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AI Revives Classic Microscopy for On-Farm Soil Health Testing

The classic microscope is getting a modern twist US researchers are developing an AI-powered microscope system that could make soil health testing faster, cheaper, and more accessible to farmers and land managers around the world.

Researchers at The University of Texas at San Antonio, U.S., have successfully combined low-cost  with machine learning to measure the presence and quantity of fungi in . Their early-stage proof-of-concept technology is presented at the Goldschmidt Conference in Prague on Wednesday 9 July.

Determining the abundance and diversity of soil fungi can provide valuable insights into soil health and fertility, as fungi play essential roles in the biogeochemical cycling of nutrients, water retention, and plant growth. With this knowledge, farmers can optimize  and sustainability by making informed decisions about soil management, including fertilizer application, irrigation, and tillage.

Optical microscopes are the oldest design of microscope and have long been used to discover and identify tiny organisms in the soil. Other forms of soil testing use techniques like phospholipid fatty acid testing and DNA analysis to detect organisms, or to measure the presence of chemicals such as nitrogen, phosphorus and potassium. While powerful, these modern methods tend to be costly or just emphasize , often overlooking the full biological complexity of soil ecosystems.

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