Modelling Specific Energy Requirement for a Power-Operated Vertical Axis Rotor Type Intra-Row Weeding Tool Using Artificial Neural Network

dc.contributor.authorKumar, Satya Prakashen
dc.contributor.authorTewari, V. K.en
dc.contributor.authorChandel, Abhilash Kumaren
dc.contributor.authorMehta, C. R.en
dc.contributor.authorPareek, C. M.en
dc.contributor.authorChethan, C. R.en
dc.contributor.authorNare, Brajeshen
dc.date.accessioned2023-09-27T14:47:29Zen
dc.date.available2023-09-27T14:47:29Zen
dc.date.issued2023-09-07en
dc.date.updated2023-09-27T12:36:19Zen
dc.description.abstractSpecific energy prediction is critically important to enhance field performance of agricultural implements. It enables optimal utilization of tractor power, reduced inefficiencies, and identification of comprehensive inputs for designing energy-efficient implements. In this study, A 3-5-1 artificial neural network (ANN) model was developed to estimate specific energy requirement of a vertical axis rotor type intra-row weeding tool. The depth of operation in soil bed, soil cone index, and forward/implement speed ratio (<i>u</i>/<i>v</i>) were selected as the input variables. Soil bin investigations were conducted using the vertical axis rotor (R<sub>VA</sub>), interfaced with draft, torque, speed sensors, and data acquisition system to record dynamic forces employed during soil&ndash;tool interaction at ranges of different operating parameters. The depth of operation (DO) had the maximum influence on the specific energy requirement of the R<sub>VA</sub>, followed by the cone index (CI) and the <i>u</i>/<i>v</i> ratio. The developed ANN model was able to predict the specific energy requirements of R<sub>VA</sub> at high accuracies as indicated by high R<sup>2</sup> (0.91), low RMSE (0.0197) and low MAE (0.0479). Findings highlight the potential of the ANN as an efficient technique for modeling soil&ndash;tool interactions under specific experimental conditions. Such estimations will eventually optimize and enhance the performance efficiency of agricultural implements in the field.en
dc.description.versionPublished versionen
dc.format.mimetypeapplication/pdfen
dc.identifier.citationKumar, S.P.; Tewari, V.K.; Chandel, A.K.; Mehta, C.R.; Pareek, C.M.; Chethan, C.R.; Nare, B. Modelling Specific Energy Requirement for a Power-Operated Vertical Axis Rotor Type Intra-Row Weeding Tool Using Artificial Neural Network. Appl. Sci. 2023, 13, 10084.en
dc.identifier.doihttps://doi.org/10.3390/app131810084en
dc.identifier.urihttp://hdl.handle.net/10919/116362en
dc.language.isoenen
dc.publisherMDPIen
dc.rightsCreative Commons Attribution 4.0 Internationalen
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/en
dc.titleModelling Specific Energy Requirement for a Power-Operated Vertical Axis Rotor Type Intra-Row Weeding Tool Using Artificial Neural Networken
dc.title.serialApplied Sciencesen
dc.typeArticle - Refereeden
dc.type.dcmitypeTexten
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