Global Agriculture Analytics Market - 2023-2030

Global Agriculture Analytics Market - 2023-2030

Global Agriculture Analytics Market reached US$ 1.2 billion in 2022 and is expected to reach US$ 2.8 billion by 2030 growing with a CAGR of 11.5% during the forecast period 2023-2030.

Agriculture analytics refers to the use of advanced technologies, data analysis, and predictive modeling techniques to gain insights and make informed decisions in the field of agriculture. Precision agriculture entails the use of technology and information to optimize farming practices on a site-specific basis. It utilizes tools along with sensors, drones, and GPS systems to accumulate records about soil conditions, crop growth, and environmental factors.

Data-driven farming refers to the practice of using agricultural records, collected through various resources inclusive of sensors, satellite imagery, and weather stations, to inform decision-making in farming operations.

Artificial intelligence (AI) and machine studying (ML) techniques are playing a important role in agriculture analytics. AI and ML algorithms are used to analyze large volumes of agricultural data, identify patterns, and generate predictive models. These models assist in predicting crop yields, disorder outbreaks, weather patterns, and optimizing resource allocation for improved decision-making and operational efficiency.

Market Dynamics

Increasing Demand for Food Production Globally is Driving the Agriculture Analytics Market

The global population continues to increase at a substantial rate. According to the Food and Agriculture Organization (FAO), cereal yield growth would slowdown to 0.7 percent per annum (0.8 percent in developing countries), and average cereal yield would by 2050 reach around 4.3 ton/ha, up from 3.2 ton/ha. According to the same source, the world population is projected to reach 9.7 billion by 2050. This population boom puts pressure at the agriculture zone to supply extra food to fulfill the rising demand.

Rapid urbanization and converting life have brought about a shift from conventional subsistence farming to commercial agriculture. This shift necessitates improved agricultural practices and the adoption of advanced technology, together with agriculture analytics, to boom productivity and performance in food production.

Integration of Internet of Things (IoT) and Sensor Technologies is Expected to Foster the Agriculture Analytics Market

The mixing of IoT and sensor technology in agriculture enables unique tracking and control of numerous parameters such as soil moisture, temperature, humidity, and crop health. According to a report by the World Economic Forum, the adoption of IoT in agriculture can lead to a 10-15% reduction in water usage and a 20-30% reduction in chemical inputs. Those technologies provide real-time statistics that may be analyzed through agriculture analytics, allowing farmers to optimize resource allocation, reduce waste, and decorate common farming performance.

IoT and sensor technology enable continuous data collection from agricultural fields, livestock, and machinery. This real-time data can be analyzed using agriculture analytics tools to provide valuable insights for decision-making. For instance, sensors can provide data on soil moisture levels, allowing farmers to precisely schedule irrigation. Real-time data analysis enables proactive responses to changing conditions, leading to improved farm management practices and increased productivity.

Lack of Awareness and Technical Expertise is Holding Back the Agriculture Analytics Market

Agriculture analytics requires a certain level of technical expertise in data analysis, interpretation, and the use of analytics tools. However, many farmers and agricultural professionals may not possess the necessary skills or knowledge in these areas. They may lack familiarity with statistical analysis, modeling techniques, and data visualization. This knowledge gap can impede the implementation and effective utilization of agriculture analytics solutions.

Farmers often face challenges in accessing training programs or support systems that provide guidance on agriculture analytics. Limited availability of training resources, workshops, or expert assistance can hinder the development of technical expertise in data analysis and the practical application of analytics tools. The lack of accessible training and support mechanisms exacerbates the gap in technical expertise.

COVID-19 Impact Analysis

The COVID-19 Analysis includes Pre-COVID Scenario, COVID Scenario, and Post-COVID Scenario along with Pricing Dynamics (Including pricing change during and post-pandemic comparing it with pre-COVID scenarios), Demand-Supply Spectrum (Shift in demand and supply owing to trading restrictions, lockdown, and subsequent issues), Government Initiatives (Initiatives to revive market, sector or Industry by Government Bodies) and Manufacturers Strategic Initiatives (What manufacturers did to mitigate the COVID issues will be covered here).

Segment Analysis

The global agriculture analytics market is segmented based on source, packaging, distribution channel, and region.

By Deployment, the Cloud Segment is Estimated to have Significant Growth During the Forecast Period

Cloud-based solutions offer scalability and flexibility, allowing users to scale their storage and computing resources based on their needs. This scalability is particularly valuable in the agriculture industry, where data volumes can vary significantly throughout the agricultural cycle. According to a journal published by Frontiers, Automation and the use of artificial intelligence (AI), internet of things (IoT), drones, robots, and Big Data serve as a basis for a global “Digital Twin,” which will contribute to the development of site-specific conservation and management practices that will increase incomes and global sustainability of agricultural systems.

Cloud-based agriculture analytics platforms can accommodate the storage and processing requirements of large and diverse agricultural datasets. The cloud enables easy access to data from anywhere, anytime, as long as there is an internet connection. This accessibility promotes collaboration and data sharing among stakeholders in the agriculture ecosystem, including farmers, researchers, consultants, and agribusinesses. Cloud-based platforms facilitate real-time data access, analytics, and collaborative decision-making, contributing to the overall adoption and dominance of the cloud segment.

Geographical Analysis

Asia Pacific is the Fastest Growing Market in the Agriculture Analytics Market

Asia Pacific is domestic to a large agricultural area and a vast population engaged in farming. The increasing demand for meals, coupled with the need to beautify agricultural productiveness, has led to the adoption of superior technology and analytics solutions. According to Asia Development Bank, with 76% of Asia’s poor living in rural areas, raising agricultural productivity and income is key to fighting poverty. By leveraging agriculture analytics, farmers in the region can optimize resource utilization, implement precision farming practices, and improve overall productivity.

Precision agriculture techniques, which heavily rely upon data-driven insights and analytics, have received traction inside the Asia Pacific region. Farmers are increasingly more adopting technology inclusive of sensors, drones, and satellite imagery to monitor crops, analyze soil conditions, and optimize resource management. Agriculture analytics performs a important role in analyzing the collected data and supplying actionable insights for precision agriculture, contributing to the market growth inside the region.

Competitive Landscape

The major global players in the market include Trimble Inc., Bayer AG, IBM Corporation, Deere & Company, Ageagle Aerial Systems Inc, Vistex, Inc., Agrivi, SAS Institute Inc., Conservis Corporation, and Iteris Inc.

Why Purchase the Report?
• To visualize the global agriculture analytics market segmentation based on component, application, deployment, farm size, and region, as well as understand key commercial assets and players.
• Identify commercial opportunities in the market by analyzing trends and co-development.
• Excel data sheet with numerous data points of agriculture analytics market-level with all segments.
• The PDF report consists of cogently put-together market analysis after exhaustive qualitative interviews and in-depth market study.
• Product mapping is available as Excel consists of key products of all the major market players.

The global agriculture analytics market report would provide approximately 69 tables, 65 figures and 190 Pages.

Target Audience 2023
• Manufacturers/ Buyers
• Industry Investors/Investment Bankers
• Research Professionals
• Emerging Companies