Bangladesh, being a developing country, has a financial limitation for applying precision farming as some of the technologies mentioned above can be somewhat expensive and high-tech to follow through for the current infrastructure.
A research paper of 2009 on the economics of VRT technology gives this estimation about the expenses:
As we can see, it’s pretty expensive. Although, a lot of years have passed since this estimation has been made. Technology has advanced since then and for sure, some of these expenses have declined by a good factor. Still, it’s not quite there where any Bangladeshi farmer can afford a VRT kit in their field. Maybe somewhere in the near future, but not yet. It’s still an approach of breaking a butterfly upon the wheel. Mostly because of the farm ownership situation of this country.
Most of our farmers are smallholders, meaning that they grow food on a small piece of land to feed their families and might have some leftovers to sell at local markets. The first world countries design the IoT devices in a manner that they can support thousands of acres of land and their data, in calibration with how big their individual farms are. So to establish this kind of technology, some kind of unification within these micro-lands must be established which itself is a tough challenge. Still, these limitations don’t completely bar the country from benefiting from some of its applications. Some exemplary ideas where precision farming may be applicable despite our financial constraints are mentioned below:
Pilot Projects on Precision farming
There is almost no doubt that precision farming will be affordable in the near future. But we really cannot sit still waiting for that day to emerge. The world is moving at a fast pace and if we don’t get aboard this technology trend we as a nation might be lagging behind. Nationwide or industry-scale precision farming may still have a long way to go. But most of the precision farming approaches, we can test out for this country as small-to-medium-scale pilot projects. The initiatives for this kind of actions might be taken by :
- The Government. or Agricultural Ministry to be specific
- Agricultural Universities or research institutes.
- Contract farming agents/companies like ACI or Pran. They can make a contract with their designated farmer upon the condition that they’ll facilitate precision farming for them.
- Agriculture-based Corporations/Companies
The initiatives can range from projects based on any scope of precision farming to establishing policies like cooperation within farmlands, granting subsidies, or anything else that facilitates the acceleration of this process. From the pilot projects, the production increase, profit margin, and feasibility can be analyzed and decisions can be taken whether to expand a particular project or not.
Analysis with sensors/peripherals on a community level
An initiative like this either requires the merging of several land areas together and the farmers collaborating, or a dedicated group of people ( preferably government officials related to agriculture ) to facilitate and enforce the practice of precision farming on a community ( like thana or union ) level with the help of some authority and ownership over the tools and sensors necessary. This is merely a concept, an exemplary proposal is mentioned below.
The Department of Agricultural Extension can play out a core role in this endeavor. They can form a committee in every said community, each of those committees will hold ownership and responsibility for the tools and sensors. The committee will deal with the data collection, sending them to a central server, and implementing/ educating farmers on the AI-driven decisions.
Plant health, disease detection, and management
Lucky for us, many plants and livestock diseases are recognizable by image processing from a smartphone image. And plant health monitoring devices have been made cheap enough to be affordable for almost any community. There’s a company named PhotoSynq that has a pretty convenient 100$ device that can effectively monitor plant health. So maybe not much work is needed to be spent “inventing” for us.
There is a catch, however. Most of these “data” and ML models are from first-world countries. The geometry, grown crops, weather, and a lot of other factors may be different than us. For example, the USA mass produces wheat as their primary crop. So, most of their research and data are on wheat. On the contrary, we mass-produce rice. Their data and trained model will not be of much use. We may very well have to collect our own data and train our own learning model to cope up with the health of our crops.
Based on that argument, the authorities may consider working on establishing this technology if they consider collecting all the farming data for further analysis and forecasting.
Predictive Analysis for farming
For farmers and governments in developing countries, crop modeling can help them prepare for undesirable circumstances such as drought, heavy rainfall. Also, the idea of supply-chain prediction for farming decisions may not be too far-fetched as well.
You can check out our previous blog on precision farming, what it is and why it’s necessary.
References and Useful Resources
- Deploying precision agriculture in developing countries provides opportunities, challenges – AgBioResearch (msu.edu)
- (PDF) Precision agriculture in the World and its prospect in Bangladesh (researchgate.net)
- Precisionagricultu.re|All precision agriculture tips and tricks
- (PDF) Precision Agriculture in Bangladesh: Need and Opportunities (researchgate.net)
- The Future of Farming – YouTube
Contributor: Istiaq Bin Salam Siaam