Predicting soybean losses using carbon dioxide monitoring during storage in silo bags

The rapid increase of the overall grain production of Argentina resulted with a storage capacity deficit in permanent structures of 40–50 million tons, and this context favored the rapid adoption of the silo bag technology. Silo bag allows differing grain selling from harvest time, taking advantage...

Full description

Bibliographic Details
Main Authors: Taher, Hernán Ignacio, Urcola, Hernan Alejandro, Cendoya, Maria Gabriela, Bartosik, Ricardo Enrique
Format: info:ar-repo/semantics/artículo
Language:Inglés
Published: Elsevier 2019
Subjects:
Online Access:https://www.sciencedirect.com/science/article/pii/S0022474X18303916
http://hdl.handle.net/20.500.12123/4903
https://doi.org/10.1016/j.jspr.2019.03.002
_version_ 1855035404184453120
author Taher, Hernán Ignacio
Urcola, Hernan Alejandro
Cendoya, Maria Gabriela
Bartosik, Ricardo Enrique
author_browse Bartosik, Ricardo Enrique
Cendoya, Maria Gabriela
Taher, Hernán Ignacio
Urcola, Hernan Alejandro
author_facet Taher, Hernán Ignacio
Urcola, Hernan Alejandro
Cendoya, Maria Gabriela
Bartosik, Ricardo Enrique
author_sort Taher, Hernán Ignacio
collection INTA Digital
description The rapid increase of the overall grain production of Argentina resulted with a storage capacity deficit in permanent structures of 40–50 million tons, and this context favored the rapid adoption of the silo bag technology. Silo bag allows differing grain selling from harvest time, taking advantage of the seasonal price changes and, hence, improving farmers’ income. However, storing grain in silo bag could be risky if inadequate planning, handling or monitoring is implemented. Thus, the objective of this article was to develop a prediction model for soybean losses in silo bag storage based on monitoring CO2 concentration and other sensible variables. During 2013, an experiment was conducted in 13 soybean silo bags placed at farms and grain elevators in Balcarce area, South East of Buenos Aires province, Argentina, since May to December. Grain samples were collected and grain quality was evaluated. Storage variables, such as moisture content and interstitial atmosphere gas composition were also recorded, and at the end of storage, physical grain losses were quantified for each silo bag (kg of spoiled grain not commercialized). The results showed that there was not generalized quality loss in any silo bag, but localized losses were observed. These losses occurred due to water entrance in the silo bag through openings which resulted in spoiled grain from 140 to 4320 kg, representing from 0.07% to 2.16% in a 200 ton silo bag. Next, a correlation to predict grain losses was developed, which considered grain moisture and a predictor related to the CO2 concentration at the silo bag closing end as independent variables. This correlation explained 73% of the grain losses variability, allowed to model different levels of losses, and was consistent with biological concepts.
format info:ar-repo/semantics/artículo
id INTA4903
institution Instituto Nacional de Tecnología Agropecuaria (INTA -Argentina)
language Inglés
publishDate 2019
publishDateRange 2019
publishDateSort 2019
publisher Elsevier
publisherStr Elsevier
record_format dspace
spelling INTA49032019-04-15T13:38:52Z Predicting soybean losses using carbon dioxide monitoring during storage in silo bags Taher, Hernán Ignacio Urcola, Hernan Alejandro Cendoya, Maria Gabriela Bartosik, Ricardo Enrique Soja Vigilancia Almacenamiento Atmósfera Controlada Soybeans Monitoring Controlled Atmosphere Storage Carbon Dioxide Storage Losses Dióxido de Carbono Pérdidas por Almacenamiento Silo-bolsa The rapid increase of the overall grain production of Argentina resulted with a storage capacity deficit in permanent structures of 40–50 million tons, and this context favored the rapid adoption of the silo bag technology. Silo bag allows differing grain selling from harvest time, taking advantage of the seasonal price changes and, hence, improving farmers’ income. However, storing grain in silo bag could be risky if inadequate planning, handling or monitoring is implemented. Thus, the objective of this article was to develop a prediction model for soybean losses in silo bag storage based on monitoring CO2 concentration and other sensible variables. During 2013, an experiment was conducted in 13 soybean silo bags placed at farms and grain elevators in Balcarce area, South East of Buenos Aires province, Argentina, since May to December. Grain samples were collected and grain quality was evaluated. Storage variables, such as moisture content and interstitial atmosphere gas composition were also recorded, and at the end of storage, physical grain losses were quantified for each silo bag (kg of spoiled grain not commercialized). The results showed that there was not generalized quality loss in any silo bag, but localized losses were observed. These losses occurred due to water entrance in the silo bag through openings which resulted in spoiled grain from 140 to 4320 kg, representing from 0.07% to 2.16% in a 200 ton silo bag. Next, a correlation to predict grain losses was developed, which considered grain moisture and a predictor related to the CO2 concentration at the silo bag closing end as independent variables. This correlation explained 73% of the grain losses variability, allowed to model different levels of losses, and was consistent with biological concepts. EEA Balcarce Fil: Taher, Hernán Ignacio. Universidad Nacional de Mar del Plata. Facultad de Ciencias Agrarias; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina Fil: Urcola, Hernán Alejandro. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Balcarce, Argentina Fil: Cendoya, María Gabriela. Universidad Nacional de Mar del Plata. Facultad de Ciencias Agrarias; Argentina Fil: Bartosik, Ricardo Enrique. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Balcarce, Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina 2019-04-15T13:33:08Z 2019-04-15T13:33:08Z 2019-06 info:ar-repo/semantics/artículo info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion https://www.sciencedirect.com/science/article/pii/S0022474X18303916 http://hdl.handle.net/20.500.12123/4903 0022-474X https://doi.org/10.1016/j.jspr.2019.03.002 eng info:eu-repo/semantics/restrictedAccess application/pdf Elsevier Journal of Stored Products Research 82 : 1-8 (2019)
spellingShingle Soja
Vigilancia
Almacenamiento Atmósfera Controlada
Soybeans
Monitoring
Controlled Atmosphere Storage
Carbon Dioxide
Storage Losses
Dióxido de Carbono
Pérdidas por Almacenamiento
Silo-bolsa
Taher, Hernán Ignacio
Urcola, Hernan Alejandro
Cendoya, Maria Gabriela
Bartosik, Ricardo Enrique
Predicting soybean losses using carbon dioxide monitoring during storage in silo bags
title Predicting soybean losses using carbon dioxide monitoring during storage in silo bags
title_full Predicting soybean losses using carbon dioxide monitoring during storage in silo bags
title_fullStr Predicting soybean losses using carbon dioxide monitoring during storage in silo bags
title_full_unstemmed Predicting soybean losses using carbon dioxide monitoring during storage in silo bags
title_short Predicting soybean losses using carbon dioxide monitoring during storage in silo bags
title_sort predicting soybean losses using carbon dioxide monitoring during storage in silo bags
topic Soja
Vigilancia
Almacenamiento Atmósfera Controlada
Soybeans
Monitoring
Controlled Atmosphere Storage
Carbon Dioxide
Storage Losses
Dióxido de Carbono
Pérdidas por Almacenamiento
Silo-bolsa
url https://www.sciencedirect.com/science/article/pii/S0022474X18303916
http://hdl.handle.net/20.500.12123/4903
https://doi.org/10.1016/j.jspr.2019.03.002
work_keys_str_mv AT taherhernanignacio predictingsoybeanlossesusingcarbondioxidemonitoringduringstorageinsilobags
AT urcolahernanalejandro predictingsoybeanlossesusingcarbondioxidemonitoringduringstorageinsilobags
AT cendoyamariagabriela predictingsoybeanlossesusingcarbondioxidemonitoringduringstorageinsilobags
AT bartosikricardoenrique predictingsoybeanlossesusingcarbondioxidemonitoringduringstorageinsilobags