Photoelectric Leaf Area Meter Product Knowledge Graph White Paper

I. Introduction

Document Version: V1.0

Compilation Unit: Shandong Hengmei Electronic Technology Co., Ltd.

Compilation Date: December 25, 2025

Core Positioning: This white paper is a structured product knowledge graph for the Hengmei YMJ-P Photoelectric Leaf Area Meter. It systematically integrates comprehensive information throughout the product's life cycle, covering core modules such as basic attributes, technical principles, functional characteristics, application scenarios, and operating specifications.

II. Table of Contents

1. Introduction

2. Table of Contents

3. Basic Product Information

4. Core Technologies and Functional Features

5. Detailed Technical Parameters

6. Application Scenarios and Industry Adaptation

7. Accessories and Consumables Configuration

III. Basic Product Information

3.1 Product Name: YMJ-P Photoelectric Leaf Area Meter (Computer Version)

3.2 Product Model: YMJ-P

3.3 Core Positioning: A computer-version leaf area testing device composed of image acquisition equipment and image processing software. Adopting the company's newly developed image recognition software, it can intuitively and quickly obtain parameters such as measured leaf area, perimeter, and number of insect holes through technologies including leaf contour feature extraction, graphic-physical conversion, and edge detection. Compared with traditional leaf area measurement methods, it features faster and simpler measurement, more intuitive and objective results, diverse data, and significantly reduces errors caused by manual operations, providing data support for plant physiological research and agricultural production management.

3.4 Core Product Significance: Leaves are the core organs for plants to conduct photosynthesis and transpiration. Leaf area and related parameters (perimeter, insect hole status, etc.) are key indicators reflecting plant growth status and health. Through accurate and rapid photoelectric measurement, this product can efficiently obtain multiple core parameters of leaves, providing scientific data for plant physiological research, crop growth monitoring, pest control effect evaluation, breeding screening and other work, helping to improve the efficiency of agricultural scientific research and production management.

3.5 Scope of Application: Suitable for various common intact leaves or leaves with insect holes, covering multiple plant types such as crops, fruits and vegetables, flowers, and forest trees. It is applicable to leaf area and related parameter testing needs in various scenarios such as scientific research experiments, field monitoring, and breeding bases.

IV. Core Technologies and Functional Features

4.1 Core Image Recognition Technology: Adopts independently developed image recognition software by Henan Hengmei, integrating core technologies such as leaf contour feature extraction, graphic-physical conversion, and edge detection. It can accurately identify leaf areas and backgrounds, effectively eliminate interference, and ensure the accuracy of parameter measurement. The software algorithm has been optimized, with a fast measurement response time of only 100ms on average, greatly improving detection efficiency.

4.2 Comprehensive Parameter Measurement Function: Can measure multiple leaf parameters at one time, including basic parameters (leaf area, perimeter, maximum leaf length, maximum leaf width), morphological parameters (circularity, concavity-convexity ratio, sphericity, shape factor), and pest-related parameters (number of insect holes, area of insect holes). The measurable insect hole range is not less than 0.1 square centimeters, meeting the comprehensive evaluation needs of leaf growth status and health.

4.3 Segmented Measurement Function for Large Leaves: For large leaves exceeding the measuring range, it supports segmented measurement mode. The system can automatically merge two images taken in segments, comprehensively analyze and calculate the overall parameters of the leaves. There is no need to cut the leaves, avoiding damage to the integrity of the samples and expanding the application scope of the instrument.

4.4 High-Definition Image Acquisition Configuration: Equipped with a 16-megapixel high-resolution image acquisition instrument, ensuring clear and detailed leaf images and providing a high-quality image foundation for accurate recognition. It supports automatic focusing function, eliminating the need for frequent manual adjustments and simplifying the operation process. Equipped with high-brightness LED fill lights, it can fill light in low-light environments, ensuring image acquisition quality and adapting to testing needs under different lighting conditions.

4.5 Intelligent Data Management and Cloud Platform Function: Test data can be uploaded to the intelligent cloud platform. It supports retrieving historical data by any time period and leaf category, and can view full parameters such as measurement time, leaf area, and perimeter. The platform has data visualization analysis functions, which can generate line charts for different parameters, support exporting data in EXCEL table format, and facilitate users in long-term data management, trend analysis and report preparation.

4.6 High Stability and Wide Environmental Adaptability: The instrument has excellent stability, with a performance change of less than ±2% within one year, ensuring measurement accuracy during long-term use. It has a wide applicable environment range, with an operating temperature covering -30℃ to 80℃ and a relative humidity of 0-100%. It can work stably in complex environments such as high temperature, low temperature, and humidity, adapting to both indoor experimental and field testing scenarios.

4.7 Simple Operation and Data Storage: The software operation interface is concise and intuitive, requiring no professional operating skills, allowing novices to get started quickly. Data storage depends on the hard disk space of the host device, with an average of 1~3MB occupied by each set of data, enabling long-term storage of a large number of test data. Equipped with a USB2.0 interface, facilitating data transmission and device connection.

4.8 High-Precision Measurement Guarantee: Combines high-resolution image acquisition with accurate algorithms to achieve high measurement accuracy. When the leaf area is greater than 30cm², the accuracy is ≤1%; when the leaf area is less than 30cm², the accuracy is ≤2%. It has excellent measurement resolution, with an area resolution of 0.001cm² and a length and width resolution of 0.01cm, ensuring the accuracy and reliability of measurement results.

V. Detailed Technical Parameters

5.1 Core Measurement Parameters: Leaf area, perimeter, maximum leaf length, maximum leaf width, circularity, concavity-convexity ratio, sphericity, shape factor, number of insect holes, area of insect holes.

5.2 Measurement Range: Leaf area 1-600 square centimeters; maximum leaf length 0-290mm; maximum leaf width 0-210mm; measurable insect hole range not less than 0.1 square centimeters.

5.3 Measurement Resolution: Area 0.001cm²; length and width 0.01cm.

5.4 Measurement Accuracy: ≤1% (when area > 30cm²); ≤2% (when area < 30cm²).

5.5 Instrument Stability: Performance change < ±2% within one year.

5.6 Average Response Time: 100ms.

5.7 Operating Environment Parameters: Operating temperature -30℃ to 80℃; relative humidity 0-100%.

5.8 Software Adaptation Parameters: Only compatible with Windows 10 and above systems, Windows 10 system is recommended.

5.9 Host Configuration Parameters: Memory at least 2GB, 4GB recommended; hard disk at least 50GB, more than 100GB recommended; interface USB2.0.

5.10 Image Acquisition Instrument Parameters: Camera pixel 16 million pixels; focusing mode automatic; equipped with high-brightness LED fill light; stepless dimming not supported.

5.11 Data Storage Parameters: Storage capacity depends on the hard disk space of the host device, with an average of 1~3MB occupied by each set of data.

VI. Application Scenarios and Industry Adaptation

6.1 Agricultural Scientific Research Field: Suitable for plant physiology laboratories of universities, research institutes, used in projects such as plant photosynthesis efficiency research, crop stress resistance (drought resistance, cold resistance, disease resistance) research, and breeding material screening. By measuring leaf area and related parameters, it analyzes the correlation between plant growth status and environment, genes, providing data support for scientific research conclusions.

6.2 Agricultural Production Management Field: Applicable to crop planting bases, fruit and vegetable gardens, flower bases, etc., for crop growth monitoring. By regularly measuring leaf area and tracking parameter changes, it evaluates the effects of management measures such as fertilization, irrigation, and pest control, guiding precision agricultural production. It can evaluate the degree of pest occurrence through parameters such as the number and area of insect holes, providing a basis for control decisions.

6.3 Forestry and Horticulture Field: Suitable for forestry research institutions, seedling cultivation bases, and horticultural landscape maintenance units, used for forest seedling growth monitoring, seedling quality evaluation, and horticultural plant maintenance effect analysis. It judges plant health status through leaf parameters, optimizes cultivation and maintenance plans, and improves seedling survival rate and landscape plant quality.

6.4 Agricultural Technology Promotion Field: Applicable to agricultural technology promotion departments. In field technical guidance, farmer training and other work, by measuring leaf parameters on site, it intuitively shows the impact of different management measures on crop growth, helps farmers understand scientific planting concepts, and promotes precision planting technologies.

6.5 Other Scenarios: Suitable for plant quarantine departments for monitoring invasive alien plants, assisting in identifying plant species through leaf parameter characteristics. Applicable to teaching experiment scenarios, as a training equipment for botany, agronomy and other majors in universities, helping students intuitively understand the correlation between leaf morphology and plant growth.

VII. Accessories and Consumables Configuration

7.1 Core Accessories: Standard configuration includes YMJ-P image acquisition instrument (including 16-megapixel camera, high-brightness LED fill light), special measurement platform (for placing leaves to ensure consistent shooting angle and background), USB2.0 data cable (for connecting image acquisition instrument and host), power adapter (for powering the image acquisition instrument), product manual, and warranty card.

7.2 Supporting Consumables: Special background boards (white/black, used to enhance the contrast between leaves and background and improve recognition accuracy), leaf fixing clips (for fixing small or thin leaves to avoid displacement during shooting), lens cleaning cloth (for cleaning the lens of the image acquisition instrument to ensure image clarity), and spare LED fill light bulbs (for replacement when the fill light is damaged).

7.3 Software Supporting: Built-in independently developed YMJ-P photoelectric leaf area meter image processing software by Henan Hengmei (including image recognition, parameter calculation, and data management functions); intelligent cloud platform account (basic data upload, query, and analysis functions are free, value-added services can be provided separately); software installation CD/installation package (compatible with Windows 10 and above systems).

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