Information inference for agronomic data generation in sugarcane applications

Patent metadata

Field	Value
Publication number	US-2020337232-A1
Application number	US-201916393364-A
Country	US
Kind code	A1
Filing date	Apr 24, 2019
Priority date	Apr 24, 2019
Publication date	Oct 29, 2020
Grant date	—

Abstract

A method for mapping an agricultural crop in a field is provided. The method comprising receiving signals, with a control unit on an agricultural machine, from a yield sensor, which senses a yield characteristic of the crop, and a processing sensor, which senses a processing characteristic of the crop, associated with an agricultural work machine; determining the presence of a void crop plant using the received signals; determining a location of the void crop plant using at least a time and a location of the agricultural work machine; and generating a void crop map showing the location of the void crop within the field.

First claim

What is claimed is:

1 . A method for mapping an agricultural crop in a field, the method comprising:
receiving signals, with a control unit mounted on an agricultural work machine, from a yield sensor, which senses a yield characteristic of the crop, and a processing sensor, which senses a processing characteristic of the crop, associated with an agricultural work machine; determining the presence of a void crop plant using the received signals; determining a location of the void crop plant using at least a time and a location of the agricultural work machine; and generating a void crop map showing the location of the void crop plant within the field.

2 . The method of claim 1 further comprising the step of classifying the received signals using at least one of a fuzzy logic, machine learning, clustering, or statistical analysis classification system.

3 . The method of claim 2 wherein the step of classifying the received signal is performed using a fuzzy logic system wherein a confidence factor is assigned to each of the received signals associated with the yield sensor and processing sensor for a sampling interval.

4 . The method of claim 3 further comprising determining the presence of a void crop plant for the sampling interval using the received signals and at least one of the associated confidence factors.

5 . The method of claim 4 further comprising determining an aggregate confidence indicator for the presence of a void crop plant based on the confidence factors related to an estimated accurateness of the received signals.

6 . The method of claim 5 wherein the accurateness of the received signal is based on at least one of (i) a range of the at least one of the received signals, (ii) a change rate of the at least one of the received signals, (iii) a noise level of the at least one of the received signals and (iv) a plant loss condition, wherein the plant loss condition is associated with at least one of a void crop plant, pest damage, weed damage, field operation damage, and drought.

7 . The method of claim 1 wherein the crop is sugarcane and the agricultural work machine is a sugarcane harvester.

8 . The method of claim 1 wherein the processing characteristic from the processing sensor corresponds to a sensed characteristic associated with at least one of base cutter pressure, chopper pressure, and elevator speed.

9 . The method of claim 1 wherein the yield sensor is within a stream of processed material of the agricultural work machine, the yield sensor sensing a yield characteristic corresponding to a mass or a volume of the processed d material.

10 . The method of claim 1 further comprising conditioning the signals by applying at least one of a filter, delay, scaling, offset and bias removal.

11 . The method of claim 1 further comprising receiving signals from at least one of a satellite navigation receiver or a location-determining receiver, each receiver producing a time, position, and velocity of the agricultural work machine.

12 . The method of claim 1 wherein the step of determining the presence of a void crop plant further comprises:
analyzing whether the received signals have a void crop characteristic; and
assigning a confidence indicator to each of the received signals with the void crop characteristic.

13 . The method of claim 12 wherein the void crop characteristic indicates at least one of a void crop plant or a developmentally delayed plant.

14 . The method of claim 1 wherein the step of generating a void crop map is performed with a processor, the processor located either onboard the agricultural work machine or offboard the agricultural work machine and the onboard or offboard generation of the void crop map occurring as the agricultural work machine moves through the field or subsequent to the agricultural work machine moving through field.

15 . The method of claim 1 further comprising generating, using the void crop map, at least one of a planting field operation prescription, harvest field operation prescription, and a crop care field operation prescription.

16 . The method of claim 15 wherein the planting field operation prescription includes replanting a void crop plant.

17 . The method of claim 15 wherein the harvest field operation prescription includes adjusting at least one of a speed, cleaning settings or engine management of harvester.

18 . The method of claim 15 wherein the crop care field operation prescription includes adjusting the operation of a sprayer, cultivator or fertilizer.

19 . A system for mapping the location of void crop plants in a field, the system comprising:
an agricultural working machine; at least two sensors associated with agricultural working machine; and a data processor configured to determine the presence of a void crop plant using the received signals from the at least two sensors and generate a void crop plant map, the map showing the location of a void crop plant within the field.

20 . The system of claim 19 wherein the at least two sensors are configured to sense parameters relating to at least one of the crop in the field or the agricultural work machine.

Assignees

• Deere & Co

Inventors

• Blank Sebastian
• Johnson Peter A
• Dighton John A

Classifications

• A01D45/10 Primary

  of sugar cane {(for digging sugar cane A01D31/00)} · CPC title

• A01D41/1271

  for measuring crop flow · CPC title

• G01S19/52

  Determining velocity · CPC title

• A01D65/02

  Lifting fingers · CPC title

• A01D43/085

  Control or measuring arrangements specially adapted therefor · CPC title