Precision Agriculture Systems Patents: Who Leads, Where the Gaps Are 2026
- Filings are still accelerating, not maturing. annual filings moved from 15 in 2017 to 95 in 2026 (partial year), with 2025 the peak so far at 125 — the growth curve has not flattened.
- India dominates the filing map. 289 of the tracked applications were filed at the Indian receiving office, versus 48 in the US and 20 in China — a very different geography from most agtech landscapes.
- Business-process claims outnumber the sensing hardware behind them. 321 records sit in G06Q (business/admin data processing) against 82 in G01N (material analysis) — most of the claim space is on decision logic, not the sensors feeding it.
What this landscape covers
This review tracks 406 patent families filed between 2017 and 2026 under a search built on precision agriculture, variable rate application and farm management system terminology, cross-referenced against remote sensing, yield mapping, prescription maps, soil sensing and decision support in the claims and description, and bounded by IPC classes covering soil working, planting equipment and commerce-oriented data processing. That combination captures the layer where field data becomes an actionable instruction — a prescription map, a variable-rate command, a harvest-timing recommendation — rather than the sensor or actuator hardware alone.
Publication lags filing by roughly eighteen months, so the 2025-2026 figures in this dataset understate the true filing volume for those years; treat the most recent bar in any trend chart as a floor, not a ceiling.
Let an AI agent run this analysis on your own technology
Pick a task. Every answer cites the patents behind it.
Filing trends and technology composition
Two views of the same 406-family dataset: how filing volume has moved year over year, and which IPC subclasses carry the claim weight.
Growth has not levelled off
Filings ran at 15 a year in 2017, sat at 11 at the 2022 midpoint, and reached 95 by 2026 with the year still open — 2025's total of 125 is the current peak. That shape (a slow first half, a steep back half) points to a field where the underlying decision-support and data-processing approaches only recently became patentable at scale, not one nearing saturation.
Data logic outweighs the sensing layer
G06Q (business/commerce data processing) appears in 321 records and G06N (AI-based computing) in 227 — both ahead of A01B (soil working, 209) and well ahead of G01N (material analysis and testing, 82). The claim density sits on how field data gets turned into a recommendation or transaction, not on the physical soil-working or sensing equipment that generates the raw signal.
Shares are the percentage of the 406 records in scope. A patent can carry several IPC classes, so the shares add up to more than 100%.
Go deeper on Precision Agriculture Systems with Eureka
This page is one run against one query. Ask Eureka your own question about precision agriculture systems and every answer comes back with the patent numbers behind it.
Try EurekaThe records other filings build on
NZ628791A — Variable rate application system for dispersal of material from an aircraft
Filed by Ravensdown Limited, this filing claims a method for aerial topdressing that acquires field data, converts a land-quality measure into a prescription map, and drives a variable-rate dispersal system mounted on the aircraft to vary material output by location.The claim chain runs from data acquisition through prescription-map generation to variable-rate dispersal — the same three-stage structure recurs across much of this dataset.
View full record| # | Publication no. | Patent title | Citations |
|---|---|---|---|
| 1 | US20050149235A1 | [method and system for spatially variable rate application of agricultural chemicals based on remotely sensed… | 130 |
| 2 | US20160215994A1 | Assessment of moisture content of stored crop, and modeling usage of in-bin drying to control moisture level … | 109 |
| 3 | US5878371A | Method and apparatus for synthesizing site-specific farming data | 106 |
| 4 | WO2016118686A1 | Modeling of crop growth for desired moisture content of targeted livestock feedstuff for determination of har… | 97 |
| 5 | US7103451B2 | Method and system for spatially variable rate application of agricultural chemicals based on remotely sensed … | 52 |
| 6 | EP3046066A1 | Precision agriculture system | 44 |
| 7 | US7184859B2 | Method and system for spatially variable rate application of agricultural chemicals based on remotely sensed … | 43 |
| 8 | US10838936B2 | Computer-implemented methods, computer readable medium and systems for generating an orchard data model for a… | 42 |
| 9 | US6813544B2 | Method and apparatus for spatially variable rate application of agricultural chemicals based on remotely sens… | 42 |
| 10 | US9792557B2 | Precision agriculture system | 39 |
Citation counts are drawn from within this searched corpus and favour older, foundational filings — read them as a map of influence, not of current filing activity.
Each row carries its publication number; clicking a row searches Eureka by that number.
Put your own technology through the same analysis
Eureka on the web
When you want the answer in the next five minutes.
The agent works the prompt against patents and technical literature, citing every source.
Run your analysis now →MCP server & REST API
When it has to run inside your own pipeline.
Patent search, landscape analysis and assignee resolution as MCP tools. Drop them into any agent framework, or call REST directly.
Browse MCP servers →What the numbers mean for filing strategy
Four read-throughs from the trend, geography and citation data that matter more than the raw counts.
This is not a US-led field
The US receiving office accounts for 48 records and China 20 — India's 289 makes it the dominant filing venue in this dataset, well ahead of the WIPO/PCT route (10). Any freedom-to-operate check that stops at the USPTO and CNIPA will miss most of the documented activity here.
The data-logic layer is the crowded one
Business-process and AI-computing classes (G06Q, G06N) outnumber material-analysis claims (G01N) by roughly four to one. Sensing hardware and soil-analysis methods carry comparatively less claim density than the decision-support and recommendation logic built on top of them.
The most-cited art predates the recent filing surge
The highest-cited records in this corpus date from the 2005-2016 window, before the 2022-2026 acceleration. That is expected in citation data — older filings accumulate citations simply by existing longer — but it means the foundational claim language was set well before the current filing wave.
Co-filing is rare and university-anchored
Only three co-assignee pairs appear across 406 families, and all three involve the same research-university partner working with a second university or an agtech firm. Co-filing has not become a common route into this space; most records carry a single assignee.
Eureka can read the same corpus for gaps instead of for coverage: under-claimed branches adjacent to precision agriculture systems, with the prior art for and against each one.
Who is filing, and how fast
Momentum is concentrated in a small set of academic and research entities, with the largest single mover more than doubling its filings year over year.
SR University is the standout momentum story
Eight filings in the latest tracked year against a 100% year-on-year increase makes SR University the clearest accelerating filer in this dataset, at a scale still small enough that a new entrant could contest the space.
A flat but persistent academic base
Vellore Institute of Technology and CVR College of Engineering both show flat year-on-year filing counts (3 and 2 respectively) rather than growth or withdrawal — a pattern of steady, incremental filing rather than a sudden push.
Several named filers show no recent activity
Agri Technovation (Pty) Ltd, Manna Irrigation Ltd and the Cohen Harris Lee filer entity all show zero filings in the latest tracked year, despite appearing in the broader assignee set — worth checking directly before assuming continued activity.
| Assignee | Recent year | YoY |
|---|---|---|
| SR UNIVERSITY | 8 | +100% |
| VELLORE INSITUTE OF TECH | 3 | 0% |
| CVR COLLEGE OF ENGINEERING | 2 | 0% |
| AGRI TECHNOVATION (PTY) LTD | 0 | — |
| MANNA IRRIGATION LTD | 0 | — |
| COHEN HARRIS LEE | 0 | — |
| Accenture Global Services Limited | 0 | — |
| Lovely Professional University | 0 | -100% |
Where to take this analysis
The dataset points to two practical next steps depending on whether you are scoping freedom-to-operate or looking for an entry point.
Check India-originated prior art directly
With 289 of 406 records filed at the Indian receiving office, a search strategy anchored on US or European filings alone will systematically undercount the closest prior art in this field.
Run a targeted prior-art searchProbe the under-claimed sub-areas before drafting
The gaps in soil-sensing calibration, multi-source yield-map reconciliation and non-liquid variable-rate dispersal are narrow enough to test with a focused claim-mapping exercise before committing to a full application.
Map claim gaps with Patsnap EurekaCommon questions on precision agriculture patents
The filing base is spread across a long tail of academic and research entities rather than concentrated in a handful of large agribusiness firms. Recent-year momentum data shows entities such as SR University growing quickly from a small base, while several previously active filers such as Agri Technovation and Manna Irrigation show no filings in the latest tracked year. This pattern suggests the field is still open to new entrants rather than locked up by a small set of incumbents.
In this dataset, 289 of 406 tracked records were filed at the Indian receiving office, compared with 48 in the United States and 20 in China. That concentration reflects a large base of Indian academic institutions and research entities filing on farm management, variable-rate application and decision-support systems, an activity pattern distinct from the more US/China-centric filing seen in many other agtech subfields. Anyone assessing freedom-to-operate for this space should search Indian filings directly rather than relying on US or PCT coverage alone.
IPC composition shows the claim weight sits on data processing and decision logic: 321 records touch G06Q (business/commerce data processing) and 227 touch G06N (AI-based computing), both ahead of A01B soil-working equipment (209) and G01N material analysis (82). In practical terms, more patent claim space covers how sensor and yield data get turned into a prescription map or recommendation than covers the sensors, soil probes or actuators generating that data.
It is still accelerating. Annual filings rose from 15 in 2017 to 95 in 2026 with that year still open for publication, and the peak so far was 125 filings in 2025. Because publication typically lags filing by around 18 months, even the 2025-2026 figures likely understate the true filing rate for those years, meaning the field's real growth curve is steeper than the visible data shows.
NZ628791A, assigned to Ravensdown Limited, claims a variable rate application system for aerial dispersal of material based on a prescription map derived from land-quality data — specifically the combination of acquiring field data, converting it into a location-based prescription map, and driving an aircraft-mounted variable-rate dispersal mechanism from that map. Anyone building an aerial variable-rate system for topdressing or similar aerial input application should check this claim chain closely, though ground-based variable-rate systems and non-aerial dispersal methods sit outside its literal scope.
Research Precision Agriculture Systems in depth with Eureka
Go past this page: query the whole precision agriculture systems corpus yourself, in your own scope.
Every answer comes back with patent numbers you can open.
Disclaimer. This page is generated from Patsnap Eureka data drawn from a limited snapshot of global patent and scientific-literature records, and is provided for general information and reference only.
Patent data carries inherent limitations: recent filings (typically the most recent 18–24 months) are under-counted due to standard publication lag; counts may be reported at either a patent-family or a patent-record basis and are not always directly comparable; classification, applicant-name, and citation data may contain errors, duplicates, or omissions; and the underlying search query defines and constrains the scope shown. As a result, the analysis may be incomplete or inaccurate and may not reflect the full technology landscape.
Nothing on this page constitutes an exhaustive prior-art, novelty, freedom-to-operate, or validity search, nor does it constitute legal, financial, investment, or professional advice, and it should not be relied upon as such. Any patent, commercial, or strategic decision should be verified independently and reviewed with qualified patent, legal, and domain professionals. Patsnap makes no warranties, express or implied, as to the accuracy, completeness, or fitness for any particular purpose of the information presented.
Machine translation. Assignee and organisation names originally recorded in Chinese, Japanese or Korean have been rendered into English by an AI translation step so that the tables stay readable. These renderings are best-effort and may not match a company’s registered English name; the original name is what the underlying patent record carries, and it is what any Eureka query launched from this page uses.