Precision Agriculture Modeling Patent Landscape 2026
Precision agriculture modeling is an early-stage but rapidly expanding field, with DTN LLC holding a commanding lead and India accounting for the majority of filings. Activity has accelerated sharply in recent years, though the latest periods remain under-counted due to publication lag.
DTN LLC leads a fragmented field dominated by academic and independent filers
DTN LLC is the clear frontrunner, ranked first in the applicant list. The field is otherwise highly fragmented, with the second-ranked filer — the Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences — holding far fewer patent records, followed by Pioneer Hi-Bred International Inc in third place.
The top five filers together account for roughly a quarter of the combined output of the hundred largest filers, indicating that no tight oligopoly controls this space. A large share of the ranked applicants are Indian academic institutions and individual inventors, reflecting the geographic skew of the corpus toward India.
| # | Applicant | Patent records | Share |
|---|---|---|---|
| 1 | DTN LLC | 15 | |
| 2 | Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences | 5 | |
| 3 | Pioneer Hi-Bred International Inc | 4 | |
| 4 | CVR College of Engineering | 3 | |
| 5 | Lovely Professional University | 2 | |
| 6 | Immanuel Prabaharan S | 2 | |
| 7 | Vaibhav Laxman Dhasal | 2 | |
| 8 | Chattopadhyay Manju K | 2 | |
| 9 | Wreath Inc | 2 | |
| 10 | Sri Eshwar College of Engineering | 2 |
| # | Applicant | Patent records | Share |
|---|---|---|---|
| 11 | Dandamudi Srilatha | 1 | |
| 12 | Nancharaiah Battula | 1 | |
| 13 | Shanmugapriya N | 1 | |
| 14 | Rupa Suhas Kawchale | 1 | |
| 15 | Shyam Nagayya Ibatte | 1 | |
| 16 | SAVEETHA INST OF MEDICAL & TECH SCI | 1 | |
| 17 | Rajeev Agrawal | 1 | |
| 18 | A Saranya | 1 | |
| 19 | R Suganthi | 1 | |
| 20 | Koneru Lakshmaiah Education Foundation | 1 |
DTN LLC’s position, built on harvest advisory and crop growth modeling patents that are also the most-cited in the corpus, suggests a durable technical moat in agronomic decision-support modeling. Challengers are currently fragmented across AI, soil, and agronomy branches without a comparable citation anchor.
The most recent 18–24 months of filings are under-counted due to patent publication lag; observed totals for 2025 and 2026 will rise as applications publish. Longer-window growth, applicant concentration, and technology-route coverage are therefore more reliable signals than the latest-year bar alone.
Filings accelerating; AI and business-data processing dominate the technology mix
Annual filing activity shows a clear upward trajectory from a near-zero base in 2017, with a sharp surge in 2024 and 2025. The technology composition reveals that computational and AI branches outweigh purely agronomic branches, signaling that software-defined modeling is the primary innovation vector.
Annual filing trend
Filings were negligible through 2019, climbed steadily from 2020 to 2023, and then surged in 2024 and 2025. The 2025 and 2026 bars are incomplete due to publication lag and will grow as applications publish; the apparent easing into 2026 does not indicate a real decline.
↗ Hover for values · click a bar to ask EurekaTechnology composition
Business and administrative data processing (G06Q) and AI-based computing (G06N) are the two most represented branches, ahead of soil working (A01B) and horticulture and forestry (A01G). This mix confirms that the modeling layer — algorithmic, predictive, and data-processing — dominates over hardware or crop-specific subclasses.
↗ Hover for values · click a bar to ask EurekaHighly cited patent families surfaced by the query
Citation-heavy patent families returned by the query. Use this section as citation context, not as a curated list of the most topic-specific patents.
INTELLIGENTE PFLANZENWACHSTUMSVORRICHTUNG MIT DIGI…
A system for growing plants for modelling a farming environment, the system comprising: an enclosed device for growing the plants for modelling the farming environment; sensors placed in the farming environment for acquiring plant growth parameters data from the farming environment; computer configured for simulating the farming environment with the… (excerpt from the patent abstract)
| # | Patent | Citations |
|---|---|---|
| 1 | Assessment of moisture content of stored crop, and… | 109 |
| 2 | Modeling of crop growth for desired moisture conte… | 97 |
| 3 | Diagnosis and prediction of in-field dry-down of a… | 80 |
| 4 | Harvest advisory modeling using field-level analys… | 62 |
| 5 | Modeling of time-variant threshability due to inte… | 25 |
| 6 | Modeling of time-variant threshability due to inte… | 21 |
| 7 | Modeling and prediction of below-ground performanc… | 20 |
| 8 | 土壤重金属累积过程时空模拟模型构建方法 | 16 |
Ranked by total forward citations. Citation counts favour older and broadly cited patent families, and broad or adjacent patents may appear when they match the search scope. Treat this section as citation context, not as a curated list of the most topic-specific patents. Some patent titles may be shown in their original, non-English language where an accurate translation could not be guaranteed.
What the competitive structure means for R&D investment decisions
The combination of rapid growth, limited concentration, and a predominantly academic filing base outside DTN LLC points to an open competitive window. Four structural factors shape where investment risk and opportunity sit.
Growth stage: annual filings still rising from a near-zero base
The lifecycle evidence classifies this field as Growth, with annual filings still rising and recent years understated by publication lag. The corpus spans only 85 patent families in total, confirming that the space has not yet accumulated the depth of a mature technology domain. Early movers can still establish durable positions across multiple sub-branches.
Growth stageLow concentration outside the leader creates entry room
The top five filers account for roughly 24% of the combined output of the hundred largest filers, and the gap between first and second is already large. The bulk of ranked applicants are Indian colleges and individual inventors filing one to three patent records each, leaving most technical routes effectively open to well-resourced entrants with a coherent portfolio strategy.
Low concentrationNo co-applicant activity detected in the current corpus
Evidence on co-applicant collaboration is pending — no joint-filing relationships appear in the current dataset. This absence may reflect the early stage of the field or the dominance of single-entity filers (academic institutions, individual inventors). Cross-sector partnerships between agronomy specialists and AI software developers represent an unoccupied structural position.
Evidence pendingIndia dominates filings; US and China are secondary markets
India is the lead jurisdiction by a wide margin, followed by the United States and China. Europe (EPO) and WIPO (PCT) together account for a small share, and Canada has minimal presence. The India-heavy filing pattern partly reflects the concentration of academic filers but also signals that protection in commercial agricultural markets — US, Europe, Brazil — remains underpenetrated relative to the technology’s global relevance.
India-ledGo beyond the landscape: Eureka’s TRIZ Solution agent breaks down an R&D problem and returns patented concept solutions, each with a technical approach and cited patent & literature evidence.
Co-filing pairs, ranked by the number of jointly-filed patent families.
DTN LLC leads on citation-rich agronomic modeling; academic challengers concentrate on AI
DTN LLC holds the top position by a decisive margin, with the most-cited patents in the corpus anchoring its lead. New academic entrants are filing in AI and data-processing branches but have not yet accumulated comparable citation weight.
DTN LLC
DTN LLC holds 15 patent records, the largest count in the corpus, and owns the top four most-cited patents — covering moisture content assessment, crop growth modeling, in-field dry-down diagnosis, and harvest advisory modeling. Its technology emphasis spans soil working (A01B), AI-based computing (G06N), and meteorology (G01W), forming a vertically integrated agronomic decision-modeling stack. No momentum data is available in the evidence, consistent with an established rather than newly entering filer.
patent records: 15Research Center for Eco-Environmental Sciences, CAS
The Research Center for Eco-Environmental Sciences of the Chinese Academy of Sciences holds 5 patent records and is flagged as a new entrant with recent filing momentum (4 recent patent records). Its technology focus centers on digital data processing (G06F) and business data processing (G06Q), indicating a modeling and analytics orientation rather than hardware-side agriculture. Pioneer Hi-Bred International Inc, with 4 patent records, focuses on business data processing and digital data processing, bringing a seed-company perspective to agronomic modeling.
patent records: 5| Applicant | Recent (3 yrs) | Trend |
|---|---|---|
| Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences | 4 | ▲ new entrant |
| CVR College of Engineering | 1 | ▲ new entrant |
| Lovely Professional University | 1 | ▲ new entrant |
| Sri Eshwar College of Engineering | 1 | ▲ new entrant |
Under-served technical branches adjacent to the dominant modeling stack
Several IPC classes appear at low share relative to the core computational branches, yet map onto high-value agricultural problems. These are observations of relative sparsity — they warrant further validation before committing R&D resources.
G01W · Meteorology — sparse weather-integration modeling
Meteorology (G01W) accounts for only 13 patent records and roughly 3% of the branch distribution, despite weather being a primary driver of crop outcomes. Iteris Inc and a small number of others have filed here, but the branch remains thin. An entrant combining high-resolution microclimate data pipelines with crop-growth models could occupy a defensible position that neither pure agronomic nor pure weather filers currently hold.
Search this in Eureka →G06V · Image/video recognition — sparse remote-sensing and imaging applications
Image and video recognition (G06V) has only 13 patent records at roughly 3% share, a low count given the proliferation of drone and satellite imagery in modern precision agriculture. The adjacent drone hardware branch (B64C) is even sparser at 2 patent records. An approach combining G06V vision models with G01S radar/positioning and A01B field-operation data could address a gap between raw sensing and actionable agronomic modeling that is currently underserved in the corpus.
Search this in Eureka →How leading filers differ by technology route
Route coverage across the main technology branches in the current evidence set.
| Player | G06Q 50 · Business, commerce & admin data processing | A01B 79 · Soil working in agriculture | G06N 20 · Computing based on AI models | A01G 25 · Horticulture & forestry | G06N 3 · Computing based on AI models |
|---|---|---|---|---|---|
| Iteris Inc | Strong · 6 | Strong · 8 | Strong · 8 | Moderate · 4 | Absent |
| CVR College of Engineering | Strong · 2 | Absent | Strong · 2 | Absent | Strong · 3 |
| Pioneer Hi-Bred International Inc | Strong · 2 | Strong · 2 | Absent | Absent | Absent |
| Adepu Venkata Pandu Ranga Chary | Strong · 1 | Absent | Strong · 1 | Strong · 1 | Strong · 1 |
| DTN LLC | Absent | Strong · 2 | Absent | Strong · 2 | Absent |
Frequently asked questions
The corpus contains 85 patent families in scope. This is a relatively small corpus consistent with an early-growth field that has seen most of its filing activity concentrated in the last three to four years.
DTN LLC leads the applicant ranking with 15 patent records, a count roughly three times that of the second-ranked filer, the Research Center for Eco-Environmental Sciences of the Chinese Academy of Sciences, which holds 5 patent records.
India is the lead jurisdiction, accounting for 69 patent records, far ahead of the United States with 17 and China with 8. Europe (EPO) and WIPO (PCT) have minimal coverage, indicating that protection in major commercial agriculture markets outside India and the US remains limited.
Business and administrative data processing (G06Q) is the most represented branch with 73 patent records, followed closely by AI-based computing (G06N) with 58. Soil working (A01B) and horticulture and forestry (A01G) are the leading agronomic branches.
The top-cited work covers moisture content assessment of stored crops (109 citations), crop growth modeling for desired moisture content (97 citations), in-field dry-down diagnosis and prediction (80 citations), and harvest advisory modeling using field-level analysis (62 citations). All four are attributable to DTN LLC’s filing activity.
No co-applicant collaboration relationships are detected in the current evidence. The field is dominated by single-entity filers — primarily academic institutions, individual inventors, and a small number of commercial companies — with no visible joint-filing partnerships at this time.
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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.
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