Smart farming: Agriculture data can reap a bumper harvest Editorial 25th Apr’19 FinancialExpress
Headline : Smart farming: Agriculture data can reap a bumper harvest Editorial 25th Apr’19 FinancialExpress
Dependence on government for agriculture data:
- Agricultural statistics is not easy to collect and compile, hence the dependence on the government.
- But this data suffers from the issues of timeliness, reliability and integrity.
- Yet, since it is only source, there is no option but to use government data.
Huge data in various silos:
- Data available with the government in various silos, not correlated, and often not inter-operable. .
- This includes data on land, ownership of lands, weather and rainfall, irrigation, electrification, crop-wise sowing, production and yield, fertiliser consumption, market arrivals and prices from APMCs,wholesale and consumer prices, procurement, etc.
- Then there are the new ‘data-driven’ schemes like soil health, PM crop insurance, PM KISAN etc, which have important data.
Issues with data:
- Data collection:
- The elaborate exercise of collection of primary data (collected by a researcher from first-hand sources) on even those crops (rice, wheat, etc) that have established systems still has design errors and implementation gaps.
- Crops like sugarcane and cotton are more difficult.
- Even the compilation and publishing of data needs to be improved.
- For example, it is is well known that data related to sowing or crop-cutting always comes late.
Agriculture data has been used by policymakers:
- A large volume of data related to agriculture exists, but in a number of segregated silos. They are collected at different intervals of time for different purposes. This data is collated, summarised and published by various government agencies.
- Historical data sets have been used extensively for analysis, understanding trends, estimating impacts of weather and policy on crops and prices, etc.
- These have helped policymakers and researchers to suggest changes in policy prescriptions, and design, implement and monitor schemes.
But has not helped the farmers much:
- But the policy prescriptions and scheme have not helped farmers take timely decisions to increase their income or even reduce losses in the event of a change in the situation.
Due to focus on macro indicators:
- Rather than providing micro level data to help the farmers, what is happening currently is that modern technology is being used to give ‘unsolicited’, often irrelevant, advice based on macro indicators.
- Most advice, though scientifically correct, is not farmer-specific, and is of limited use.
Need micro-level data for farmers to benefit:
- The farmer will be better off if provided with specific crop, soil ,weather and market information advisories.
- This requires micro-climate details like rainfall, moisture levels, soil fertility, etc, are mapped along with his crops as also advisories on fertilisation and irrigation schedules, pest control measures and market trends are given on time.
- Today’s technology is capable of doing this in real time.
This information can be provided by tech entrepreneurs:
- Modern technology enables using of data in the agriculture sector to help farmers take more informed decisions and further the prosperity and income of farmers.
- Young technology entrepreneurs today can offer farmers specific solutions using data from the sky, the soil and the market.
But they need help:
- These new start-ups can help the farmers if two core issues are addressed:
- Access to existing data
- The revenue model
- Give open, but ‘limited’ (limited on account of privacy and national security issues) access to primary data in the government.
- Provide technical backing to agri start-ups and enable a revenue model to enable them to participate in the extension space.
GS Paper III: Economy