Performance of machinery in potato production in one growing season

Abstract

Statistics on the machinery performance are essential for farm managers to make better decisions. In this paper, the performance of all machineries in five sequential operations, namely bed forming, stone separation, planting, spraying and harvesting in the potato production system, were investigated during one growing season. In order to analyse and decompose the recorded GPS data into various time and distance elements for estimation of the machinery performance, an automatic GPS analysis tool was developed. The field efficiency and field capacity were estimated for each operation. Specifically, the measured average field efficiency was 71.3% for bed forming, 68.5% for stone separation, 40.3% for planting, 69.7% for spraying, and 67.4% for harvesting. The measured average field capacities were 1.46 ha/h, 0.53 ha/h, 0.47 ha/h, 10.21 ha/h, 0.51 ha/h, for the bed forming, stone separation, planting, spraying, and harvesting operations, respectively. These results deviate from the corresponding estimations calculated based on norm data from the American Society of Agricultural and Biological Engineers (ASABE). The deviations indicate that norms provided by ASABE cannot be used directly for the prediction of performance of the machinery used in this work. Moreover, the measured data of bed forming and stone separation could be used as supplementary data for the ASABE which does not provide performance norms for these two operations. The gained results can help farm managers to make better management and operational decisions that result in potential improvement in productivity and profitability as well as in potential environmental benefits.Additional key words: GPS data analysis; operation management; machinery management; field efficiency; field capacity; Solanum tuberosum L.

SIMULATION OF EFFICIENCY IN AVAILABILITY FOR DIFFERENT SUGARCANE (Saccharum spp.) TRANSPORT EQUIPMENT

“…Production time is exclusively for productive work, that is, when the equipment is effectively performing the agricultural operation. In this context, according to Alizadeh (2011), Araldi et al (2013), Griffel et al (2020), Grisso et al (2002), Linhares et al (2012), Mohamed et al (2011), Oduma et al (2019), Pitla et al (2014), Santos et al (2018b), Shamshiri & Ismail (2013), and Zhou et al (2015), the operational times of service result in the field efficiency (Eff), which corresponds, in this study, to the availability efficiency (Efa) of the equipment of the sugarcane transport system. Efa comprises the worked hours that the equipment effectively performs its productive function, the auxiliary hours that are required according to the operation that the equipment necessarily needs for its full use (Banchi & Lopez, 2007).…”

ECONOMIC ANALYSIS OF DIFFERENT HYDRAULIC SPRAYERS USED IN SUGARCANE (Saccharum spp.)

“…According to Jokiniemi et al (2012), Rivera et al (2012), Shamshiri & Ismail (2013), Zaied et al (2014), and Oduma et al (2015), field efficiency has a direct influence on the operational field capacity of a machine and on mechanized operations themselves. As stated by Araldi et al (2013), Zhou et al (2015), and Santos et al (2018), mechanized operations are performed considering operational times to improve their field efficiency. In this line, Yousif et al (2013), Ma et al (2015), and Cervi et al (2015) claimed that field efficiency is the ratio between the effective time spent in harvesting operations and the total time that a machine remains in the field.…”

SIMULATION OF DISTANCE BETWEEN FIELD AND REPLENISHMENT PUMP IN MECHANIZED SPRAYING OF SUGARCANE (Saccharum spp.)

“…For Araldi et al (2013); Banchi et al (2008a); Barbosa et al (2015); Cervi et al (2015); Jokiniemi et al (2012); Oduma et al (2015); Linhares et al (2012); Ma et al (2015); Nascimento et al (2016); Neres et al 2012; Rivera et al (2012); Simões et al (2011) and Yousif et al (2013), this is the ratio between effectively used time and total time for equipment operation. The operational time Santos et al (2015a); Shamshiri & Ismail (2013) and Zhou et al (2015) and Çanakci et al (2011); Civelek & Say (2016); Santos et al (2015b); Santos et al (2014a) and Zaied et al (2014) have a participation in the equipment operational performance, which has a direct influence on the economic performance.…”