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Using NIR Technology to Improve Feed Accuracy & Pig Performance

Friday, May 22, 2026

By Limei Chen, NIR Manager, and Wilfredo Mansilla, Formulation and Nutrition Manager, Trouw Nutrition North America

Technology has become a normal part of today’s swine farm operations, be it automated feeders, ventilation control, or herd-management software. The same shift is happening on the feed side with tools like nearinfrared (NIR) spectroscopy. This technology provides rapid, non-destructive analysis of feed ingredients, giving us the ability to understand the nutritional composition of raw materials in real time. With more accurate ingredient data, producers and nutritionists can make better nutrition decisions that help manage costs and support consistent animal performance.

What is NIR spectroscopy?

NIR spectroscopy is an analytical technique that measures how a sample absorbs and reflects light in the nearinfrared region (700–2500 nm). Different molecular bonds, particularly those found in organic materials, absorb light at specific wavelengths. These absorption patterns create a unique spectral ‘fingerprint’ for each sample.

By pairing these ‘fingerprints’ with reference analyses from laboratories, a prediction model (or calibration) can be developed. Once calibrated, NIR instruments can estimate nutrient content in unknown samples, including protein, fat, moisture, and fibre, within minutes.

Impact of ingredient variability

Even when purchasing the same ingredient from the same supplier, nutrient composition can vary widely from load to load. Factors such as soil conditions, growing environment, harvest timing, processing methods, and storage conditions all influence the nutrient profile of common feedstuffs. These natural fluctuations create challenges for feed formulation. When nutritionists rely on static book values, two risks emerge:

  • Underestimating nutrient content can increase feed costs unnecessarily.

In grow-finish diets, for example, a one percentage point underestimation of soybean meal crude protein has been shown to increase feed cost by up to $1.00–$2.50 per tonne, depending on the feeding phase, soybean price and amino acid levels of the diet.

  • Overestimating nutrient content results in lower nutrient delivery than intended, potentially compromising growth performance, carcass quality, or feed efficiency.

How NIR supports real-time decision-making

Ingredient assessment via wet chemistry provides highly accurate results, but it is costly, slow, and impractical for the routine testing of every batch of material. NIR technology enables frequent, onsite analysis at a fraction of the cost, making it suitable for daily quality monitoring.

Regular NIR testing allows for:

  • Verification of raw material quality before use;
  • Adjustment of formulation matrices based on current ingredient composition;
  • Maintenance of tighter nutrient specifications in finished feed;
  • Reduction in the risk of under or overformulation;
  • Quick response to shifts in ingredient supply or quality.

This data-driven approach ultimately supports more consistent and more predictable animal performance.

Example of soybean meal variation

In 2025, Trouw Nutrition analyzed over 3,000 soybean meal samples from across Ontario and Quebec. Across these samples, the crude protein content ranged from 40 per cent to 48 per cent.

The impact of this variability in crude protein in a grow-finish diet was simulated. As an example, the simulation revealed that formulating a diet with a 47.7 per cent (NRC, 2012) crude protein book value when the actual crude protein was 45 per cent would result in ~1.5 per cent lower lysine supply, potentially reducing the animal’s growth rate. Although the final effect may vary depending on several factors (e.g., ingredient quality variability), this example highlights how protein overestimation can have significant implications.

Moving toward more precise nutrition

For swine producers, having accurate, up-to-date nutrient information is more than an exercise in quality control; it directly affects feed cost, growth performance, and overall profitability.

pigs eating from a feeder
    Jodie Aldred Photography photo

Ingredient variability is unavoidable, but its impact can be managed when real-time data is available to make more informed decisions. By incorporating NIR technology into routine ingredient evaluation, producers gain greater confidence that the diets entering the barn consistently match what was intended on paper (this is especially important for on-farm millers).

In an industry with tight margins, tools that improve nutritional precision offer a meaningful advantage to protecting your pigs’ performance and your profitability. BP

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