The Mushroom Initiative Ltd. is inviting more people to pay attention to the nutrient content in natural and non-processed food and we aim at providing some certain objective indicators to understand our food.
To do so, we are now developing a portable plant nutrient meter which is a device for measuring nutrient contents and freshness of vegetables and fruits. On top of information such as the products’ origins, appearance and prices, consumers can now use the meter to measure the polyphenol and chlorophyll contents of our foods. (Read more to understand why polyphenol and chlorophyll contents are used as indicators.)
How Does It Work?
The meter is a portable, easy to operate and instant tool for general consumers to know the nutrient content of the fruits or vegetables. The user simply needs to scan the vegetable or fruit sample and then the paired smartphone will display the result on the mobile app for his/her reference. The specific result includes the polyphenol and chlorophyll content in the sample.
Apart from household application, the meter would also be beneficial to growers or landscape greening professionals, to assess plants’ chlorophyll level. As chlorophyll is a general plant health indicator, this enables users to make informed agronomic decisions, e.g. fertilizer application, abiotic and biotic stress (i.e. pathogen, pest attacks) countermeasures.
The meter incorporates the techniques of a fluorescence spectrometer. Under UV-radiation, plant cells of the vegetables and fruits will be activated. Then, the cells will emit two types of fluorescence: blue-green and red/infra-red fluorescence emission spectrum. Blue-green fluorescence is emitted by several compounds, but mainly from polyphenols. Besides, red/infra-red fluorescence is derived from chlorophyll.
After collecting and analyzing the spectrum, a graph as below will be generated and uploaded to the cloud database.
The cloud database stores data collected by developers and users. Based on the extensive database, the above graph will be presented in a layman and user-friendly feedback, e.g. whether the sample is above or below the average by comparing among the database.