India surpassed the European Union as the world’s largest milk producer in 2016, producing around 25% of global milk output. The Indian dairy industry is one of the world’s fastest-growing. It sustains a total of 100 million dairy farmers, the majority of which own a small herd of two or three cows. India is also the world’s largest consumer of milk. This implies that the industry has enormous potential in the region.
Despite this, the market is highly fragmented and plagued by problems. Problems include identity fraud, disease transmission, and distrust between farmers and insurance companies.
Here are four ways in which Artificial Intelligence (AI) could transform the sector. AI can enhance the lives of smallholder farmers, as well as how public-private collaborations would be vital to their success.
Digital Identity
Cattle in many nations, including the EU, the UK, and the US, have “cattle passports”. Officials use this to track infectious disease outbreaks, ensure the successful implementation of government programmes, and file insurance claims.
In fact, this suggests that certain cattle have tags inserted into their ears to identify them. These tags are not only unpleasant for the animals, but they are also ineffective. Farmers in some developed nations, such as India, cut the cattle’s ears to conduct identity theft and fake insurance claims.
Cattle facial recognition is an ideal solution to the issue of cattle identification. In India, it is known as the Aadhar of cattle in India. Thanks to recent developments in computer vision, it’s also a scientifically validated approach.
These solutions can also help farmers and insurance providers strengthen their relationships. Because of the high rate of identity theft, there is a lot of distrust between farmers and insurance providers. It is shown by the low penetration rate in the cattle insurance market. Farmers and insurance providers will thus benefit from automated identification and testing mechanisms.
Health Monitoring
Cattle wellbeing is the most critical feature of any dairy activity since it is directly related to milk production. Sub-clinical mastitis is one of the most prevalent diseases in the dairy industry. It costs the Indian dairy industry $1 billion every year.
Currently, IoT sensors are used in the animal-health-monitoring industry. It helps to gather real-time data on cattle. The real-time data includes their walking habits, rumination patterns, and temperature shifts. The collar, which goes around the neck of the cattle and transmits massive quantities of data every second. It is the most common IoT system in the dairy industry.
Cattle Trading
Another field that is still somewhat unorganized and has a lot of room for development is cattle trading. Cattle prices are currently determined by agreements between buyers and sellers.
We can use Machine Learning models to create a live cattle market exchange. It is possible if we can collect knowledge about a cattle’s history, such as milk productivity, age, health records, sire and dam. This will help buyers and sellers communicate via a transparent platform.
Financial Inclusions
Several government initiatives, such as the Pradhan Mantri Jan Dhan Yojana, increased the banked population from 35% to 80% overall. Yet, financial inclusions of India’s rural population, or banking the unbanked, has remained a major challenge. Even so, cash accounts for nearly 72% of all transactions in India.
When it comes to rural India, the numbers are much worse. Moreover, the dairy industry in the country is extremely divided. Additionally, it displays a consolidated dairy accounting for just around 20% of the market. Many farmers in desperate need of credit are unable to obtain credit from structured outlets due to their lack of digital financial footprints. Because of high-interest rates and inhumane collecting practices, informal lines of credit will also make the farmer’s situation worse.
However, AI can solve this problem. It is by using indirect methods of measuring farmer creditworthiness and disbursing loans on the basis of these scores. Multiple companies in the sector are calculating the creditworthiness of farmers and to extend loans to them. They use modern data such as psychometric questionnaires, social media and network links, phone/app use, SMS, phone calls, and other datasets.
Roadblocks in AI Implementation
There are three big barriers to India’s dairy sector’s path to achieving AI vision.
1. The first most important impediment to these developments is the shortage of datasets. There are no proper datasets available for AI applications. Necessary datasets for this purpose can be health tracking, financial instruments, or a livestock trading marketplace.
To make these solutions a reality, the government and private sector must collaborate to build a dairy data stack. The government can help by providing data on livestock profiling, cattle genetics, and milk yields for individual farmers. Private companies can contribute with financial background datasets, low-cost IoT devices for smallholder growers, and up-to-date infrastructure tools.
2. Second, the bulk of government policies and programmes focuses on the crop agriculture sector rather than the dairy industry. However, the government sees dairy as a secondary source of income for farmers. Therefore, the crop agriculture market gets preference in the new policies of the government, then in dairy. For example, the PKCC (Pashu Kisan Credit Card for animal husbandry and dairy) went active 20 years after the KCC (Kisan Credit Card for crop agriculture). Additionally, the National Digital Agriculture Blueprint agri-stack system, which is a farmer- database, does not provide open-source dairy data during its initial launch.
3. Third, extending high-end technological technologies to the rural community can have complications. Governments must build environments that allow innovators to improve the lives and incomes of smallholder farmers. It is only after this that AI can disrupt India’s dairy industry and benefit farmers. Building multi-stakeholder alliances can tap into these possibilities. Additionally, it can jointly develop a roadmap to a dairy market in India with AI-empowerment is the best way forward.
The Bottomline
Artificial Intelligence has the potential to transform India’s dairy sector. It is possible only if the right data are accessible to the right stakeholders. If we want to understand AI’s ability to support smallholder farmers, we’ll need an open-source dairy data stack. There is a need for more dairy-focused government policies although.
