A novel method, known as LIGHt smartphone colorimetry, has been developed for the rapid detection of starch content in tobacco leaves using smartphone technology. This innovative technique combines chemistry and smartphone imaging capabilities, offering results comparable to traditional spectral methods.
The method employs anthrone-sulfuric acid colorimetry, which reacts with starch to produce distinct color changes measurable by smartphone cameras. This process allows for quick, low-cost, and efficient assessment of starch content, which is pivotal for determining the quality and maturity of tobacco leaves.
Traditional methods for measuring starch, including iodine tests and various spectroscopic approaches, though reliable, often require expensive equipment and trained personnel. LIGHt colorimetry overcomes these barriers, providing immediate results without specialized tools, making it particularly valuable for the tobacco industry where quality control is imperative.
The research team, including scientists from the Shanghai Tobacco Company, demonstrated this method’s efficacy with tobacco leaf samples. Their results revealed an average relative error of 5.74%, with detection limits as low as 1.53 µg/mL and impressive recovery rates of 95.72%. These findings suggest significant potential for LIGHt smartphone colorimetry to transform the quality control processes not only for tobacco but also for other agricultural products.
This technology capitalizes on the widespread accessibility of smartphones, leveraging their enhanced imaging capabilities to facilitate on-site data collection. The use of RGB values extracted from camera images allows for rapid assessment of starch levels, aligning with the industry's need for efficiency.
Given the compound growth of consumer demand for higher-quality plant products and the shift toward more sustainable agricultural practices, efficient and accurate detection methods like LIGHt smartphone colorimetry can play a significant role. It facilitates timely quality assessments right at the point of production, thereby supporting the overall goal of improving product standards.
Overall, this groundbreaking work points to exciting possibilities not only for the future of tobacco leaf quality monitoring but also for broader applications across various food and agricultural sectors, emphasizing the innovative fusion of portable technology with practical agricultural science.