Evaluation of a simulation model for deep-bed drying of hybrid rice seeds (Record no. 8802)

MARC details
000 -LEADER
fixed length control field 02330nam a22003257a 4500
003 - CONTROL NUMBER IDENTIFIER
control field OSt
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20250130094001.0
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 250130b |||||||| |||| 00| 0 eng d
022 ## - INTERNATIONAL STANDARD SERIAL NUMBER
International Standard Serial Number 0119-7312
040 ## - CATALOGING SOURCE
Transcribing agency DSSC
082 ## - DEWEY DECIMAL CLASSIFICATION NUMBER
Classification number Per/581.4/M319/2023
100 ## - MAIN ENTRY--PERSONAL NAME
Personal name Manuel, Luther John R.
9 (RLIN) 12224
130 ## - MAIN ENTRY--UNIFORM TITLE
Uniform title Philippine Journal of Agricultural and Biosystems Engineering
9 (RLIN) 12184
245 ## - TITLE STATEMENT
Title Evaluation of a simulation model for deep-bed drying of hybrid rice seeds
Statement of responsibility, etc by Luther John R. Manuel, Joanne Foliente, Mengke Lu and Kevin F. Yaptenco
300 ## - PHYSICAL DESCRIPTION
Extent pp. 17-34
Dimensions 23cm.
336 ## - CONTENT TYPE
Content type term text
337 ## - MEDIA TYPE
Media type term unmediated
338 ## - CARRIER TYPE
Carrier type term volume
440 ## - SERIES STATEMENT/ADDED ENTRY--TITLE
Volume number/sequential designation 19(1)
International Standard Serial Number 0119-7312
500 ## - GENERAL NOTE
General note This 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.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element hybrid rice
9 (RLIN) 12434
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element deep-bed drying
9 (RLIN) 12435
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element heterogeneous diffusion model
9 (RLIN) 12436
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element germination test
9 (RLIN) 12437
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element variable temperature drying
9 (RLIN) 12438
700 ## - ADDED ENTRY--PERSONAL NAME
Personal name Foliente, Joanne
9 (RLIN) 12440
700 ## - ADDED ENTRY--PERSONAL NAME
Personal name Lu, Mengke
9 (RLIN) 12441
700 ## - ADDED ENTRY--PERSONAL NAME
Personal name Yaptenco, Kevin F.
9 (RLIN) 12330
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Source of classification or shelving scheme Dewey Decimal Classification
Koha item type Periodical Indexing
Holdings
Withdrawn status Lost status Source of classification or shelving scheme Damaged status Not for loan Home library Current library Date acquired Total Checkouts Full call number Date last seen Price effective from Koha item type
    Dewey Decimal Classification     DSSC LEARNING RESOURCE CENTER DSSC LEARNING RESOURCE CENTER 2025-01-30   Per/581.4/M319/2023 2025-01-30 2025-01-30 Periodical Indexing