عنوان مقاله [English]
نویسندگان [English]چکیده [English]
An analysis of the stages of crop growth presents an important step in the improvement of production management. Through growth analysis, planning for planting systems, fertilization, pruning operations, harvest time as well as obtaining economical yield can be more accessible. Therefore, a development of mathematical models simulating plant growth would be helpful in improving crop management, particularly fruit growth. In the present study, in addition to linear model, six nonlinear growth models as well as a linearized biexponential (LinBiExp) model were employed to make modelings of the inherent growth pattern of ‘Red Spur’ apple fruit based on the measured parameters of fruit length, diameter and volume. The parameters were estimated using the Marquardt iterative method of nonlinear regression. A selection of the most appropriate model calls for the use of such quantitative model selection criteria, as r2, partial F-test, the Akaike information criterion as well as the Schwarz Bayesian information criterion. Throughout the study, it was found that the LinBiExp model was a more suitable one than the other nonlinear growth models as regards fitting the apple growth data attained from the assessed dimensional traits. Moreover, a study of the effect of crop yield on the fruit growth pattern revealed that the final fruit size was in direct relationship with the growth rate in the linear portion. A high crop yield trial led to a decrease in the linear growth rate portion, resulting in smaller size fruits at harvest.