Is that apple ripe?

Researchers at MIT have designed a device to quickly determine the ripeness of apples.

The new device, presented in Scientific Reports, is an ultra-portable, wireless smartphone spectrometer that determines the properties of an object based on how it interacts with light. In this case, by measuring the UV florescence from chlorophyll in the apple’s skin during the ripening process.

The researchers are also releasing an open source platform that has all the information needed to replicate and further develop the device. It will be available here.

We spoke with the study’s lead author Anshuman Das.

ResearchGate: Can you tell us about the new device?

Anshuman Das: The device is a smartphone based wireless spectrometer that is low-cost, low power, extremely portable and standalone. The spectrometer is basically a sensitive color sensor which can pick up subtle changes that may be impossible to distinguish visually. Chlorophyll, that is present in leaves and fruits, glows red when excited by UV or blue light. We can use this emission to study interesting aspects of growth, ripening and damage in plants.

RG: What was your motivation in developing it?

Das: There is a lack of such tools in the market. Most spectrometers are expensive and the compact versions are USB based which require a laptop to operate. This makes it unattractive for use in the field. Most of us already carry around a very powerful computing device – the smartphone – so we began exploring how we could build a device that works with a smartphone.

RG: What were the biggest challenges in creating the prototype?

Das: We decided to take up the challenge of only using the bare sensor in the spectrometer assembly. Which meant getting rid of all USB based circuitry. Understanding the sensor and getting the raw signal was the biggest challenge. The sensor like other spectrometers sends out a train of pulses with amplitudes depending on the incident light level. The position of the pulse in this train corresponds to wavelength of light through a calibration step. We had to understand this pattern and capture the signal precisely in order to arrive at the spectrum.

RG: Why apples? Can this be expanded to other fruit?

Das: Apples have been very well studied and there is large amount of literature already present. They are easy to store and readily available. When developing a new device, we felt it would be more effective to test it on well-established studies. This would simplify the data analysis and comparison. This technique can easily be expanded to other fruits and vegetables. There is already work done on a variety of them including guava, broccoli, avocado among others.

RG: What applications do you foresee for your device?

Das: We think the device can be used for a range of applications like point-of-care diagnostics, geology, food sensing, and others. There are several minerals and rocks that are also fluorescent under UV, like calcite, which our device should be able to identify and study. Several biological compounds and structures like porphyrins, collagen, and certain types of bacteria also have fluorescent properties so the device could be used to study these materials.

RG: What are the next steps in your research?

Das: The form factor of the device makes it convenient to capture large datasets. We plan to extend the study to collect larger datasets, which will enable machine learning and eventually automated analysis. For instance, we may be able to distinguish different varieties of produce and identify the source.

Featured image courtesy of flickr.