Unpredictable climate change has led to Indian farmers losing $5.1Bn worth of crop, since agricultural practices traditionally follow predictable seasonal patterns.

This includes 27000 farmers who contract farm for Lay’s but lose 20% of their crop every year despite following best practices. To make our farms climate change resilient, we completely reinvented our agri-chain operations.

By creating ‘Smart Farm’- a real-time monitoring system using satellite-imagery and remote-sensing to generate early warnings. Successfully digitizing Lay’s farms, Smart Farm is a ground breaking platform transforming traditional agriculture practices to sustainable algorithmic practices- empowering our farmer’s with predictive intelligence amidst unpredictable climate change.

Global climate change is creating unexpected and extreme conditions. This poses a serious threat to Indian agriculture as 86.6% of Indian farmers are small and marginal, implementing traditional agricultural practices which are tied to predictable seasonal patterns. With climate deviating from the norm, these agricultural practices are no longer working.

Lay’s partners with 27000 farmers to cultivate chip grade potatoes. The impact of climate change has led to them losing over 20% of their crop, creating supply-chain inefficiencies that are detrimental to farmers, agriculture and business.

This crafted a mission for our sustainable initiative: To help our farmers become climate change resilient, by putting in a system to mitigate risk and create climate-smart agricultural practices that maximize value.

To combat climate change farmers need to closely monitor every crop, every single day. But Indian farmlands are fragmented into smaller land parcels spread over large distances of 20 kilometers- making every day monitoring, humanly impossible.

Farmers needed to reduce their response time to climate crisis by making land monitoring easy. The pace of climate change didn't allow for trial-and-error based solutions, only data could mitigate unpredictability.

We realised that our long-term partnership with farmers gave us access to unique historical intelligence of yield, soil health, use of fertilizer, pesticides, water and crop diseases- at a crop to pixel level- simplifying land monitoring.

Our strategy was simple: use historical data with predictive insights and transform traditional Indian agricultural practices to climate-smart algorithmically-mediated practices.

For our first year, we green-lit Smart Farm with the help of our agronomists in Madhya Pradesh and Gujarat- leading states of Lay’s

In 2018 Cropin rolled out their Artificial Intelligence & Machine Learning powered predictive modelling solution to help farmers with forecasts.

In November 2021, we first reached out to Cropin to partner with their AgTech tools and started creating a ag-ecosystem intelligence platform using our own historical data of Lay's farms.

May 2022 was when we began data Preparation and training of the AI of +4year of intelligence of +3000 heaters of land of Lay's leading potato States- Madhya Pradesh. and Gujarat.

Our agronomists in these states began onboarding and advocating about Smart farm to farmers starting August 2022.

The project was kicked off first in Madhya Pradesh in Sep 2022 and in Gujarat in Nov 2022 with farm data collection as an ongoing affair as we need to continuously monitor crop growth, health, weather parameters, soil conditions, pest and disease outbreaks, and water stress, among others.

To empower farmers in their fight against climate change, we created ‘Smart Farm’- a real-time monitoring system that uses satellite-imagery and remote-sensing to create an early warning system. This system makes the tech scalable and affordable.

Partnering with Cropin’- an AgTech platform, and leading satellite agencies, we leveraged the world’s largest agri-knowledge graph and trained the AI with 4 years of intelligence of +3000 hectares of our farms. Converging it with satellite imagery, weather forecast and time, Smart Farm analyzes factors affecting growth at crop, plot and pin code level.

By colour coding predictive data, Smart Farm ensures farmers are in check of every crop, the level of emergency, and the actionable tasks to abate risks. For instance, the variation in green indicates intake of nitrogen, gradients of yellow signal water stress and uneven-ness of crop indicates disease. It has successfully mitigated various risks including one where the green cover showed healthy crop but data exposed signs of blight disease.

By obtaining real-time data about the smallest land parcel on their smartphones, our farmers advised by our agronomists, have been able to put in preparatory measures to survive weather anomalies while increasing efficiencies.

Smart Farm has strengthened Lay’s supply-chain efficiencies by making our agricultural practices climate change resilient. Within first year of implementation, Smart Farm has:

1. Made farms climate resilient with 92.5% adaptability to climatic events

2. Increased profitability by increasing yield of upto 25%

3. Reduced crop pandemic risk by 80.3%

4. Ensures financial stability of farmers by increasing their income by $55/acre

Enriched with data from diverse farming techniques of India, Smart Farm’s knowledge graph is now being initiated across Lay’s farms in countries like, Pakistan, Egypt and South Africa – where the population of marginal farmers is high.

It also ensures the financial stability of farmers, enables sustainable use of resources, abates crop-pandemics and is a small step towards strengthening the food security of the planet.

Smart Farm also cements our 2030 pledge to scale regenerative farming practices across 7 million acres- equivalent to our entire global agricultural footprint.

Karif, Rabi and Zaid are the three classifications of crops that India largely follows. Rabi crops are known as winter crops, Kharif crops are known as monsoon crops and

Zaid crops are summer season crops, sometimes even sown in-between.

This is how for decades farmer's would decide on which crop to sow. However, the un-seasonality has made this traditional knowledge of farming irrelevant.