New Jersey, NJ -- (SBWIRE) -- 02/07/2019 -- Agriculture analytics refer as the analytics which can safeguards the risk against the climate uncertainty and thus it reduces crop losses by providing the reliable information of agricultural. The systematic deployment of agriculture analytics services enables to get real-time access to information such as rainfall and other weather conditions for the end-users. Also due to the rising adoption of machine learning technique, advanced data analytics and drone analytics there is significant contribution towards the market growth
Top Key Vendors Profiled in This Report include,
Deere & Company (United States), IBM (United States), SAP SE (Germany), Trimble (United States), Monsanto Company (United States), Oracle (United States), Accenture (Ireland), Iteris (United States), Taranis (Israel), Agribotix (United States), Agrivi (United Kingdom), DTN (United States), aWhere Inc. (United States), Conservis Corporation (United States), DeLaval (Sweden), Farmer's Business Network (United ,States), Farmers Edge (United States), GEOSYS (United States), Granular (United States), Gro Intelligence (United States)
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The livestock analytics application segment includes feeding management, heat stress management, milk harvesting, breed management, behaviour monitoring and management, and others (calf management, genetic management, and cattle sorting). The livestock agriculture includes varied task performed daily, which generate large volumes of critical data about the animal. Any, miss-management in the diet or tracking of the animals may result in major loss for farmers. Hence, farmers are investing in analytics solutions that help them in managing their livestock process for quality production.
Data security concerns among the end users is contributing to the higher adoption of on-premises agriculture analytics solution globally. The on-premises agricultural analytics solution is majorly deployed by large farms as they have better ability to invest. Moreover, large farms have a wide variety of business segments with serving to broader geographic region; hence, data security is of utmost importance.
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Agriculture analytics solutions have various application areas, including farm analytics, livestock analytics, aquaculture analytics, orchid, forestry, and horticulture. Farm analytics can broadly be categorized under 3 phases: planning, farm production, and post-harvest activities. The planning phase comprises various activities including field mapping, crop scouting, weather data analytics, and soil moisture analysis. The farm production phase includes activities such as irrigation and water management, fertilizer management, crop growth and health, farm labor management, and yield monitoring.
Table of Content
1. Market Overview
1.1. Introduction
1.2. Scope/Objective of the Study
1.2.1. Research Objective
2. Executive Summary
2.1. Introduction
3. Market Dynamics
3.1. Introduction
3.2. Market Drivers
3.2.1. Increase in the need for improving the farm productivity and farming operations associated with it
3.2.2. Increase in the demand for specialised digital agriculture service providers, that can offer services associated with cloud-based analytics
3.2.3. Shortage of labour availability
3.3. Market Challenges
3.3.1. High investment required for adopting agriculture analytics solutions
3.3.2. Lack of Standardisation in agriculture industry related to the data management and data aggregation
3.3.3. Lacking in the of Technicality of Know-How among the farmers
3.4. Market Trends
3.4.1. Emergence of data analytics in agriculture
3.4.2. Advances in agriculture infrastructure
3.4.3. Global adoption of the on-premises agriculture analytics
4. Market Factor Analysis
4.1. Porters Five Forces
4.2. Supply/Value Chain
4.3. PESTEL analysis
5. Global Agriculture Analytics, by Application, Deployment model, Component, Farm size and Region (value) (2012-2017)
5.1. Introduction
6. Agriculture Analytics: Manufacturers/Players Analysis
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