• Title of article

    Analysis of Safflower leaf growth indices using regression modeling

  • Author/Authors

    HASANVANDI، Mohammad Saeed نويسنده Department of Agronomy , , BAGHERI، Azimeh نويسنده Department of Agronomy ,

  • Issue Information
    روزنامه با شماره پیاپی 0 سال 2013
  • Pages
    9
  • From page
    2752
  • To page
    2760
  • Abstract
    ABSTRACT:Identification and study of physiological indices of growth plays very important role in analysis of factors influencing the yield and yield components. In order to study the effect of nitrogen fertilizer and plant density on most important physiologic indices of safflower growth (cultivar IL 111), an experiment was performed with split plots based on randomized complete block design with four replicates in crop year 2006-2007. Treatments included nitrogen fertilizer as the main factor with three levels (N1=0, N2=75 and N3=75 kg net nitrogen/ha) and plant density as sub factor with three levels (D1=40, D2=50 and D3=60 plant/m2). In order to have more accurate study, Growing Degree Day (GDD) index was used for fitting growth curves, and then appropriate model was selected for each growth index using non-linear regression models. Results of studying the growth index showed that nitrogen application increased the indices such as leaf area, leaf area ratio and specific leaf area, and leaf area duration, but reduced the specific leaf weight. No significant change was observed in indices such as leaf area index, and leaf area ratio, leaf weight with increasing in plant density due to branching property of safflower, but a decreasing and an increasing was found in leaf area duration and specific leaf weight, respectively. It can be stated that according to overall results, nitrogen application has more impact on leaf growth indices of safflower than plant density variations.
  • Journal title
    International Journal of Agriculture and Crop Sciences(IJACS)
  • Serial Year
    2013
  • Journal title
    International Journal of Agriculture and Crop Sciences(IJACS)
  • Record number

    941740