Implementing Dynamic Feed Formulation and Precision Nutrition in Poultry Production

Feed formulation should always consider the nutrient content of ingredients and the nutrient needs of animals based on the target growth or egg production rate to maximize profit, depending on market demands and economic conditions. However, the nutrient composition of feedstuffs varies, and nutritionists or feed mills do not always obtain nutrient content information promptly for necessary feed formula adjustments.

Traditional analysis of nutrient content using wet chemistry methods can take several hours or days.
Often, wet chemistry introduces additional variability between and within labs that is not related to the ingredient being analyzed.
Aminograms for amino acid profiles require a significant financial investment that may not pay off if the information isn’t used quickly.
Determining the energy content of feed ingredients with in vivo experiments can take several weeks.
Linear prediction equations used to estimate the energy value of feedstuffs based on proximate analysis results are often inaccurate.

Many nutritionists and feed companies choose to use table or book values that reflect the most common averages for each feed ingredient. These values are revised periodically as new information becomes available. However, the level of segregation of this data doesn’t allow for accounting for the variability in feedstuff quality that arrives at feed mills. As a result, feed formulation has become rigid and not adaptable enough to respond to changes in feed ingredient quality, processing, storage time, or feed additive effects, among other factors.

This approach is known to be risky when the goal is to ensure optimal feed nutrient and energy content.
It has been shown that variability in feed nutrients can be costly for poultry operations.
This variability is a key cause of differences in bird performance and even health problems.

Nutrient information, variability, and dynamic formulation

Tools like rapid analysis methods, including near-infrared spectroscopy (NIRS), address the issue of ingredient information by providing fairly accurate measurements of amino acid and energy content, digestibility coefficients, fiber, and antinutrients, along with several quality parameters that enhance nutrient, energy, and digestibility predictions.

All these parameters can be quickly determined from samples at a lower cost and with minimal sample processing.
More frequent analysis results help quantify actual variability and improve understanding of how to manage it.

Using these tools, it is possible to adopt dynamic feed formulation to improve precision nutrition. Dynamic feed formulation is already in use at some feed mills and poultry companies around the world. There are positive experiences, but there is still much to learn and improve. The goal of this article is to discuss some of the needs and challenges of implementing dynamic feed formulation and advancing poultry precision nutrition.

The feed formulation method

Traditional least-cost feed formulation is a linear mathematical method that doesn’t easily or accurately allow us to account for nutrient variability in feed ingredients or variations in nutrient targets to meet performance or profitability goals. There are other options for feed formulation.

For example, non-linear feed formulation could be a better alternative when combined with mathematical models of animal growth and performance. Unfortunately, these methods are not yet widely available, as they lack standard models and always require customized solutions.

Implementing dynamic formulation and precision nutrition

Improving precision in poultry nutrition relies not only on nutrient data but also on better feed formulation techniques. Feed mill infrastructure, resource management, and trained personnel at both the feed mill and farms can be barriers to implementing dynamic feed formulation and precision nutrition.

Dynamic feed formulation may indicate more diets, diverse formulas to mix and this increase complexity in the feed mills and farms.

Limitations to adopting precision nutrition and dynamic feed formulation include:

1. SCALE SENSITIVITY/ACCURACY AND PRECISION IN AUTOMATED FEED MILLS

Major, minor, micro, and liquid scales must be improved to account for slight variations in the formulas.
Ingredients like limestone, which may constitute less than 1% of the diet most of the time, are overdelivered in feed mills. Diets formulated to contain 0.78% to 0.80% calcium can be 70 to 75% of the time 25 to 30% above the target level.
Levels of calcium that are almost double the target are not infrequent. Calcium excess may have a deleterious effect on feed intake, fecal moisture, efficacy of phytase and other enzymes, and phosphorus utilization.

2. STORAGE ABILITY

The appropriate number of microbins and feed bins to segregate more feed ingredients according to their quality should be set in advance when seeking precision nutrition. The warehousing and accounting of feed ingredients must be improved.

3. TYPE OF FEED MILLING SYSTEM

In feed milling, both batch and continuous (in-line) mixing systems are used, and sometimes a combination of both is employed to optimize production. Batch mixing offers precise control over ingredient ratios and mix quality, while continuous mixing provides steady throughput.
The best approach depends on factors like production volume, ingredient variability, and desired level of automation.
Dynamic feed formulation and changes in diets create challenges for software batching systems, feed delivery, and accounting. The existing mill software, produced by Beta-Raven, Repete, and Comco, may face challenges in controlling variability in feed formulas.
The hardware, electrical demands, and software security should be adapted when producing more variable feed batches.

4. FEED MILL PERSONNEL TRAINING

As feed manufacturing becomes more complex, personnel need improved training to handle different feed batches. They must know how to adjust software, hardware, and manage warehousing effectively.

5. CONSISTENCY IN PARTICLE SIZE PRODUCTION, MOISTURE CONTENT, AND PELLET QUALITY

It is known that grinding affects the energy and nutrient utilization of all feedstuffs and the ability of birds to cope with antinutrients like trypsin inhibitors. Broilers tend to grow better when fed diets with coarse (1,300 μm dgw) solvent-extracted soybean meal containing high trypsin inhibitor levels than when the same soybean meal is ground fine (530 μm dgw).
The particle size of a grain can be very variable. It is affected by miller settings, but also by moisture at harvest, drying temperature, and storage time. All these factors, especially moisture content in the mixer, may also affect pellet durability, which is also critical for broiler performance.
Then, measuring and controlling grain particle size and moisture during feed manufacturing is an important parameter, but its determination is time-consuming. Recently, several research groups have been trying to automate these processes using NIRS-online.

6. FARM-LEVEL IMPLEMENTATION

Farms must have enough bins to manage diverse diets typical of dynamic feed formulation and precision nutrition. Staff should be trained to understand how to feed these varied diets and provide the correct amounts based on age or productive phase.
Feed consumption should be measured more accurately. New methods such as image or ultrasound sensors for monitoring feed bins are now available, allowing precise predictions of daily feed intake.

Several aspects, including methods of analysis, management of information, feed mill infrastructure, quality control and assurance, equipment, and personnel, can be improved to enhance precision nutrition. These present critical challenges for implementation.