I. Purpose

Automatically and periodically image hydroponic and agar medium-cultured crop root systems, dynamically monitor root growth speed, track structural changes in roots, and perform macroscopic dynamic statistical analysis of overall developmental changes at different time points. It serves as an excellent tool for crop resistance analysis. Utilizes AI deep learning-based automatic recognition and extraction of in-situ soil-cultured root images, automatically identifying and extracting ≥80% of in-situ soil-cultured root volume (in approximately 2 minutes), significantly reducing the workload of interactive guidance and correction for root analysis. It can also analyze washed root systems or aeroponically cleaned root systems to obtain biomass data, enabling scientific and objective evaluation of key factors affecting plant growth quality, such as analyzing the impact of light, water, fertilizer, and temperature/humidity environments on growth and stress resistance.

II. Main Performance Indicators

1. A large-depth-of-field imaging device + backlight imaging kit can capture images of hydroponic root systems from positions such as the side of the plant. Adjustable settings allow for automatic imaging of hydroponic roots at intervals of 0.5 to 48 hours. The monitoring computer can complete full-automatic imaging within 1 minute and be used for other tasks.

2. Real-time monitoring of hydroponic crop plants across 4 fields of view, with 4 sets of dynamic growth monitoring and imaging hardware included as standard (including 4 transparent culture flat boxes measuring 240mm wide × 380mm high).

3. Standard configuration includes 1 set of 10 transparent agar culture flat boxes with internal dimensions of 205mm wide × 270mm high × 5mm thick, enabling left-right comparisons for scanning fine in-situ agar-cultured root images down to 0.2mm in diameter.

4. The system automatically generates dynamic data on the overall development and growth of hydroponic and agar-cultured crop root systems, dynamically marking daily new growth of live roots and統(tǒng)計(jì) corresponding new root growth, including changes in root volume at different depth positions. The system features an early warning mechanism for abnormal root growth.

5. Displays density heatmaps of root volume changes over time by partitioned monitoring areas of the root system, with customizable精細(xì)度 for changes in each area based on partition size.

6. Automatically generates videos of root growth for retrospective viewing at specific time points.

7. Utilizes AI deep learning-based automatic recognition and extraction of in-situ soil-cultured root images, automatically identifying and extracting ≥80% of in-situ soil-cultured root volume (in approximately 2 minutes), significantly reducing the workload of interactive guidance and correction for root analysis. Allows interactive guidance analysis of in-situ soil-cultured root images, locking and editing root paths, and correcting root length, thickness, position, etc. Features a mouse-editable point-following magnifier. Capable of automatically stitching multiple in-situ root images.

8. Capable of washed root analysis:

1) Total root length; 2) Average root diameter; 3) Total root surface area; 4) Total root volume; 5) Root tip count; 6) Branching count; 7) Overlap count; 8) Root diameter class distribution parameters; 9) Root tip segment length distribution; 10) Customizable segment diameters with unequal spacing, automatically measuring length, projected area, surface area, volume, etc., for each diameter segment, and their distribution parameters; 11) Performs root color analysis to determine viable root quantity, outputting diameter, length, projected area, surface area, and volume for roots of different colors; 12) Performs root topological analysis, automatically determining root connectivity and relationship angles, and separately analyzing main roots or any lateral root’s length and branching count. Can individually display and mark parameters for any diameter segment of the root system (number of classes and class diameter range are customizable with unequal spacing), and allows root branching pruning, merging, connection corrections, with undo functionality for 100% accurate results; 13) Automatically measures root fractal dimension using the box-counting method. Analyzes the volume proportion of rhizobia in the root system to objectively determine their contribution; 14) High-throughput fully automatic root analysis, with editable and correctable results for each analysis image; 15) Capable of high-throughput automated estimation of root biomass distribution; 16) Features gravitropic angle analysis, path analysis, and main root extraction analysis; 17) Automatically measures parameters such as thickness, length, arc length, and chord height of pod stems, bodies, and beaks for rapeseed, soybean, etc.; 18) Automatically measures awn length of various grains; 19) Measures leaf area, length, and thickness of various needle leaves; 20) Saves analysis images, distribution maps, and result data, exports results to Excel, and outputs analysis-marked images.

9. The instrument supports a cloud platform, allowing analysis data to be saved to the cloud for access anytime, anywhere.

III. Standard Configuration

1. RootGA Root Dynamic Growth Monitoring and Analysis System software USB drive and software lock (1 set)

2. Autofocus 8-megapixel large-depth-of-field imaging device + backlight panel and positioning base plate + transparent culture flat box kit (4 sets)

3. Dual-light source color scanner with optical resolution of 4800 dpi and A4 extended size (1 unit)

4. Set of 10 agar culture transparent flat boxes (1 set)

5. Barcode scanner (1 unit)

6. Computer (12th Gen Intel Core i5 CPU / 16GB RAM / 500GB HDD / 21" color display / wireless card) (1 unit)