Crop Phenotyping AI/ML Patent Snapshot 2026
Crop phenotyping AI/ML is an early-stage, fast-expanding field: the corpus stands at 19 patent families, with a 550% surge in recent three-year filings versus the prior window, anchored primarily by image recognition and horticulture-class innovations. Activity is thinly distributed across a long tail of individual inventors and small firms, with Agri Victoria Services the only applicant holding a meaningful block of patent records.
Agri Victoria leads a fragmented early field
Agri Victoria Services Pty Ltd tops the applicant ranking with 6 patent records, followed by Crocus Labs GmbH with 3 and Deere & Co with 2; all remaining ranked applicants hold a single record each, signalling a field with one clear front-runner and a wide dispersal of smaller participants.
The top five filers account for 30% of the ranked applicants visible in this query’ combined total — a low concentration figure that reflects the nascent, pre-consolidation state of the technology. No second-tier cluster has yet formed to challenge the leader.
| # | Applicant | Patent records | Share |
|---|---|---|---|
| 1 | Agri Victoria Services Pty Ltd | 6 | |
| 2 | Crocus Labs GmbH | 3 | |
| 3 | DEERE & CO | 2 | |
| 4 | Vaideghy A | 1 | |
| 5 | Shihezi University | 1 | |
| 6 | Yash Sunil Kshirsagar | 1 | |
| 7 | Sayali Prakash Shinde | 1 | |
| 8 | Prof. Aditya Muriidhar Patil | 1 | |
| 9 | Dr. Raj Kumar | 1 | |
| 10 | Dr. Maheswari P | 1 |
| # | Applicant | Patent records | Share |
|---|---|---|---|
| 11 | Prof. Suma C C | 1 | |
| 12 | Dr. Jain Jacob M | 1 | |
| 13 | Dr. Arunfred N | 1 | |
| 14 | Prof. Minal Arvind Gholpe | 1 | |
| 15 | Dr. Asha P N | 1 | |
| 16 | S. Aiswarya Priyadharshini | 1 | |
| 17 | Vishwakarma Institute of Technology | 1 | |
| 18 | Dr. Smitha Kurian | 1 | |
| 19 | Dr. Ganaga Durga Devi R | 1 | |
| 20 | Dr. Krishnan A R | 1 |
Agri Victoria’s position rests on image and video recognition (G06V) and material analysis (G01N) — core sensing modalities for field-based phenotyping — while Deere & Co’s presence signals that established agriculture equipment manufacturers are beginning to stake claims, which may intensify consolidation pressure over the next filing cycle.
The most recent 18–24 months of filings are under-counted due to standard patent publication lag; apparent recent softness should not be read as a slowdown. Longer-window growth, applicant concentration, and technology-route coverage are therefore more reliable signals than the latest-year bar alone.
A 2022 filing surge reshaped the technology mix
Two charts capture the field’s trajectory: annual filing volume reveals a sharp 2022 inflection that lifted the three-year average far above its predecessor, while the IPC class breakdown shows where technical effort is concentrated and where coverage remains thin.
Annual filing trend
Filings were negligible from 2018 through 2020, spiked sharply in 2022 (the peak year to date), and have moderated since — consistent with a Growth-stage field that has eased from its peak. Post-2023 figures are understated by publication lag and should not be read as a plateau.
↗ Hover for values · click a bar to ask EurekaTechnology composition
Horticulture and forestry (A01G) is visible in with 10 records, flanked by roughly equal coverage across material analysis (G01N), image data processing (G06T), image/video recognition (G06V), data recognition (G06K), AI model computing (G06N), and bioinformatics (G16B) — each with 5–6 records. Drone-related classes (B64C, B64D) and soil working (A01B) each hold only 2–3 records, indicating partial but shallow coverage.
↗ 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.
Cotton aphid stress monitoring method and system b…
The present disclosure relates to the technical field of pest stress monitoring, and discloses a cotton aphid stress monitoring method and system based on a high-throughput plant phenotyping platform and deep learning. Hyperspectral images of cotton leaves are obtained by using a hyperspectral imaging system; with single cotton leaves as regions of… (excerpt from the patent abstract)
Open this patent in Eureka →| # | Patent | Citations |
|---|---|---|
| 1 | Plant phenotyping techniques using mechanical mani… | 16 |
| 2 | Systems and Methods for Automated Hyperspectral Ve… | 10 |
| 3 | Systems and methods for automated hyperspectral ve… | 9 |
| 4 | Plant phenotyping techniques using optical measure… | 9 |
| 5 | Controlled environment agriculture method and syst… | 4 |
| 6 | Plant phenotyping techniques using mechanical mani… | 2 |
| 7 | Controlled environment agriculture method and syst… | 1 |
| 8 | Systems and methods for automated hyperspectral ve… | 1 |
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.
Assignee snapshot from the current evidence set
The applicants below are visible in this query result. Because the evidence set is relatively small, read this section as a directional snapshot rather than a full competitive ranking.
Agri Victoria Services Pty Ltd
The field’s visible filer with 6 patent records, all established as a new entrant in the recent filing window. Technical emphasis falls on image and video recognition (G06V 20, G06V 10) and optical material analysis (G01N 21), reflecting a sensor-fusion approach to field-based plant phenotyping. Its combination of breadth across sensing modalities and Australian home-jurisdiction filing suggests a strategy oriented toward IP protection of a commercial platform.
patent records: 6Crocus Labs GmbH
The second-ranked applicant with 3 patent records, also entering as a new entrant in the recent window. Technology focus clusters on horticulture and forestry (A01G 7, A01G 9) and LED/electric lighting circuits (H05B 45), pointing to a controlled-environment or indoor phenotyping approach that complements — rather than directly replicates — Agri Victoria’s field-sensing orientation. This differentiated niche may limit head-to-head competition in the near term.
patent records: 3Frequently asked questions
The corpus stands at 19 patent families. It is a small but fast-growing field: recent three-year filings exceeded the prior three-year window by 550%, placing it firmly in a Growth lifecycle stage.
Agri Victoria Services Pty Ltd leads with 6 patent records, focused on image and video recognition and optical material analysis. Crocus Labs GmbH is second with 3 records, oriented toward controlled-environment horticulture. Deere & Co holds 2 records, and all remaining ranked applicants hold one each.
India and the United States each account for 6 patent records, followed by Australia and Europe (EPO) at 3 each, and WIPO (PCT) at 1. India’s count reflects a cluster of individual inventor filings, while the US and Australia reflect commercial applicant activity.
Horticulture and forestry (A01G) leads with 10 records. Material analysis (G01N), image data processing (G06T), image/video recognition (G06V), data recognition (G06K), AI model computing (G06N), and bioinformatics (G16B) each carry 5–6 records. Drone-related classes and soil working classes are present but thin at 2–3 records each.
No co-filing relationships are detected in the current corpus. Development appears to be proceeding through independent parallel efforts. This is common in early-stage AI/agriculture intersections where proprietary training data confers competitive advantage.
G06N (AI model computing) and G16B (bioinformatics) each carry only 5 records at an 8% share among the top-ranked filers — sparse relative to the core sensing classes. AI model architecture innovations tailored to on-device phenotyping inference, and integrations linking phenotypic image data to genomic databases, represent areas with plausible technical value and low current claim density.
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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.
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