Jian Jin, an assistant professor in the Department of Agricultural and Biomedical Engineering at Purdue has built a handheld sensor to easily and accurately measure the health of crops.

Jian's device collects physical data about a plant, such as its moisture, chlorophyll and nutrient levels, along with the effect of chemical sprays on the plant and possible disease symptoms to determine if the plant is healthy or under stress. Jian said this device will help allow farmers to detect changes in the health of plants days or hours before they are evident to the human eye. It will also inform farmers of necessary changes needed to produce more crops using less resources. 

The device will make it possible for farmers to carry just the handheld device and a smartphone through a field and receive the same information provided by much more expensive phenotyping systems recently constructed.

"We have 600 million farmers worldwide, and very few of them are benefitting from high-end plant sensor technologies. Now, with this handheld device, most farmers can benefit," said Jian in a Purdue news release. 

The sensor can scan a plan in under five seconds, and is capable of detecting hundreds of bands of color in each pixel instead of the three bands of color detected with normal cameras. This, and a burst of fluorescent light bounced off the plant, measure for stress and nutrition levels in the plants. The device is also equipped with constantly updating plant features prediction models and an advanced image processing algorithm developed by scientists at Purdue, allowing for the most accurate predictions for its users.

Users can upload their data from the device with geo-locations to a web-based cloud map service developed by a team at Purdue's Advanced Computing Group led by Carol Song. Song's system creates nutrition heat and plant stress maps based on the information provided by the sensors, allowing for interactive agricultural data at farm and regional levels. This data could provide data to state and federal officials about how to aid farmers in times of severe stress to crops, and also what types of harvests to expect. 

Last winter, Jian and his group worked with a senior design group in the School of Mechanical Engineering and created a robot to automatically use the sensor to scan the plants in their greenhouse. Due to this success, Jian and his team are now designing a robot to scan crops in a farm setting. Their prototype is expected to be functioning by next year's growing season. 

Jin is currently looking for collaborators interested in marketing and mass-producing his device. He believes that the best approach is to offer the device to the public at a low cost.

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