NIR TECHNOLOGY ON DAIRY FARMS

Feed is one of the largest expenses on most dairy farms, so even small improvements in feed efficiency can have a significant impact on profitability. The quality of feed also has a direct influence on overall herd performance, including milk production, cow health, and reproduction. This makes feeding a consistent diet while minimizing feed waste an important priority on farms. However, maintaining a consistent ration can be difficult, especially with the occurrence of variation in dry matter (DM) content. As a result, near-infrared (NIR) technology has been showing some promising results as a tool for feed management.

NIR technology works through an infrared light shining on a sample and measuring the amount of light reflected. Different nutrients reflect and absorb light differently due to their unique chemical bonds. By analyzing these patterns of light absorbance at specific wavelengths, NIR is able to provide information about the sample’s composition.

In order to make sense of the information given from NIR, the technology must be calibrated. These calibrations are created through compiling data from traditional wet chemistry and combining it with NIR samples used as a reference. The more samples used for calibration, the better the equations, so hundreds of samples are needed to calibrate the device.

Using NIR on a farm is simple. A feed sample is placed in front of a scanner; the scanner then analyzes the feed sample and then quickly returns a result. This allows the farmer or nutritionist to make decisions regarding the feed at that moment.

NIR technology is available in a few forms. One option is a portable hand-held scanner. This allows for a quick analysis of feed or forage samples anywhere on the farm. Their current use on dairy farms is more commonly through nutrition companies. Another option is an NIR system that can be installed directly into a feed mixer. These systems continuously analyze the feed ingredients and total mixed ration (TMR) during mixing. This can help monitor DM of forage in real time and automatically adjust ingredients when forage conditions change, ensuring cows receive a more consistent diet (Haan, 2023).

Monitoring DM is especially important since it can vary daily, particularly when using larger bunks or during changes in weather conditions. These fluctuations can lead to significant forage variability on farms, making it difficult to maintain a consistent TMR. Even small changes in forage moisture can alter the amount of nutrients cows receive, potentially affecting milk production, cow health, and overall herd performance. For example, if the target ration is 55 lb DM/day/cow and haylage is 20% of that diet with a DM of 32%, a cow would receive 34.4 lb of haylage as-fed (11 lb DM of haylage). However, if the DM of the haylage unknowingly changes to 42% and the cow still gets fed 34.4 lb of haylage as-fed, the cow would now be receiving 14.4 lb of DM haylage. This means that the cow is now receiving about 6% more DM than intended. This will change the total intake and the balance of the ration. Being able to detect that DM change when it happens would allow for the correct ration to be fed.

Research has shown that NIR is able to help improve feed management. One study evaluated an on-farm NIR system and found that dairy farms using the technology had lower feed costs compared to farms not using it. The study also mentioned an improvement in herd health, based on changes in blood parameters and reduced mastitis incidences (Piccioli-Cappelli et al., 2019).

Overall, NIR technology can help farmers and nutritionists monitor forage DM and nutrient levels in real time and react immediately to these changes. These immediate adjustments to the diet can help improve TMR consistency, feed efficiency, and overall herd management, which can help support milk production, health, and cow performance, while also reducing feed waste across the herd. However, while NIR shows strong potential, particularly for DM determination, continued refinement of calibration equations is still needed to improve accuracy.

— Corina Warren

cwarren@whminer.com