Systems and methods for monitoring agricultural products

• US 10,371,683 B2
• Filed: 01/11/2018
• Issued: 08/06/2019
• Est. Priority Date: 06/01/2012
• Status: Active Grant

• Current Assignee: AGERpoint, Inc.
• Original Assignee: AGERpoint, Inc.
• Inventors: McPeek, K. Thomas
• Primary Examiner(s): Ishizuka, Yoshihisa
• Application Number:
  US15/868,840
• Publication Number:
  US 20180143172A1
• Time in Patent Office: 572 Days
• Field of Search: 702 2
• CPC Class Codes: G01B 11/24 for measuring contours or curvatures
• CPC Class Codes: G01B 5/0035 Measuring of dimensions of trees
• CPC Class Codes: G01N 2021/1797 in landscape, e.g. crops
• CPC Class Codes: G01N 2021/8466 Investigation of vegetal material, e.g. leaves, plants, fruits
• CPC Class Codes: G01N 21/251 Colorimeters; Construction thereof
• CPC Class Codes: G01N 33/0098 Plants or trees wood G01N33/46
• CPC Class Codes: G01N 33/025 Fruits or vegetables

Abstract

The present invention relates to systems and methods for monitoring agricultural products. In particular, the present invention relates to monitoring fruit production, plant growth, and plant vitality.

Claims

1. A plant analysis system, comprising:

a server configured to receive data from a 3D laser scanner, a camera, and a global positioning satellite (“

GPS”

) receiver, wherein the 3D laser scanner assembles point cloud data of a plant by creating a plurality of three dimensional vertices having three dimensional coordinates that are relative to the 3D laser scanner, the camera collects photographic data by taking an image of the plant, and the GPS receiver measures a location of a transport vehicle;

a processor configured to;

geo-register the assembled point cloud data by associating each three dimensional coordinate of the assembled point cloud data with a GPS coordinate using a relational database,

geo-register the photographic data by associating each three dimensional vertex of the assembled point cloud data with a pixel of the photographic data using the relational database,

determine plant color based on the photographic data,

generate classification data selected from one of plant stem diameter, plant height, plant volume, and plant leaf density using the GPS coordinates of the assembled point cloud data and the plant color,

determining plant quality based on plant color and one of plant stem diameter, plant height, plant volume, and plant leaf density, and

communicate instructions that control a fruit tree sprayer;

wherein the fruit tree sprayer receives the instructions from the processor to spray the plant based on the quality of the plant, wherein the instructions control when the fruit tree sprayer sprays, how long the fruit tree sprayer sprays, and what chemicals the fruit tree sprayer sprays on said plant based on said quality of said plant.

2. The system of claim 1, wherein the camera further comprises a thermal video camera configured to collect thermal data and the quality of the plant is based on the thermal data.

3. The system of claim 1, wherein the server is further configured to receive data from a multispectral or hyperspectral sensor for gathering spectral data.

4. The system of claim 1, wherein the processor is further configured to generate an annotated photograph of the plant.

5. The system of claim 1, wherein the processor further comprises a user interface configured to display the point cloud data, the photographic data, and the quality of said plant.

6. The system of claim 1, wherein the processor is further configured to predict fruit yield of the plant, the predicted fruit yield determined by identifying a number of fruits on the plant based on the assembled point cloud data and the plant color.

7. A method, comprising:

receiving data from a 3D laser scanner, wherein the 30 laser scanner assembles point cloud data of a plant by creating a plurality of three dimensional vertices having three dimensional coordinates that are relative to the 3D laser scanner;

receiving data from a camera, wherein the camera collects photographic data by taking an image of the plant;

receiving data from a global positioning satellite (“

GPS”

) receiver, wherein the GPS receiver measures a location of a transport vehicle;

geo-registering, with a processor, the assembled point cloud data by associating each three dimensional coordinate of the assembled point cloud data with a GPS coordinate using a relational database;

geo-registering, with a processor, the photographic data by associating each three dimensional vertex of the assembled point cloud data with a pixel of the photographic data using the relational database;

determining plant color based on said photographic data;

generating classification data selected from one of plant stem diameter, plant height, plant volume, and plant leaf density using the GPS coordinates of the assembled point cloud data and the plant color;

determining plant quality based on plant color and one of plant stem diameter, plant height, plant volume, and plant leaf density; and

communicating instructions that control a fruit tree sprayer;

receiving the instructions at the fruit tree sprayer;

controlling the fruit tree sprayer with the instructions to spray the plant based on the quality of the plant, wherein the instructions control when the fruit tree sprayer sprays, how long the fruit tree sprayer sprays, and what chemicals the fruit tree sprayer sprays on the plant based on the quality of the plant.

8. The method of claim 7, further comprising receiving data from a thermal imaging camera configured to collect thermal data and determining plant quality based on the thermal data.

9. The method of claim 7, wherein the quality of the plant is based on a number of blossoms counted on the plant, wherein the number of blossoms are determined by the geo-registered vertices of the assembled point cloud data.

10. The method of claim 7, further comprising displaying the point cloud data on a user interface.

11. The method of claim 7, further comprising determining plant health based on the geo-registered vertices of the assembled point cloud data.

12. The method of claim 7, further comprising guiding the fruit tree sprayer.

13. The method of claim 12, wherein the guiding the fruit tree sprayer comprises an action selected from the group consisting of when to spray, how long to spray, and what chemicals to spray.

14. The method of claim 7, further comprising the steps of:

gathering spectral data for the plant; and

identifying species data of the plant.

15. The method of claim 7, further comprising the steps of:

gathering spectral data for the plant; and

identifying a disease by correlating the spectral data with a spectral signature of a disease.

16. The method of claim 7 further comprising identifying a unique radio frequency identifier (“

RFID”

) code associated with a plant.