TY  - REP
AU  - Du Toit,A.S.
AU  - Booysen,J.
AU  - Human,J.J.
AU  - White,J.W.|Grace,P.
TI  - Use of linear regression and a correlation matrix to evaluate CERES3 (Maize)
T2  - CIMMYT NRG-GIS Series
SN  - 970-648-47-1
SN  - 1405-7484
PY  - 2000///
CY  - Mexico, DF (Mexico)
PB  - CIMMYT
KW  - Environmental factors
KW  - Linear models
KW  - Plant production
KW  - Research projects
KW  - Simulation models
KW  - Zea mays
KW  - AGROVOC
KW  - Yields
KW  - CIMMYT
N2  - A historical dataset (soil water content; growth, phenology, yield) for six cultivars and three planting dates was used to evaluate the CERES3 crop growth model. Linear regression and a correlation matrix were used to identify model algorithms in need of calibration. Results indicated that the model simulates yield and kernel number with low accuracy under local conditions. Ears per plant and water stress before and during silking were identified as factors that could explain the low accuracy.||'n Historiese datastel (grondwaterinhoud, groei,fenologie en opbrengs) bestaande uit 6 curtivars en 3 plantdatums is gebruik om die CERES3 gewasgroeimodel te evalueer. Met behulp van linére regressie en korrelasie matriks is algoritmes in die model geidentifiseer wat gekalibreer moet word. Die resultate toon aan dat die model graan opbrengs en pitmassa met lae akkuraatheid simuleer. Aantal koppe per plant en water stremming voor en gedurende blom is as faktore geidentifiseer wat die lae akkuraatheid vir beide pit aantal en opbrengs simulasie verklaar|
ER  -