02205nam a22003017a 4500003000400000005001700004008004100021022001400062040000900076082002400085100002700109130006700136245015400203300002200357336000900379337001600388338001200404440002100416500127800437650001701715650002101732650003501753650002101788650003301809700002201842700001601864700002301880OSt20250130094001.0250130b        |||||||| |||| 00| 0 eng d  a0119-7312  cDSSC  aPer/581.4/M319/2023  aManuel, Luther John R.  aPhilippine Journal of Agricultural and Biosystems Engineering   aEvaluation of a simulation model for deep-bed drying of hybrid rice seedscby Luther John R. Manuel, Joanne Foliente, Mengke Lu and Kevin F. Yaptenco  app. 17-34c23cm.   atext  aunmediated   avolume   v19(1)x0119-7312  aThis study evaluates a simulation model of drying hybrid rice seeds in deep-bed set-up. This model is based on a heterogenous diffusion model for predicting grain moisture at different levels on a deep-bed drying set-up was developed. To evaluate this, hybrid rice seeds were dried in a laboratory dryer with a 50-cm depth test cell. Three drying setups (45 C, 55 C, and stepwise) were used. During drying, moisture content was measured at different levels of cell and at specified time intervals. Around four months after storage, germination percentage of samples from different drying setting and grain locations were obtained. The drying experiment revealed that the fastest drying time is achieved with the 55 C drying temperature. Parameter estimation and model validation of the simulation have revealed that the model used can well predict the moisture  content of seeds across the deep-cell drying bin at any given time. This can be further supported by the mean relative error of the model which is below its acceptable values. Germination results have also shown that the drying procedures used have no negative effect on the seed quality. Thus, using simulation model could be an accurate way to predict the moisture content with no effect on its seed quality.  0ahybrid rice  0adeep-bed drying  0aheterogeneous diffusion model  0agermination test 0avariable temperature drying   aFoliente, Joanne   aLu, Mengke   aYaptenco, Kevin F.