The Digital Revolution and Its Impact on Agriculture Production and Quality
Digitalization is happening: big data, the internet of things, sensor technology and cloud computing are becoming a normal part of our lives. According to the McKinsey Digital Europe report from 2016, the agricultural sector has one of the lower rates of digital technology utilization (Figure 1). But things are starting to change.28.02.2020
Within agriculture, weather prediction and satellite navigation (satnav) technologies such as GPS are well established in crop farming. Nevertheless, the livestock and feed sectors are starting to take advantage of a host of new technologies that rely on sensors, information collection, tracking, analysis and automation in order to improve their operations.
In Precision Livestock Farming (PLF), cameras, microphones, pathogen sensors and movement sensors, are used for health and welfare monitoring, weight control and animal management. They provide additional eyes and ears to the farmer and can support them in decisions or even make decisions for the farmer.
The livestock and feed sectors are starting to take advantage of a host of new technologies
Where does digitalization take place?
The trend towards PLF is not growing at the same rate in all species in all countries. Rather, it is unevenly distributed, with more activity in certain countries and for certain species. Looking at the number of patents generated and scientific publications, we see that the main areas of PLF activity are countries such as China, South Korea, Japan, Germany, the Netherlands and the US.
Dairy at the forefront
Dairy cows receive the most attention in regard to PLF, according to a market study commissioned by BIOMIN in 2017. In this study, technologies in the fields of reproduction monitoring, and health and disease monitoring and automation were screened for their level of market readiness. At that time, approximately five times more technologies could be identified in the ruminant sector compared to the swine and poultry sectors (Figure 3).
This can be explained by:
- the size of an animal
- the value of an individual animal.
Larger animals can more easily be fitted with the necessary equipment e.g. sensors such as pedometers which fit to the leg of a cow but not of a laying hen. High-value and long-term producing animals, e.g. breeding stock, can also merit the investment associated with such programs.
The technologies found in the study most often related to animal movement and position, followed by those monitoring body weight and health. It is expected that as these tools develop and improve, their value to agriculture producers will also increase.
Digitalization in animal nutrition
When it comes to feeding livestock, digitalization has a number of use cases that hold promise for the industry. Indeed, BIOMIN has recently invested in this area through several initiatives, including the introduction of a Digital Lab at the BIOMIN Research Center that brings a digitalization to all our research and development efforts.
Anticipating anti-nutritional factors
Anti-nutritional factors in animal diets – of which mycotoxins are the most notorious – pose a threat to the health, performance and well-being of farm animals. These fungi-produced toxins occur in crops both during harvest and storage.
Using algorithmic modeling based on dozens of factors that influence the growth of fungi and the formation of mycotoxins on crops, we are able to predict the occurrence of mycotoxins in feed ingredients such as corn (maize) and wheat.
Our Mycotoxin Prediction Tool draws upon weather data (temperature, precipitation, humidity, etc.) using data from sixty thousand weather stations situated across the globe in order to calculate the probability of mycotoxin contamination.
This allows us to help our customers better understand and anticipate the particular mycotoxin challenge that they may face in the weeks and months ahead, and hence be better prepared.
Mycotoxins are the most notorious anti-nutritional factor that pose a threat to the health, performance and well-being of farm animals, but with the Mycotoxin Prediction Tool, we can predict the probability of mycotoxin contamination in feed ingredients
Improving gut health
Novel DNA and RNA sequencing such as genomics and transcriptomics (so-called ‘-Omics’ technologies) provides deeper insights into the physiological pathways of animals than ever before. With the help of bioinformatics (a combination of biology, computer science and statistics) we are able to gather information on an animal’s gut health.
One use case involves nutrigenomics, which relates to effects of nutrition on gene expression. In one study, BIOMIN researchers demonstrated that birds fed a phytogenic feed additive had 73 genes expressed differently than that of birds fed a control diet, and that some of these were associated with signalling pathways related to the inflammatory response of the birds.
Additionally, -Omics technologies give us a clearer picture of the pathogens within an animal’s gastrointestinal tract (pathobiome) and the set of antibiotic resistance genes within an animal’s microbiota (resistome).
Taken together, these tools allow us to develop safer and more natural alternatives to antibiotics that promote animal gut health, producer profitability, food safety and sustainability.
The emergence of PLF tools holds considerable promise for the future of feed, egg, milk and meat production. We are fortunate to have so many possibilities at our disposal to raise the quality and output of agricultural goods as we meet the challenge of feeding a burgeoning global population.
This paper was given at the Animal Feed Manufacturers Association (AFMA) Forum 2020 held in Sun City, South Africa.