Automate forage
analysis across every crop
A full forage analysis means 30+ parameters, each with its own chemistry method — some running hours or days. The NIRSC estimated a complete analysis at 325 operator-hours; NIR delivers the same analysis in minutes. The Phoenix Sideloader with Autosampler goes further — load up to 50 samples and it runs them automatically and unattended.
That throughput is why many of North America's commercial agriculture labs — running hundreds of samples a day — adopted the Phoenix.
Several are calibration providers themselves and offer their forage calibrations on the Phoenix, so a new lab can start on proven calibrations from day one.
Measured head-to-head — and it led the field on accuracy
A prospective buyer designed and ran the test: the Phoenix against three competing NIR and FT-NIR analyzers on soybean-meal protein.
All four ran the same 21 samples, each on its own native commercial calibration, against an independent validation set held out from calibration.
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The customer designed and ran the evaluation — not the vendor
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Same 21 soybean-meal samples, protein 44.4–47.6%
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Each analyzer on its own native commercial calibration
The Result
The Phoenix delivered the lowest prediction error (SEP) of any analyzer tested — and the highest correlation to the reference lab.
Agrees with the combustion lab — in seconds, not minutes
A global protein processor evaluated the Phoenix using an independent validation set of 13 meat & bone meal samples. Protein predictions matched the LECO with a 0.45 SEP across a 42–53% range and an R² of 0.98. Moisture, fat, and ash tracked the reference with comparable agreement.
With no reagents and minimal sample preparation, NIR carries less operator variation — which translates into tighter repeatability, with results in seconds rather than minutes.
As a secondary method, NIR cannot exceed the reference method's accuracy and typically carries 1–1.5× its error. The 0.45% SEP observed here is exactly consistent with that expectation.
NIR's Honest Limitation
Every parameter becomes a quality-control point
Pet-food quality is a process-control challenge: every bag must match, batch after batch. Moisture governs dryer control and shelf life; degree of cook reflects extruder conditions and drives digestibility and texture; protein and fat set palatability; ash tracks mineral consistency.
Because results return in seconds, operators can adjust the dryer or extruder to bring a drifting batch back into spec — before it becomes rework.
THIS IS NIR DESIGNED FOR ANIMAL NUTRITION
See how the Phoenix fits your lab or plant
Tell us your samples and throughput, and we'll match you to the right configuration and calibrations — with a hands-on evaluation on your own material.