Mold appearance and modeling on selected corn stover components during moisture sorption

2008 ◽  
Vol 99 (14) ◽  
pp. 6365-6371 ◽  
Author(s):  
C IGATHINATHANE ◽  
A WOMAC ◽  
L PORDESIMO ◽  
S SOKHANSANJ
2007 ◽  
Vol 50 (6) ◽  
pp. 2151-2160 ◽  
Author(s):  
C. Igathinathane ◽  
A. R. Womac ◽  
S. Sokhansanj ◽  
L. O. Pordesimo

2009 ◽  
Vol 25 (1) ◽  
pp. 65-73 ◽  
Author(s):  
C. Igathinathane ◽  
L. O. Pordesimo ◽  
A. R. Womac ◽  
S. Sokhansanj

2015 ◽  
Vol 33 (14) ◽  
pp. 1768-1778 ◽  
Author(s):  
Ian J. Bonner ◽  
David N. Thompson ◽  
Farzaneh Teymouri ◽  
Timothy Campbell ◽  
Bryan Bals ◽  
...  

2013 ◽  
Vol 2013 ◽  
pp. 1-12 ◽  
Author(s):  
C. Karunanithy ◽  
K. Muthukumarappan ◽  
A. Donepudi

Moisture content is an important feedstock quality in converting it into energy through biochemical or thermochemical platforms. Knowledge of moisture sorption relationship is useful in drying and storage to preserve the quality of feedstocks. Moisture sorption isotherms for potential feedstocks such as corn stover and big bluestem are missing. EMC values of corn stover and big bluestem were determined using static gravimetric technique with saturated salt solutions (ERH 0.12–0.89) at different temperatures (20, 30, and 40°C). Depending upon the ERH values, EMC values were ranged from 8.0 to 19.6 and 8.8 to 19.2% db for corn stover and big bluestem, respectively, and they followed typical type II isotherm found in food materials. Nonlinear regression was used to fit five commonly used three-parameter isotherm models (i.e., modified Oswin model, modified Halsey model, modified Chung-Pfost model, modified Henderson model, and the modified Guggenheim-Anderson-de Boer (GAB) model) to the experimental data. Modified Halsey emerged as the best model with highF-statistic andR2values with lowEmandEsand fairly random scattered residual plot for corn stover and big bluestem. These models can be used to predict the equilibrium moisture content of these feedstocks starting from harvesting, drying, preprocessing, transportation, storage, and conversion.


2017 ◽  
Vol 60 (4) ◽  
pp. 1015-1023 ◽  
Author(s):  
Oluwafemi A. Oyedeji ◽  
Shahab Sokhansanj ◽  
Erin Webb

Abstract. The moisture content of a maturing crop varies as the harvest season progresses. For crop residues such as corn stover, moisture content at the time of harvest can be as high as 75% (wet mass basis) to less than 20% depending on the geographic location (climate conditions) and stage of harvest. Biomass moisture content is critical for baling and extended storage. It is therefore essential to have an estimate of the quantities of corn stover available as wet or dry for various parts of the U.S. To this end, we analyzed hourly weather data (temperature, humidity, and rainfall) from the Typical Meteorological Year v.3 (TMY3) dataset developed by the National Renewable Energy Laboratory. A recently published set of equations for calculating the moisture content of stover as a function of hourly temperature, humidity, and rainfall were used. The annual start and end of corn grain harvest along with annual grain production (in bushels) for each state were extracted from USDA National Agricultural Statistics Service reports. Using these datasets and moisture sorption equations, the percentage of corn stover tonnage with moisture content less than 20%, between 20% and 40%, or greater than 40% was estimated from the length of time that the biomass was in these moisture content ranges. These calculations were carried out for several locations within each of the states for which TMY data were available. It was concluded that about 37.2% of corn stover is dry (<20% moisture content), whereas 36.5% is wet (>40% moisture content) nationwide. The remaining 27.0% of corn stover is between 20% and 40% moisture content. Keywords: Corn stover, Equilibrium moisture content, Field drying, Moisture content, Stover harvest, Typical Meteorological Year data.


2012 ◽  
Author(s):  
William Edwards ◽  
Chad Hart ◽  
Kelvin Leibold
Keyword(s):  

Crop Science ◽  
1976 ◽  
Vol 16 (4) ◽  
pp. 505-507
Author(s):  
W. C. Leask ◽  
T. B. Daynard
Keyword(s):  

2020 ◽  
Vol 204 ◽  
pp. 106407 ◽  
Author(s):  
Shengxin An ◽  
Wenzhi Li ◽  
Fengyang Xue ◽  
Xu Li ◽  
Ying Xia ◽  
...  

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