Modelling the influence of crop density and weather conditions on field drying characteristics of switchgrass and maize stover using random forest

dc.contributor.author Khanchi, Amit
dc.contributor.author Khanchi, Amit
dc.contributor.author Birrell, Stuart
dc.contributor.author Mitchell, Robert
dc.contributor.author Birrell, Stuart
dc.contributor.department Agricultural and Biosystems Engineering
dc.date 2019-12-02T22:26:26.000
dc.date.accessioned 2020-06-29T22:43:19Z
dc.date.available 2020-06-29T22:43:19Z
dc.date.issued 2018-05-01
dc.description.abstract <p>Field drying trials were conducted using both field baskets as well as grab sampling techniques to study drying behaviour of switchgrass and maize (corn) stover (CS). Environmental conditions such as hourly solar radiation, vapour pressure deficit (VPD), average wind speed, rainfall amount, harvesting method, and field operations such as swath density were used as variables for model development. A powerful classification-based algorithm, which uses a collection of decision trees called random forest (RF) was utilised to predict moisture content (MC) of switchgrass and CS on wet basis. RF predicted the MC of switchgrass and CS with a coefficient of determination of 0.77 and 0.79, respectively. Rainfall, hours after harvest, average change in solar radiation in past 12 h, average solar radiation in past 12 h, and swath density were found to be the important variables affecting the MC of CS. Drying CS in low density (LD) and medium density (MD) swaths facilitated quick drying even in moderate drying conditions. Rainfall events ranging from 1.5 to 7.5 mm were experienced during the switchgrass drying period which delayed crop drying by one day to several days depending on the weather conditions after rainfall. Several rewetting events were also observed due to dew at night which increased the MC in LD switchgrass and CS by 5–15%. The models developed in the current study will help in decision-making of switchgrass and CS collection after harvest, based on forecast weather conditions in lower Midwestern states.</p>
dc.description.comments <p>This article is published as Khanchi, Amit, Stuart Birrell, and Robert B. Mitchell. "Modelling the influence of crop density and weather conditions on field drying characteristics of switchgrass and maize stover using random forest." <em>Biosystems Engineering </em>169 (2018): 71-84. DOI: <a href="http://dx.doi.org/10.1016/j.biosystemseng.2018.02.002" target="_blank">10.1016/j.biosystemseng.2018.02.002</a>. Posted with permission.</p>
dc.format.mimetype application/pdf
dc.identifier archive/lib.dr.iastate.edu/abe_eng_pubs/872/
dc.identifier.articleid 2155
dc.identifier.contextkey 11660900
dc.identifier.s3bucket isulib-bepress-aws-west
dc.identifier.submissionpath abe_eng_pubs/872
dc.identifier.uri https://dr.lib.iastate.edu/handle/20.500.12876/1682
dc.language.iso en
dc.source.bitstream archive/lib.dr.iastate.edu/abe_eng_pubs/872/2018_Khanchi_ModelingInfluence.pdf|||Sat Jan 15 02:16:04 UTC 2022
dc.source.uri 10.1016/j.biosystemseng.2018.02.002
dc.subject.disciplines Agriculture
dc.subject.disciplines Agronomy and Crop Sciences
dc.subject.disciplines Bioresource and Agricultural Engineering
dc.subject.disciplines Environmental Indicators and Impact Assessment
dc.subject.keywords Field drying
dc.subject.keywords Random forest
dc.subject.keywords Switchgrass
dc.subject.keywords Weather forecasting
dc.subject.keywords Crop density
dc.subject.keywords Drying models
dc.title Modelling the influence of crop density and weather conditions on field drying characteristics of switchgrass and maize stover using random forest
dc.type article
dc.type.genre article
dspace.entity.type Publication
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relation.isOrgUnitOfPublication 8eb24241-0d92-4baf-ae75-08f716d30801
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