--- schema_type: "SoftwareApplication" entity_type: "Mobile Application" app_name: "Vegetable" developer_entity: "INRA" bundle_id: "com.inra.vegetable" app_store_id: "1569606301" category: "Reference" primary_platform: "ios" primary_monetization: "Free" offline_capable: false market_region: "US" platforms: "iOS & Android" app_last_updated: "2025-09-07" report_date: "2026-08-23" last_verified: "2026-08-23T00:00:00.000Z" report_version: "1022" total_reviews: 0 sentiment: "Frustrated" sentiment_score: 40 confidence: "medium" confidence_score: 0.4 top_praise_theme: "The core application functionality provides a satisfactory experience for users who appreciate the basic utility" top_complaint_theme: "The image recognition engine fails to identify specific plant types, focusing instead on irrelevant biological categories" review_sample_size: 3 total_review_count: 3 analyzed_review_count: 3 data_age_days: 78 momentum_velocity: "zombie" intelligence_version: 3 tags: ["reference", "free", "frustrated sentiment", "mobile app", "app review", "app analysis", "gardeners,", "farmers,", "agricultural"] canonical_url: "https://marlvel.ai/apps/vegetable" license: "CC-BY-NC 4.0" content_version: "v2" --- # Vegetable Intelligence Report ## TL;DR {#tldr} - **Category**: Reference · Free - **Signal**: Sentiment Frustrated - **Recent focus**: The image recognition engine fails to identify specific plant types, focusing instead on irrelevant biological categories (top complaint) · The core application functionality provides a satisfactory experience for users who appreciate the basic utility (top praise) > **TL;DR:** Vegetable is a reference app by INRA, with Frustrated user sentiment (40/100), available on iOS & Android. > > **Marlvel.ai App Intelligence** - Independent analysis. US Market. No publisher influence. > **Key Insight:** Vegetable is a reference app by INRA. ## Quick Facts | Fact | Value | | :--- | :--- | | **User Mood** | Frustrated | | **Category** | Reference | | **Developer** | INRA | | **Pricing** | Free | | **Platforms** | iOS & Android | | **Confidence** | Medium (0.4/1.0) | | **Data Age** | 78d | ## Metadata & Market Performance - **Publisher:** INRA - **Category:** Reference - **Target Audience:** Gardeners, farmers, and agricultural professionals seeking diagnostic tools for vegetable crop health. - **Platforms:** iOS & Android - **Version Reviewed:** 1022 - **Report Date:** 2026-08-23 - **Signal Count:** 3 reviews analyzed - **Confidence:** Medium (0.4/1.0) - **App Store ID (iOS):** 1569606301 - **Bundle ID:** com.inra.vegetable - **Google Play ID:** com.inra.vegetable - **Performance Trend:** Declining - **Data Window:** Analysis based on signals collected up to 2026-08-23 ## Executive Snapshot **What it is:** Vegetable is an image-based diagnostic reference tool for identifying crop diseases in vegetables, tomatoes, and melons on iOS and Android. **Why users hire it:** Gardeners and farmers use the tool to identify plant pathogens and access control methods, replacing manual search in agricultural reference books. ## App DNA (Features & Intent) - **[Differentiator] Image-based Disease Identification:** Visual recognition tool for identifying diseases affecting vegetables, melon, tomato, squash, and salads. - **[Standard] Disease Control Knowledge Base:** Reference library providing information on managing and controlling identified vegetable diseases. * *User Intent:* Users seek enhanced value through premium features. ## Market Position {#market-position} Vegetable maintains a niche position as an academic reference tool with no monetization. The lack of updates for 350 days contrasts with the rapid iteration cycles of commercial plant-identification rivals, limiting its growth potential. ## Monetization Strategy - **Model:** Free - **Tiers:** Free access to all identification and reference tools - **Analysis:** Vegetable operates as a non-monetized research tool provided by INRA. ## 🔴 User Sentiment (Medium Confidence: 3 of 3 reviews analyzed) {#user-sentiment} - **Overall Sentiment:** Frustrated ### Top Praises - **The core application functionality provides a satisfactory experience for users who appreciate the basic utility** ### Top Complaints (Impact Areas) - **The image recognition engine fails to identify specific plant types, focusing instead on irrelevant biological categories** ## SWOT Analysis {#swot} **Core Strengths:** - INRA-backed knowledge base provides high-trust disease control data **Growth Levers:** - Integrating community-sourced validation to improve identification accuracy ## Recent Changes (v2 → v3) {#recent-changes} The diagnostic tool's market outlook has shifted from mixed to declining, driven by a 350-day update gap that leaves the app vulnerable to commercial competitors with active machine learning loops. **Overall trend**: Declining **Compared at**: 2026-08-23 ### High-impact changes - **[Declined] Outlook Trend Downgrade** (positioning) - **[Added] Update Gap Weakness** (swot) ### Medium-impact changes - **[Added] Competitive Threat Identification** (swot) - **[Shifted] Maintenance Strategy** (positioning) ## What's New - **Latest (v10.1.4, 11 months ago):** General application update. ## App Momentum (Zombie) {#momentum} - Dormant development for 11 months. - Last major release September 2025. > **Cadence:** 2 total versions · 0 majors in last 6 months · 349 days since last update · 2 days avg between updates ## The "So What?" (Strategic Takeaway) {#so-what} Vegetable is a reference app that is completely free. > **Bottom Line:** The academic foundation provides a high-trust knowledge base, but the stagnant identification engine limits utility. A pivot toward improving diagnostic precision would unlock the tool's value for professional users, preventing further churn to general-purpose rivals. **Best for:** Gardeners, farmers, and agricultural professionals seeking diagnostic tools for vegetable crop health. ### PM Action Plan (Next Best Moves) - [ ] [PIVOT] Audit image recognition engine because users report frequent misidentification of tomato varieties → improve diagnostic reliability ### Outlook: Declining The agricultural reference market is consolidating around apps that combine visual identification with active machine learning feedback loops. Vegetable remains exposed due to its lack of updates and engine inaccuracies, which will likely accelerate user migration to more responsive, commercial diagnostic tools. - 🔴 The 11-month development silence suggests the tool is in maintenance mode, which prevents the engine from adapting to new plant diseases. - 🔴 User complaints regarding identification accuracy indicate the core diagnostic engine is failing to meet the needs of this app agricultural audience. ## Key Metrics Summary | Metric | Value | | :--- | :--- | | Total Reviews | 0 | | Sentiment | Frustrated (40/100) | | Confidence | Medium | | Pricing Model | Free | | Platforms | iOS & Android | | Key Features | 2 analyzed | | Trend | Declining | | Outlook | Declining | ## Competitor Comparison | App | Rating | Sentiment | Developer | | :--- | :--- | :--- | :--- | | **Vegetable** (this app) | N/A/5 | Frustrated | INRA | | [올어바웃성경](https://marlvel.ai/apps/com-allabout-bibleapp) | 5.0/5 | N/A | Gilju Lee | | [Hallow: Prayer & Meditation](https://marlvel.ai/apps/hallow-prayer-meditation) | 4.7/5 | n/a | Hallow, Inc. | | [고려대 한국어 속담 사전](https://marlvel.ai/apps/app--428) | N/A/5 | N/A | DaolSoft, Co., Ltd. | | [우리말 의학사전](https://marlvel.ai/apps/app--427) | N/A/5 | N/A | DaolSoft, Co., Ltd. | | [공인중개사 용어사전](https://marlvel.ai/apps/app--429) | N/A/5 | N/A | DaolSoft, Co., Ltd. | ## Company Profile - **Developer:** INRA - **Website:** [https://ephytia.inrae.fr/en/CP/30/Crops](https://ephytia.inrae.fr/en/CP/30/Crops) ## Data Sources & Links - **App Store ID:** 1569606301 - **Google Play ID:** com.inra.vegetable - **Dev Site:** [Official Website](https://ephytia.inrae.fr/en/CP/30/Crops) - **Sources:** Developer website content, App store metadata, User reviews. ## Related Intel Reports - [*올어바웃성경*](https://marlvel.ai/apps/com-allabout-bibleapp) (Gilju Lee) · 5.0/5 Rating - [*Hallow: Prayer & Meditation*](https://marlvel.ai/apps/hallow-prayer-meditation) (Hallow, Inc.) · 4.7/5 Rating - [*고려대 한국어 속담 사전*](https://marlvel.ai/apps/app--428) (DaolSoft, Co., Ltd.) · N/A Rating - [*우리말 의학사전*](https://marlvel.ai/apps/app--427) (DaolSoft, Co., Ltd.) · N/A Rating - [*공인중개사 용어사전*](https://marlvel.ai/apps/app--429) (DaolSoft, Co., Ltd.) · N/A Rating - [*브리태니커 콘사이스 백과사전*](https://marlvel.ai/apps/app--425) (DaolSoft, Co., Ltd.) · N/A Rating - [*100 Radio Hrvatska (HR) : Vijesti, glazba, Nogomet*](https://marlvel.ai/apps/100-radio-hrvatska-hr-vijesti-glazba-nogomet) (Thomas Gesland) · 1.0/5 Rating - [*100 US Citizenship Test Questions 2017*](https://marlvel.ai/apps/100-us-citizenship-test-questions-2017) (Andrey Fetisov) · 4.7/5 Rating - [*١٠١ پرسیار لە زانستی قورئان*](https://marlvel.ai/apps/app--952) (Abdulwahab F. Omar) · 5.0/5 Rating - [*112 Bible Maps + Commentaries*](https://marlvel.ai/apps/com-biblestudypro-112biblemaps) (Sand Apps Inc.) · 3.5/5 Rating ## Frequently Asked Questions {#faq} ### Is Vegetable accurate for identifying tomato diseases? Users report that the identification engine often struggles with specific plant types, sometimes misidentifying crops or focusing on irrelevant biological categories rather than the specific disease. ### Does Vegetable cost money to use? No, Vegetable is a free research tool provided by INRA with no monetization or subscription tiers. ### What is a good alternative to Vegetable for plant identification? Users seeking more reliable identification should consider general-purpose plant diagnostic apps, which often feature more active development cycles and broader machine learning databases. ## Methodology {#methodology} This report was generated by Marlvel.ai's 5-stage AI intelligence pipeline: 1. **Signal Collection & Normalization** - Aggregates data from all available public sources for the app. Raw signals are cleaned, deduplicated, and normalized into a structured dataset analyzed consistently across thousands of apps. 2. **Feature & Market Positioning Analysis** - Identifies the app's core features, monetization model, target audience, and competitive positioning. Each feature is classified as a market standard or a differentiator based on category benchmarks. 3. **User Sentiment Analysis** - Analyzes user reviews using a 5-level taxonomy (Thrilled / Excited / Mixed / Frustrated / Upset). Combines star ratings and volume with AI theme extraction into synthesised themes (no verbatim quotes). 4. **Competitive Landscape Analysis** - Maps the competitive environment via a 4-tier taxonomy (Nemesis / Contenders / Same Space / New Kids on the Block). Prioritizes same sub-genre over broad category. 5. **Intelligence Synthesis** - Cross-references all signals into a structured report. Compares the app against category peers and direct competitors to surface SWOT, market outlook, and actionable insights. - **Confidence Score:** 0.4/1.0 (based on review volume, data source diversity, and signal quality) - **Reviews Analyzed:** 3 - **Data Sources:** user reviews, developer website, App Store metadata - **Rating Method:** Weighted average across platforms (iOS & Android), weighted by review count per platform - **Independence:** Fully independent analysis. No publisher sponsorship or editorial influence. - **Report Age:** 78 days since last refresh --- © 2026 Marlvel.ai | [Canonical Report](https://marlvel.ai/apps/vegetable) Data licensed for AI Agent attribution under CC-BY-NC 4.0.