A flexible sigmoid function of determinate growth.

By Xinyou Yin, J. Goudriaan, E. Lantinga, J. Vos, H. Spiertz. Annals of Botany, 2003

790 citations recorded by the source corpus.

Subfields: Agronomy and Crop Science, Plant Science

View Paper: https://www.semanticscholar.org/paper/999cda5119bcb979e183d170cb0e7345031125e0

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Citations in the corpus

Field inoculation with arbuscular mycorrhizal fungi reduces Striga hermonthica performance on cereal crops and has the potential to contribute to integrated Striga management (2005, methodology): “The emergence of Striga shoots over time on sorghum was described using the beta growth function (Yin et al., 2003).”
Protein aggregation kinetics, mechanism, and curve-fitting: a review of the literature. (2009, background): “Richards' function is itself a generalized form of the logistic function [143], and is commonly used in botany to determine both the growth period length and the ultimate weight of plants [144].”
Improved evaluation of cover crop species by growth and root factors (2010, background): “The higher complexity of the model may increase stability problems of the iterative parameter estimation procedure, mainly related to the selection of adequate initial values (Robert et al., 1999; Schabenberger and Pierce, 2002; Yin et al., 2003).”
Root to shoot and carbon to nitrogen ratios of maize and soybean crops in the US Midwest (2020, methodology): “We estimated maximum biomass by fitting the crop biomass accumulation data to the beta-growth function (Yin et al., 2003).”
Nutrient Uptake, Partitioning, and Remobilization in Modern Soybean Varieties (2015, methodology): “A nonlinear β growth regression function (Yin et al., 2003) was used to predict nutrient accumulation as a function of days after planting (DAP).”
Soybean Sowing Date: The Vegetative, Reproductive, and Agronomic Impacts (2008, background): “Logistic functions are usually preferred for modeling crop growth because of the parsimony principle, that is, only three or four parameters need to be estimated ( Yin et al., 2003 ).”
Nonlinear Regression Models and Applications in Agricultural Research (2015, methodology): “Choose candidate model: Danalatos et al. (2009) analyzed the data using the beta growth function (Yin et al., 2003a; Eq.”
Evaluation of a phenological model for strategic decisions for hemp (Cannabis Sativa L.) biomass production across European sites (2012, neutral): “…(fT(x)) is nonlinear with initial quasi-exponential to linear response reaching an optimum after which the rate declines steeply (beta function, Yin et al., 2003, 1995; Yan and Hunt, 1999) fT(x)[x = 1, 2, 3] = ∣∣∣∣ 0 T ≤ Tb, T ≥ TcTc − T Tc − To · ( T − Tb To − Tb )(To−Tb)/(Tc−To) Tb < T <…”