Evaluating dry matter loss rates of 14 to 22% moisture content soybeans at 35°C using a dynamic grain respiration measurement system

Soybeans are biologically active after harvest, continuing to respire during storage and processing. Soybean respiration rate (v_(〖CO〗_2 )) and, thus, dry matter loss rate (v_DML) are affected by moisture content (w) and temperature (T). Knowledge of v_(〖CO〗_2 ) or v_DML is useful in developing maxi...

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Main Author: Trevisan, Lucas Renato
Other Authors: Gates, Richard S, Danao, Mary-Grace C, Rausch, Kent D
Format: Text
Language:English
Published: 2017
Subjects:
DML
Online Access:http://hdl.handle.net/2142/99429
id ftunivillidea:oai:www.ideals.illinois.edu:2142/99429
record_format openpolar
spelling ftunivillidea:oai:www.ideals.illinois.edu:2142/99429 2023-05-15T16:01:57+02:00 Evaluating dry matter loss rates of 14 to 22% moisture content soybeans at 35°C using a dynamic grain respiration measurement system Trevisan, Lucas Renato Gates, Richard S Danao, Mary-Grace C Rausch, Kent D 2017-12 application/pdf http://hdl.handle.net/2142/99429 en eng http://hdl.handle.net/2142/99429 Copyright 2017 Lucas Renato Trevisan Carbon dioxide Grain storage Storage time Grain deterioration Post-harvest loss Dry matter loss Text 2017 ftunivillidea 2018-07-07T22:30:44Z Soybeans are biologically active after harvest, continuing to respire during storage and processing. Soybean respiration rate (v_(〖CO〗_2 )) and, thus, dry matter loss rate (v_DML) are affected by moisture content (w) and temperature (T). Knowledge of v_(〖CO〗_2 ) or v_DML is useful in developing maximum allowable storage time (MAST) guidelines for soybeans, which are currently sorely lacking for high w and T storage conditions. Therefore, in this study, v_(〖CO〗_2 ) and v_DML were measured for soybeans at a wide range of w (14 to 22 %) stored at 35°C. A dynamic grain respiration measurement system (D-GRMS) was used to measure grain deterioration rates of 14 to 22 % moisture content soybeans stored at 35ºC. Results showed that the pooled dry matter loss rates, (v_DML±〖SE〗_(v_DML ) )_p were 0.128 ± 0.001, 0.250 ± 0.004, and 0.253 ± 0.005 % d-1 for 14, 18, and 22 % moisture content soybeans, respectively. These corresponded to pooled respiration rates, (v_(〖CO〗_2 )±〖SE〗_(v_(〖CO〗_2 ) ) )_p of 1.879 ± 0.028, 3.664 ± 0.064, and 3.708 ± 0.068 mg CO2 (kg d)-1, respectively. The time to reach 0.5% DML, t_0.5±σ_(t_0.5 ), were also highly variable at 8.32 ± 2.89, 5.88 ± 1.47, and 3.83 ± 0.54 d for 14, 18, and 22 % moisture content soybeans, respectively, due to variable lag times before 0.05 % DML was reached. Using a minimum significant difference to be detected of δ=4(v_DML )_p of 0.0032 % d-1 from respiration tests with 18 % moisture content soybeans, a statistical power analysis showed that a minimum of four replications was needed for a 3w x 1T factorial experiment. The analysis of variance (ANOVA) results, however, showed that across the w tested, the minimum significant difference between treatments was δ = 0.066 % d-1 and a minimum of one replication was needed. It is recommended that future soybean respiration experiments proceed with at least four replications. The effects of w on v_DML were best described with an exponential question [v_DML=β_1 exp⁡(β_2 w)] with a mean relative error, MRE = 0.15 % d-1; standard error of regression, 〖SE〗_reg=0.02 % d-1; F-statistic = 149.18, and an estimated coefficient of determination, R^2= 0.97. The D-GRMS, protocols, and statistical analyses of grain deterioration parameters presented in this study are useful for conducting robust grain respiration measurements in the future towards building a set of MAST guidelines for soybeans and other cereal or oilseed commodities. Text DML University of Illinois at Urbana-Champaign: IDEALS (Illinois Digital Environment for Access to Learning and Scholarship)
institution Open Polar
collection University of Illinois at Urbana-Champaign: IDEALS (Illinois Digital Environment for Access to Learning and Scholarship)
op_collection_id ftunivillidea
language English
topic Carbon dioxide
Grain storage
Storage time
Grain deterioration
Post-harvest loss
Dry matter loss
spellingShingle Carbon dioxide
Grain storage
Storage time
Grain deterioration
Post-harvest loss
Dry matter loss
Trevisan, Lucas Renato
Evaluating dry matter loss rates of 14 to 22% moisture content soybeans at 35°C using a dynamic grain respiration measurement system
topic_facet Carbon dioxide
Grain storage
Storage time
Grain deterioration
Post-harvest loss
Dry matter loss
description Soybeans are biologically active after harvest, continuing to respire during storage and processing. Soybean respiration rate (v_(〖CO〗_2 )) and, thus, dry matter loss rate (v_DML) are affected by moisture content (w) and temperature (T). Knowledge of v_(〖CO〗_2 ) or v_DML is useful in developing maximum allowable storage time (MAST) guidelines for soybeans, which are currently sorely lacking for high w and T storage conditions. Therefore, in this study, v_(〖CO〗_2 ) and v_DML were measured for soybeans at a wide range of w (14 to 22 %) stored at 35°C. A dynamic grain respiration measurement system (D-GRMS) was used to measure grain deterioration rates of 14 to 22 % moisture content soybeans stored at 35ºC. Results showed that the pooled dry matter loss rates, (v_DML±〖SE〗_(v_DML ) )_p were 0.128 ± 0.001, 0.250 ± 0.004, and 0.253 ± 0.005 % d-1 for 14, 18, and 22 % moisture content soybeans, respectively. These corresponded to pooled respiration rates, (v_(〖CO〗_2 )±〖SE〗_(v_(〖CO〗_2 ) ) )_p of 1.879 ± 0.028, 3.664 ± 0.064, and 3.708 ± 0.068 mg CO2 (kg d)-1, respectively. The time to reach 0.5% DML, t_0.5±σ_(t_0.5 ), were also highly variable at 8.32 ± 2.89, 5.88 ± 1.47, and 3.83 ± 0.54 d for 14, 18, and 22 % moisture content soybeans, respectively, due to variable lag times before 0.05 % DML was reached. Using a minimum significant difference to be detected of δ=4(v_DML )_p of 0.0032 % d-1 from respiration tests with 18 % moisture content soybeans, a statistical power analysis showed that a minimum of four replications was needed for a 3w x 1T factorial experiment. The analysis of variance (ANOVA) results, however, showed that across the w tested, the minimum significant difference between treatments was δ = 0.066 % d-1 and a minimum of one replication was needed. It is recommended that future soybean respiration experiments proceed with at least four replications. The effects of w on v_DML were best described with an exponential question [v_DML=β_1 exp⁡(β_2 w)] with a mean relative error, MRE = 0.15 % d-1; standard error of regression, 〖SE〗_reg=0.02 % d-1; F-statistic = 149.18, and an estimated coefficient of determination, R^2= 0.97. The D-GRMS, protocols, and statistical analyses of grain deterioration parameters presented in this study are useful for conducting robust grain respiration measurements in the future towards building a set of MAST guidelines for soybeans and other cereal or oilseed commodities.
author2 Gates, Richard S
Danao, Mary-Grace C
Rausch, Kent D
format Text
author Trevisan, Lucas Renato
author_facet Trevisan, Lucas Renato
author_sort Trevisan, Lucas Renato
title Evaluating dry matter loss rates of 14 to 22% moisture content soybeans at 35°C using a dynamic grain respiration measurement system
title_short Evaluating dry matter loss rates of 14 to 22% moisture content soybeans at 35°C using a dynamic grain respiration measurement system
title_full Evaluating dry matter loss rates of 14 to 22% moisture content soybeans at 35°C using a dynamic grain respiration measurement system
title_fullStr Evaluating dry matter loss rates of 14 to 22% moisture content soybeans at 35°C using a dynamic grain respiration measurement system
title_full_unstemmed Evaluating dry matter loss rates of 14 to 22% moisture content soybeans at 35°C using a dynamic grain respiration measurement system
title_sort evaluating dry matter loss rates of 14 to 22% moisture content soybeans at 35°c using a dynamic grain respiration measurement system
publishDate 2017
url http://hdl.handle.net/2142/99429
genre DML
genre_facet DML
op_relation http://hdl.handle.net/2142/99429
op_rights Copyright 2017 Lucas Renato Trevisan
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