SBIR-STTR Award

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.

The broader impact/commercial potential of this project is to increase overall crop health and production with the proposed smartphone compatible crop health sensor. More specifically, crop disease remains a significant threat to global food security, and with the ability to perform pre-visual screening, the proposed platform enables cost efficient, quantitative detection of crop disease, empowering farmers to take action to reduce disease impact. Initially the sensor platform provides a timely solution for cost effective, high throughput, and pre-visual screening of citrus Huanglongbing disease (HLB), enabling citrus growers to effectively manage HLB in their groves and remain profitable. The pre-visual, cost efficient and quantitative detection capability also translates to detection of diseases in other crops. In addition, the sensing technology developed can be used for quantitative assessment of crop nutrient and water stress, enabling farmers to optimally manage crop health, providing a means to optimize profits, increase crop yields, and reduce environmental impacts. This is critical to ensuring national and global food security, and protecting national water supplies by reducing eutrophication of water bodies due to misdiagnosis and mistreatment of crop stressors.This Small Business Innovation Research (SBIR) Phase 2 project is built upon Atoptix?s patented compact self-referenced spectrophotometer design, which reduces the size and cost of an optical spectrophotometer to enable field use and integration with smartphone technology. For each spectral measurement, the sensor simultaneously records a self-referenced spectrum, retaining the sensitivity and reliability generally reserved for costlier and bulkier spectrophotometer designs, but also enabling a non-technical user to collect data in the field at the push of a button. Distinct from surface reflection methods, the proposed sensor enables pre-visual detection of a pathogen, as it only captures light that has penetrated inside of a leaf and interacted with internal structures. By lowering the cost of the optical sensor through patented designs, increasing ease of use via a smartphone, and joining the precision of optical spectroscopy with machine learning based analytics, the proposed sensor can enable widespread adoption by growers in disease prone regions, where community wide screening is key for protecting grower assets.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.