On Farm In Bin Drying and Storage of Rough Rice. Griffiths G. Atungulu, PhD

Transcription

1 On Farm In Bin Drying and Storage of Rough Rice Griffiths G. Atungulu, PhD

2 On-farm NA drying bins with Cables 18% Green Rice (Wet) 66 Weather Station Communication System 16% Drying Zone 71 13% 75 Dry Rice MC cable Temp. Cable Fan Control System

3 weather conditions may lead to slower drying of high MC grain, especially at the top layer of the bin, leading to mold growth and mycotoxin (e.g. aflatoxin) development in grain mass. Some mycotoxins are carcinogenic and known to poses a severe health hazard to human and animal consumers of grains and co products

4 .besides the problem of aflatoxin, deterioration of nutritional, functional and sensory quality may ensue as well.

5 Settling scores birth pangs since the cabling systems are still new among most rice producers when issues of grain quality occurs it is very natural to point fingers.in most cases malfunctions may well be due to not obeying recommendable operation procedures other malfunctioning issues are clearly still due to unknowns and debatable: e.g. issues with rice staining (heat related, mold related, and if mold what type?)

6 Objectives Perform field based experiments to verify accuracy of field data of rough rice moisture content (MC) and temperature profiles during natural air (NA) in bin drying and storage of rough rice

7 Methods Accurate equations for establishing rice EMC isotherms [separate adsorption and desorption constant] Mathematical modeling and simulations to predict rice MC and temperature profiles and compare with actual field sensor data [Bin C & Bin D] Bin A North Center South 4 feet Bins B, C, & D Field sensor data of in bin, rice MC vs. lab oven measured rice MC data comparison [Bin A &Bin B]

8 Bin Configurations in Simulations Bin C Bin D Bin Location Dermott, Ark. Dermott, Ark. Bin Diameter m (48 ft) m (48 ft) The Top most Sensor Depth Fan Configuration Center: 7.32 m (24 ft) Side: 6.1 m (20 ft) 30 HP 1750 RPM centrifugal fan; 2 fans in parallel Center: 7.32 m (24 ft) Side: 6.1 m (20 ft) 30 HP 1750 RPM centrifugal fan; 2 fans in parallel Fan Control Strategy EMC NA EMC NA Target EMC 12.5% (w.b.) 12.5% (w.b.) Targeted EMC Range 13.5% 10.5% (w.b.) 14.5% 10.5% (w.b.) Simulation start Date and Time 26 Sept at 12:00 AM 03 Oct at 4:00 AM Simulation end Date and Time 21 Oct at 11:59 PM 27 Oct at 11:59 PM

9 Statistics and Definitions Experiments to determine EMC constants were triplicated Statistical analysis : JMP ANOVA (α = 0.05) Nonlinear regression Root mean square error (RMSE) measure of the differences between simulated and measured data = Microsoft Excel 2013 was used to calculate of RMSE, Nash Sutcliffe efficiency (NSE) and Percent bias (PBIAS)

10 Statistical analyses and Definition Percent bias (PBIAS) measures the average tendency of the simulated data to be larger or smaller than their observed counterparts (%) Nash Sutcliffe efficiency (NSE) determines the relative magnitude of the residual variance compared to the measured data variance ( to 1) = ( ) =

11 Oven vs. Field Sensor Determined MCs Bin location Bin A (Dermott, Ark.) Bin B (Burdette, Ark.) Sampling Date (dd/mm/yyyy) In bin Sensordetermined MC data (%w.b.) Ovenmeasured MC (%w.b.) 12/10/ /10/ /11/ /11/ /09/ /09/ /10/ /10/ RMSE (%w.b.) PBIAS (%)

12 Simulations and Field Sensor MCs (Bins located at Dermott, Arkansas) Bin D sensor determined MC vs. simulated MC Moisture Content (%w.b.) /10/2014 8/10/ /10/ /10/ /10/ /10/2014 S1 S2 S3 S4 S5 S6 Layer1 Layer2 Layer3 Layer4 Layer5 Layer6

13 Simulation vs. Field Sensor MCs Bin C Layer Mean RMSE (% w.b. C) ±0.29 * NSE ±0.23 * PBIAS (%) ±2.00 Bin D Layer Mean RMSE (% w.b.mc) ±0.10 * NSE ±0.50 * PBIAS (%) ±0.97 * Numbers represent the mean and the standard deviation. Numbers represent the mean and the standard deviation of the absolute value of the PBIAS (mean absolute PBIAS = )

14 Simulation vs. Field Sensor Temperatures (Bin Located at Dermott, Arkansas) Temperature ( C) Bin D sensor recorded temperature vs. simulated temperature 9 3/10/2014 8/10/ /10/ /10/ /10/ /10/2014 S1 S2 S3 S4 S5 S6 Layer1 Layer2 Layer3 Layer4 Layer5 Layer6

15 Simulation vs. Field Sensor Temperatures Bin C Layer Mean RMSE ( C) ±0.11* NSE ±0.03* PBIAS (%) ±1.21 Bin D Layer Mean RMSE ( C) ±0.21* NSE ±0.04* PBIAS (%) ±0.69 * Numbers represent the mean and the standard deviation. Numbers represent the mean and the standard deviation of the absolute value of the PBIAS (mean absolute PBIAS = )

16 Concluding remarks Statistical parameters (RMSE, NSE, and PBIAS) indicated that the simulated rough rice MC and temperature profiles predicted well the rough rice temperature and MC data, determined using field sensors. Generally, the field installed sensor agreed with simulated and lab oven determined MCs

17 Guidelines for rice on farm drying Drying duration 30 days Maximum DML 0.5% Percent over drying 10% Air Flowrate, m 3 min-t -1 (cfm bu -1 ) The green squares represent the suitable drying operation range. The red squares represent the unsuitable drying operation range.

18 Acknowledgments Arkansas Rice Research and Promotion Board University of Arkansas Division of Agriculture University of Arkansas Rice & Grain Processing Programs Arkansas Rice Producers

19 Thank you!