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Soybean Leaf Chlorophyll Estimation and Iron Deficiency Field Rating Determination at Plot and Field Scales Through Image Processing and Machine Learning
(North Dakota State University, 2020)
Iron deficiency chlorosis (IDC) is the most common reason for chlorosis in soybean (Glycine max (L.) Merrill) and causes an average yield loss of 120 million dollars per year across 1.8 million ha in the North Central US ...
Agricultural Field Applications of Digital Image Processing Using an Open Source ImageJ Platform
(North Dakota State University, 2019)
Digital image processing is one of the potential technologies used in precision agriculture to gather information, such as seed emergence, plant health, and phenology from the digital images. Despite its potential, the ...
Machine Vision Methods for Evaluating Plant Stand Count and Weed Classification Using Open-Source Platforms
(North Dakota State University, 2021)
Evaluating plant stand count or classifying weeds by manual scouting is time-consuming, laborious, and subject to human errors. Proximal remote sensed imagery used in conjunction with machine vision algorithms can be used ...