The use of near-infrared spectroscopy on agricultural harvesters has the advantage of not being time and resources consuming. In contrast to conventional sample-based methods, near-infrared spectroscopy on agricultural harvesters secures a good distribution of measurements within plots and covers substantially larger amounts of plot material (Welle et al., 2003). Thus, this method reduces the sampling error and therefore, provides more representative measurements of the plot material.

Spectral reflectance of plant canopy is a non-invasive phenotyping technique that enables the monitoring with high temporal resolution of several dynamic complex traits, such as biomass accumulation (Montes et al., 2007). Investigations at the individual plant level under well controlled environmental conditions showed that spectral reflectance could be used to monitor plant photosynthetic pigment composition, assess the water status and detect abiotic or biotic plant stresses (Penuelas, and Filella, 1998; Chaerle, and Van Der Straeten, 2000).

Current methods for measuring biomass production in cereal plots involves destructive sampling which is not suitable for routine use by plant breeders where large numbers of samples are to be screened. The measurement of spectral reflectance using ground-based remote sensing techniques has the potential to provide a nondestructive estimate of plant biomass production. Quick assessment of genetic variations for biomass production may become a useful tool for breeders. The potential of using canopy spectral reflectance indices (SRI) to assess genetic variation for biomass production is of tremendous importance. The potential of using water-based SRI as a breeding tool to estimate genetic variability and identify genotypes with higher biomass production would be helpful to achieve higher grain yield in crops.