Key Emerging Trends in Precision Farming

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Key Opportunities and Challenges in the Precision Farming Market

(EMAILWIRE.COM, October 25, 2019 ) The precision farming market was valued at USD 5.1 billion in 2018 and is projected to reach USD 9.5 billion by 2023, at a CAGR of 13% between 2018 and 2023.

What opportunities will the integration of smartphones with Internet of Things (IoT) devices and software applications present to the market for precision farming?

Smartphone is among the most widely used technological inventions in history, and with the availability of multiple user-friendly farming applications (apps), smartphones are becoming powerful, easy-to-carry tools for farmers. Smartphone apps provide a wide range of farming-related information and are mostly inexpensive. These apps effectively disseminate the latest technological know-how of farming, helping farmers make informed and smart decisions.

Farmers can consult smartphone apps for precise information on climate, weather, etc., which help them in planning planting and harvesting cycles. Smartphones could also be used for sample collection, aerial imaging, and record-keeping (a task recommended by experts). Some farming apps can load field information and then grid it acre-wise.

Smartphones also help small-scale farmers connect with customers and agents who were previously unreachable. According to Farm Journal Media’s survey conducted in February 2015, 87% of farmers were already using smartphones and tablet computers. Smartphone usage by farmers has been steadily growing since 2009 and is expected to grow further in the coming years.

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How does the management of data prove to be a challenge for the precision farming market?

Management of data is a major challenge for the growth of the precision farming market. Precision farming regularly produces high volumes of important data pertaining to mapping, variable rate seeding, soil testing, yield monitoring, and historical crop rotation. This data must be stored and managed properly as successful precision farming relies entirely on it for assessing farm conditions. Data management is key to making smart farm-management decisions and improving farm operations.

Data is collected in raw format, processed by context, relevance, and priority, and it is then presented in a manner that can be used to make decisions. A major challenge faced by farmers is managing this data—which requires expertise and knowledge. Also, many users of precision farming do not know how to analyze their precision data. The adoption rate of precision farming could be boosted by providing easy data-management solutions to farmers. However, to utilize it better, efforts should also be made to standardize the data format of precision agriculture processes.

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