Details
| Originalsprache | Englisch |
|---|---|
| Seiten (von - bis) | 19-38 |
| Seitenumfang | 20 |
| Fachzeitschrift | Scientia horticulturae |
| Jahrgang | 80 |
| Ausgabenummer | 1-2 |
| Publikationsstatus | Veröffentlicht - 12 Jan. 1999 |
Abstract
An empirical model derived from data of field experiments is presented that predicts development and dry matter partitioning in cauliflower under conditions of unrestricted nutrient and water supply. The model is a combination of an empirical relationship between temperature sum and leaf number, a vernalization model, an allometric approach of dry matter partitioning between leaf and stem and an empirical logistic function describing the fraction of dry matter allocated to the curd depending on the temperature sum after the end of the vernalization process. This model was incorporated in a simple dry matter production model which calculated dry matter production using the product of intercepted photosynthetic active radiation and light use efficiency. However, the parameter values light use efficiency and specific leaf area of the model had to be fitted to every experiment in order to get an acceptable description of cauliflower dry matter production. Applied to an independent data set the model was able to predict measurable parameters like leaf number (r2 = 0.73), the proportion of leaf, stem and curd on total dry matter (r2 = 0.55, 0.08 and 0.77) and the length of the growing season (r2 = 0.69).
ASJC Scopus Sachgebiete
- Agrar- und Biowissenschaften (insg.)
- Gartenbau
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in: Scientia horticulturae, Jahrgang 80, Nr. 1-2, 12.01.1999, S. 19-38.
Publikation: Beitrag in Fachzeitschrift › Artikel › Forschung › Peer-Review
}
TY - JOUR
T1 - A simple empirical model for predicting development and dry matter partitioning in cauliflower (Brassica oleracea L. botrytis)
AU - Kage, H.
AU - Stützel, H.
PY - 1999/1/12
Y1 - 1999/1/12
N2 - An empirical model derived from data of field experiments is presented that predicts development and dry matter partitioning in cauliflower under conditions of unrestricted nutrient and water supply. The model is a combination of an empirical relationship between temperature sum and leaf number, a vernalization model, an allometric approach of dry matter partitioning between leaf and stem and an empirical logistic function describing the fraction of dry matter allocated to the curd depending on the temperature sum after the end of the vernalization process. This model was incorporated in a simple dry matter production model which calculated dry matter production using the product of intercepted photosynthetic active radiation and light use efficiency. However, the parameter values light use efficiency and specific leaf area of the model had to be fitted to every experiment in order to get an acceptable description of cauliflower dry matter production. Applied to an independent data set the model was able to predict measurable parameters like leaf number (r2 = 0.73), the proportion of leaf, stem and curd on total dry matter (r2 = 0.55, 0.08 and 0.77) and the length of the growing season (r2 = 0.69).
AB - An empirical model derived from data of field experiments is presented that predicts development and dry matter partitioning in cauliflower under conditions of unrestricted nutrient and water supply. The model is a combination of an empirical relationship between temperature sum and leaf number, a vernalization model, an allometric approach of dry matter partitioning between leaf and stem and an empirical logistic function describing the fraction of dry matter allocated to the curd depending on the temperature sum after the end of the vernalization process. This model was incorporated in a simple dry matter production model which calculated dry matter production using the product of intercepted photosynthetic active radiation and light use efficiency. However, the parameter values light use efficiency and specific leaf area of the model had to be fitted to every experiment in order to get an acceptable description of cauliflower dry matter production. Applied to an independent data set the model was able to predict measurable parameters like leaf number (r2 = 0.73), the proportion of leaf, stem and curd on total dry matter (r2 = 0.55, 0.08 and 0.77) and the length of the growing season (r2 = 0.69).
KW - Cauliflower
KW - Development
KW - Leaf initiation
KW - Model
KW - Partitioning
KW - Vernalization
UR - http://www.scopus.com/inward/record.url?scp=0344958710&partnerID=8YFLogxK
U2 - 10.1016/S0304-4238(98)00226-X
DO - 10.1016/S0304-4238(98)00226-X
M3 - Article
AN - SCOPUS:0344958710
VL - 80
SP - 19
EP - 38
JO - Scientia horticulturae
JF - Scientia horticulturae
SN - 0304-4238
IS - 1-2
ER -