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  • Writer's pictureLev Mikulitski

Prediction in poultry farming; a goldmine for feed and animal health companies

It is evidenced that livestock diseases impact the whole production ecosystem, particularly feed and nutrition companies, animal health companies, and even human health companies. It is reported that 60% of the infectious agents of humans are exchanged between animals/birds and humans (zoonosis). Most of the food-borne diseases are transferred via food chains, e.g., Salmonella spp. are mainly associated with food-borne diseases. Moreover, the environmental disturbance in the poultry farms may develop odors that are complex mixtures of the gases. The inspiration and extended exposures of these odors/gases have severe consequences on the health of the birds/animals, but also workers, thus, it affects the whole ecosystem. Therefore, the latest Biosecurity technological advances (multiple sensor technologies & artificial intelligence) and prediction technologies are a true blessing for poultry farmers, and the entire ecosystem. These technologies aimed to optimize disease surveillance and anticipation at poultry production farms. Hence, they reflect the enhanced forecasting capability of any disease outbreak at the production farms. In this way, the whole ecosystem is optimized. It makes the poultry farmers pro-active to perform the best husbandry practices. These practices ensure optimum productivity, traceability, food security, and profitability.



If we can predict, we can prevent


It is well-established that the prediction and early disease detection related data advances the poultry farmers to take real-time decisions regarding the management and production performance. This data is the principal actor for the animal health and nutrition companies because the inputs that these technologies produce allow them to respond in real time on the one hand, and on the other hand to refine their value proposition over time. Ultimately it is necessary to understand that the production environment in poultry is dynamic and changing and therefore it is important for learning and constant improvement of production resources.


As notably mentioned in the "Health for Animals" report cunducted by the global animal health association, software systems can harness the wealth of data provided by digital technologies to predict disease or health challenges before they occur. In some cases, the right technology can indicate a high ‘probability of disease’ that could allow for earlier treatment with the right regulatory framework. In fact, these insights are essential not only for farmers integrations, but also for the whole ecosystem.


The data of prediction and early disease detection interaction with the animal feed companies;


It is well-known that the objective of the animal feed and nutrition companies is to provide the animal feeds according to their requirement. Hence, it compromises the growth performance and productivity of birds. Therefore, these companies should be interlinked with the prediction and early disease detection data. It is real-time data that is provided by sensor-based IoT-related technologies and processes with AI/ML Algorithms. This data directs the animal feed companies to ensure precise feed formulation. It means using the right quantity of the feed ingredients at the right time following the provided data. It assures more precision about the selection and finalization of the feed ingredients.

This data enables these companies to respond to the nutritional changes efficiently. Thus, animal feed companies have become more realistic to provide precise feeding. Based on the data, feed is supplied according to animal requirements and adaptability. It provides more accuracy and better-streamlined procedures regarding raw material, feed processing, and formulation. Hence, this data assists the animal nutrition companies to take the best decisions during procurement to the quality control and operational management. The provision of the specific nutrients reflects the precise understanding of the animal's health/well-being. It is a way forward towards optimum animal health and productivity (i.e., improved feeding efficiencies).


When it comes to diseases, the infrastructure that provides feed and water to birds is also the conduit through which diseases pass. On the one hand, the feed that is fed into the feed silos undergoes a quality control process, and on the other hand, most of the food-borne diseases are transferred via these chains afterwards, e.g., Salmonella spp. In this case the ability to identify the preconditions for the development of various bacteria in food is an asset of great significance both for the integration but also for the feed & nutrition supplier who will need to prepare accordingly in order to provide the integration with alternative produce.


Therefore, it is concluded that the animal feed and nutrition companies become more efficient through the biosecurity surveillance data and prediction technologies. They can optimize their feeding products (feed additives, formulations) through the life cycle assessments and be aware in time when there are issues that require intervention and operational desicion. Ultimately, they ensure sustainable productivity.


The data of prediction and early disease detection interaction with the animal health companies;


The main goal of animal health companies is to advocate safer production with the appropriate usage of the drugs. For this purpose, these companies make investments in R&D (Research & Development) to provide innovative medicinal products for food-producing animals. However, it is not possible when these companies are backed by the traditional practices occurring at the farms. These practices compromise the disease surveillance records. Therefore, the blessings of AI & sensor-based technologies provide the best disease surveillance data. This data reflects the earlier prediction and detection of the diseases. It provides opportunities to these animal health companies to become more efficient and precise in their research and product developments. It lights the way for these companies to devise the best disease prevention schemes (i.e., vaccination).


Hence, this data assists these companies for the earlier diseases diagnosis (on-spot/remote) and precise treatment strategies. Thus, it betters animal health delivery systems and ultimately improves their well-being and performance.


To sum up:


It is concluded that animal feed and health companies are the major key players that provide innovative solutions backed by disease surveillance data and prediction technologies. These companies offer a new horizon in animal health and production, which provides the best prevention and cure strategies. These companies aimed to minimize the disease threats at production farms. They reduce the cost of production associated with the diseased animals. They restrict the exchange of disease-causing agents among humans and people. They also reduce the emissions of harmful poultry farm houses gases. Thus, they benefit the whole ecosystem. Finally, it ensures improved well-being, optimum productivity, traceability, food security, and profitability. Eventually, collaboration through data becomes an unprecedented ability to exhaust joint business processes.

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