Conventional imaging practices used for the inspection and monitoring of biological specimens employ RGB cameras with limited capabilities for early identification of diseases or abnormalities. In this work, we demonstrate and validate a quick, non-destructive, and precise inspection method utilizing an in-house developed push broom ultra-spectral imager. Precise image classification based on ultra-spectral signatures can provide fully automated machine vision capabilities, reducing inspection time, human errors, and man-hours. The proposed method has high spectral resolution (Δλ < 1 nm) with 756 spectral bands, improved detection sensitivity, and high spatial resolution, which could potentially enable early-stage detection and accurate classification of abnormalities or diseases. Two potential applications of the developed system in agriculture and biomedical fields are demonstrated.
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