Our Core Technology: AI-Powered NIRS
NIRS is a non-destructive, eco-friendly analytical technique that uses light absorption to assess sample composition. Smartspectra’s NIRS technology, enhanced with AI, provides real-time, accessible data that meets the diverse needs of businesses, communities, and individuals.
Non-Destructive - Preserves sample integrity.
Chemical-Free: Reduces the need for hazardous chemicals.
Energy-Efficient: Lowers energy consumption and minimizes waste.
Our AI-powered NIRS technology supports sustainable, inclusive practices, making precise analytics accessible across all sectors and communities.
Chemometrics & AI: Making Complex Data Accessible
Smartspectra’s chemometric approach, powered by AI, turns complex data into understandable insights. By applying machine learning to chemometric models, Smartspectra offers predictive data that is accessible to organizations, community projects, and individual users, helping everyone make informed, data-driven decisions.
data-driven insights: AI-powered chemometrics transforms complex data into clear insights.
Machine learning enhances our chemometrics, making Smartspectra’s solutions adaptable and relevant across diverse applications.
Research and Development
Smartspectra is committed to advancing accessible, eco-friendly solutions through continuous R&D. Our projects explore innovative applications of NIRS and chemometrics to support underserved communities, sustainable agriculture, and health equity.
R&D Focus Areas:
Non-Destructive Quality Assessment: Designing NIRS techniques for non-invasive evaluation of biological and agricultural samples, allowing for quality control without compromising sample integrity.
Precision Agriculture and Crop Monitoring: Innovating tools for soil, crop, and nutrient analysis to enhance sustainable farming practices, optimize yields, and improve resource use efficiency.
Custom Calibration and Quality Control Models: Developing tailored calibration models for specific client needs, enabling precise and reliable analysis across diverse industry applications.
Pathogen Detection and Profiling in Agriculture: Developing NIRS-based techniques for rapid identification of plant pathogens, aiding in disease management and biosecurity to reduce crop and livestock losses.
Food Safety and Authenticity: Creating rapid, on-site NIRS methods for verifying food authenticity, detecting contaminants, and profiling nutritional content, ensuring product quality and safety.
Environmental Pathogen and Pollution Monitoring: Expanding NIRS applications for detecting pathogens and pollutants in soil, water, and air, supporting public health surveillance and environmental sustainability.
Collaborative Research Initiatives: Partnering with universities and research institutions to explore innovative applications of NIRS, advancing knowledge in agriculture, environmental science, and food technology.
Through R&D and partnerships, Smartspectra continues to push the boundaries of AI-enhanced analytics, creating transformative, sustainable solutions.
Product Process Optimization: Implementing NIRS for real-time monitoring and process optimization, improving manufacturing efficiency, quality, and regulatory compliance.
Meet Dr. Mariana Santos-Rivera: A Visionary in Analytical Science
Dr. Mariana Santos-Rivera, a passionate scientist born in the beautiful landscapes of Colombia, has dedicated her career to pioneering advancements in spectroscopy and chemometrics. She holds a degree in Veterinary Medicine from the University of Tolima, where her journey in scientific exploration began. In 2010, she took her first role at the Scientific Research Center Caucaseco, working on groundbreaking preclinical trials to develop malaria vaccines. This critical work, paired with her bilingual skills, opened doors to her next role with the Albert and Vivian Puzey Foundation (Quantaspec, Inc.) in Vermont, USA. Here, Dr. Santos-Rivera delved into Fourier Transform Infrared (FTIR) Spectroscopy to develop innovative diagnostic tools for malaria, sparking a deep passion for infrared analytical techniques.
Eager to further this interest, Dr. Santos-Rivera returned to Colombia in 2013, joining the National Coffee Research Center, where she focused on applying Near-Infrared Spectroscopy (NIRS) to understand and enhance the quality of coffee. During her time there, she mastered advanced chemometric analysis, laying the groundwork for her future as a leader in NIRS technology. Her commitment to advancing the field led her to pursue a Ph.D. in Biochemistry at Mississippi State University in 2017, where she not only deepened her expertise in NIRS and chemometric techniques but also conducted groundbreaking research on pathogen detection in both dairy calves and plants. Her work focused on developing precise analytical methods to identify and monitor pathogens, providing valuable insights into disease management in agricultural settings. These studies contributed to a better understanding of pathogen behavior and prevention strategies, reinforcing her role as a leader in applying spectroscopy to address challenges in animal and plant health.
After completing her doctoral studies, Dr. Santos-Rivera took on a role as the R&D manager at Qima Coffee, where she applied her skills to enhance quality assessment and traceability in coffee production. Her work at Qima Coffee brought sophisticated NIRS applications to the coffee industry, helping achieve greater quality and transparency.
Today, as Chief Technology Officer of SmartSpectra, Dr. Santos-Rivera is at the forefront of analytical innovation, leading cutting-edge research in NIRS and chemometrics to unlock transformative insights across diverse industries. Her remarkable journey from Colombia to the global stage reflects her unwavering commitment to pushing the boundaries of science, making her an invaluable leader and visionary in the field.
read the recent scientific publication by Dr. Mariana Santos-Rivera
Identifying the origin of Yemeni green coffee beans using near infrared spectroscopy: a promising tool for traceability and sustainability
