Specific energy requirements and soil pulverization of a combined tillage implement

Usaborisut, Prathuang; Prasertkan, Kittikhun

doi:10.1016/j.heliyon.2019.e02757

Cited by 24 publications

(9 citation statements)

References 14 publications

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“…Conservation tillage methods are based on a wide range of interventions [21][22][23][24], that contribute to preserving soil fertility through the reduction of the number of machine passes and of working depth, such as the soil tillage without inversion of the layers [25] and the contemporary superficial secondary tillage, by means of combined implements [26], and the minimum tillage, with cultivators and disk harrows [27]. These machines perform soil fragmentation by absorbing only the tractor drawbar power.…”

Section: Introductionmentioning

confidence: 99%

Conventional and Conservation Seedbed Preparation Systems for Wheat Planting in Silty-Clay Soil

Fanigliulo¹,

Pochi²,

Servadio³

2021

Sustainability

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Conventional seedbed preparation is based on deep ploughing followed by lighter and finer secondary tillage of the superficial layer, normally performed by machines powered by the tractor’s Power Take-Off (PTO), which prepares the seedbed in a single pass. Conservation methods are based on a wide range of interventions, such as minimum or no-tillage, by means of machines with passive action working tools which require two or more passes The aim of this study was to assess both the power-energy requirements of conventional (power harrows and rotary tillers with different working width) and conservation implements (disks harrow and combined cultivator) and the soil tillage quality parameters, with reference to the capability of preparing an optimal seedbed for wheat planting. Field tests were carried out on flat, silty-clay soil, using instrumented tractors. The test results showed significant differences among the operative performances of the two typologies of machines powered by the tractor’s PTO: the fuel consumption, the power and the energy requirements of the rotary tillers are strongly higher than power harrows. However, the results also showed a decrease of these parameters proceeding from conventional to more conservation tillage implements. The better quality of seedbed was provided by the rotary tillers.

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Section: Introductionmentioning

confidence: 99%

Conventional and Conservation Seedbed Preparation Systems for Wheat Planting in Silty-Clay Soil

Fanigliulo¹,

Pochi²,

Servadio³

2021

Sustainability

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“…Likewise, a combined tillage implement is equipped with multiple tillage tools on a single frame to reduce the tractor passes compared to conventional method. The combined tillage saves time, fuel, and energy to obtain the desired soil conditions [142,143]. Therefore, [144] proposed the CI models (NN and ANFIS) to predict the energy indices of the tractor-implement system during a combined tillage operation.…”

Section: Tillagementioning

confidence: 99%

Application of Computational Intelligence Methods in Agricultural Soil-Machine Interaction : A Review

Badgujar¹,

Figueroa²,

Das³

et al. 2022

Preprint

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Soil working tools, implements, and machines are inevitable in mechanized agriculture. The soil-tool/machine interaction is a multivariate, dynamic, and intricate process. The accurate interpretation, description, and modeling of a soil-machine interaction is key to providing a solution to sustainable crop production by reducing energy input, excessive soil pulverization, and compaction. The traditional method provides insight into soil-machine interaction but often provides inadequate solutions and lacks broad applicability. Computational intelligence (CI) is a comprehensive class of approaches that rely on approximate information to solve complex problems. The CI method has been extensively studied and applied in soil tillage and traction domain in recent decades. The study critically reviews the CI techniques implemented in soil-machine interactions, especially in the context of tillage, traction, and compaction. The traditional methods and their limitation are discussed. The fundamental of CI methods and a detailed overview of the most popular methods are provided. The study reviews and summarizes the 50 selected articles on soil-machine interaction studies where CI methods were employed. It discusses the strength and limitations of employed CI methods. It also suggests the emergent CI methods and future applications are discussed. The outlined study would serve as a concise reference and a quick and systematic way to understand the applicable CI methods that allow crucial farm management decision-making.

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“…ANN is well-suited for complex non-linear modelling tasks, particularly when prior knowledge about the input-output relationship is lacking. In the past, researchers have successfully implemented ANN models to quantify soil-tool interactions [29,30].…”

Section: Introductionmentioning

confidence: 99%

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

Kumar,

Tewari,

Chandel

et al. 2023

Applied Sciences

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Specific 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 (u/v) were selected as the input variables. Soil bin investigations were conducted using the vertical axis rotor (RVA), interfaced with draft, torque, speed sensors, and data acquisition system to record dynamic forces employed during soil–tool interaction at ranges of different operating parameters. The depth of operation (DO) had the maximum influence on the specific energy requirement of the RVA, followed by the cone index (CI) and the u/v ratio. The developed ANN model was able to predict the specific energy requirements of RVA at high accuracies as indicated by high R2 (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–tool interactions under specific experimental conditions. Such estimations will eventually optimize and enhance the performance efficiency of agricultural implements in the field.

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Specific energy requirements and soil pulverization of a combined tillage implement

Cited by 24 publications

References 14 publications

Conventional and Conservation Seedbed Preparation Systems for Wheat Planting in Silty-Clay Soil

Conventional and Conservation Seedbed Preparation Systems for Wheat Planting in Silty-Clay Soil

Application of Computational Intelligence Methods in Agricultural Soil-Machine Interaction : A Review

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

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