Blue and UV LED-induced fluorescence in cotton foreign matter

Abstract

BackgroundCotton is an important domesticated fiber used to manufacture a variety of products and industrial goods. During harvesting with cotton strippers and cotton pickers, it is contaminated with foreign matter from botanical and non-botanical sources which adversely affect the quality and consistency of cotton, and therefore reduces its market value. To improve the current grading done by the High Volume Instrument (HVI) and human inspectors, it was explored whether fluorescence imaging can be used for cotton foreign matter detection.ResultsEight types of botanical foreign matter (bark, bract, brown leaf, green leaf, hull, seed coat, seed, stem), and four types of non-botanical foreign matter (paper, twine, plastic bale packaging, plastic bag) were subjected to a fluorescence spectroscopy analysis to determine their optimal excitation and emission wavelength range. Matrix 3D scans were performed in the excitation range from 300 nm to 500 nm, and emission range from 320 nm to 700 nm, and the results indicated the photo-excitable fluorescence in the aforementioned excitation range for all the selected foreign matter categories. Consequently, the blue and the UV LEDs were selected as the excitation sources. The blue LED light provided optimal excitation light for bark, brown leaf, bract, green leaf, hull, and stem, while the UV LED light provided optimal excitation light for paper, plastic bag, plastic packaging, seed, seed coat, and twine.ConclusionsUV and blue light induces fluorescence in 12 types of botanical and non-botanical cotton foreign matter. An imaging apparatus with blue and UV light excitation sources, and a consumer grade SLR camera was successfully developed to capture and characterize fluorescent images of cotton foreign matter. Based on the results, fluorescent imaging could be a promising method for cotton foreign matter detection. Future studies will focus on the classification of cotton foreign matter categories and to further refine the image processing sequence.Electronic supplementary materialThe online version of this article (doi:10.1186/1754-1611-8-29) contains supplementary material, which is available to authorized users.

Cotton contamination detection and classification using hyperspectral fluorescence imaging

“…Based on the results of a previous study, 11 a total of seven categories of foreign matter optimally excited under UV light were used in the current research (Figure 1). The selected foreign matter included four categories of non-botanical origin (paper, plastic bag, plastic packaging, and twine) and three categories of botanical origin (inner part of seed coat (SCI), outer part of seed coat (SCO), and seed).…”

“…They were closely correlated with the optimal wavelengths presented in the previous study. 11 Therefore, the 19 wavelengths provided the most relevant information regarding the properties of the samples, which could be used for future studies or applications.…”

“…A comprehensive study using fluorescence spectroscopy was conducted to explore the optimal fluorescence emission wavelengths of both botanical and non-botanical foreign matter. 11 A total of 12 types of foreign matter found in the US cotton showed obvious fluorescent emission under blue and UV excitation. The optimal emission wavelengths of the 12 types of foreign matter ranged from 320 to 700 nm.…”

Shortwave infrared hyperspectral reflectance imaging for cotton foreign matter classification

“…Compared to the spectroscopy technique, the imaging approach can provide spatial information of foreign matter such as size, shape, and spatial distribution of the color (Mustafic et al, 2014). The color imaging systems are inexpensive, relatively easy to build, and therefore have been intensively investigated previously to detect cotton FM.…”

“…Despite its success, this study only investigated non-botanical FM and another limitation of the system was that this color-imaging system can only detect FM with distinct colors. To overcome this limitation, Mustafic et al (2014) developed a fluorescence imaging system to identify twelve types of cotton FM excited under blue and UV LED. Results showed that there were different levels of fluorescence among the twelve FM and cotton lint, and fluorescence imaging could be effective in detecting FM with similar color but different fluorescence emissions.…”