INFERRING MOISTURE FROM COLOR

Techniques are described herein for using artificial intelligence to predict crop yields based on observational crop data. A method includes: obtaining a first digital image of at least one plant; segmenting the first digital image of the at least one plant to identify at least one seedpod in the fi...

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Bibliographic Details
Main Authors Zheng, Ming, Yuan, Bodi, Yuan, Zhiqiang
Format Patent
LanguageEnglish
Published 02.11.2023
Subjects
AGRICULTURE
ANIMAL HUSBANDRY
CALCULATING
COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
COMPUTING
COUNTING
FERTILISING
FISHING
FORESTRY
HUMAN NECESSITIES
HUNTING
IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
PHYSICS
PLANTING
SOWING
TRAPPING
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Summary:Techniques are described herein for using artificial intelligence to predict crop yields based on observational crop data. A method includes: obtaining a first digital image of at least one plant; segmenting the first digital image of the at least one plant to identify at least one seedpod in the first digital image; for each of the at least one seedpod in the first digital image: determining a color of the seedpod; determining a number of seeds in the seedpod; inferring, using one or more machine learning models, a moisture content of the seedpod based on the color of the seedpod; and estimating, based on the moisture content of the seedpod and the number of seeds in the seedpod, a weight of the seedpod; and predicting a crop yield based on the moisture content and the weight of each of the at least one seedpod.
Bibliography:Application Number: US202318341434