Can Big Data Algorithms on Agriculture be ignored by agriculturalists and governing bodies, considering the peril in today’s times?

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9.5 billion humankind by 2050. Yes, that’s the sheer number of people on this planet who need to be taken care of, where the “taking care of” rightly begins with adequate food and nutrition. In the adversary of global warming and climate change, release of human and industrial hazardous contamination’s in the soil and sea, adoption of various debatable GMO’s, ruthless finishing on high seas etc. have caused irreplaceable damage to the eco system in which we exist today. Contrastingly, we also live in a technologically advancing society which is upgrading and advancing itself every minute across the globe, but even then, there are over a billion people who currently suffer from extreme malnutrition, poverty and hunger.

Hence, with all the technological advancements, it does make some sense to take a leaf out of it and apply the same to our current global agricultural practices in good faith of making our farms more profitable, by creating more and better quality yield, by changing the current business models and making them more evolving and above all ensuring that our current practices of farming (and available farm lands) are sufficient for the generations ahead.

This is where the Ag Tech (Agriculture Technology) takes birth, enhancing our food chain and the eco system we live in (land, air and sea) towards a sustainable future and profitable business models, for the good of society.

The evolution of mankind take its own time and so does his adoption to adverse changes. Likewise, look at our practices of farming i.e. from various nomadic practices to use of tractors today, use of hybrid seeds, greenhouse farming, biotechnology and now satellite technology adoptions to name a few.

Today, the constant changes in technology has brought us to the door step of GSI (geographic information system), Remote sensing, Cloud and Data Analytics, without which, meeting the demand and large economies of scale for agricultural produces is not sustainable. All these technology aid us to see, analyze, understand, generate insights and make predictions which are preventive and decisive concerning the food chain – soil, sea, ground water level, surrounding atmosphere, future production of crops and existing impacts caused by man due to over fishing, oil spillage, contamination of farm lands due to industrial hazards and toxicity of nuclear waste.

So how can the algorithms of ‘AgTech’, Cloud Computing and mining of farm data add benefit in simplifying the complexity of current practices?

  1. Automation, helps in time and effort management. Helps in better productivity and coordination, giving one ample time to plan, connect, coordinate and advice their field farmers, machines tools and dealers (input seeds, fertilizers, MRL residue testing laboratories) simultaneously at the click or touch of few buttons.
  1. Insight mining of farm data helps the myth involved in package of practices in farming and in handling big data analytics for Agriculture. While there will always be challenges in adoption of new technology and practices, especially in the field of agriculture where the package of practices is framed and driven by age old practices. Insight mining helps most importantly in evidence based decision making. In an environmental context, ensuring that individuals have access to information empowers them to make decisions informed by evidence. In agricultural context, open data has the potential to allow information sharing and so enable a culture of continuous improvement, where farming goes beyond sustainable to being productive farming.
  1. Remote Sensing in simple term refers to monitoring, observing and evaluating any particular data (image or statistics) from a different location of presence. Remote sensing platform for agriculture can be either from ground based, balloon, drone based, satellite monitoring or a mix of these together. Remote sensing for precision agriculture and monitoring crop stress helps bring in better traceability and transparency on various factors affecting agriculture such as weather, soil, ground water, vegetation, Land degradation, Crop Health Monitoring, Chlorophyll, Terrain and allied via reflections of the solar light falling on the earth in various color spectrum. Spatial resolution is typically referred to by GSD (Ground Sampling Distance) or pixel size of the remotely sensed imagery. GSD is the minimum size that can be detected of the features on ground/farm lands.
  1. Satellites have never played the significant role, the way they are playing in this century. The Satellite industry is now looking beyond weather, defense and allied purposes towards creating a sustainable and an ensured productive role in agriculture industry where demands are ever increasing but with limited land bank, unpredictable weather conditions and tight margins on business. The satellite imagery helps one (company and individual) understand the layout of his land and optimize his overall plantation. In the near future of today, the GSP (Global Satellite Positioning) can allow farming tools such as tractors to function independently. Most importantly be it organic or generic, satellites can independently detect and share insights on which selected group of crops need nutrients, cross planting for soil nutrition retention and what kind of nutrients and pesticides, delivering exactly the precise amount of it, thus benefiting the overall MRL level prescribed for specific variety of agricultural produce.
  1. With use of technologies such as synthetic aperture radar (SAR) and the highly technologically advanced Copernicus Program of the European Union, today an average of 1.5 Terabyte of information is shared across every day for free distribution via the catapults online data tool.

These technological changes will shift the paradigm once again in current agriculture practices, the evolution mankind has been witnessing and has been advancing in ages. Though there always will be challenges such as adoption – psychological acceptance of change, financial – investment on farming techniques (R&D by food & beverage conglomerates, seed – fertilizer production companies), implementation challenges – Literacy & wireless communication in the rural spaces of developing and under developed third world countries, geo political – coming together of International Organizations under the UN and under AID from various developed nations (by understanding various long term and sustainable humanitarian solutions) and importantly, agriculturalist and agronomists understanding the potential and future predictions contribute in the power of harnessing insights based in big farm data analytics.


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