ArticleSensors (Basel, Switzerland)2020
Predictive Modeling of a Leaf Conceptual Midpoint Quasi-Color (CMQ) Using an Artificial Neural Network.
Article in Sensors (Basel, Switzerland), 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
5 citing papers in PubMed, 18 citations in OpenAlex.
- A major and stable QTL confers impatiens necrotic spot virus resistance in lettuce cv. Eruption.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2025Article
- Phytochemical and Agronomic Characterization of High-Flavonoid Lettuce Lines Grown under Field Conditions.Plants (Basel, Switzerland) · 2023Article
- Genetic determinants of lettuce resistance to drop caused by Sclerotinia minor identified through genome-wide association mapping frequently co-locate with loci regulating anthocyanin content.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2023Article
- Image-based phenotyping to estimate anthocyanin concentrations in lettuce.Frontiers in plant science · 2023Article
- Genetic and physiological determinants of lettuce partial resistance to Impatiens necrotic spot virus.Frontiers in plant science · 2023Article
Corrections and comments
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Authors and funding
1 author at 1 institution in 1 country.
Funding
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Abstract
The color of plant leaves is moderated by the content of pigments, which can show considerable dorsiventral distribution. Two typical examples are leafy vegetables and ornamentals, wherein red and green color surfaces can be seen on the same leaf. The proof of concept is provided for predictive modeling of a leaf conceptual mid-point quasi-color (CMQ) from the content of pigments. The CMQ idea is based on the hypothesis that the content of pigments in leaves is associated with the combined color from both surfaces. The CMQ, which is calculated from CIELab color coordinates at adaxial and abaxial antipodes, is thus not an actual color, but a notion that can be used in modeling. The CMQ coordinates, predicted from the content of chlorophylls and anthocyanins by means of an artificial neural network (ANN), matched well with the CMQ coordinates empirically found on photosynthetically active leaves of lettuce (
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