The Analysis of Topping Results of Faba Bean Varieties (Vicia faba L.) by Using Logistic Nonlinear Regression Model

Growth analysis is a valuable method to quantify crop growth, development and production. Because, parameters of nonlinear regression models have significant physiological meanings, it was decided to study the effect of topping and variety on crop growth indices by using a logistic nonlinear regression model in a factorial experiment, based on randomized complete block design with 3 replications, at the Research Farm of Gonbad University during 2014-2015. The first factor consisted of five faba bean verities (Zohreh, Shami, Sheshband, Sarazeri and Barkat) and the second factor of two levels, topping and control. Results showed that using this molel described well the variation pattern of dry matter accumulation and LAI by time. It was also revealel that the difference between verities for the time to reach maximum leaf area index and the time required to reach 50 percent of maximum dry matter were not significant. The effect of variety on leaf area index was significant at the 5% level. The maximum and minimum leaf area index, total dry matter and crop growth rate of Barkat, Zohre and the Saraziri were higher than Shami and Sheshband varieties, and thus this was resulted in higher yield. Leaf area index in all varieties was the critical leaf area index. The average critical leaf area index in varieties was 1.37. The maximum and minimum relative growth rate at the beginning of the growing season belonged to the Saraziri and Barkat with 0.066 and 0.055 g/g.day, respectively.