NIR instruments can be used for several applications within the feed manufacturing process. Sending samples to a laboratory at a different location however can induce time delays, which may mean that fewer samples are sent and batches which are low quality may be accepted. Introducing a hand-held NIR instrument can increase the number of samples analysed.
Traditionally, NIR is seen as a large instrument placed on a bench in a laboratory, and while this is often still the case, in recent years the size of spectrometers has shrunk to the point where you can now carry one in your pocket allowing the device to be taken away from the laboratory to e.g. a feed mill, or into the field. In addition to being more portable, these hand-held NIR (HHNIR) devices are also very simple and straightforward to use. NIR analysis can be incorporated into many aspects of the feed manufacturing process:
1. Ingredient intake – approve or reject depending on supplier standards, update formulations, segregate ingredients in different silos based on the nutrient content
2. Grinding – ensure consistent particle size
3. Mixing – calculate mixer efficiency by scanning samples from the batch mixer
4. Loading – analyse finished feeds
Hand-held devices have a wavelength coverage and resolution which allows a similar calibration accuracy to that of a benchtop instrument, and within expected uncertainty of the reference method (±1-1.5% for soybean meal crude protein by Dumas/Kjeldahl) (Table 1).
When plotted on a graph, there is no clear difference in the variability of results from any of the three analysis methods. It is interesting to note the variability between different reference methods is similar to the variability between reference vs. NIR (Figure 1).
PRACTICAL EXAMPLE: USING HHNIR TO MONITOR QUALITY OF INCOMING SOYBEAN MEAL
The portability of the HHNIR lends itself to being at locations other than in a laboratory, for example at the intake of the feed mill for raw material analysis. In the example below (Table 2), a HHNIR instrument was used to measure the crude protein (CP) content of incoming soybean meal, which then provided an actionable insight to either accept or reject the incoming load from the supplier. The minimum acceptable crude protein level was 46.5%. All the incoming loads were scanned with the HHNIR, and the samples with low crude protein level, as well as other samples selected at random, were also analysed by wet chemistry to confirm the NIR results. The NIR and wet chemistry results are presented below, highlighted are the samples with different NIR and wet chemistry outcomes. Overall, no sample was accepted by the NIR when it should have been rejected. In other words, no “accept” NIR outcome occurred when wet chemistry outcome was “reject”, proving that NIR can be used as a reliable screening tool for soybean meal protein content. All disagreements between NIR and reference apart from one were within one standard error of the reference method, in these cases, the sample can be rapidly analysed again by HHNIR to validate the NIR result, which is easy, quick and cheap compared to re-analysis by wet chemistry.
Dependent on supplier, an NIR result may be sufficient as proof for a claim. Alternatively, the samples identified as being rejected by NIR can be sent for wet chemistry analysis if further validation is required.
This evaluation demonstrates that NIR can be used as a tool which allows instant decision making by characterising the quality of ingredients, and either accept or reject a load from a supplier or assign loads to different silos (Table 2).
Another benefit to screening all incoming samples is the monitoring of incoming ingredients, which could highlight trends. For example, the NIR allows to compare ingredient quality between suppliers.
The table below shows 10 samples of soybean meal from 3 different suppliers with an expected crude protein content greater than 46.5%. It is clear that supplier B tends to provide a lower crude protein level. This information can be passed to the procurement team, and these materials may be sorted into silos based on protein content, allowing for a more consistent finished feed product, or rejected at intake (Table 3).
NIR instruments can be used for several applications within the feed manufacturing process. Sending samples to a laboratory at a different location however can induce time delays, which may mean that fewer samples are sent and batches which are low quality may be accepted. Introducing a hand-held NIR instrument can increase the number of samples analysed, which can create enough data to spot trends and generate more insight into the feed manufacturing process, maximising the consistency and quality of the feed.
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About Virginie Blanvillain Rivera
Born and raised in France, Virginie moved to Canada after completing her PhD in poultry nutrition and modeling and learning about the poultry feed industry in different parts of the world. She pursued her carrier in the animal feed industry by working in feed formulation, research and development, technology transfer and quality assurance, with strong focus on monogastrics. Over the past years, she has been involved in the development of innovative products and services in Europe and America, while consistently focusing on the end customer needs to provide sustainable and practical solutions to the feed industry. As part of her current role at AB Vista, she supports customers in understanding and optimizing the carbon footprint of their livestock production systems worldwide.
About Gwyneth Jones
Gwyneth studied Animal Science at Aberystwyth University, with a focus on animal production and nutrition. After a short period travelling in New Zealand, she joined AB Vista as a Laboratory Analyst in 2016 where she analysed enzymes and feed for the company’s customers. Since 2020 Gwyneth has been working as the Technical Services Coordinator for AB Vista, with responsibility in Europe, Middle East and Africa. She is based in West Wales, where she enjoys spending time in the countryside with her horses and dogs.