Assessment of kernel presence in winter wheat ears at spikelet scale using near-infrared hyperspectral imaging

The scope of the article is to propose an innovative method based on Near Infrared Hyperspectral Imaging (NIR-HSI) to rapidly and non-destructively evaluate the presence or absence of kernels in winter wheat ears (Triticum aestivum L.). This preliminary study has allowed the evaluation of the potential of the method using winter wheat ears collected in a field trial in Belgium. NIR-HSI combined with chemometric tools identified spectral bands potentially characteristic of the presence of kernels inside the ears. A chemometric model has been built using Partial Least Squares Discriminant Analysis (PLS-DA) to identify ears with and without kernels. The PLS-DA results presented in the article allowed to track the presence or absence of kernels in winter wheat ears at spikelet level. These results indicate that NIR-HSI might be a useful method to provide, in a non-destructive way, information assessing the status of kernels inside the ear which plays an important role in yield assessment.