NIR Spectroscopy & Real-Time Quality Analysis – Interview With Buchi
Friday, 9 January 2026
We’re happy to introduce a new interview series hosted by our Conference Programming Chair, Adam Moore. Leading up to the show Adam with be talking to some of the experts speaking at The Fertilizer Show about current issues and future trends impacting the fertilizer industry.
Beginning the series is Isaac Rukundo, NIR Product Specialist at Büchi Corporation discussing Near-Infrared (NIR) spectroscopy – a fast, non-destructive, and highly accurate method for assessing fertilizer composition.
To accompany the interview we have a more in depth written piece below to expand your knowledge of NIR.
Join us at The Fertilizer Show at the Tampa Convention Center from March 25 – 26 and see Isaac present on stage on March 26.
Introduction
What is NIR spectroscopy and why is it well suited to fertilizer production?
Near-Infrared (NIR) spectroscopy is an analytical technique that measures how materials absorb near-infrared light to determine their chemical composition. In some cases, it can also provide insight into physical characteristics. It is particularly well suited to fertilizer production because it is fast, non-destructive, and requires little to no sample preparation. Most importantly, it can be deployed directly in the process – on conveyors, chutes, or pipes – allowing producers to continuously monitor product quality rather than waiting for laboratory results.
What challenges in traditional fertilizer quality analysis does NIR help to overcome?
Traditional quality analysis relies heavily on manual sampling and laboratory testing, which is time-consuming and provides delayed feedback. By the time results are available, significant volumes of product may already be off-spec. NIR addresses this by delivering instant measurements, reducing sampling errors, minimizing laboratory workload, and enabling faster corrective actions.
Why is real-time quality analysis more critical today than in the past?
Today’s production environment is characterized by tighter specifications, greater raw material variability, rising energy costs, and stronger sustainability requirements. Real-time quality analysis allows plants to operate closer to optimal setpoints, reduce waste, and respond immediately to process disturbances – capabilities that simply weren’t possible with batch-based laboratory analysis.
Technical Insight
What key quality parameters can NIR measure in fertilizer products in real time?
NIR can measure parameters such as nutrient content (for example nitrogen or urea concentration), moisture, coating levels, and, in some cases, overall composition trends or uniformity. Moisture is especially critical, as it directly affects granulation, caking, and downstream handling. We have also seen success measuring elements such as phosphorus, potassium, magnesium, zinc, and iron, often through secondary correlations within the sample matrix.
How does NIR performance compare with laboratory-based methods?
Laboratory methods remain the reference standard, and as a secondary method, NIR cannot be more accurate than the reference method it is calibrated against. However, well-calibrated NIR systems can achieve excellent correlation with lab results. The key advantage is not just accuracy, but speed and consistency – NIR delivers hundreds or thousands of measurements per hour, providing a far more representative view of the process.
What are the main considerations when implementing in-line or at-line NIR systems?
Key considerations include selecting the right measurement location, ensuring representative sampling, managing dust and vibration, and integrating the system with existing automation if desired. Equally important is developing and maintaining robust calibration models that are specific to the production process.
How do calibration models handle variability in raw materials, moisture, and particle size?
Calibration models must be built using a broad set of representative samples that capture normal process variability. NIR is particularly sensitive to factors such as particle size and moisture, but variability can also come from raw material origin, supplier changes, formulation shifts, or operator practices. Advanced chemometric techniques help separate chemical information from physical effects, while regular validation and model updates ensure long-term robustness.
Operational & Business Impact
Can you share an example where real-time NIR improved efficiency or reduced waste?
A common example is moisture control during granulation. Real-time moisture monitoring allows operators to immediately adjust dryers or granulators, reducing off-spec material, lowering recycle rates, and stabilizing throughput. Another example is the use of at-line benchtop NIR systems, which in some cases have reduced sample testing time by more than 95% once calibrations are established.
How does NIR-enabled process control impact off-spec production and rework?
NIR shifts quality control from reactive to proactive. Instead of identifying off-spec material after it has already been produced, operators can correct the process in near real time, significantly reducing rework, reprocessing, and scrapped product.
What kind of return on investment do producers typically see?
Many producers achieve payback within 6 to 18 months, though this varies by plant. ROI typically comes from reduced waste, lower energy consumption, improved throughput, less rework, and reduced reliance on laboratory testing – all of which add up quickly in high-volume fertilizer operations.
How does NIR support sustainability and resource efficiency?
By reducing waste, reprocessing, and energy usage, NIR directly lowers emissions and resource consumption. It also enables tighter nutrient control, helping fertilizers meet specifications that reduce environmental impact downstream. An often-overlooked benefit is the reduced use of chemicals associated with traditional wet-chemistry laboratory testing.
Integration & Digitalization
How does NIR data integrate with existing process control systems?
NIR systems typically integrate directly with PLCs, DCS, or LIMS platforms using standard industrial protocols such as OPC, Modbus, or TCP/IP. This allows quality data to be used alongside traditional process variables for monitoring, alarming, and control.
What role do data analytics or AI play in maximizing NIR value?
Advanced analytics and AI can enhance calibration models, detect subtle process trends, and predict quality deviations before they occur. This transforms NIR from a measurement tool into a predictive process optimization solution – and this is an area of very active development.
Are you seeing NIR becoming part of closed-loop, autonomous process control strategies?
Yes. Increasingly, plants are using NIR measurements as direct inputs to closed-loop control systems, automatically adjusting variables such as feed rates, moisture, or temperature with minimal operator intervention.
Future Outlook & Closing
What developments in NIR technology are you most excited about?
Smaller and more rugged sensors, improved calibration transfer, and tighter integration with digital twins are especially promising. AI-driven control strategies are particularly exciting, as they will make NIR systems even more accessible and impactful.
How do you see NIR supporting precision agriculture beyond the production plant?
NIR helps ensure consistent nutrient composition, which is essential for precision agriculture. Uniform, reliable fertilizers enable more accurate nutrient application in the field, improving crop yields while reducing environmental impact.
For producers considering NIR for the first time, what advice would you give?
Start with a clear business objective, involve both operations and quality teams early, and invest in strong calibration development. NIR delivers the most value when it is treated as a process control tool- not just an analyzer.
For more information on Büchi’s Near-Infrared (NIR) spectroscopy, click here.