It is widely recognised that raw material nutrient content varies between seasons, growing regions and even individual batches from the same source. However, the true extent of this variability and its potential economic impact remain much less well understood. Feed costs have historically represented between 65 and 75% of the variable costs of swine production and are even more now for many producers.
Cereals are the main ingredient of the diets resulting in large variations in the energy value (Figure 1). The range in the digestible energy content of wheat, triticale and barley was relatively large, being from approximately 600 to 950 kcal/kg dry matter, but only around 239 kcal/kg for sorghum and corn. With such variations, the key target for nutritionists is to provide the animal with the correct amount of nutrients and energy to support optimal performance. Both situations occurring an excess or a lack of nutrients may result in economic losses, through higher costs and very likely lower animal performance.
Figure 1. Range in the digestible energy content of grain species for pigs. 32 samples of sorghum, 23 samples of corn, 79 samples of wheat, 23 samples of triticale and 57 samples of barley were evaluated (Adapted from Black et al., 2019)
With an increased focus on ingredient knowledge and quality control, near-infrared spectroscopy (NIRS) manufacturers and software developers have introduced new products into the market that are able to provide nutritionists a very valuable snapshot of information, thus improving precision in feed formulation. NIRS offers a quick, cost effective, and non-destructive alternative to conventional chemical assays to predict the conventional composition of feeds and raw material, but NIRS can also be used to predict the non-conventional compounds like reactive and total lysine in protein sources, in vivo energy values in cereals, as well as phytate-P and non-starch polysaccharides (NSP).
While corn and soybean meal are the standard in the feed industry for supplying energy and protein in swine nutrition, there are other ingredient alternatives that meet nutritional requirements. These alternatives reduce feed costs, and they may be included cost effectively as demand for corn and soybeans increases or as actual inventory shortages develop. Despite their large content of anti-nutritional factors, the application of NIRS and the mitigation of such anti-nutritional factors through exogenous enzymes are profitable strategies from the time they are implemented by the nutritionists.
Assessing cereal variability has previously involved time-consuming and expensive methods of analysis. The historical nature of the results meant that past averages and ranges were used as a guide to adjust formulations, but there was little opportunity to adjust formulations based on actual cereal batch analysis. Although corn is not the most variable cereal (Figure 1), it is one of the most important cereal in livestock in the world and used herein as an example.
Advances in NIRS technology can be used to predict the metabolizable energy (ME) of corn, which has been shown to vary by more than 400 kcal/kg among 4,100 Brazilian corn samples scanned by the Feed Quality Service of AB Vista (Figure 2). There is no doubt that NIRS helps nutritionists better understand their corn variation, optimise diet formulation, and monitor incoming corn from suppliers. Given the corn inclusion rate in pig diets, this equates to a potential variation in the finisher feed of up-to 270 kcal/kg. Nowadays the cost of 100 kcal energy/kg is around 15 USD/ton, then the economic savings come when the ME variability is large.
Figure 2. Distribution of the energy metabolizable energy in pigs of 4,134 corn samples from Brazil scanned by the Feed Quality Service of AB Vista
To showcase how this variability might happen in practice, we assessed the corn used in the manufacturing process of the feeds for a pig study from wean to finish. The trial was performed in the region of Paraná in Brazil in 2019 and it lasted 143 days.
The aim was to detect the nutritional variation across the phases and how these variations can determine the response of pigs and to what extent the supplementation with the stimbiotic can ameliorate such differences.
Variations on the predicted ME, total arabinose plus xylose (A+X), protein solubility index (PSI) and vitreousness are presented in Figure 3. Although the average ME was 3,329 kcal/kg, a maximum difference of 147 kcal/kg was detected from one corn used in the nursery and one corn used in the finisher diets. PSI as an indicator of corn quality and the total A+X resulted in variations of more than 10% indicating that the soluble protein and the content of fibre is highly variable, and this can influence the response of pigs.
Vitreousness variation was, however, lower (2%). As our knowledge of NSPs advances, being able to measure feed ingredients rapidly through NIRS may enable us to link these fibre fractions with animal performance and health. In this referred trial, the supplementation with the stimbiotic from wean to finish for 143 days increased by 2.8 kg the body weight of pigs regardless of the nutritive value of corn fed in every phase. The improvement of animal performance by the application of products like this stimbiotic offers another reason of interest on its utilisation when the variability of ingredients cannot be assessed on time.
Figure 3. Prediction by NIRS of the metabolizable energy, total arabinose plus xylose (A+X), protein solubility index (PSI) and vitreousness variability (as is) of the 13 corns used in the sequential feed manufacturing across all feeding phases (4 corns in nursery, 4 corns in grower and 5 corns in finisher) from wean to finish in a trial to evaluate the efficacy of a stimbiotic in pigs. Data is represented in box plots and individual data points.
Variation in cereal quality can significantly increase feed cost, particularly for swine producers. Recent cereal quality data, collected by AB Vista from one trial in Brazil, shows the swine ME variation in corn can be as high as 3,423 kcal/kg and as low as 3,275 kcal/kg, which means 148 kcal difference between them. Differences in other regions may well exist although they have not been explored yet like in this example. The potential for economic wins comes when the total ME variability is large, but even 147 kcal/kg differences still represent considerable savings during diet formulation.
Price relationships vary greatly depending on seasonal variability, global and local markets. Pork producers must be able to evaluate the cost effectiveness and nutritional value of various feed ingredients to supply a nutritionally balanced diet at a minimal cost.
NIRS is a handy tool to predict the nutritional content of feed and raw materials, especially fibre, as well as to control feed formulation. Working in this way it is possible to reduce costs and allow a swifter turnaround time when compared to traditional chemical-based analysis.
