Regression modeling of growth indices of Lentil affected by Bio-fertilizers with Superabsorbent polymer

Analyzing growth is a precious method to analyze the quantity of growth, development and production of crops. To study the physiological growth indices of Lentil under rain fed conditions, a factorial test in the randomized complete block formation with 3 replications was inducted in 2010 in the Agricultural Research Station located in the city of Khorramabad, Lorestan University, Iran. In this Study eight biological fertilizer treatment with Superabsorbent polymer were tested over two cultivars of the lentil plant. The tested factors included 8 levels of fertilizer compounds with the Superabsorbent polymer (?1:Control,B2:Mycorrhiza bio-fertilizer,B3: Azotobacter bio-fertilizer, B4: Superabsorbent polymer, B5: Mycorrhiza bio-fertilizer + Superabsorbent polymer,B6: Azotobacter bio-fertilizer + Superabsorbent polymer,B7: Mycorrhiza bio-fertilizer + Azotobacter bio-fertilizer + Superabsorbent polymer, B8: Mycorrhiza bio-fertilizer + Azotobacter bio-fertilizer) and two cultivars (Gachsaran: C1 and Phillip: C2). In order to have a 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. The results of analyzing the growth indices show the B6 treatment in indices such as leaf area and product growth rate and also dry material accumulation was better than the other treatments. Among the other growth indices no significant difference was observed between treatments. According to the achieved results it was determined that Azotobacter and Superabsorbent polymer were more effective than the Mycorrhiza bio-fertilizer over the growth indices analyzed in this study.