The high demand for cotton production worldwide has demonstrated the need for standardized classification of foreign matter present with cotton. Cotton trash can become comingled with fiber during the ginning and harvesting processes. The conventional instrumental method used to determine the amount of cotton trash present with cotton fiber, the high volume instrument (HVI), lacks specificity in the identification of individual trash components (leaf, etc.). Fourier transform near-infrared (FT-NIR) spectroscopy was investigated to distinguish the individual types of cotton trash from the fiber. In this study, the concept of monitoring differences in spectral bands of cotton and cotton trash by FT-NIR spectroscopy was demonstrated and provided a ‘proof of concept.’ A spectral library based on NIR spectral data and pre-processing methods was developed using cotton and cotton trash samples (hull, leaf, seed coat, and stem) yielding over 97% identification accuracy of cotton trash components in the prediction set.

Cotton is and has been a large cash crop in the United States and abroad for many years. Part of the widespread interest and utility of this product is due to its attractive chemical and physical properties for use in textiles. The textile industry could benefit from the presentation of a quick, reliable method to classify U.S. from foreign cottons so that the appropriate tariffs can be levied for non-American cottons. In addition, there is some interest in avoiding cotton identity theft. Thus, an accurate and precise instrumental method would be of interest to correctly identify the country of origin of cotton. This study provides an analytical method to identify domestic and foreign cotton fibers using near-infrared (NIR) spectroscopy coupled with principal component analysis (PCA). Samples from American cottons were evaluated along with a representative amount of international samples. The results provide a proof of concept that indicates that PCA analysis can be used to separate the respective domestic and foreign cotton groups.

Currently, oven drying in air is often utilized to generate the percentage of moisture in cotton fibers. Karl Fischer Titration, another method for cotton moisture measurement, has been compared to the oven drying method. The percentage of moisture as generated by the oven method tracks those of Karl Fischer Titration, but there are differences between the two. In fact, a bias exists in the measured moisture loss employing the standard oven drying method. In addition, the moisture data collected via Karl Fischer Titration demonstrates smaller variances than those data collected in the oven. The aim of this study is to determine what is causing those differences. In the current report, particulate matter formation and browning of oven-treated cotton samples have been observed, suggesting visible indirect evidence that cotton oxidation may be occurring. It is noteworthy that three types of oxidation processes may be occurring during the current study: heating in air, scouring and bleaching, and periodate-driven processes. The first two oxidative processes yield non-specific products, whereas the periodate-driven oxidative products are well-defined in the literature. Thus, a method was needed to gain direct evidence for this postulated cotton oxidation that may be contributing to the bias in the standard oven drying method used to calculate moisture loss in cotton. Thus, this preliminary study employed Attenuated Total Reflectance/Fourier Transform Infrared spectroscopy to determine if direct evidence for oxidation can be observed for oven-treated cotton samples.

Botanical and field cotton trash comingled with Upland cotton lint can greatly reduce the marketability and quality of cotton. Trash found comingled with cotton lint during harvesting, ginning, and processing is of interest to the textile community. In the current study attenuated total reflectance-Fourier transform infrared (ATR-FTIR) spectroscopic imaging was employed as an analytical technique to analyze cotton trash. Some benefits of this technique were its non-destructive nature and lack of required sample preparation. The technique used in this study, specifically ATR-FTIR spectroscopic chemical imaging, allows for three-dimensional spectral and spatial data to be obtained. In the current study, cotton in mixtures with botanical and field trash types have been identified spectrally and spatially using ATR-FTIR imaging. Botanical trash types (trash derived from the cotton plant) were evaluated and identified independently from cotton, even though both contained cellulose. The field trash types were easily identified from cotton due to their differences in chemical composition. This study can complement current cotton qualitative studies by adding spectral and spatial information to sample analysis.