scholarly journals Modelling effective soil depth at field scale from soil sensors and geomorphometric indices

2017 ◽  
Vol 66 (2) ◽  
Author(s):  
Mauricio Castro Franco ◽  
Marisa Domenech ◽  
José Luis Costa ◽  
Virginia Carolina Aparicio
Keyword(s):  
Electrical Conductivity ◽  
Random Forest ◽  
Buenos Aires ◽  
Soil Depth ◽  
Buenos Aires Province ◽  
Field Scale ◽  
Soil Sensors ◽  
Statistic Model ◽  
Apparent Electrical Conductivity

The effective soil depth (ESD) affects both dynamic of hydrology and plant growth. In the southeast of Buenos Aires province, the presence of petrocalcic horizon constitutes a limitation to ESD. The aim of this study was to develop a statistic model to predict spatial patterns of ESD using apparent electrical conductivity at two depths: 0-30 (ECa_30) and 0-90 (ECa_90) and geomorphometric indices. To do this, a Random Forest (RF) analysis was applied. RF was able to select those variables according to their predictive potential for ESD. In that order, ECa_90, catchment slope, elevation and ECa_30 had main prediction importance. For validating purposes, 3035 ESD measurements were carried out, in five fields. ECa and ESD values showed complex spatial pattern at short distances. RF parameters with lowest error (OOBerror) were calibrated. RF model simplified which uses main predictors had a similar predictive development to it uses all predictors. Furthermore, RF model simplified had the ability to delineate similar pattern to those obtained from in situ measure of ESD in all fields. In general, RF was an effective method and easy to work. However, further studies are needed which add other types of variables importance calculation, greater number of fields and test other predictors in order to improve these results.

scholarly journals Combined use of remote sensing and soil sensors to detect variability in orchards with previous changes in land use and landforms: consequences for management

2017 ◽  
Vol 8 (2) ◽  
pp. 492-497
Author(s):  
J. A. Martínez-Casasnovas ◽  
E. Daniele ◽  
A. Uribeetxebarría ◽  
A. Escolà ◽  
J. R. Rosell-Polo ◽  
...  
Keyword(s):  
Prunus Persica ◽  
Soil Depth ◽  
Strong Relationship ◽  
Water Holding Capacity ◽  
Management Zones ◽  
Soil Sensors ◽  
Combined Use ◽  
Apparent Electrical Conductivity ◽  
Water Holding ◽  
Peach Orchard

The present work investigated the application of detailed airborne images and a resistivity soil sensor (Veris 3100) to detect soil and crop spatial variability to assist in orchard management. The research was carried out in a peach orchard (Prunus persica). Soil apparent electrical conductivity (ECa), NDVI from a multispectral image (0.25 m/pixel) and soil properties at 40 sampling points (0–30 cm) were acquired. The ECa was standardized at 25°C. It showed a strong relationship with former landforms, altered by land levelling. A positive correlation of EC25 with EC1:5, water holding capacity at −1500 kPa and soil depth was found. NDVI was correlated only in the textural fractions coarser than clay. Two types of management zones were proposed: a) to improve the water holding capacity of soils and b) to regulate tree vigour and yield.

Soil inorganic carbon in Pampean agroecosystems: distribution and relationships with soil properties in Buenos Aires province

Soil Research ◽  
2016 ◽  
Vol 54 (7) ◽  
pp. 777 ◽  
Author(s):  
Gabriela Civeira
Keyword(s):  
Soil Profile ◽  
Inorganic Carbon ◽  
Buenos Aires ◽  
Soil Depth ◽  
Landscape Position ◽  
Soil Profiles ◽  
Buenos Aires Province ◽  
Change Models ◽  
Soil Inorganic Carbon ◽  
Soil Inorganic

Changes in contents of soil organic carbon and soil inorganic carbon (SOC and SIC, respectively) could have a great effect on the global carbon balance. Quantifying SIC at regional level is essential in climate change models. The spatial distribution of SIC depends on climate, soil particle size, soil type, landscape position and SOC fraction, among other factors. This study compared the SIC storage in soil profiles at different depths in different soil great groups and landscape positions in Buenos Aires province, Argentina. The objectives were to: (i) quantify SIC content and distribution in the soil profile (depths of 0–20, 20–100 and 0–100 cm) for different soil types and landscape positions; (ii) identify relationships between the distribution of SIC and edaphic properties; and (iii) analyse the relationship between SIC and SOC in soils of the area. The analysis was based on 150 soil profiles of Argiudolls, Hapludolls, Natraquolls and Haplustolls from Buenos Aires province. The data on SIC were expressed by soil great group, landscape position (summit, shoulder slope and toe slope) and depth in the soil profile (0–20, 20–100 and 0–100 cm). In the whole profile (0–100 cm) the order of decrease for SIC was Haplustolls > Hapludolls > Natraquolls > Argiudolls. Concentrations of SIC for landscape positions were shoulder slope > toe slope > summit. pH was positively correlated with SIC content within the 100-cm soil depth and in the AC horizon in Haplustolls (P < 0.05), and with SIC content in the C horizons in Hapludolls and Haplustolls. Silt was positively correlated with SIC in Haplustolls. There were changes in the contents of SIC due to increased SOC. Landscape position and great group determined the distribution of SIC in these Pampean agroecosystems. These results may be useful to predict SIC responses to land use change at local and regional levels.

Occurrence of Cryptosporidium and other enteropathogens and their association with diarrhea in dairy calves of Buenos Aires province, Argentina

2021 ◽  
Vol 24 ◽  
pp. 100567
Author(s):  
Carlos J. Garro ◽  
Gabriel E. Morici ◽  
Mariela L. Tomazic ◽  
Daniel Vilte ◽  
Micaela Encinas ◽  
...  
Keyword(s):  
Buenos Aires ◽  
Dairy Calves ◽  
Buenos Aires Province

Chemically reduced graphene oxide-coated knitted fabric imparted conductivity and outstanding hydrophobicity

2021 ◽  
pp. 004051752199547
Author(s):  
Min Hou ◽  
Xinghua Hong ◽  
Yanjun Tang ◽  
Zimin Jin ◽  
Chengyan Zhu ◽  
...  
Keyword(s):  
Electrical Conductivity ◽  
Graphene Oxide ◽  
Reduced Graphene Oxide ◽  
Chemical Reduction ◽  
Knitted Fabric ◽  
Mesh Structure ◽  
Reduced Graphene ◽  
Chemically Reduced Graphene Oxide ◽  
Modified Hummers Method

Functionalized knitted fabric, as a kind of flexible, wearable, and waterproof material capable of conductivity, sensitivity and outstanding hydrophobicity, is valuable for multi-field applications. Herein, the reduced graphene oxide (RGO)-coated knitted fabric (polyester/spandex blended) is prepared, which involves the use of graphite oxide (GO) by modified Hummers method and in-situ chemical reduction with hydrazine hydrate. The treated fabric exhibits a high electrical conductivity (202.09 S/cm) and an outstanding hydrophobicity (140°). The outstanding hydrophobicity is associated with the morphology of the fabric and fiber with reference to pseudo-infiltration. These properties can withstand repeated bending and washing without serious deterioration, maintaining good electrical conductivity (35.70 S/cm) and contact angle (119.39°) after eight standard washing cycles. The material, which has RGO architecture and continuous loop mesh structure, can find wide use in smart garment applications.

scholarly journals Water Footprint and Virtual Water Trade of Maize in the Province of Buenos Aires, Argentina

Water ◽  
2021 ◽  
Vol 13 (13) ◽  
pp. 1769
Author(s):  
Maria Macarena Arrien ◽  
Maite M. Aldaya ◽  
Corina Iris Rodriguez
Keyword(s):  
Buenos Aires ◽  
Water Footprint ◽  
Local Level ◽  
Virtual Water ◽  
Buenos Aires Province ◽  
Pollution Load ◽  
Basin Scale ◽  
Water Volumes ◽  
Water Scarce ◽  
First Time

Agriculture is the largest fresh water consuming sector, and maize is the most produced and consumed crop worldwide. The water footprint (WF) methodology quantifies and evaluates the water volumes consumed and polluted by a given crop, as well as its impacts. In this work, we quantified for the first time the green WF (soil water from precipitation that is evapotranspired) and the green virtual water exports of maize from Buenos Aires province, Argentina, during 2016–2017, due to the relevance of this region in the world maize trade. Furthermore, at local level, we quantified the green, blue (evapotranspired irrigation), and grey (volume of water needed to assimilate a pollution load) WF of maize in a pilot basin. The green WF of maize in the province of Buenos Aires ranged between 170 and 730 m3/ton, with the highest values in the south following a pattern of yields. The contribution of this province in terms of green virtual water to the international maize trade reached 2213 hm3/year, allowing some water-scarce nations to ensure water and water-dependent food security and avoid further environmental impacts related to water. At the Napaleofú basin scale, the total WF of rainfed maize was 358 m3/ton (89% green and 11% grey) and 388 m3/ton (58% green, 25% blue, and 17% grey) for the irrigated crop, showing that there is not only a green WF behind the exported maize, but also a Nitrogen-related grey WF.

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