Spatial distribution of soil mechanical strength in a controlled traffic farming system as determined by cone index and geostatistical techniques

Controlled traffic farming (CTF) is a mechanisation system in which all load-bearing wheels are confined to the least possible area of permanent traffic lanes and where crops are grown in permanent, non-trafficked beds. In well-designed systems, the area affected by traffic represents less than 15%...

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Otros Autores: Alesso, Carlos Agustín, Cipriotti, Pablo Ariel, Masola, M. J., Carrizo, María Eugenia, Imhoff, Silvia del Carmen, Rocha Meneses, L., Antille, D. L.
Formato: Artículo
Lenguaje:Inglés
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Acceso en línea:http://ri.agro.uba.ar/files/intranet/articulo/2020alesso.pdf
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Aporte de:Registro referencial: Solicitar el recurso aquí
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245 1 0 |a Spatial distribution of soil mechanical strength in a controlled traffic farming system as determined by cone index and geostatistical techniques 
520 |a Controlled traffic farming (CTF) is a mechanisation system in which all load-bearing wheels are confined to the least possible area of permanent traffic lanes and where crops are grown in permanent, non-trafficked beds. In well-designed systems, the area affected by traffic represents less than 15% of the total field cropped area. The extent and distribution of soil compaction at locations laterally outboard of the permanent traffic lanes may explain the performance of the crop on the rows located either side of the wheeling. This compaction is due to lateral displacement of soil caused by repetitive wheeling, the effect of soil-tyre interaction and the soil conditions (strength) at the time of traffic. The impact of compaction on crop rows adjacent to permanent traffic lanes is also dependent on the seasonal effect of weather, because of changes in soil water availability. This work was conducted to model the spatial distribution of soil mechanical strength under increasing number of tractor passes to simulate the soil conditions that may be encountered in CTF systems at locations near-permanent traffic lanes. The study was conducted on a Typic Argiudoll (26% clay, 72% silt, 2% sand) with four traffic intensities (0, 6, 12 and 18 passes) using a 120 HP tractor (overall mass: 6.3 Mg). Traffic treatments were applied to experimental plots using a completely randomized block design with three replications per treatment. The spatial distribution of soil strength within wheeled and non-wheeled zones was determined using a cone penetrometer (depth range: 0–300 mm) and geostatistical techniques. In all treatments, cone index showed a quadratic response with depth, which explained between 67% and 88% of the variation in soil strength. The number of tractor passes had no effect on the range of spatial dependence of residuals. No differences were observed in the proportion of grid cells where penetration resistance was greater than 2 MPa (considered to be the soil strength limit for root growth of most arable crops) between-traffic treatments, or wheeled and non-wheeled zones, respectively. The overall mean proportion (± 95% confidence interval) of grid cells (4.9 ± 4.5%) suggested that this measure has a relatively high variability and therefore may not be a reliable parameter to be used in the design of future experimental work. 
650 |2 Agrovoc  |9 26 
653 |a FIELD TRAFFIC 
653 |a SOIL COMPACTION 
653 |a SOIL MECHANICAL PROPERTIES 
653 |a SOIL PENETRATION RESISTANCE 
700 1 |9 48420  |a Alesso, Carlos Agustín  |u Universidad Nacional del Litoral. ICiAgro Litoral. Esperanza, Santa Fe, Argentina.  |u CONICET - Universidad Nacional del Litoral. ICiAgro Litoral. Esperanza, Santa Fe, Argentina. 
700 1 |9 20940  |a Cipriotti, Pablo Ariel  |u Universidad de Buenos Aires. Facultad de Agronomía. Instituto de Investigaciones Fisiológicas y Ecológicas Vinculadas a la Agricultura (IFEVA). Buenos Aires, Argentina.  |u CONICET – Universidad de Buenos Aires. Instituto de Investigaciones Fisiológicas y Ecológicas Vinculadas a la Agricultura (IFEVA). Buenos Aires, Argentina. 
700 1 |a Masola, M. J.  |u Universidad Nacional del Litoral. ICiAgro Litoral. Esperanza, Santa Fe, Argentina.  |u CONICET - Universidad Nacional del Litoral. ICiAgro Litoral. Esperanza, Santa Fe, Argentina.  |9 73078 
700 1 |a Carrizo, María Eugenia  |u Universidad Nacional del Litoral. ICiAgro Litoral. Esperanza, Santa Fe, Argentina.  |u CONICET - Universidad Nacional del Litoral. ICiAgro Litoral. Esperanza, Santa Fe, Argentina.  |9 48419 
700 1 |a Imhoff, Silvia del Carmen  |u Universidad Nacional del Litoral. ICiAgro Litoral. Esperanza, Santa Fe, Argentina.  |u CONICET - Universidad Nacional del Litoral. ICiAgro Litoral. Esperanza, Santa Fe, Argentina.  |9 48421 
700 1 |a Rocha Meneses, L.  |u Estonian University of Life Sciences, Institute of Technology, Chair of Biosystems Engineering.Tartu, Estonia.  |9 73079 
700 1 |a Antille, D. L.  |u CSIRO Agriculture and Food, Black Mountain Science and Innovation Precinct. Canberra, Australia.  |9 73080 
773 0 |t Agronomy Research  |g Vol.18, supl. esp.2 (2020), p.1115–1126, grafs., fot.  |w SECS001014 
856 |f 2020alesso  |i En reservorio  |q application/pdf  |u http://ri.agro.uba.ar/files/intranet/articulo/2020alesso.pdf  |x ARTI202111 
856 |u http://agronomy.emu.ee/  |z LINK AL EDITOR 
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