Big data in the agricultural sector
Many farmers have expressed concern about what has happened to their once secluded nosiness as big data has infiltrated the agricultural sector. They are especially concerned about what the large seed companies could do with the information gathered from farmers. Farmers are also concerned about an increase in seed prices offered by the same companies that create farming technology. The case study examines three big agricultural data analysis technologies used by farmers and companies including Monsanto and Dupont. It refers to the amount of information that is valuable or useful to farmers. The case study analyses how Monsanto and Dupont are using technology and data provided by the farmers to enhance farming.
Discussion Questions
Response to Question 1
a) Global Positioning System(GPS): It is a satellite-based navigation system in which the computer receives from earth orbiting satellites to track every piece of the location of the equipment. Besides, GPS helps steer the equipment in such a way that the farmers can see the progress in their mobile devices such as iPads (Laudon & Laudon, 2016). Finally, the system gives instructions for the hoses to deliver the exact amount of fertilizer right into the grooves cut by the tiller.
b) Prescriptive farming: It involves analysis of data by the agricultural data companies which is collected from farmers around a particular area relating to the soil condition, the trends of crop yield in the past years, field boundaries, seed performance as well as the type of soils (Laudon & Laudon, 2016). The company later sends back the information with recommendations to the farmer in digital form such that the farmer uploads the data in his computerized planting equipment.
c) FieldScript: It is a system that takes into account variables such as the amount of sunlight and shade, as well as variations in soil nitrogen and phosphorous content of a small area (Laudon & Laudon, 2016).
Response to Question 2
Both prescriptive planting and FieldScripts provide operational intelligence to the farmers. FieldScripts allow farmers to identify the areas in his farm that require less or more fertilizer than the standard quantity. That way, they can save some costs which would have been incurred if they spread fertilizer across the field and at the same time increase crop yield and profitability (Laudon & Laudon, 2016). On the other hand, farmers can use the prescriptive farming report to determine the kind of fertilizer and seed that should be used as well as the quantity. Besides, the agricultural data analysis companies advise the farmers on the future weather conditions.
Response to Question 3
Prescriptive planting allows farmers to avoid guess work as they plant and harvest their crops. It provides farmers with the exact quantity of seed and fertilizer to use while planting thus improving the crop yield which in turn increases the profit a farmer generates (Laudon & Laudon, 2016). Prescriptive planting support three decisions which include the amount and the type of seed for a given type of soil, the quantity of fertilizer to be added in every part of the field as well as factors such as weather that assist farmers in managing their crops as they grow (Laudon & Laudon, 2016).
Response to Question 4
The technology is not likely to benefit small-scale farmers because of the cost the service and acquiring the planting equipment is very high. Similarly, the cost of replacing the current planting equipment with the modern ones is very high and will hard press the small-scale farmers while for the large-scale farmers it will be much easier to replace or acquire the equipment that supports agricultural technologies such as GPS, FieldScript, and prescriptive planting (Laudon & Laudon, 2016). Altogether, the size of the farm does not matter, what matters is the fact that the impact of the new data-driven software programs will be low in favorable because, despite the decision made, the yields will be high. However, the impact of technology would be felt if the farming conditions were unfavorable.
Conclusion
From the above analysis, it is evident that the agricultural companies such as Monsanto and Dupont are using data corrected from the farmers to develop technology software that allows farmers to work more efficiently and effectively. With the forms of technologies analyzed in the case study, farmers can make informed decisions, reduce farming costs, as well as increase profitability.
References
Laudon, K. C., & Laudon, J. P. (2016). Management Information Systems: Managing the Digital Firm (14th ed.). New Jersy: Pearson.
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