Application of near infrared reflectance spectroscopy for rapid and non-destructive discrimination of hulled barley, naked barley, and wheat contaminated with Fusarium

Authors: LIM, JONGGUK - Korean Rural Development Administration; KIM, GIYOUNG - Korean Rural Development Administration; MO, CHANGYEUN - Korean Rural Development Administration; OH, KYOUNGMIN - Korean Rural Development Administration; KIM, GEONSEOB - Korean Rural Development Administration; HAM, HYEONHEUI - Chonbuk National University; KIM, SEONMIN - Chonbuk National University; Kim, Moon

Submitted to: Sensors
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 12/23/2018
Publication Date: 1/2/2018
Citation: Lim, J., Kim, G., Mo, C., Oh, K., Kim, G., Ham, H., Kim, S., Kim, M.S. 2018. Application of near infrared reflectance spectroscopy for rapid and non-destructive discrimination of hulled barley, naked barley, and wheat contaminated with Fusarium. Sensors. 18(1):113. https://doi.org/10.3390/s18010113.
DOI: https://doi.org/10.3390/s18010113

Interpretive Summary: Fusarium is one of the most deleterious plant pathogens, causing red rot fungus in barley and wheat and root-rotting diseases in many other plants. In this study, a near-infrared (NIR) spectroscopy method was used to rapidly and non-destructively discriminate Fusarium-contaminated barley and wheat kernels. NIR measurements in the wavelength range of 1175 nm to 2170 nm were acquired from hulled barley, naked barley, and wheat samples contaminated with Fusarium. Following the measurements, the samples were cultured in a medium to validate their Fusarium infection status. A numerical model developed using the NIR spectra correctly identified the contaminated samples with over 98% accuracy. The results demonstrated that the methods can be used as a non-destructive tool to detect Fusarium-contaminated samples. This research provides insightful information to grain production and processing industries seeking rapid means to identify Fusarium-contaminated kernels.

Technical Abstract: Kernel samples contaminated with Fusarium were discriminated rapidly and non-destructively using a near-infrared reflectance spectroscopic technique and a statistical prediction model. Reflectance spectra were acquired from hulled barley, naked barley, and wheat samples contaminated with Fusarium using NIR spectroscopy in the wavelength range of 1175–2170 nm. After measurement, the samples were cultured in a medium to promote Fusarium growth and experimentally identify contaminated samples. A PLS-DA prediction model was developed using the acquired reflectance spectra and the culture results. The correct classification rates (CCRs) of Fusarium contamination in the hulled barley, naked barley, and wheat samples obtained from the raw spectra were 98% or higher, and the identification accuracy of the prediction improved when second and third order derivative pretreatments were applied. The proposed method was verified to offer potential as a non-destructive discrimination method that could be applied to advance food safety and public health.