scholarly journals The 13C Discrimination of Crops Identifies Soil Spatial Variability Related to Water Shortage Vulnerability

Agronomy ◽  
2020 ◽  
Vol 10 (11) ◽  
pp. 1691
Author(s):  
Jan Haberle ◽  
Renata Duffková ◽  
Ivana Raimanová ◽  
Petr Fučík ◽  
Pavel Svoboda ◽  
...  

Spatial variability of crop growth and yields is the result of many interacting factors. The contribution of the factors to variable yields is often difficult to separate. This work studied the relationships between the 13C discrimination (Δ13C) of plants and the spatial variability of field soil conditions related to impacts of water shortage on crop yield. The 13C discrimination, the indicator of water shortage in plants, 15N (δ15N) discrimination, and nitrogen (N) content were determined in grains of winter wheat, spring barley, and pea. The traits were observed at several dozens of grid spots in seven fields situated in two regions with different soil and climate conditions between the years 2017 and 2019. The principles of precision agriculture were implemented in some of the studied fields and years by variable rate nitrogen fertilization. The Δ13C significantly correlated with grain yields (correlation coefficient from 0.66 to 0.94), with the exception of data from the wetter year 2019 at the site with higher soil water capacity. The effect of drought was demonstrated by statistically significant relationships between Δ13C in dry years and soil water capacity (r from 0.46 to 0.97). The significant correlations between Δ13C and N content of seeds and soil water capacity agreed with the expected impact of water shortage on plants. The 13C discrimination of crop seeds was confirmed as a reliable indicator of soil spatial variability related to water shortage. Stronger relationships were found in variably fertilized areas.

2016 ◽  
Vol 30 (3) ◽  
pp. 349-357 ◽  
Author(s):  
Aura Pedrera-Parrilla ◽  
Eric C. Brevik ◽  
Juan V. Giráldez ◽  
Karl Vanderlinden

Abstract Understanding of soil spatial variability is needed to delimit areas for precision agriculture. Electromagnetic induction sensors which measure the soil apparent electrical conductivity reflect soil spatial variability. The objectives of this work were to see if a temporally stable component could be found in electrical conductivity, and to see if temporal stability information acquired from several electrical conductivity surveys could be used to better interpret the results of concurrent surveys of electrical conductivity and soil water content. The experimental work was performed in a commercial rainfed olive grove of 6.7 ha in the ‘La Manga’ catchment in SW Spain. Several soil surveys provided gravimetric soil water content and electrical conductivity data. Soil electrical conductivity values were used to spatially delimit three areas in the grove, based on the first principal component, which represented the time-stable dominant spatial electrical conductivity pattern and explained 86% of the total electrical conductivity variance. Significant differences in clay, stone and soil water contents were detected between the three areas. Relationships between electrical conductivity and soil water content were modelled with an exponential model. Parameters from the model showed a strong effect of the first principal component on the relationship between soil water content and electrical conductivity. Overall temporal stability of electrical conductivity reflects soil properties and manifests itself in spatial patterns of soil water content.


2020 ◽  
Vol 20 (3) ◽  
pp. 860-870 ◽  
Author(s):  
Tao Li ◽  
Jian-feng Zhang ◽  
Si-yuan Xiong ◽  
Rui-xi Zhang

Abstract Assessing the spatial variability of soil water content is important for precision agriculture. To measure the spatial variability of the soil water content and to determine the optimal number of sampling sites for predicting the mean soil water content at different stages of the irrigation cycle, field experiments were carried out in a potato field in northwestern China. The soil water content was measured in 2016 and 2017 at depths of 0–20 and 20–40 cm at 116 georeferenced locations. The average coefficient of variation of the soil water content was 20.79% before irrigation and was 16.44% after irrigation at a depth of 0–20 cm. The spatial structure of the soil water content at a depth of 20–40 cm was similar throughout the irrigation cycle, but at a depth of 0–20 cm a relatively greater portion of the variation in the soil water content was spatially structured before irrigation than after irrigation. The autocorrelation of soil water contents was influenced by irrigation only in the surface soil layer. To accurately predict mean soil moisture content, 40 and 20 random sampling sites should be chosen with errors of 5% and 10%, respectively.


2020 ◽  
Vol 13 (1) ◽  
pp. 194
Author(s):  
Mohamed A. E. AbdelRahman ◽  
Yasser M. Zakarya ◽  
Mohamed M. Metwaly ◽  
Georgios Koubouris

Detailed knowledge of soil properties is fundamentally important for optimizing agriculture practices and management. Meanwhile, the spatial distribution of soil physicochemical properties is considered a fundamental input of any sustainable agricultural planning. In the present study, ordinary kriging, regression kriging and IDW were chosen for deciphering soil spatial variability and mapping soil properties in a reclaimed area of the Behera Governorate of Egypt where soil arose from two different types, one sandstone and the other limestone. Geostatistics were used to show the interrelationships and conditions of soil properties (available phosphorus, potassium and nitrogen, EC, pH, Sp, ESP, CEC, OC, SAR, and CaCO3). The results of mapping spatial soil variability by Geostatistics could be used for precision agriculture applications. Based on the soil test results, nutrient management recommendations should be applied regarding variable rates of fertilizers. The performance of the maps was evaluated using Mean square error (MSE). Inverse distance weight (IDW) showed higher efficiency than Kriging as a prediction method for mapping the studied soil properties in the study area. The results of the present study suggest that the application of the selected fit model worldwide in any relevant study of soil properties of different geological sources is feasible.


2021 ◽  
Author(s):  
Andreas Ibrom ◽  
Norbert Pirk ◽  
Klaus Steenberg Larsen ◽  
Linsey Marie Avila ◽  
Konstantinos Kissas ◽  
...  

<p>Peatlands store large amounts of organic carbon, which is subject to microbial decomposition and mineralization to either CO<sub>2</sub> or CH<sub>4</sub>.  Drained peatlands are characterized by large horizontal variability in soil water contents and saturation, with dryer parts closer to the drainage ditches. The greenhouse gas (GHG) production in these systems is expected to be sensitive to temperature, substrate chemistry, oxygen concentration thus on soil water contents. Methane production should take place in the wetter parts, while respiration should dominate in drier parts. The seasonality of weather conditions modulates the spatial variability. In this complex situation, we are interested in how the seasonal weather variability triggers the microbial processes in the different micro-topographical situations and how this affects the overall GHG budgets of such sites.</p><p>We investigate two neighboring, drained ombrotrophic bogs in Norway close to Trysil, Innlandet, 61.1N- 12.25E, 640 m a. s. l.. One site (South) on an upper slope is about 45 m higher than the other site (North) in a saddle like flattening.  We use an automated chamber method to examine the seasonality of GHG production at microsites that cover some contrasting local situations with in the large range of small scale spatial heterogeneity. With eddy covariance CO<sub>2</sub> and CH<sub>4</sub> flux measurements, we integrate over a larger spatial scale, with, however, shifting footprints depending on weather conditions and wind direction. We present a comparative  analysis of 1.5 years continuous measurements, where we examine shifting spatial patterns of GHG production at different scales and relate them to soil conditions.</p><p>While the CO<sub>2</sub> fluxes compared very well between the two investigated sites, the CH<sub>4</sub> fluxes in the lower and wetter of the two sites (North) was higher and their spatial variability was lower than in the South site. Only in the South site, the CH<sub>4</sub> fluxes correlated with the coverage of well drained versus less well drained areas. We will present results on how the spatial variability changed with the seasonality of soil temperatures and the water table.</p><p>The automated chambers (five chambers within each footprint of the eddy flux towers) showed higher spatial variability for CH<sub>4</sub> fluxes than for CO<sub>2</sub> with higher CH<sub>4</sub> emissions in the wetter plots furthest away from ditches, i.e. CH<sub>4</sub> fluxes correlate well to ground water depth at both sites. N<sub>2</sub>O emissions were observed in short events during the early summer season. Overall, there was a good alignment of fluxes measured with eddy flux and chamber technologies.</p><p>Information on factors that constrain the spatio-temporal variability are important for estimating areal GHG budgets and for predicting possible effects of peatland management, such as draining or re-wetting on the climate effects from these ecosystems.  From the results, we expect higher effects of peatland restoration on GHG budgets in the South site.</p>


2004 ◽  
Author(s):  
Dennis L. Corwin ◽  
Scott M. Lesch ◽  
Peter J. Shouse ◽  
Richard Soppe ◽  
James E. Ayars

2009 ◽  
Vol 13 (9) ◽  
pp. 1635-1648 ◽  
Author(s):  
E. A. C. Costantini ◽  
S. Pellegrini ◽  
P. Bucelli ◽  
P. Storchi ◽  
N. Vignozzi ◽  
...  

Abstract. The adoption of precision agriculture in viticulture could be greatly enhanced by the diffusion of straightforward and easy to be applied hydropedological models, able to predict the spatial variability of available soil water. The Lin's and Host hydropedological models were applied to standard soil series descriptions and hillslope position, to predict the distribution of hydrological functional units in two vineyard and their relevance for grape yield and wine quality. A three-years trial was carried out in Chianti (Central Italy) on Sangiovese. The soils of the vineyards differentiated in structure, porosity and related hydropedological characteristics, as well as in salinity. Soil spatial variability was deeply affected by earth movement carried out before vine plantation. Six plots were selected in the different hydrological functional units of the two vineyards, that is, at summit, backslope and footslope morphological positions, to monitor soil hydrology, grape production and wine quality. Plot selection was based upon a cluster analysis of local slope, topographic wetness index (TWI), and cumulative moisture up to the root limiting layer, appreciated by means of a detailed combined geophysical survey. Water content, redox processes and temperature were monitored, as well as yield, phenological phases, and chemical analysis of grapes. The isotopic ratio δ13C was measured in the wine ethanol upon harvesting to evaluate the degree of stress suffered by vines. The grapes in each plot were collected for wine making in small barrels. The wines obtained were analysed and submitted to a blind organoleptic testing. The results demonstrated that the combined application of the two hydropedological models can be used for the prevision of the moisture status of soils cultivated with grape during summertime in Mediterranean climate. As correctly foreseen by the models, the amount of mean daily transpirable soil water (TSW) during the growing season differed considerably between the vineyards and increased significantly along the three positions on slope in both vineyards. The water accumulation along slope occurred in every year, even during the very dry 2006. The installation of indicators of reduction in soils (IRIS) tubes allowed confirmation of the occurrence of reductive processes in the most shallow soil. Both Sangiovese grape yield and quality of wine were influenced by the interaction between TSW content and salinity, sometimes contrary to expectations. Therefore, the studied hydropedological models were not relevant to predict grape yield and wine quality in all the hydrological functional units. The diffusion of hydropedological models in precision viticulture could be boosted considering salinity along with topography and soil hydrological characteristics.


1988 ◽  
Vol 60 (7) ◽  
pp. 631-660
Author(s):  
Ari Ilola ◽  
Esko Elomaa ◽  
Seppo Pulli

The biological and meteorological data were collected at Jokioinen in 1982—87. Potential and actual (water limited) production of dry matter were simulated using a Danish WATCROS model for spring barley, spring turnip rape and timothy grass. The most important data of the biological programme comprised weekly measurements of the crop surface (GAI), dry matter yield, root growth, soil water content and yield analyses of the harvest. All these measurements were performed for both irrigated and non-irrigated plots. The needed meteorological parameters for the daily simulation of the dry matter yield were global radiation, air temperature and precipitation. The simulated dry matter production results with the WATCROS model were generally higher than those measured. In order to obtain a better fit into the Finnish climatic and soil conditions, the Finnish model should take soil water conditions and efficient use of photosynthetically active radiation into consideration.


2013 ◽  
Vol 12 (2) ◽  
pp. vzj2012.0182 ◽  
Author(s):  
Ole Wendroth ◽  
Susmitha Nambuthiri ◽  
R. Jason Walton

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