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Tuesday, November 19, 2019
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Big Data for Smart Agriculture

Although the agriculture sector in India has been lagging behind sectors like banking and retail in taking up Big Data approaches, it could soon catch up. First movers in the big data landscape in agriculture are already achieving positive results, which is prompting other stakeholders to follow suit.

Introduction These days Big Data is one of the hottest buzzwords in the ICT world and has come to the forefront of everyone’s attention. While its definition may be still in the realm of debate, unanimity exists on its being a definitive source of competitive edge across various sectors.

Agriculture is no different. Beyond Agriculture is no different. Beyond improving the accuracy, quality and yield of production, Big Data in agriculture is being used to predict climate shifts and accurate weather forecasts.

With the world’s population increasing and the challenge of ensuring food security across the world by 2050 looming large, dynamics of agriculture are rapidly changing. Data drive many of the decisions behind these changes.

Big data allows farmers make better and informed decisions.

Big Data Think of a farmer who’s about to cultivate some crop in his agricultural land, but has no idea when the rains will take place. However, if he gets to know about the precise date and time of rainfall as well as the expected amount of rainfall and soil moisture, he is on a firm footing to take his next step.

Some years back Colombian farmers were hit hard by climate change, which has substantially reduced their rice yields. Researchers at the Colombia based International Center for Tropical Agriculture (CIAT) took upon themselves the task of analyzing weather and crop data of 10 years to understand the impact of climate change on rice yields.

After feeding the patterns in climate and yields into a computer model, the researchers were able to predict a drought and advised the farmers in some regions against the sowing. The National Federation of Rice Growers served an advisory not to plant in the first of the two annual growing seasons. The farmers who concurred with this advice were able to avoid massive economic losses estimated at USD 1.7 million. Consequently the project was awarded at the UN Big Data Climate Challenge.

Big data based analytics solutions can be utilized to offer weather forecasting, cloud-hosted information resources for farmers, real-time optimization of farming machinery, automated irrigation recommendations and monitoring of crop prices. Social Media, Mobile Computing, Analytics and Business Intelligence and Cloud Computing (SMAC) technology, facilitate e-Markets and Value Chain Analysis providing technological advantages to farmers. In addition, Geospatial Technologies safeguard the efforts of farmers by reducing cultivation uncertainties, and sowing seeds of prosperity. The emerging GRIN Technologies: Genetics, Robotics, Informatics & Nano-Technology is generating lots of data paving the way for Big Data Analytics in Agriculture in a big way in days to come. “Precision Agriculture uses GPS and Big Data Analytics for crop management in which, Analytics facilitates in determining the best crops to plant and operationalizing effective farm health management, considering both sustainability and profitability,” says Prof. Madaswamy Moni, Director General (Retd), National Informatics Centre & Professor Emeritus & chairman, Centre for Agricultural Informatics & e-Governance Research Studies (CARIS), Shobhit University Meerut.

Improving Index Insurance Products

There is no denying that erratic weather and climate shifts cost farmers and fisher folk much. The rising frequency and severity of droughts, storms and other extreme weather events play havoc with the livelihood of many farmers. Banks are hesitant to lend to farmers because they are apprehensive that a drought might lead to defaults on the part of the farmers.

Most poor and vulnerable farmers don’t have the financial wherewithal to invest in improved seeds and other agricultural inputs. Even if they take risk by investing, chances are that they might suffer due to bad weather.

Harnessing big data, the Weather index-based insurance is a viable proposition to manage weather and climate risk. Since an indexbased insurance uses a weather index, there is no need for an insurance company to visit the policyholder to assess damages and arbitrate claims. It simply sees if the rainfall is below a previously agreed threshold. All this has been made possible by the use of Big Data.

According to the estimates, the software market for precision farming tools such as field mapping, yield monitoring, weather forecasting and crop scouting is slated to grow 14% by 2022 in the US. India is a lucrative market for the providers of farm management software.

Monsanto has reveled in a report that the data science market in agriculture could be worth as much as US$20 billion.

Role of Big Data

In Indian Agriculture Agriculture plays a crucial role in India’s economy. About 60 per cent of the rural households are dependent on agriculture as their principal means of livelihood. Along with fisheries and forestry, agriculture is one of the largest contributors to the Gross Domestic Product (GDP).

As per the 2nd advised estimates by the Central Statistics Office (CSO), the contribution of agriculture and allied sectors (including agriculture, livestock, forestry and fishery) to the Gross Value Added (GVA) stands at 17.3 per cent of the Gross Value Added (GVA) during 2016-17 at 2011-12 prices.

Agriculture productivity is dependent on multiple factors like weather, soil, pest infestation, quality of seeds, and water availability for crops, to name a few.

Abhishek Raju, Director, SatSure, says “The correlation between these factors can be studied using historic datasets, and matched with market factors like demand, supply, and pricing to better assess what crops to grow where, how much yield and acreage can be expected of crops, leading to better planning & management of logistics and inventory to and predictive market information of prices.”

Drought Monitoring

Almost 16 per cent of India’s total area is drought prone. On an average 191 of 543 districts are affected by draught. More than 68 per cent of the land in the country is vulnerable to draught. About 50 million people are annually affected by draught. It’s difficult to know in advance which areas are particularly vulnerable to draught.

However, making better use of environmental data such as rainfall records could provide early warnings of drought, letting agricultural stakeholders taking next steps accordingly.

With availability of Big Data, drought monitoring can be an easier task which will help in evolving suitable policy formulations.

Although the agriculture sector in India has lagged behind sectors like banking and retail in taking up Big Data approaches, it could soon catch up. First movers in the big data landscape in agriculture are already achieving positive results, which is prompting other stakeholders to follow suit.

Monitor, Predict and Manage risk

Agriculture is an inherently risky business. With changing weather conditions and occurrence of natural disasters and erratic rainfall, it is becoming more unpredictable relative to the crops and practices that have worked well for generations.

The ability to harness big data technologies and techniques to predict outcomes enables the stakeholders to participate more effectively in risk management and to gain insight into the impact of the changing conditions.

There are several agricultural intelligence firms which provide information and insights to support agriculture across the value chain. Most of them are equipped with big data platforms that have the potential of processing billions of information points relating to the agricultural environment such as forecast weather, historical weather, soils, pest and disease risk, agronomics and planting characteristics.

It can be said without a shadow of doubt that the Big Data has the potential of boosting innovations in organizations and leading to the improvement of agricultural models.

Areas in agriculture that would most benefit from the application of big data technologies are,

Irrigation

Irrigation is a crucial alternative to predominantly monsoon dependent Indian agriculture.

About 46% of 142 million hectares of net sown area in the country is irrigated. The balance 54% is dependent on monsoons. Rising demand for higher agricultural productivity and over exploitation of natural water resources means that there is a need increase irrigated area by 15% – 22% in the next decade.

Today irrigation solutions are employing sensor-based internet of things (IoT) technology which efficiently regulates water management activities for agriculture including optimal utilization of electricity, water, and fertilizers. The technology is also used to monitor crop health conditions.

Equipped with Big Data Analytics the cloud based intelligent irrigation scheduling increases crop yield and decreases fertilizer consumption. You can also use the large repository of data on crop models linked with on-field irrigation water requirements.

Investing in state-of-the-art agriculture tools may not suffice to circumvent the problem of food scarcity. This is where big data comes to the rescue. Apart from tracking and optimizing harvests it also increases yield production. Data-mining technologies are all set to prove to be transformative, allowing agriculturists to generate better agricultural produce.

With specific crop history data on farmland in the country, farmers can now predict their potential harvests in a more effective manner. By aggregating local pricing in real time, they can get the best prices for their produce without a mediator.

Challenges of Agriculture Big Data

The increasing use of Big Data in the farming sector offers exciting possibilities for the agriculture sector. However, it also raises significant concerns with respect to the ownership of data and its uses and protection. Concerns on the ownership of data and privacy protection are the most pressing problems among the others. “Farms and farmers produce data aplenty, which need interpretation using Information technology for strengthening Agriculture Value Chain. However, the farmers who generate data, need to agree upon data use and sharing with other shareholders,” says Prof. Moni.

Conclusion

The rising population and the ever growing demand for food have led to the finding of innovative ways to meet these ever rising demands. Big Data opens vast untapped potential for farmers and stakeholders to improve efficiency of food production. Though nascent in the use of Big Data, the Indian agriculture sector is all set to embrace the technology on a large scale in the near future.