Fertilizer Response of Traditional Rice Cultivars at Four Different Levels as Analyzed by Multi-Criteria Decision Making Model

Abstract

Aims: to understand the effect of various polygenic traits on grain yield of traditional rice cultivars at four different fertilizer levels namely no fertilizer, x ½ recommended dose (x ½ RD), recommended dose (RD) andx2 recommended dose (x 2 RD). Study Design: Randomized complete block design with four replicates. Place and Duration of Study: Faculty of Agriculture, University of Ruhuna, Mapalana, Sri Lanka from 2011 to 2013. Methodology: Germinated seeds were planted in rows with 15 cm X 20 cm spacing. Experiment was conducted with four replications according to the randomized complete block design and each replicate consisted of three lines. Twenty plants were included in to each line. Data were collected on plant height (cm), number of tillers/plant, number of fertile tillers/plant, panicle length (cm), panicle weight (g), number of spikelets/panicle, number of fertile spikelets/panicle, 100 grain weight (g) and yield/plant (g). Path analysis was conducted to measure the degree of association between variables (traits). Multi-criteria decision-making model was used to rank the studied traditional rice genotypes according to the measured various yield attributing traits and the degree of association of each trait on yield as described by path analysis. Total effects of Path analysis were used as criteria weights to quantify the variables (traits). Data matrix was multiplied by the criteria weight to obtain the relative distances and cumulative values of relative distances were used to calculate the ideal distances (Lp). Genotypes were ranked according to the ideal distances (Lp) to understand the effect of fertilizer on yield and yield attributing factors of traditional rice genotypes at each fertilizer level. This procedure was applied separately to all of the four fertilizer levels. Results: The effects of various yield attributing traits on grain yield/plant were varied with four different levels of fertilizer. The effect of plant height on yield/plant was decreased linearly with the increased fertilizer. The highest effect was recorded by the panicle weight (0.872) at X 2 RD. Plant height (0.215), number of fertile tillers/plant (0.864), panicle length (0.082), and number of fertile spikelets/panicle (0.870) recorded the highest effect on yield/plant at no fertilizer condition. Conclusion: It emphasized the less fertilizer response of traditional rice genotypes. Excess application of fertilizer badly decreased the effect of yield attributing factors on final yield. Multi-criteria decision making model can be utilized to rank traditional rice genotypes according to their performances at different fertilizer levels.