People can be accurate sensors of crop status

Information from an ‘eyeball’ assessment of how well crops are doing may not sound very trustworthy or scientific, but new research shows that this type of qualitative evaluation can carry a lot of high-value information for crop monitoring and yield prediction. It can be so accurate that it may even be used to assess the value of other technology-based crop monitoring methods.

A collaboration between researchers at the Spanish Research Council (CSIC) and the University of Montana developed statistical methods that strip all perception and judgment biases from categorical assessments of crop status performed by USDA surveyors. “Once the biases are removed, people become amazing sensors of crop status,” said Marco Maneta, UM Geosciences associate professor and coauthor of the study. “This is because humans have the capacity to integrate contextual information into their assessment that standard sensors typically don’t capture, such as prior meteorological conditions, agricultural practices and technology, and other relevant nuances that are difficult to measure or quantify.”

The USDA conducts weekly qualitative surveys of crop status during the growing season for all major crops in the US. These surveys are an important source of information for policymakers, market analysts, and farm insurance companies, among others. The surveys started in the mid 1980s and can be used to study how production responds to varying climate conditions. “These visual surveys have been available for a long time but have been underutilized by physical scientists for research purposes because human judgment is subjective and has been deemed unreliable for scientific studies,” said Dr. Santiago Begueria, from the Spanish Research Council and lead author of the study. “We converted this qualitative survey into a continuous quantitative metric of crop condition that is devoid of the personal or location biases of the surveyors,” Begueria added, “resulting in a rich metric of crop condition that can be used for scientific analysis or for crop monitoring and early warning systems.”

The new crop condition metric was shown to predict crop yields mid-season more accurately that the predictions issued by the USDA or the predictions used by analysts. Maneta described another critical application of the new metric: “It can also be used to anticipate the impacts of drought on agriculture and inform where to allocate relief funds, which has the potential to reduce agricultural market volatility and improve food security.”

The paper was recently published in the Proceedings of the National Academy of Sciences.