2018
DOI: 10.51983/ajeat-2018.7.2.900
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Influence of Tillage Depth and Plough Speed on Performance of Primary Tillage Tools

Abstract: In India near about 60% population is engaged in agriculture. Soil loosening is a primary method of cultivation before seeding. There are number of tillage tools used for primary cultivation i.e. cultivators, rotary tillers, moldboard plough and chisel plough, rotavators etc. During soil cultivation wear occurs due to interaction of tillage implement and soil particles, which in turn decreases tillage quality and increase draft forces and fuel consumption of tractor. Tool wear reduces farmer’s efficiency, cost… Show more

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Cited by 5 publications
(6 citation statements)
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“…More interesting is that the exponent of the speed that achieves the maximization is quite close to 2, as it was shown in chapter 3.4. It should be mentioned that the value of 2 of the forward speed exponents is very common in the calculation formulas proposed for the tillage draft force generated by agricultural machines intended for soil processing (Letosnev M.N., 1959;American Society of Agricultural Engineers, 2003;Ranjbar et al, 2013;Singh et al, 2018). In Moeenifar et al, (2014), a formula with an exponent, generally non-integer, is used for the forward speed.…”
Section: Commentsmentioning
confidence: 99%
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“…More interesting is that the exponent of the speed that achieves the maximization is quite close to 2, as it was shown in chapter 3.4. It should be mentioned that the value of 2 of the forward speed exponents is very common in the calculation formulas proposed for the tillage draft force generated by agricultural machines intended for soil processing (Letosnev M.N., 1959;American Society of Agricultural Engineers, 2003;Ranjbar et al, 2013;Singh et al, 2018). In Moeenifar et al, (2014), a formula with an exponent, generally non-integer, is used for the forward speed.…”
Section: Commentsmentioning
confidence: 99%
“…In the last decades, numerous kinds of research in the field of working processes of agricultural machines intended for work have been methodically directed in the last decades towards experimental or theoretical-empirical research (Moeenifar et al, 2014;Ranjbar et al, 2013;Naderloo et al, 2009;Singh et al, 2018;Al-Shamiry et al, 2020;Elsheikha et al, 2021;Kushwaka et al, 1996;Al-Suhaibani et al, 2010). The classical literature until then was dominated by theoretical calculation supplemented by experiments for the calculation of model constants and validation (Cârdei et al, 2023;Krasnicenko et al, 1964;McKyes E., 1985;Sandru et al, 1982;Sandru et al, 1983;Scripnic et al, 1979;Tecusan & Ionescu, 1982;Toma et al, 1978).…”
Section: Introductionmentioning
confidence: 99%
“…Tayel et al (2015) indicated that The increase in the depth of one centimeter led to an increase in fuel consumption from 0.5 to 1.5 per hectare. Singh et al (2018) noted that increase in plowing depth from35 to 65 cm increased the consumption of fuel by 40% and increased the percentage of slippage by 18% also increases the plowing speed plow from 1 to 4 km / h increased the percentage of slippage from 17 to 25%. The main objective of the process of tillage provides a suitable seedbed for germination and growth by improving the ventilation of the soil and infiltration the water to the root area thereby the plant takes needs of the nutrients necessary for growth (Kumar et al, 2018).…”
Section: Introductionmentioning
confidence: 97%
“…This phenomenon has been widely studied due to the large losses caused in the mechanised tools used in the different tasks of agricultural processes. It is generally quantified by measuring the loss of material, and currently experimental (Pérez et al, 2010;López, 2011;González, 2012;Jia y Zhou, 2012;Rojek, 2014;Singh et al, 2017;Obrad et al, 2018;Chen et al, 2018;Bedolla et al, 2018) and numerical methods have been used for its study. Among the numerical ones, the Distinct or Discrete Element Method (DEM) has the most application for the study of abrasive wear (Graff, 2010;Rojek, 2014;Perazzo et al, 2016;Hoormazdi et al, 2018;Chen et al, 2018;Ucgul et al, 2017, Graff, 2010, Bedolla et al, 2018Montes, Herrera, López, Pérez, & Torres, 2023;Zolotarevskiy, Gallo, Pereira, & Barnett, 2022;Zhang, Fu, Ren, Liu, Lin, Zhang & Zhang, 2024).…”
Section: Introductionmentioning
confidence: 99%