Forage and feed analysis with NIR spectroscopy

Alfalfa is a legume that is grown all over the world because of its high protein content and rapid digestibility for animal feed, mainly for livestock. Nowadays, due to the nature of the primary activity itself, various controls are carried out to determine the quality of the product, especially for export to the Chinese and Persian Gulf markets. One of the main parameters determining the quality of alfalfa is crude protein (CP), but other parameters such as acid detergent fibre (ADF) and neutral detergent fibre (NDF) determine the nutritional value of the fodder and the terms of trade in its commercialisation.

Table 1. Quality of alfalfa (less than 10% grasses) for marketable forage according to USDA Livestock, Hay & Grain Market News (Putnam and Undersander, 2006).

Currently, wet chemistry is still the reference method for determining forage quality, although infrared spectroscopy has been used in quality laboratories for years in order to speed up the process and time required for traditional analysis.

However, the use of portable devices such as the Visum Palm™ analyser opens up a new field for improving the whole process and enables the development of predictive models that mathematically combine references from wet chemistry and other laboratory NIR devices. To this end, calibration is required to mitigate the error intrinsic to the references, especially those from generic libraries, which do not take into account the inherent variability of the raw material and the heterogeneity of samples present in the real world, whether due to weather, soil conditions or other factors.

NIR is not only a useful tool for manufacturers and traders, but also in livestock farming to optimise animal diets according to their nutritional value and to classify incoming raw material according to its nutritional value. In this way, farmers can measure the chemical composition of the diets used without having to resort to wet chemistry methods or external analysis. This helps them to determine their nutritional value and the amount needed to get the maximum yield with optimal nutrition without having to overfeed the animals unnecessarily, reducing their costs.

Regarding the lifetime of the NIR calibrations, it will depend on the changes introduced in the process. If, for example, the raw material is changed or a new product line is created with a different composition, it will be better to make an adjustment of the predictive model to introduce the new variability, since the accuracy of the method will be intrinsically related to any change in its structure and the interaction of the ingredients (cereals, grains, flours or others, characteristic of the feed), hence the errors that the generic NIR libraries usually have.

NIR is not only a useful tool for manufacturers and traders, but also in livestock farming to optimise animal diets according to their nutritional value and to classify incoming raw material according to its nutritional value. In this way, farmers can measure the chemical composition of the diets used without having to resort to wet chemistry methods or external analysis. This helps them to determine their nutritional value and the amount needed to get the maximum yield with optimal nutrition without having to overfeed the animals unnecessarily, reducing their costs.

In conclusion, the use of real-time NIR spectroscopy is becoming more and more widespread in the animal feed sector and particularly in feed analysis, applications which are now extending to the introduction of this technology online for the monitoring of the entire manufacturing process.