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Non-destructive evaluation of chlorophyll content in quinoa and amaranth leaves by simple and multiple regression analysis of RGB image components
M. Riccardi
*
, G. Mele, C. Pulvento, A. Lavini, R. D'Andria, Sven-Erik Jacobsen
*
Corresponding author for this work
Section for Crop Sciences
46
Citations (Scopus)
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Dive into the research topics of 'Non-destructive evaluation of chlorophyll content in quinoa and amaranth leaves by simple and multiple regression analysis of RGB image components'. Together they form a unique fingerprint.
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Medicine & Life Sciences
Chenopodium quinoa
100%
Chlorophyll
83%
Color
14%
Costs and Cost Analysis
5%
Genotype
12%
In Vitro Techniques
3%
Noise
8%
Regression Analysis
35%
Software
6%
SPAD
56%
Agriculture & Biology
cameras
18%
chlorophyll
38%
color
10%
digital images
21%
field methods
11%
genotype
10%
image analysis
14%
laboratory techniques
10%
leaf chlorophyll content
10%
leaves
23%
methodology
4%
nondestructive methods
11%
physiological state
9%
prediction
6%
rapid methods
9%
regression analysis
46%
Chemical Compounds
Amaranth
77%
Amount
3%
Chlorophyll
58%
Leaf Like Crystal
45%
Time
2%