Use of Colorimetric and Chemometric Methods for the Detection of Target Compounds in the Forestry Industry

Abstract

Formaldehyde is a hazardous volatile organic compound widely used in the engineered wood composites industry, especially in the production of phenol-formaldehyde resins. The widespread use of formaldehyde-based adhesives in products such as particleboard and medium-density fiberboard has raised significant health and environmental concerns. This study aims to develop a cost-effective paper-based analytical device for the detection of formaldehyde in air. Using cellulose fibers, colored probes, and natural polymers, the paper-based analytical device will provide a fast and easy-to-use solution for monitoring formaldehyde emissions. Device performance was validated to the American Society for Testing and Materials D6007-14 standards and compared to electronic formaldehyde sensors, focusing on concentrations ranging from 1 to 5 ppm. The correlation between color changes in the paper-based analytical device and formaldehyde exposure was statistically analyzed to establish a consistent linear relationship. This innovative approach aims to address industry challenges by providing an effective alternative for formaldehyde control, ensuring compliance with stringent environmental regulations.

Additionally, the second chapter of this study addresses the detection of Lecanosticta acicola (Thüm.) Syd. infection in loblolly pine (Pinus taeda L.), a predominant timber species native to the southeastern United States. The forestry industry in Alabama is one of the most important industries in the country, generating $2 billion in forest product exports in 2022 and employing nearly 40,000 people in the forest products sector. Lecanosticta acicola is a fungus that causes the disease brown spot needle blight, which affects loblolly pine plantations—a species of significant economic importance for Alabama's forestry industry. Its rapid spread is a concern, emphasizing the importance of developing effective detection methods to control this disease.

Near-infrared spectroscopy (NIR) is a tool that has gained significant relevance for chemical composition analysis across various industries. It is a powerful, fast, and versatile method for predicting the content of compounds in the forest industry, such as lignin. This research involved analyzing 200 samples of loblolly pine needles. The needles were freeze-dried, milled, and subjected to near-infrared spectroscopy. The lignin content was determined using the Determination of Structural Carbohydrates and Lignin in Biomass method from the National Renewable Energy Laboratory. The NIR spectroscopy data were coupled with lignin content using a chemometric model to predict lignin levels in pine needles. Lignin content serves as an important indicator for the preliminary evaluation of fungal infections, such as brown spot needle blight, offering a versatile method for early detection. Preliminary results from the near-infrared spectroscopy and chemometric model show promising potential for this approach.

This dual-approach research leverages colorimetric methods to enhance environmental safety and forest health. By integrating innovative paper-based analytical devices for formaldehyde detection with near-infrared spectroscopy for fungal infection detection, this study utilizes color changes to deliver rapid, reliable, and cost-effective solutions. These methods are designed to protect human health from formaldehyde exposure and to safeguard economically important loblolly pine species from devastating fungal infections such as brown spot needle blight (BSNB). The results will empower private landowners and forest managers to monitor, plan, and adjust their management strategies, thereby mitigating the impacts of formaldehyde emissions and fungal diseases in the forest industry.