The broader impact/commercial potential of this project is to optimize and reduce agro-chemical and irrigation applications for the United States agricultural industry, reducing environmental contamination, and increasing overall crop health and production with a smart phone compatible miniaturized optical sensor. The diagnostic sensor, designed for use in the precision agriculture market sector, captures optical spectrographs of a plant that can be used to diagnose the overall health of the plant, and provide recommendations for optimizing care. In discerning whether a plant suffers from a nutrient deficiency, a water stress, or a disease pressure, the sensor provides a means for substantial commercial impact. By providing this market sector with the needed quantitative information to both specialize and optimize crop treatment plans, substantial agro-chemical and irrigation resources are saved. From a societal perspective, these commercial savings directly translate into reduced agro-chemical applications of crops, which help reduce eutrophication of environmental water bodies, protecting drinking water supplies. By optimizing irrigation usage, the sensor reduces irrigation demands, helping ensure the longevity of these sources of irrigation. By enabling big data analysis of optical spectrographs that correlate with underlying crop health conditions, the project provides insight into physiological factors governing crop health, advancing scientific understanding.
This Small Business Technology Transfer (STTR) Phase I project is directed towards miniaturizing high precision optical spectrophotometers, traditionally confined to laboratory usage, for use in precision agriculture. The agricultural industry struggles to identify or anticipate changes in crop health and take appropriate measures of response. As multiple environmental stressors or factors can cause similar visual symptoms in a crop, optimal decision-making becomes decidedly difficult, and can lead to costly commercial and societal impacts. In response to this problem, this project aims to first develop a handheld smart phone-based spectrophotometer for real time diagnosis of crop health. Afterwards, the capabilities of the device will be extensively tested in controlled greenhouse studies of crops under varying nutrient and hydration conditions. Finally, the data collected in these studies will be analyzed and benchmarked against gold standard techniques of assessment. From these studies, the performance of the optical sensor will be clearly assessed. Specifically, the degree to which the sensor can discern amongst varying environmental stressors affecting a crop, and also the degree to which the sensor can provide quantitative feedback about the severity of those stressors, will be provided.
