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dc.contributor.author
Taher, Hernán Ignacio
dc.contributor.author
Urcola, Hernan Alejandro
dc.contributor.author
Cendoya, María Gabriela
dc.contributor.author
Bartosik, Ricardo
dc.date.available
2021-01-05T18:17:51Z
dc.date.issued
2019-01
dc.identifier.citation
Taher, Hernán Ignacio; Urcola, Hernan Alejandro; Cendoya, María Gabriela; Bartosik, Ricardo; Predicting soybean losses using carbon dioxide monitoring during storage in silo bags; Pergamon-Elsevier Science Ltd; Journal of Stored Products Research; 82; 1-2019; 1-8
dc.identifier.issn
0022-474X
dc.identifier.uri
http://hdl.handle.net/11336/121520
dc.description.abstract
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 Mayto 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.
dc.format
application/pdf
dc.language.iso
eng
dc.publisher
Pergamon-Elsevier Science Ltd
dc.rights
info:eu-repo/semantics/restrictedAccess
dc.rights.uri
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
dc.subject
CO2
dc.subject
Soybean
dc.subject
Preventing monitoring
dc.subject
Losses prediction
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Hermetic storage
dc.subject.classification
Agricultura
dc.subject.classification
Agricultura, Silvicultura y Pesca
dc.subject.classification
CIENCIAS AGRÍCOLAS
dc.title
Predicting soybean losses using carbon dioxide monitoring during storage in silo bags
dc.type
info:eu-repo/semantics/article
dc.type
info:ar-repo/semantics/artículo
dc.type
info:eu-repo/semantics/publishedVersion
dc.date.updated
2020-11-18T16:44:10Z
dc.journal.volume
82
dc.journal.pagination
1-8
dc.journal.pais
Estados Unidos
dc.journal.ciudad
Amsterdam
dc.description.fil
Fil: Taher, Hernán Ignacio. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Mar del Plata; Argentina. Instituto Nacional de Tecnología Agropecuaria; Argentina
dc.description.fil
Fil: Urcola, Hernan Alejandro. Instituto Nacional de Tecnología Agropecuaria. Centro Regional Buenos Aires Sur. Estación Experimental Agropecuaria Balcarce. Área de Investigación en Agronomía; Argentina
dc.description.fil
Fil: Cendoya, María Gabriela. Universidad Nacional de Mar del Plata; Argentina
dc.description.fil
Fil: Bartosik, Ricardo. Instituto Nacional de Tecnología Agropecuaria. Centro Regional Buenos Aires Sur. Estación Experimental Agropecuaria Balcarce. Área de Investigación en Agronomía; Argentina
dc.journal.title
Journal of Stored Products Research
dc.relation.alternativeid
info:eu-repo/semantics/altIdentifier/url/https://www.sciencedirect.com/science/article/abs/pii/S0022474X18303916?via%3Dihub
dc.relation.alternativeid
info:eu-repo/semantics/altIdentifier/doi/https://doi.org/10.1016/j.jspr.2019.03.002
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