Detection of sprout damage in Canada Western Red Spring wheat with multiple wavebands using visible/near-infrared hyperspectral imaging

By J. Xing, S. Symons, M. Shahin, D. Hatcher. 2010

69 citations recorded by the source corpus.

Subfields: Analytical Chemistry, Animal Science and Zoology, Biomedical Engineering

View Paper: https://www.semanticscholar.org/paper/7198fd4a8622836df30facaa5abe59e77aa39272

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Analytical Chemistry

1. M. Whitworth
2. Nicola Caporaso
3. Ian D Fisk

In Biomedical Engineering

1. M. Whitworth
2. Nicola Caporaso
3. Ian D Fisk

Citations in the corpus

• Near-Infrared spectroscopy and hyperspectral imaging for non-destructive quality assessment of cereal grains (2018, methodology): “lations in a single model, which gave 100% and 97% accuracy for sound and sprouted kernels, respectively (42).”
• Using hyperspectral imaging to discriminate yellow leaf curl disease in tomato leaves (2018, methodology): “Xing et al. (2010) used a visible near-infrared (VNIR) hyperspectral imaging system (400–1000 nm) in the reflectance mode to discriminate sprouted wheat kernels.”