US 12,232,438 B2
System and method for real-time crop management
Itzhak Khait, Kibbutz Ein Zivan (IL); and Moshe Bar, Rishon Le-Zion (IL)
Assigned to Centure Applications LTD, Tel Aviv (IL)
Filed by Centure Applications LTD, Tel Aviv (IL)
Filed on Aug. 21, 2024, as Appl. No. 18/810,722.
Application 18/810,722 is a continuation of application No. 17/758,439, previously published as PCT/IL2020/051206, filed on Nov. 23, 2020.
Claims priority of provisional application 63/060,834, filed on Aug. 4, 2020.
Claims priority of provisional application 62/960,880, filed on Jan. 14, 2020.
Prior Publication US 2024/0423113 A1, Dec. 26, 2024
Int. Cl. G06T 7/00 (2017.01); A01B 79/00 (2006.01); A01B 79/02 (2006.01); C12N 15/82 (2006.01)
CPC A01B 79/005 (2013.01) [A01B 79/02 (2013.01); C12N 15/8212 (2013.01); C12N 15/8213 (2013.01); G06T 7/0002 (2013.01); G06T 2207/10032 (2013.01); G06T 2207/30188 (2013.01)] 20 Claims
OG exemplary drawing
 
1. A system for selective crop management, comprising:
an agricultural vehicle;
one or more image sensors mounted on the agricultural vehicle, the one or more image sensors configured to acquire an image of a respective region of an agricultural field along a direction of travel of the agricultural vehicle, the respective region including a genetically modified plant configured to modify a visual characteristic of at least a portion of the genetically modified plant in response to a predetermined physiological state of the genetically modified plant, the genetically modified plant having a first state in which the visual characteristic is unmodified and the genetically modified plant does not have the predetermined physiological state, and a second state in which the visual characteristic is modified and the genetically modified plant has the predetermined physiological state;
a selective sprayer mounted on the agricultural vehicle;
a computer on the agricultural vehicle, the computer including at least a processor circuit and non-transitory memory, the processor configured to:
detect a state of the genetically modified plant represented in the image using a trained machine learning (ML) model stored in the non-transitory memory, the training ML model having been trained with first images that include one or more genetically modified plants in the first state and second images that include one or more genetically modified plants in the second state;
produce a trigger signal that causes the selective sprayer to spray the respective region of the agricultural field when the second state is detected.