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COMPARISON AMONG BOLTZMANN AND CUBIC POLYNOMIAL MODELS FOR ESTIMATION OF COMPOSITIONAL NUTRIENT DIAGNOSIS STANDARDS: OPUNTIA FICUS-INDICA L. CASE
Authors:Ricardo David Valdez-Cepeda  Rafael Magallanes-Quintanar  Fidel Blanco-Macías  Edwin A. Hernández-Caraballo  José Luis García-Hernández
Affiliation:1. Universidad Autónoma Chapingo, Centro Regional Universitario Centro-Norte , Zacatecas , Mexico;2. Unidad Académica de Matemáticas, Universidad Autónoma de Zacatecas , Zacatecas , Mexico;3. Unidad Académica de Ingeniería Eléctrica, Universidad Autónoma de Zacatecas , Zacatecas , Mexico;4. Universidad Autónoma Chapingo, Centro Regional Universitario Centro-Norte , Zacatecas , Mexico;5. Departamento de Química y Suelos, Universidad Centro-Occidental Lisandro , Estado Lara , Venezuela;6. Facultad de Agricultura y Zootecnia, Universidad Juárez del Estado de Durango , Durango , Mexico
Abstract:Compositional Nutrient Diagnosis technique involves a yield target for discriminating between high- and low-yield subpopulations when developing norms. Traditionally, this yield value is estimated by finding the inflection point of the cumulative variance ratio function versus yield relationship through a third-order equation. However, yield targets frequently lie outside of the experimental yield range. A comparison among traditional (unrestricted) and restricted cubic model, and restricted and unrestricted Boltzmann equations was performed using a database (n = 360) of fresh matter yield and nutrient concentrations in one–year old cladodes of Opuntia ficus-indica L. The unrestricted Boltzmann equation resulted to have the best goodness-of-fit. The yield target was 27.01 kg plant?1 associated to the unrestricted Boltzmann equation for phosphorus cumulative variance ratio function versus yield relationship. Proposed nutrient optimum concentrations are: 11.4 g kg?1 for nitrogen (N), 3.4 g kg?1 for phosphorus (P), 42.3 g kg?1 for potassium (K), 42.5 g kg?1 for calcium (Ca), and 16.2 g kg?1 for magnesium (Mg).
Keywords:target yield  nutrient norms  goodness-of-fit  cubic models
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