Machine learning analysis of hyperspectral images of damaged wheat kernels

HIGHLIGHTS

• who: Kshitiz Dhakal et al. from the School of Plant and Environmental Sciences, Virginia Tech, Blacksburg, VA, USA Department of Agricultural and Biological Engineering, Purdue University, West Lafayette, IN, USA have published the Article: Machine Learning Analysis of Hyperspectral Images of Damaged Wheat Kernels, in the Journal: Sensors 2023, 3523 of /2023/
• what: The authors explored the use of hyperspectral imaging (HSI) to evaluate the damage caused by FHB in Jupyter notebooks for the analysis in this work are provided in the following non-symptomatic kernel pixels from low images and 2000 from symptomatic kernel . . .
  

   

  

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