# Measuring and Comparing Forces Acting on Moldboard Plow and Para-Plow with Wing to Replace Moldboard Plow with Para-Plow for Tillage and Modeling It Using Adaptive Neuro-Fuzzy Interface System (ANFIS)

^{1}

^{2}

^{3}

^{4}

^{*}

## Abstract

**:**

## 1. Introduction

## 2. Materials and Methods

#### Designing the ANFIS Fuzzy Neural System

## 3. Results and Discussion

#### Predicting Draft, Vertical, and Lateral Forces Acting on Implements Using ANFIS Model

## 4. Conclusions

## Author Contributions

## Funding

## Conflicts of Interest

## References

- Jacobs, C.O.; Finnery, J.B. Soil Managemen; Farming Press Publication: Totnes, UK, 1993; pp. 187–189. [Google Scholar]
- Dexter, A.R.; Czyz, O.P.; Gat, E. A method for soil penetration resistance. Soil Till. Res.
**2007**, 93, 412–419. [Google Scholar] [CrossRef] - Kheiralla, A.F.; Yahya, A.; Zohadie, M.; Ishak, W. Design and development of three point auto hitch dynamometer for an agricultural tractor. AJSTD
**2003**, 20, 271–288. [Google Scholar] [CrossRef] [Green Version] - Harrison, H.; Licsko, Z. Soil reacting forces for models of three bentleg plows. Soil Tillage Res.
**1989**, 15, 125–135. [Google Scholar] [CrossRef] - Pidgeon JDSoane, B.D. Effects of tillage and direct drilling on soil properties during the growing season in a long-term barely mono-culture system. J. Agric. Sci.
**1977**, 88, 431–442. [Google Scholar] [CrossRef] - Al-Janobi, A.; Al-Suhaibani, S.A. Draft of primary tillage implements in sandy loan soil. Appl. Eng. Agric.
**1998**, 14, 343–348. [Google Scholar] [CrossRef] - Fervers, C. Improved FEM simulation model for tire–soil interaction. J. Terramech.
**2004**, 41, 87–100. [Google Scholar] [CrossRef] - Nakashima, H.; Oida, A. Algorithm and implementation of soil–tire contact analysis code based on dynamic FE–DE method. J. Terramech.
**2004**, 41, 127–137. [Google Scholar] [CrossRef] - Yong, R.; Boonsinsuk, P.; Fattah, E. Tyre flexibility and mobility on soft soils. J. Terramech.
**1980**, 17, 43–58. [Google Scholar] [CrossRef] - Alsuhaibani, S.A.; Aljnobi, A.A.; Almajhadi, Y.N. Tractors and Tillage Implements Performance. In Proceedings of the CSBE/SCGAB 2006 Annual Conference, Edmonton, AB, Canada, 16–19 July 2006. [Google Scholar]
- Scholtz, D.C. A three-point hitch dynamometer for restrained linkages. J. Agric. Eng. Res.
**1966**, 11, 33–37. [Google Scholar] [CrossRef] - Kirisci, V.; Blackmore, B.S.; Kilgour, J.; Godwin, R.J.; Babier, A.S. A Three-Point Linkage Dynamometer System. In Proceedings of the International Conference on Agriculture Engineering, Uppsala, Sweden, 1–4 June 1992. [Google Scholar]
- Godwin, R.; Reynolds, A.; O’Dogherty, M.; Al-Ghazal, A. A Triaxial Dynamometer for Force and Moment Measurements on Tillage Implements. J. Agric. Eng. Res.
**1993**, 55, 189–205. [Google Scholar] [CrossRef] - Khan, J.; Godwin, R.J.; Kilgour, J.; Blackmore, B.S. Design and Calibration of a BI-Axial Extended Octagonal Ring Transducer System for the Measurment of Tractor-Implement Forces. J. Eng. Appl. Sci.
**2007**, 2, 16–20. [Google Scholar] - Askari, M.; Komarizade, M.; Nikbakht, A.; Nobakht, N.; Teimourlou, R. A novel three-point hitch dynamometer to measure the draft requirement of mounted implements. Res. Agric. Eng.
**2011**, 57, 128–136. [Google Scholar] [CrossRef] [Green Version] - Irshad Ali, M.; Changying, J.; Leghari, N.; Ghulam Ali, B.; Farman Ali Ch ChuadryArslan Ch Sattar, A.; Huimin, F. Analyses of 3-dimensional draught and soil deformation forces caused by mouldboard plough in clay loam soil. Glob. Adv. Res. J. Agric. Sci.
**2015**, 4, 259–269. [Google Scholar] - Godwin, R.; O’Dogherty, M.; Saunders, C.; Balafoutis, A. A force prediction model for mouldboard ploughs incorporating the effects of soil characteristic properties, plough geometric factors and ploughing speed. Biosyst. Eng.
**2007**, 97, 117–129. [Google Scholar] [CrossRef] - Roul, A.; Raheman, H.; Pansare, M.; Machavaram, R. Predicting the draught requirement of tillage implements in sandy clay loam soil using an artificial neural network. J. Biosyst. Eng.
**2009**, 104, 476–485. [Google Scholar] [CrossRef] - Al-Hamed, S.A.; Wahby, M.F.; Al-Saqer, S.M.; Aboukarima, A.M.; Sayedahmed, A.A. Artificial Neural Network Model for Predicting Draft and Energy Requirements of a Disk Plow. J. Anim. Plant Sci.
**2013**, 23, 1714–1724. [Google Scholar] - Akbarnia, A.; Mohammadi, A.; Farhani, F.; Alimardani, R. Simulation of draft force of winged share tillage tool using artificial neural network model. Agric Eng. Int. CIGR J.
**2014**, 16, 57–65. [Google Scholar] - Pentoś, K.; Pieczarka, K. Applying an artificial neural network approach to the analysis of tractive properties in changing soil conditions. Soil Tillage Res.
**2017**, 165, 113–120. [Google Scholar] [CrossRef] - Abbaspour-Gilandeh, Y.; Sedghi, R. Predicting soil fragmentation during tillage operation using a fuzzy logic approach. J Terrramech.
**2015**, 57, 61–69. [Google Scholar] [CrossRef] - Abbaspour-Gilandeh, S.S. Automatic grading of emperor apples based on image processing and ANFIS. Tarım Bilim. Derg. J. Agric. Sci.
**2015**, 21, 326–336. [Google Scholar] [CrossRef] - Askari, M.; Shahgholi, G.; Abbaspour-Gilandeh, Y. New wings on the interaction between conventional subsoiler and paraplow tines with the soil: Effects on the draft and the properties of soil. Arch. Agron. Soil Sci.
**2018**, 65, 88–100. [Google Scholar] [CrossRef] - Page, A.L.; Miller, R.H.; Keeney, D.R. Methods of Soil Analysis; American Society of Agronomy (Publ.): Madison, WI, USA, 1982. [Google Scholar]
- Abbaspour-Gilandeh, Y.; Khanramaki, M. Design, Construction and Calibration of a Triaxial Dynamometer for Measuring Forces and Moments Applied on Tillage Implements in Field Conditions. Met. Soc. India
**2013**, 28, 119–127. [Google Scholar] [CrossRef] - Askari, M.; Shahgholi, G.; Abbaspour-Gilandeh, Y.; Tash-Shamsabadi, H. The Effect of New Wings on Subsoiler Performance. Appl. Eng. Agric.
**2016**, 32, 353–362. [Google Scholar] - De Souza, E.G.; Lima, J.S.S.; Milanez, L.F. Overall Efficiency of Tractor Operating in the Field. Trans. ASAE
**1994**, 106, 771–775. [Google Scholar] [CrossRef] - Raheman, H.; Jha, S. Wheel slip measurement in 2WD tractor. J. Terramech.
**2007**, 44, 89–94. [Google Scholar] [CrossRef] - Sharifat, K.; Kushwaha, R.L. Modeling soil movement by tillage tools. Can. Agric. Eng.
**2000**, 42, 165–172. [Google Scholar] - Kasisira, L.; Du Plessis, H. Energy optimization for subsoilers in tandem in a sandy clay loam soil. Soil Tillage Res.
**2006**, 86, 185–198. [Google Scholar] [CrossRef] - Al-janobi, A. A data-acquistion system to monitor performance of fully mounted implements. J. Agric. Eng. Res.
**2000**, 75, 167–175. [Google Scholar] [CrossRef]

**Figure 1.**(

**a**) Para-plow. Bend angle of para-plow leg or Ω was 45°; (

**b**) Top view of the forward and (

**c**) backward wings.

**Figure 2.**(

**a**) The mechanism used for field experiments includes: (

**b**) the three-point connection dynamometer to measure the force applied to devices; (

**c**) fifth wheel mechanism for measuring real progressive speed; (

**d**) para-plow with the backward wings; (

**e**) data logger and laptop for data recording; (

**f**) the battery built into the cabin to power the data logger and laptop.

**Figure 3.**Partitioning of the membership functions of the input parameters and the membership function of the output parameter.

**Figure 4.**Mean draft forces under different implements and treatments, S and D show speed and depth, respectively.

**Figure 5.**Mean vertical forces under different implements and treatments, S and D show speed and depth, respectively.

**Figure 6.**Mean lateral forces under different implements and treatments, S and D show speed and depth, respectively.

**Figure 9.**Surface graph showing the relationship of implements and depth with (

**a**) draft force (Fd), (

**b**) vertical force (Fv), and (

**c**) lateral force (Fl).

**Figure 10.**The relationship between the values measured and predicted by the ANFIS models for (

**a**) draft force (Fd), (

**b**) vertical force (Fv), and (

**c**) lateral force ($\mathrm{Fl}$); y indicates the regression relationship between the measured values and the predicted values.

Property | |
---|---|

Sand (0.02–2 mm) | 41 g 100 g^{−1} |

Silt (0.002–0.02 mm) | 28 g 100 g^{−1} |

Clay (<0.002 mm) | 33 g 100 g^{−1} |

Organic carbon | 0.29 g 100 g^{−1} |

Electrical Conductivity (EC) | 0.41 ds m^{−1} |

Liquid limit | 30 g 100 g^{−1} |

Plastic limit | 20.05 g 100 g^{−1} |

Field capacity (ds) | 25.13 g 100 g^{−1} |

Dry bulk density (0–10 cm) | 948 kg m^{−3} |

Dry bulk density (0–20 cm) | 1004 kg m^{−3} |

Dry bulk density (0–30 cm) | 1112 kg m^{−3} |

Moisture content (ds) (0–10 cm) | 7.76 g 100 g^{−1} |

Moisture content (ds) (0–20 cm) | 11.24 g 100 g^{−1} |

Moisture content (ds) (0–30 cm) | 18.46 g 100 g^{−1} |

Mean Square | Degree of Freedom | Source of Variation | ||
---|---|---|---|---|

Lateral Force $\left({\mathbf{F}}_{\mathbf{l}}\right)$ | Vertical Force $\left({\mathbf{F}}_{\mathbf{v}}\right)$ | Draft Force $\left({\mathbf{F}}_{\mathbf{d}}\right)$ | ||

${41.8088}^{\text{}**}$ | ${4.19177}^{\text{}**}$ | ${2423.4941}^{\text{}**}$ | ||

${20.0341}^{\text{}**}$ | ${36.8328}^{\text{}**}$ | ${543.7585}^{\text{}**}$ | 3 | Tools |

${4.61797}^{\text{}**}$ | ${6.9408}^{\text{}**}$ | ${175.0482}^{\text{}**}$ | 2 | Speed |

${4.5637}^{\text{}**}$ | ${3.04847}^{\text{}**}$ | ${76.329}^{\text{}**}$ | 2 | Depth |

${0.2329}^{\text{}**}$ | ${2.6498}^{\text{}**}$ | ${1.5481}^{\text{}**}$ | 6 | Tools × Speed |

${0.17838}^{\text{}**}$ | ${1.2186}^{\text{}**}$ | ${1.41198}^{\text{}**}$ | 6 | Tools × Depth |

${0.35314}^{\text{}**}$ | ${0.60144}^{\text{}**}$ | ${4.3113}^{\text{}**}$ | 4 | Speed × Depth |

0.007409 | 0.00127 | 0.01021 | 144 | Error |

Root Mean Square Error (RMSE) | FIS Models for Forces | |
---|---|---|

Test Data | Train Data | |

0.037602 | 0.02149 | Draft force ($\mathrm{Fd}$) |

0.018901 | 0.01426 | Vertical force ($\mathrm{Fv}$) |

0.021046 | 0.01658 | Lateral force ($\mathrm{Fl})$ |

Type of Membership Functions | Number of Membership Functions | Learning Method | ANFIS Models for Forces | RMSE | (%)ε | ${R}^{2}$ | ||
---|---|---|---|---|---|---|---|---|

Input | Output | Input | Epoch | - | - | - | - | - |

- Trimf | Linear - | - 5 | - 30 | - Hybrid | - | - | - | - |

$\mathrm{Fd}$ | 0.3756 | 0.0214 | 0.9999 | |||||

$\mathrm{Fv}$ | 0.0142 | 0.0142 | 0.9981 | |||||

$\mathrm{Fl}$ | 0.0166 | 0.0166 | 0.9977 |

Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. |

© 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).

## Share and Cite

**MDPI and ACS Style**

Abbaspour-Gilandeh, M.; Shahgoli, G.; Abbaspour-Gilandeh, Y.; Herrera-Miranda, M.A.; Hernández-Hernández, J.L.; Herrera-Miranda, I.
Measuring and Comparing Forces Acting on Moldboard Plow and Para-Plow with Wing to Replace Moldboard Plow with Para-Plow for Tillage and Modeling It Using Adaptive Neuro-Fuzzy Interface System (ANFIS). *Agriculture* **2020**, *10*, 633.
https://doi.org/10.3390/agriculture10120633

**AMA Style**

Abbaspour-Gilandeh M, Shahgoli G, Abbaspour-Gilandeh Y, Herrera-Miranda MA, Hernández-Hernández JL, Herrera-Miranda I.
Measuring and Comparing Forces Acting on Moldboard Plow and Para-Plow with Wing to Replace Moldboard Plow with Para-Plow for Tillage and Modeling It Using Adaptive Neuro-Fuzzy Interface System (ANFIS). *Agriculture*. 2020; 10(12):633.
https://doi.org/10.3390/agriculture10120633

**Chicago/Turabian Style**

Abbaspour-Gilandeh, Mohammadreza, Gholamhossein Shahgoli, Yousef Abbaspour-Gilandeh, Miguel Apolonio Herrera-Miranda, José Luis Hernández-Hernández, and Israel Herrera-Miranda.
2020. "Measuring and Comparing Forces Acting on Moldboard Plow and Para-Plow with Wing to Replace Moldboard Plow with Para-Plow for Tillage and Modeling It Using Adaptive Neuro-Fuzzy Interface System (ANFIS)" *Agriculture* 10, no. 12: 633.
https://doi.org/10.3390/agriculture10120633