Data sharing: The key to optimizing poultry feed

Greater digitalization and data sharing in the poultry value chain would help feed manufacturers produce optimal diets.

Near-infrared spectroscopy (NIR) analytics provide real-time data for improving feed. | Evonik
Near-infrared spectroscopy (NIR) analytics provide real-time data for improving feed. | Evonik

Feeding poultry the right amount of nutrients—based on bird genetics and environmental conditions—is essential to optimize production, and data plays an essential role in achieving this. 

Accurate feed analysis and quality control processes are critical for the design of the production setting and the actual feed formulation, and resulting in feed production that better meets birds’ needs. 

Need for connectivity

Nobody has yet developed the perfect digital insight into the entire poultry production process, and there are several reasons why. 

First, poultry production is complex with diverse production targets. Secondly, numerous competencies are needed to handle all aspects of the processes and, finally, only limited data is digitally accessible.

There are software and hardware products that enable us to digitize production processes, optimizing them using solid data. However, most are independent software tools or suites for specific processes. Only a few connect data pools from different production stages.

Digital connection does occur, for example, in the sharing of feed ingredient quality control data with the procurement and nutrition department, however, the degree of data sharing and monitoring remains limited.

Benefits of sharing

More sophisticated solutions share data from quality control to feed formulation almost in real time and in an aggregated way so the feed formulator and nutritionist can decide within minutes if a nutrient matrix for a feed ingredient needs to be updated. 

To achieve this, quality control needs to map analytics from feed ingredients to finished feed regularly, disclosing potential variations in ingredients or in feed mill production processes. Backed up by the combined chemical analysis and feed structure data, the production unit will then be able to optimize their target “feed uniformity” iteratively.

The last step of connectivity – connecting feed uniformity with final broiler weight uniformity remains the least developed. Except for delivery tracking and feed consumed, there is no real mapping of feed uniformity with broiler/flock uniformity.

How do we improve data flow?

Improving data flow is best achieved through increased digitalization. A better digital framework can provide ongoing monitoring of crop quality at harvest and incoming ingredient quality at reception. 

This could support the procurement team to buy more efficiently, based on nutrient quality and, at the same time enable nutritionists to update their nutrient matrix more frequently. An automated link between quality control, feed formulation and the real-time performance of the birds, could lead to faster reactions on quality issues and help in adapting feeds and feeding to health issues or weather conditions, for example. 

Digitalization will also help with the analysis of existing production data and allow the combination of new parameters with actual data sets to improve predictability for slaughter weight and provide an individualized feeding strategy for each production target based on individual farm settings.

Finally, it supports innovation and the development of new products and services, as field data will show the potential of innovations immediately. 

The power of data

The consequent use of data will improve accuracy in feed formulation, and support optimization of all processes around feed ingredients, finished feed and livestock production. This is a great step forward, because good nutrition, animal health, welfare and performance start with knowing the quality and nutrient value of feed ingredients, but equally important, requires the use of the obtained data. 

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