Patent filings in this space cover using near-infrared light, typically in the 700-2500 nm range, to measure a sample's composition inline or at-line during manufacturing rather than sending it to a lab. Applications documented in this dataset span material analysis and testing (G01N, 59.4% of the 593 records), non-invasive diagnostic measurement (A61B, 21.6%), and animal feed analysis (A23K, 10.8%). The recurring technical problems these patents solve are chemometric calibration, probe fouling, model transfer between instruments, and sample presentation — all conditions that affect measurement accuracy outside a controlled lab environment.

Filing is only moderately concentrated: the leading assignee in the ranked set holds 59 records, and the top 5 combined account for 136 records, or 22.9% of the 593 records in scope. The top 10 combined reach 212 records, 35.8% of the total. That leaves a long tail of smaller filers, meaning no single company controls the field outright, and new entrants have room to file around the most cited prior art rather than through it.

The dataset shows filings climbing from 33 in 2017 to a peak of 55 in 2020, which lines up with a broader industry push toward inline process analytics and remote quality monitoring around that period. Filings then dipped before rebuilding, rising from 7 in 2021 to 21 in 2024, a +200% increase over that three-year span. Readers should treat 2025 and 2026 figures as understated rather than declining, since publication typically lags the actual filing date by around 18 months.

US20020084415A1 claims a specific calibration sequence for liquid-sample NIR measurement: applying monochromatic near-infrared light in the 700-1100 nm range to a reference ceramic plate, then measuring a temperature-controlled liquid sample using the same procedure. It blocks that particular reference-plate-to-sample-cell workflow in that wavelength band, not near-infrared liquid analysis generally. Teams using a different reference standard, a different wavelength window, or a different calibration order sit outside its literal claim scope, though a clearance review is still worthwhile before commercializing a similar workflow.

The thinnest documented branches relative to the core G01N filing volume are healthcare informatics (G16H, 6.7% of 593 records) combined with AI-based computing (G06N, 8.9%), and microorganism/genetic-engineering applications (C12N, 5.1%). These represent calibration-as-data-pipeline approaches — model transfer, drift correction, and bioprocess-specific monitoring — that are filed far less densely than the hardware-centric core. That gap suggests room for claims tying model maintenance or drift metrics to a specific clinical or bioprocess measurement step rather than to generic spectrometer hardware.