs nor the NDVI provided a good estimation of GY, apparently because of the saturation of the VI response in conditions of complete soil cover and high plant density.