ArticleApplications in plant sciences2020
A comparison of seed germination coefficients using functional regression.
Article in Applications in plant sciences, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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Who cites it
12 citing papers in PubMed.
- Insights into Salinity Stress-Induced Morpho-Physiological and Molecular Responses and Nanoparticle- and Nanobiochar-Mediated Tolerance Mechanisms During Seed Germination.Nanomaterials (Basel, Switzerland) · 2026Review
- Proteomic insights into nano-chitosan-induced salinity tolerance in solid matrix-primed mung bean seedlings.Scientific reports · 2026Article
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- Temperature-dependent germination dynamics of herbicide-resistant and susceptible blackgrass (Alopecurus myosuroides) and silky windgrass (Apera spica-venti) from Poland.Scientific reports · 2025Article
- An integrated assessment of seed germination performance using classical and complementary metrics under abiotic stress.Scientific reports · 2025Article
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- Cold tolerance SNPs and candidate gene mining in the soybean germination stage based on genome-wide association analysis.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2024Article
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- Trial Protocol for Evaluating Platforms for Growing Microgreens in Hydroponic Conditions.Foods (Basel, Switzerland) · 2022Review
- Effects of Trichoderma asperellum on Germination Indexes and Seedling Parameters of Lettuce Cultivars.Current microbiology · 2021Article
- A comparison of seed germination coefficients using functional regression.Applications in plant sciences · 2020Article
- Physical Dormancy Release inPlants (Basel, Switzerland) · 2020Article
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Authors and funding
4 authors.
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Abstract
premiseSeed germination over time is characterized by a sigmoid curve, called a germination curve, in which the percentage (or absolute number) of seeds that have completed germination is plotted against time. A number of individual coefficients have been developed to characterize this germination curve. However, as germination is considered to be a qualitative developmental response of an individual seed that occurs at one time point, but individual seeds within a given treatment respond at different time points, it has proven difficult to develop a single index that satisfactorily incorporates both percentage and rate. The aim of this paper is to develop a new coefficient, the
methodsTo create the new index, the germination curves were smoothed using nondecreasing splines and the CGI was derived as the area under the resulting spline. For the comparison of the CGI with other common indexes, a regression model with functional response was developed.
resultsUsing both an experimentally obtained wild pea ( DISCUSSION: The CGI can be used advantageously for the characterization of the germination process. Moreover,
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