In this paper the utilization of smartphone as a detection platform for colorimetric quantification of biological macromolecules has been demonstrated. Using V-channel of HSV color space, the quantification of BSA protein, catalase enzyme and carbohydrate (using D-glucose) have been successfully investigated. A custom designed android application has been developed for estimating the total concentration of biological macromolecules. The results have been compared with that of a standard spectrophotometer which is generally used for colorimetric quantification in laboratory settings by measuring its absorbance at a specific wavelength. The results obtained with the designed sensor is found to be similar when compared with the spectrophotometer data. The designed sensor is low cost, robust and we envision that it could promote diverse fields of bio-analytical investigations. Schematic illustration of the smartphone sensing mechanism for colorimetric analysis of biomolecular samples.

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Nitrite level estimation in soil and water bodies is critical to monitor the ecosystem of our environment and agricultural yield. Herein, we report a carbon nanodots (C-dots) and neutral red (NR)-based photometric and fluorescence mode sensing scheme using which trace detection of nitrite in water and soil has been done. The proposed scheme utilizes a handheld compact sensing platform developed on a smartphone. For the present sensing studies, the C-dots and NR act as donors and acceptors, respectively, in the frequency resonance energy transfer (FRET) process. The presence of nitrite in the C-dot–NR mixture affects the FRET process, which causes a decrease in the absorption wavelength conditions at 560 nm while increasing the fluorescence intensity at 563 nm upon excitation with a source of wavelength 375 nm. These variations have been correlated to quantify the concentration of the nitrite level in the medium. With the designed sensing system, variations of nitrite concentration from 0.1 to 3.0 μg/mL have been measured with a high degree of accuracy. The designed sensor has been implemented to estimate the nitrite level of infield water and soil samples, and the experimental results are compared with the laboratory standard tools. With the advantages of being low-cost, field portable, and relatively convenient to handle, it is anticipated that the proposed smartphone sensor could emerge as a potential avenue for onsite assessment of other parameters of water and soil as well.

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A simple yet effective, handheld and flexible bright-field and fluorescence microscopic platform on a smartphone with varying optical magnifications is reported for morphological analysis and onboard cell counting features.