US 12,228,504 B2
Material evaluating arrangement for an agricultural work machine
Peter Schade, Bad Dürkheim (DE); Helge Klein, Kaiserslautern (DE); and Frank Weber, Kaiserslautern (DE)
Assigned to Deere & Company, Moline, IL (US)
Filed by Deere & Company, Moline, IL (US)
Filed on Feb. 12, 2021, as Appl. No. 17/248,895.
Claims priority of application No. 102020000904.2 (DE), filed on Feb. 12, 2020.
Prior Publication US 2021/0247305 A1, Aug. 12, 2021
Int. Cl. G01N 21/3577 (2014.01); A01C 23/00 (2006.01); A01D 41/127 (2006.01); G01N 21/27 (2006.01); G01N 21/31 (2006.01); G01N 21/3563 (2014.01); G01N 21/359 (2014.01); G01N 21/84 (2006.01); G01N 33/02 (2006.01); G06N 3/045 (2023.01); G06N 3/08 (2023.01)
CPC G01N 21/3577 (2013.01) [A01C 23/007 (2013.01); A01D 41/1277 (2013.01); G01N 21/274 (2013.01); G01N 21/31 (2013.01); G01N 21/3563 (2013.01); G01N 21/359 (2013.01); G01N 33/02 (2013.01); G06N 3/045 (2023.01); G06N 3/08 (2013.01); G01N 2021/8466 (2013.01); G01N 2201/1211 (2013.01); G01N 2201/1214 (2013.01); G01N 2201/1218 (2013.01); G01N 2201/127 (2013.01); G01N 2201/1296 (2013.01)] 20 Claims
OG exemplary drawing
 
1. A material evaluating apparatus for an agricultural work machine comprising:
interface circuitry;
computer-readable instructions; and
at least one processor circuit to be programmed by the computer-readable instructions to:
cause a light source to illuminate a sample of a material in a tank of the agricultural work machine;
determine a spectral signal related to a wavelength-specific intensity of light reflected by a constituent material of the sample;
determine a prediction of a content of the constituent material using a neural network, the neural network to use the spectral signal of a spectrometer, calibration data, and a property signal relating to a property of the sample, the property signal to include at least one of a temperature, a pH, a flow rate, an air humidity, and/or a pressure of the sample; and
cause an actuator of the agricultural work machine to change an application rate of the material in the tank based on the prediction of the content of the constituent material.