Growth patterns of cotton (Gossypium hirsutum) plant parts and some physiological parameters
1994
Tallon, R.B. | Barroga, M.E. | Cosico, V.B. (Cotton Research and Development Inst., Batac, Ilocos Norte (Philippines). Research Utilization Div.)
The study was conducted at the Cotton Research and Development Inst., Central Experiment Station, Batac, Ilocos Norte [Philippines] from December, 1993 to April 1991. The study determined some developmental growth patterns and the statistical regression and correlation tools applicable for the growth models. The basic criterion in the selection of the model plant was on the seedcotton yield. Critical yield level was set at 3 tons per hectare. Plant spaced at 75 cm between rows and 30 cm between hills applied with 225-25-0 kg/ha N-P2O5-K2O produced 3.6 tons per hectare, hence its growth and developmental patterns were analyzed to describe the empirical growth equation models. The pattern for plant height, total dry matter yield per plant, dry matter yield of vegetative parts and LAI [leaf area index] were best fitted to the logistic growth curve regression model as the sigmoidal curve. A logarithmic regression model described the increase in the number of main stem nodes, number of sympodial branches, net assimilation rate, number of fruiting points and number of bolls per plant. Meanwhile a second-degree regression model (quadratic) described the growth pattern of the total leaf area, number of main stem leaves, crop growth rate and the number of squares per plant. A power regression model described the dry matter accumulation of the reproductive parts while R:V ratio was best fitted to an exponential regression model. It is to be highlighted though, that interpretations of the results particularly the derived equations are limited to some agroclimatic conditions specially at Batac, Ilocos Norte. Nonetheless, the growth and developmental patterns of the plant parameters against plant age are maintained irrespective of location or treatments. Hence, the identified regression and correlation models can be applied to analyze, prepare and establish field monitoring growth models for the crop in the different representative agroclimatic conditions in cotton-growing areas of the country
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