F
Taking
NIR beyond feedstuffs
- analysis to enhance pork production profitability
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by Hadden Graham, AB Vista Feed Ingredients and Chris Piotrowski, AB Vista Feed Ingredients and Ming Yang Tan, Aunir Singapore
wine production has been facing substantial economic challenges in recent years, due to poor crop yields and increased competition for raw materials from the biofuel industry. As a consequence, feed prices have been variable and more industrial by-products have become available. At the same time, we have experienced increasing sustainability demands on animal production, for example to reduce nutrient release in effluent, while producing more and cheaper food for an increasing world population. All this has driven the swine industry to implement more professional, accurate and precise practises. With feed costs accounting for 50 to 80 percent of total variable production costs, nutrition continues to be an area of major focus. The key target for nutritionists is to provide the animal with the correct amount of nutrients to support optimal performance. Both excess and a lack of nutrients are likely to result in economic
Unfortunately, the majority of these analyses are time-consuming and expensive which restricts the number of samples that can be analysed and creates a delay between sampling and receiving results of the analyses. Alternatively, a Near Infra-red (1100-2500 nm wavelength) Reflectance spectrometer (NIR) can be used to predict composition, as this technology is cost effective and fast. This allows nutritionists to get almost immediate feedback on in-coming ingredients and out-going feeds, and to analyse many more samples at a much-reduced cost. However, NIR has much greater potential uses in animal production. This article will discuss the use of NIR in feedstuff analysis and diet formulation, and opportunities to extend this technology beyond standard analysis to support greater efficiencies in swine production.
Predicting feed composition
NIR can predict chemical and physical properties by relating vibrational spectra obtained on a set of known samples to reference analytical methods performed on the same sample set. The resulting calibration can be used to predict Table 1. Range in DE (MJ/kg as fed) and intake index (0-100) of cereal grains in pigs (from Black and Spragg, 2010) the composition of As-fed basis Wheat Triticale Barley Sorghum Pearl millet1 Rice1 unknown samples of the Faecal DE (kcal/kg) 12.8 - 15.1 11.3 - 14.6 10.8 - 14.7 14.1 - 15.2 13.9 - 14.4 14.5 - 14.6 same type of materials. Ileal DE (MJ/kg) 9.34 - 13.40 7.99 - 12.90 6.08 - 12.9 11.5 - 13.7 12.6 - 13.3 13.7 - 14.0 NIR offers important Faecal DE intake index 40.0 - 85.0 42.0 – 100.0 34.0 - 90.0 37.0 - 96.0 advantages over traditional methods, in that it is rapid, nonlosses, through higher costs and/or lower animal performance. destructive, requires no chemicals and hence produces no waste. Thus, it is important for the nutritionist and raw material It is easy to operate, once calibrated, and requires minimal sample purchaser to have correct information on the composition and preparation. nutritional value of available ingredients. Accurate and regular It is common practice for nutritionists to formulate diets with analysis of feedstuffs and complete feed, to confirm diets are average compositional data for ingredients, taking either a correctly formulated, is a key quality control measure. book value or actual analytical data, and often a safety margin To ensure consistency in diets, nutritionists traditionally based on the expected variability in the data. Safety margins used proximate analysis from approved laboratories where can vary, depending on the formulator and the feedstuff, usually ingredients and feeds are analysed for their nutritional contents. varying between zero (average data used) and one standard 42 | Milling and Grain