Grain Loss Sensing Patents: Who Leads, Where the Gaps Are 2026
- 76.9% of all 117 records sit with the top five assignees alone, leaving a long tail of single or few-filing entrants below tenth place.
- Filing peaked in 2018 at 14 and the tracked 2021-to-2024 span shows a -100% swing, though recent years are still filling in as publications lag filing.
- A01D and A01C dominate the IPC mix, but a quarter of records also carry G06Q or H04N classes — sensing is increasingly bundled with data and imaging claims.
Filing growth compares 2021 (1 records) with 2024 (0) — a three-year span. 2024 is the most recent year we treat as complete: publication lags filing by roughly 18 months, so 2025 onwards are still filling in and any growth rate that ends there would understate the field. Top-5 share is the combined record count of the five largest assignees divided by all 117 records in scope (CR5), not by the ranked leaders only.
What this landscape covers
Grain loss sensing sits at the intersection of mechanical harvester design and the data systems built around it. The search scope pulls together records describing impact plate sensors, signal calibration routines, loss rate estimation and the automatic adjustment loops that feed sensor output back into combine settings, alongside the operator-facing displays that surface loss data in the cab.
The 117 records in scope span 2015 through the current data cut-off, with the ranked assignee list covering 19 companies. Because publication trails filing by roughly 18 months, the most recent one or two years in any trend chart will read lower than actual filing activity — that is a lag in the record, not a real drop in interest.
Filing trends and technology composition
Two views of the same 117 records: how filing activity has moved year over year, and which IPC subclasses the underlying claims fall into.
Filing trend, 2017–2026
Filings ran at 13 in 2017 and peaked the following year at 14. The tracked span from 2021 (1 filing) to 2024 (0 filings) shows a -100% change; treat 2025 and 2026 as incomplete rather than as evidence the field has gone quiet.
IPC subclass composition
A01D (harvesting and mowing) covers 46.2% of the 117 records, roughly double the next largest mechanical class, A01C (planting and sowing) at 23.9%. Data-processing and communications classes — G06Q, H04N and H04W — each sit near or above a quarter of records, showing that grain loss claims are frequently bundled with data handling, imaging or wireless transmission rather than filed as pure mechanical sensor claims.
Shares are the percentage of the 117 records in scope. A patent can carry several IPC classes, so the shares add up to more than 100%.
Go deeper on Grain Loss Sensing in Harvesting with Eureka
This page is one run against one query. Ask Eureka your own question about grain loss sensing in harvesting and every answer comes back with the patent numbers behind it.
Try EurekaMost-cited records and a recent representative filing
System and method for controlling machine based on cost of harvest (US12575493B2, Deere & Company, 2026-03-17)
A control system for an agricultural machine ties a fuel sensor and a grain loss sensor together with user-set cost values, so the controller can weigh fuel burn against grain lost during a harvest operation rather than treating loss reduction as a standalone target.Abstract trimmed for length; full claim language is available in the source record.
| # | Publication no. | Patent title | Citations |
|---|---|---|---|
| 1 | US20140215984A1 | Method for Setting the Work Parameters of a Harvester | 140 |
| 2 | US20160066505A1 | Collecting data to generate an agricultural prescription | 133 |
| 3 | US20170235471A1 | Harvesting machine capable of automatic adjustment | 128 |
| 4 | US20180000011A1 | Grain quality sensor | 124 |
| 5 | US9629308B2 | Harvesting machine capable of automatic adjustment | 119 |
| 6 | US20120227647A1 | Air seeder monitoring and equalization system using acoustic sensors | 119 |
| 7 | US9631964B2 | Acoustic material flow sensor | 95 |
| 8 | US9904963B2 | Updating execution of tasks of an agricultural prescription | 95 |
| 9 | US9226449B2 | Method for setting the work parameters of a harvester | 92 |
| 10 | US20160071410A1 | Updating execution of tasks of an agricultural prescription | 91 |
Citation counts inside this corpus favour older filings that have had more time to accumulate citations; read them as a signal of influence on the field, not as a ranking of current importance.
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Three patterns stand out once the records are broken down by assignee, year and IPC class.
Filing is concentrated among a handful of assignees
The top five assignees account for 76.9% of all 117 records in scope, and the top ten reach 98.3%. Below tenth place the ranking thins quickly to single-digit and single-filing entrants, which means most of the useful prior art for freedom-to-operate work sits with a small number of organisations.
Recent filing counts have dropped off, with a caveat
The tracked span from 2021 (1 filing) to 2024 (0 filings) shows a -100% change. Filing peaked earlier, in 2018 at 14, and the intervening years show a field that filed heavily around initial impact-plate and calibration concepts, then thinned. Treat 2025–2026 figures as incomplete given publication lag.
Sensor claims increasingly travel with data and imaging claims
Beyond the core A01D and A01C mechanical classes, close to a quarter of records also carry G06Q (business/data processing) or H04N (pictorial communication) classifications. That pattern suggests loss-sensing claims are being filed alongside prescription-generation, display or camera-based verification features rather than as isolated hardware claims.
Eureka can read the same corpus for gaps instead of for coverage: under-claimed branches adjacent to grain loss sensing in harvesting, with the prior art for and against each one.
Assignee landscape and collaboration patterns
The ranked list covers 19 companies; concentration is heavy at the top with a thin tail below it.
One assignee holds a clear lead
The leading assignee in the ranking holds 35 of the 117 records in scope, well ahead of fifth place at 7 and tenth place at 4. That gap between first and fifth is the clearest sign of where the deepest prior art sits.
A small inventor cluster files together repeatedly
Three pairings — each sharing 8 records — recur across the co-assignee data, pointing to a tight internal engineering group whose combined output likely maps to a single corporate filing programme rather than three independent efforts.
Most of the ranking files rarely
Once past the top ten assignees — who together already cover 98.3% of the 117 records — the remaining entrants in the 19-company ranking contribute only a handful of records between them, typical of a field where a few players set the technical baseline and everyone else files defensively or opportunistically.
| Assignee | Recent year | YoY |
|---|---|---|
| Intelligent Agricultural Solutions LLC | 0 | — |
| Climate Corp | 0 | — |
| APPAREO SYSTEMS LLC | 0 | — |
| REICH ADAM A | 0 | — |
| GELINSKE JOSHUA N | 0 | — |
| CLIMATE LLC | 0 | -100% |
| BATCHELLER BARRY D | 0 | — |
| CNH Industrial America LLC | 0 | — |
Where to take this
The dataset points to a concentrated field with specific gaps rather than a wide-open one.
Check freedom-to-operate against the top assignees first
With 76.9% of records held by five assignees, a targeted clearance search against that group covers most of the risk before looking at the long tail.
Explore assignee claims in EurekaWatch the data-and-imaging overlap classes
G06Q and H04N each cover close to a quarter of records alongside the core mechanical classes — a sign that new filings are increasingly bundling sensing with software and display claims.
Trace IPC overlap in EurekaTreat 2025–2026 filing counts as provisional
Publication lag means the true filing picture for the last 18 months is still forming; revisit the trend once later publications land.
Track filing updates in EurekaCommon questions on grain loss sensing patents
The ranked assignee list for this dataset covers 19 companies, and the leading assignee alone holds 35 of the 117 records in scope. The top five assignees combined account for 76.9% of all records, so the bulk of the relevant prior art sits with a small number of organisations rather than being spread evenly. Below the top ten, which together reach 98.3% of records, filing activity thins to single-digit and often single-record entrants.
Filing activity peaked in 2018 at 14 records after starting at 13 in 2017. The tracked span from 2021 (1 filing) to 2024 (0 filings) shows a -100% change, marking a clear slowdown through that period. Figures for 2025 and 2026 should be read cautiously, since publication typically lags actual filing by around 18 months and those years are still filling in.
The core mechanical classes are A01D (harvesting and mowing), covering 46.2% of the 117 records, and A01C (planting and sowing) at 23.9%. Alongside these, G06Q (business and data processing), H04N (pictorial communication) and H04W (wireless networks) each appear in roughly a fifth to a quarter of records, showing that many filings combine physical sensing with data transmission, imaging or business-logic claims rather than staying purely mechanical.
US12575493B2, assigned to Deere & Company and dated 2026-03-17, describes a control system that combines a fuel sensor and a grain loss sensor with operator-set cost values, letting the controller balance fuel consumption against grain loss during a harvest operation. It is a recent representative filing in this dataset rather than the oldest or most-cited one. Anyone building a cost-optimisation feature that weighs loss against another operating cost should review its claim scope directly rather than relying on the abstract alone.
The IPC composition suggests claim space is thinner in areas that combine core sensing with adjacent functions: vibration-interference compensation, multi-sensor calibration across different header types, moisture-linked automatic threshold adjustment, and tighter integration between operator displays and prescription data. These are read from the relative class shares rather than from a gap analysis of individual claims, so they should be treated as starting points for a deeper search, not as confirmed open ground.
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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.