Optimization of Processing Parameters of Soybean Seeds Dried in a Constant-bed Dryer Using Response Surface Methodology

In some conditions, to avoid deterioration and field losses of soybean seeds (Glycine max Merr.) from weathering at end of the season, farmers start to harvest seeds with a high moisture content and so, careful post-harvest drying would be required to maintain the physiological quality of seeds. Response Surface Methodology (RSM) was used to optimize the operating conditions of soybean seed drying. The study was performed using a three-level, four-factor fractional factorial design and aimed at determining the optimum combination of initial moisture content (X1), drying air temperature (X2), air velocity (X3), and depth of loading (X4) that could result in high germination, vigor and field emergence. The seeds of two soybean cultivars (Clark and Sahar) with initial moisture content of 15 to 45% dry weight basis )d.w.b), were dried in different drying air temperatures from 35 to 55°C, air velocity ranging from 0.5 to 1.5 m s-1 and a loading depth of 0.5 to 10 cm. According to the results of germination and vigor tests, the optimum drying conditions for seeds of cv. Clark were obtained at an air temperature of 52ºC, which needs to be decreased with higher initial moisture content. Harvesting can start at about 30% d.w.b initial seed moisture content, if drying is done carefully, but cv. Sahar was more susceptible and the drying air temperature should not exceed 41ºC and harvesting should take place when seeds reach an initial moisture content of below 32%. Moreover, it is strongly recommended to use moderate depths of loading because of best aeration and air circulation and to avoid overdrying. The seed quality indices in this experiment were more sensitive to both air temperature and initial moisture content than air velocity and depth of loading.

Optimization of Processing Parameters of Soybean Seeds Dried in a Constant-bed Dryer Using Response Surface Methodology Keywords:

Germination , Drying , Response surface methodology , Seed quality