Precision Agriculture Market Research Share, Size, Analysis & Forecast | FMI

Precision agriculture is also known as satellite agriculture, precision ag or precision farming, as-needed farming, and site-specific crop management. The site-specific crop management is a farming management theory based on measuring, responding, and observing to plant and intra-field variability in the crop.

Precision agriculture is used for transforming agricultural extension in emerging countries using the latest available technologies and research methods. The goal of precision agriculture is to ensure sustainability, protection, and profitability of the environment.

Precision agriculture relies upon specific equipment, IT services, and software. Predictive analytics software uses the data to help with guidance about soil management, optimal planting times, a crop rotation, and harvesting times.

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Precision Agriculture Market: Drivers

Precision agriculture has a variety of technology opportunities that improves farming operation, from drones to climate monitoring systems.

Rapid use of IoT in agriculture sector is providing to the growth of the precision farming market. These technologies can be the Internet of Things, mobile phones, artificial intelligence, and the use of data by farmers.

The adoption of various technologies in precision agriculture are electromagnetic, photo electricity, remote sensing data, ultrasounds, and conductivity are used to structure, texture measures temperature, etc. Sensor technology use has been widely reported to provide information on water status/plant fertility and soil properties.

Precision agriculture technologies will generally require the use of software to carry out various tasks such as information layers mapping, display-controller interfacing, farm accounting of inputs per field, pre and post-processing data analysis and interpretation, farm accounting of inputs per area, and many others software.

The factors driving precision agriculture technology is the increasing use of smartphones, the rising application of technology, and the growing use of cloud-based technology to minimize the human efforts and losses. The rising demand to boost food production in government initiatives and available agricultural land to increase the usage of new technologies in agriculture are driving market growth.

Precision Agriculture Market: Competition Landscape

Some of the prominent players manufacturing precision agriculture are

  • Fuse Technologies,
  • IBM,
  • Grownetics Inc.,
  • Fairport Farm Software,
  • Agribotix,
  • Case IH Agriculture,
  • Farmers Edge Inc.,
  • Bayer CropScience AG,
  • ClearAg Operations,
  • Deere & Company,
  • MapShots Inc.,
  • SST Software,
  • Raven Industries,
  • Conservis Corporation, and
  • Granular AG.

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Precision Agriculture Market: Regional overview

Based on the region, the trends of the precision agriculture market fluctuate across various geographical regions. The precision agriculture market includes a leading share in many countries of Asia-Pacific, North America, and the rest of the world. North America has been noticed to receive the major share of the precision agriculture market due to the increasing adoption of the high-level agricultural equipment and solutions like steering, farm management software, guidance systems, and sensors.

The USA leads the market in this region due to the presence of many critical manufactures of high technologies awareness among people precision agriculture high technologies in the region. The European market quietly proceeds with significant growth opportunities for precision agriculture technologies in the Eastern Europe region.

Presence of essential agricultural producing countries, such as Indonesia, India, China, Argentina, and Brazil in this region is expected to boost the market for advanced agricultural techniques.

The Precision Agriculture market report is a compilation of first-hand information, qualitative and quantitative assessment by industry analysts, and inputs from industry experts and industry participants across the value chain.

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