Advancements in the ingredient composition matrix for precision feeding

Optimizing feed costs in pig production is essential for the viability of this economic industry. Today, it is also very important to conduct this activity in a sustainable way, which involves increasingly efficient use of resources in production along with assessing and reducing its impact on the environment. From an animal feeding standpoint, this can be achieved through various strategies, as shown in Table 1.

Table 1. Animal feeding strategies to improve the sustainability of production. Adapted from den Hartog et al. (2016) and Choct (2016).

Among the alternatives indicated is applying precision nutrition methods that include:

• a better understanding of the nutritional value of the raw materials used in swine feed,
• a better understanding of the nutritional needs of animals in their different production phases, and
• systems (e.g. sensors, feeding stations, modeling) to adjust nutrient intake to the needs of the animals.

In this article, we will focus on the application of more accurate nutritional values of raw materials in view of the recent publication of the new edition of the FEDNA Tables in 2019. These tables represent an advancement in estimating the nutritional value of the raw materials used in Spain, which improves the accuracy of feed formulation and, therefore, contributes to improving the utilization of resources and the economics of production.

For many years, the various institutions and companies that have proposed feed assessment tables (e.g. NRC, INRA, ARC, Rhône-Poulenc, Adisseo, Degussa, Evonik, etc., and FEDNA itself) have offered "static" nutritional values for raw materials, so that their application to raw materials with highly variable compositions, as most of them have, has not allowed for much precision.

However, new tables have recently come out from institutions such as NRC in the United States, CVB in the Netherlands, INRA in France, the Brazilian tables, and the recent edition of FEDNA, which offer prediction equations to be able to assess the nutritional value of the raw materials used according to their composition (see Table 2). This is particularly critical in the case of energy, since it is the most expensive component of feed, and because it is not possible to determine it directly, but rather through prediction equations.

Table 2. Main characteristics of the recently published nutritional value tables for raw materials used in swine.

The main advantage of the FEDNA tables is that they draw from the most recent international research on the nutritional assessment of the raw materials used in animal feed and, above all, because they are the result of collaboration between the university and the company. As a result, information is available on the main raw materials used in Spain, as well as on their variability. In addition, the energy prediction equations are relatively simple to apply because they include easily determinable parameters (see Table 3), unlike other tables (e.g. CVB), in which many parameters are incorporated and many of them cannot be analyzed in a simple way.

Table 3. Prediction equation for the energy value of cereals according to FEDNA tables (2019).

The almost general availability of NIRS (near infra red spectroscopy) technology, to assess the composition of the immediate principles of the raw materials arriving at the plant, makes it possible to apply prediction equations for the main nutritional components of the feed (mainly energy value, digestible amino acids, and digestible phosphorus).

Table 4 presents an example of the advantages of estimating the energy value of barley in swine, by means of dynamic tables, through estimation equations, compared to the use of static tables. This table shows the chemical composition of barley according to the FEDNA tables (2019) and the average values analyzed by Trouw Nutrition Spain (TNS) during the year 2021. In addition, two barleys with extreme starch values and their corresponding analyzed composition are shown. With these data and the prediction equations recommended by FEDNA, their respective digestible energy (DE), metabolizable energy (ME), and net energy (NE) contents for growing pigs have been calculated.

One can observe that variations in the composition of one or more of its analytical components can result in an energy value that can vary up to more than 200 kcal EN/kg of barley, for example.

Given that energy is the most expensive nutrient in a formulation, it is easy to imagine the impact it can have on the final cost of a growing pig diet (considering an NE cost of 0.10 €/kcal, using current data, this difference of 200 kcal NE/kg in the valuation of barley, would represent a savings, or increase in feed cost, of about 10 €/t if the inclusion rate is 50%. In addition, this inaccuracy in the nutritional assessment will lead to irregular and unpredictable production results.

The use of dynamic assessment of raw materials makes it possible to adjust their nutritional value precisely according to their chemical composition and, consequently, to formulate feedstuffs as closely as possible to the properties of the raw materials and the needs of the animals. Additionally, it allows for the reduction of possible excesses of nutrients and their effect on the environment. A fast and frequent quality control system is needed to be able to work with these dynamic values.

Table 4. Energy valuation of barley according to its composition