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The article “Can Big Data Feed the World?” mentioned an array of technologies that can boost agricultural processes and provide the world with more food. Such technologies included data-driven planting, hyper-local weather forecasts, following food, and plant breeding through using Big Data. Data-driven planting is associated with providing farmers with detailed information on crops they plant, soil characteristics, data on territorial boundaries, and so on. Hyper-local weather forecasts use technologies to assess real-time atmospheric conditions for facilitating enhanced farming and avoid negative implications of climate fluctuations. Big Data plant breeding is a technology that modifies breeds of plants for achieving their desired traits; for example, hybrid farmers have used Big Data for improving strawberry plants through various breeding programs. The following food is another strategy that allows farmers to improve the quality of their crops; it implies tracking for illness prevention, profit increases, and waste reduction.
Big Data is expected to feed the world in the future by analyzing large volumes of data associated with predicting the weather, finding appropriate regions for farming and agriculture, and eliminating possible adverse outcomes. To prevent widespread hunger, international organizations involve large corporations such as IBM in the development of technological solutions for data collection and management. Current solutions include cloud-based information systems that track weather from millions of locations each day. This means that farmers who use such solutions can make informed decisions about their next steps of effective crop management and upkeep. Apart from improving operations of farmers, Big Data is expected to reduce waste and thus increase the amount of food available for consumption
Predictive weather farming has become an essential component for forecasting possible dangerous situations for crops and developing emergency strategies to address such dangers. “Can Big Data Feed the World?” mentioned that IBM, which is a large technological corporation, has entered the arena of agriculture for contributing to the generation of hyperlocal weather forecasts. Such technological solutions allow farmers to access data on the weather in their region every ten minutes for making accurate forecasts. Through predicting possible changes in weather, farmers will have opportunities to make reasonable decisions. These decisions can vary depending on the nature of crops and the processes involved in their control and management. Three different types of decisions that could be supported by predictive weather farming include the following:
- Quantities of water needed for the adequate maintenance of crops: knowing about upcoming rain or high humidity levels is likely to reduce the unnecessary watering of crops, which could subsequently reduce water waste;
- Making changes in crop varieties and sowing dates: a non-intensified strategy that is supported by weather forecasting to managing a wide variety of crops;
- Introducing crop variability in different geographical regions: predictive weather forecasting can give farmers knowledge about the possible weather conditions in different regions and thus allow making decisions on which geographical region would suit which crops.
Big Data is helpful to individual farmers and the agriculture sector overall because it provides opportunities to manage big amounts of data, which leads to enhanced capabilities of decision-making (Wolfert et al. 69). With the management of large data amounts come great shifts in roles and relationships associated with power among “traditional and non-traditional players” (Wolfert et al. 69). The introduction of Big Data is expected to contribute to the effective farm management that includes such processes as sensing and monitoring, analysis, and decision-making, as well as interventions. When it comes to specific technology solutions that use Big Data for the enhancement of farming, Climate Pro developed by Climate Corporation can provide farmers with opportunities to increase their profit by $100 per acre when investing $15 per acre (Noyes). Developed with the help of statistical algorithms and models, Big Data solutions for farmers are gaining momentum in their use among farmers that care about their profitability and want to improve agricultural processes to enhance the industry overall. The enhanced profitability of individual farmers is expected to lead to the improvement of the agricultural industry as a unity because of the possibilities to base relevant decisions on actual and real-time data that directly influences farmers’ outcomes.
The Big Data gap is associated with the unequal territorial distribution of technological resources for enhancing farming. For instance, there are many more Big Data solutions for farmers in developed regions such as the U.S. and Europe where technologies have reached high levels. However, these regions are not enough to produce food for the entire world. Filling such a gap will be achievable through the provision of Big Data technologies for all countries around the world free of charge. Governmental cooperation should focus its efforts on making sure that such regions as Asia, Africa, and South America are also taken into consideration when developing Big Data solutions for farming. As to the recent developments in this field, Gilpin mentioned that the Open Data Alliance was planning to provide farmers with free of charge Big Data services and encourage them to share their findings across other platforms.
Works Cited
“Can Big Data Feed the World?” Knowledge Wharton. 2014. Web.
Gilpin, Lyndsey. “How Big Data Is Going to Help Feed Nine Billion People by 2050.” Techrepublic, 2012. Web.
Noyes, Katherine. “Cropping Up on Every Farm: Big Data Technology.” Fortune, 2014. Web.
Wolfert, Sjaak, et al. “Big Data in Smart Farming – A Review.” Agricultural Systems, vol. 153, 2017, pp. 69-80.
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