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Sampled soil volume is a main experimental factor which must be properly considered to obtain a reliable estimation of soil physical quality (SPQ) and, thus, to obtain credible evaluation of the impact of a conservative-conventional soil management system on the soil air–water relationship. In this investigation, two ring sizes were used to sample two fine textured soils and soil management for durum wheat cultivation, namely, conventional tillage (CT) and no-tillage (NT). The soil water retention was determined; soil bulk density (BD), macroporosity (MACpor), air capacity (AC), and relative field capacity (RFC) were estimated to assess the soil physical quality indicators, in agreement with the guidelines suggested in the literature. The main results showed that the sampling volume for the soil affected the soil water retention estimation (θ) and, consequently, affected the SPQ estimation, given that (i) higher θ values (by a factor 1.11 as mean) were generally obtained with a large diameter than a small one; these differences decreased (by a factor 1.20, 1.10 and 1.03) as the imposed pressure head value decreased (respectively, at h = 0, −10 and −100 cm); (ii) among SPQ indicators considered, soil volume samples seemed to impact the BD–RFC estimation more than AC–MACpor, as statistical differences were identified only in the former case; iii) NT soil was significantly more compact, and had lower macroporosity or air capacity, when compared with CT; at the time of sampling, the mean SPQ was always poor for AC–RFC, or optimal for BD, regardless of soil management, and it was intermediate or poor when the MACpor was evaluated under CT or NT. This study contributes toward understanding the impact of soil management on soil physical properties in Mediterranean agro-environments.
Mirko Castellini; Luisa Giglio; Francesca Modugno. Sampled Soil Volume Effect on Soil Physical Quality Determination: A Case Study on Conventional Tillage and No-Tillage of the Soil under Winter Wheat. Soil Systems 2020, 4, 72 .
AMA StyleMirko Castellini, Luisa Giglio, Francesca Modugno. Sampled Soil Volume Effect on Soil Physical Quality Determination: A Case Study on Conventional Tillage and No-Tillage of the Soil under Winter Wheat. Soil Systems. 2020; 4 (4):72.
Chicago/Turabian StyleMirko Castellini; Luisa Giglio; Francesca Modugno. 2020. "Sampled Soil Volume Effect on Soil Physical Quality Determination: A Case Study on Conventional Tillage and No-Tillage of the Soil under Winter Wheat." Soil Systems 4, no. 4: 72.
The conversion from conventional tillage (CT) to no-tillage (NT) of the soil is often suggested for positive long-term effects on several physical and hydraulic soil properties. In fact, although shortly after the conversion a worsening of the soil may occur, this transition should evolve in a progressive improvement of soil properties. Therefore, investigations aiming at evaluating the effects of NT on porous media are advisable, since such information may be relevant to better address the farmers’ choices to this specific soil conservation management strategy. In this investigation, innovative and standard methods were applied to compare CT and NT on two farms where the conversion took place 6 or 24 years ago, respectively. Regardless of the investigated farm, results showed negligible differences in cumulative infiltration or infiltration rate, soil sorptivity, saturated hydraulic conductivity, conductive pores size, or hydraulic conductivity functions. Since relatively small discrepancies were also highlighted in terms of bulk density or soil organic carbon, it was possible to conclude that NT did not have a negative impact on the main physical and hydraulic properties of investigated clay soils. However, a significantly higher number of small pores was detected under long-term NT compared to CT, so we concluded that the former soil was a more conductive pore system, i.e., consisting of numerous relatively smaller pores but continuous and better interconnected. Based on measured capacity-based indicators (macroporosity, air capacity, relative field capacity, plant available water capacity), NT always showed a more appropriate proportion of water and air in the soil.
Mirko Castellini; Francesco Fornaro; Pasquale Garofalo; Luisa Giglio; Michele Rinaldi; Domenico Ventrella; Carolina Vitti; Alessandro Vittorio Vonella. Effects of No-Tillage and Conventional Tillage on Physical and Hydraulic Properties of Fine Textured Soils under Winter Wheat. Water 2019, 11, 484 .
AMA StyleMirko Castellini, Francesco Fornaro, Pasquale Garofalo, Luisa Giglio, Michele Rinaldi, Domenico Ventrella, Carolina Vitti, Alessandro Vittorio Vonella. Effects of No-Tillage and Conventional Tillage on Physical and Hydraulic Properties of Fine Textured Soils under Winter Wheat. Water. 2019; 11 (3):484.
Chicago/Turabian StyleMirko Castellini; Francesco Fornaro; Pasquale Garofalo; Luisa Giglio; Michele Rinaldi; Domenico Ventrella; Carolina Vitti; Alessandro Vittorio Vonella. 2019. "Effects of No-Tillage and Conventional Tillage on Physical and Hydraulic Properties of Fine Textured Soils under Winter Wheat." Water 11, no. 3: 484.
The accurate estimation of crop grain nitrogen (N; N in grain yield) is crucial for optimizing agricultural N management, especially in crop rotations. In the present study, 12 process-based models were applied to simulate the grain N of i) seven crops in rotations, ii) across various pedo-climatic and agro-management conditions in Europe, iii) under both continuous simulation and single year simulation, and for iv) two calibration levels, namely minimal and detailed calibration. Generally, the results showed that the accuracy of the simulations in predicting grain N increased under detailed calibration. The models performed better in predicting the grain N of winter wheat (Triticum aestivum L.), winter barley (Hordeum vulgare L.) and spring barley (Hordeum vulgare L.) compared to spring oat (Avena sativa L.), winter rye (Secale cereale L.), pea (Pisum sativum L.) and winter oilseed rape (Brassica napus L.). These differences are linked to the intensity of parameterization with better parameterized crops showing lower prediction errors. The model performance was influenced by N fertilization and irrigation treatments, and a majority of the predictions were more accurate under low N and rainfed treatments. Moreover, the multi-model mean provided better predictions of grain N compared to any individual model. In regard to the Individual models, DAISY, FASSET, HERMES, MONICA and STICS are suitable for predicting grain N of the main crops in typical European crop rotations, which all performed well in both continuous simulation and single year simulation. Our results show that both the model initialization and the cover crop effects in crop rotations should be considered in order to achieve good performance of continuous simulation. Furthermore, the choice of either continuous simulation or single year simulation should be guided by the simulation objectives (e.g. grain yield, grain N content or N dynamics), the crop sequence (inclusion of legumes) and treatments (rate and type of N fertilizer) included in crop rotations and the model formalism
Xiaogang Yin; Kurt Christian Kersebaum; Chris Kollas; Kiril Manevski; Sanmohan Baby; Nicolas Beaudoin; Isik Öztürk; Thomas Gaiser; Lianhai Wu; Munir Hoffmann; Monia Charfeddine; Tobias Conradt; Julie Constantin; Frank Ewert; Iñaki Garcia De Cortazar-Atauri; Luisa Giglio; Petr Hlavinka; Holger Hoffmann; Marie Launay; Gaëtan Louarn; Remy Manderscheid; Bruno Mary; Wilfried Mirschel; Claas Nendel; Andreas Siegfried Pacholski; Taru Palosuo; Dominique Ripoche-Wachter; Reimund Rötter; Françoise Ruget; Behzad Sharif; Mirek Trnka; Domenico Ventrella; Hans-Joachim Weigel; Jørgen E. Olesen. Performance of process-based models for simulation of grain N in crop rotations across Europe. Agricultural Systems 2017, 154, 63 -77.
AMA StyleXiaogang Yin, Kurt Christian Kersebaum, Chris Kollas, Kiril Manevski, Sanmohan Baby, Nicolas Beaudoin, Isik Öztürk, Thomas Gaiser, Lianhai Wu, Munir Hoffmann, Monia Charfeddine, Tobias Conradt, Julie Constantin, Frank Ewert, Iñaki Garcia De Cortazar-Atauri, Luisa Giglio, Petr Hlavinka, Holger Hoffmann, Marie Launay, Gaëtan Louarn, Remy Manderscheid, Bruno Mary, Wilfried Mirschel, Claas Nendel, Andreas Siegfried Pacholski, Taru Palosuo, Dominique Ripoche-Wachter, Reimund Rötter, Françoise Ruget, Behzad Sharif, Mirek Trnka, Domenico Ventrella, Hans-Joachim Weigel, Jørgen E. Olesen. Performance of process-based models for simulation of grain N in crop rotations across Europe. Agricultural Systems. 2017; 154 ():63-77.
Chicago/Turabian StyleXiaogang Yin; Kurt Christian Kersebaum; Chris Kollas; Kiril Manevski; Sanmohan Baby; Nicolas Beaudoin; Isik Öztürk; Thomas Gaiser; Lianhai Wu; Munir Hoffmann; Monia Charfeddine; Tobias Conradt; Julie Constantin; Frank Ewert; Iñaki Garcia De Cortazar-Atauri; Luisa Giglio; Petr Hlavinka; Holger Hoffmann; Marie Launay; Gaëtan Louarn; Remy Manderscheid; Bruno Mary; Wilfried Mirschel; Claas Nendel; Andreas Siegfried Pacholski; Taru Palosuo; Dominique Ripoche-Wachter; Reimund Rötter; Françoise Ruget; Behzad Sharif; Mirek Trnka; Domenico Ventrella; Hans-Joachim Weigel; Jørgen E. Olesen. 2017. "Performance of process-based models for simulation of grain N in crop rotations across Europe." Agricultural Systems 154, no. : 63-77.
Crop productivity and water consumption form the basis to calculate the water footprint (WF) of a specific crop. Under current climate conditions, calculated evapotranspiration is related to observed crop yields to calculate WF. The assessment of WF under future climate conditions requires the simulation of crop yields adding further uncertainty. To assess the uncertainty of model based assessments of WF, an ensemble of crop models was applied to data from five field experiments across Europe. Only limited data were provided for a rough calibration, which corresponds to a typical situation for regional assessments, where data availability is limited. Up to eight models were applied for wheat. The coefficient of variation for the simulated actual evapotranspiration between models was in the range of 13%–19%, which was higher than the inter-annual variability. Simulated yields showed a higher variability between models in the range of 17%–39%. Models responded differently to elevated CO2 in a FACE (Free-Air Carbon Dioxide Enrichment) experiment, especially regarding the reduction of water consumption. The variability of calculated WF between models was in the range of 15%–49%. Yield predictions contributed more to this variance than the estimation of water consumption. Transpiration accounts on average for 51%–68% of the total actual evapotranspiration.
Kurt Christian Kersebaum; Joop Kroes; Anne Gobin; Jozef Takáč; Petr Hlavinka; Miroslav Trnka; Domenico Ventrella; Luisa Giglio; Roberto Ferrise; Marco Moriondo; Anna Dalla Marta; Qunying Luo; Josef Eitzinger; Wilfried Mirschel; Hans-Joachim Weigel; Remy Manderscheid; Munir Hoffmann; Pavol Nejedlik; Muhammad Anjum Iqbal; Johannes Hösch. Assessing Uncertainties of Water Footprints Using an Ensemble of Crop Growth Models on Winter Wheat. Water 2016, 8, 571 .
AMA StyleKurt Christian Kersebaum, Joop Kroes, Anne Gobin, Jozef Takáč, Petr Hlavinka, Miroslav Trnka, Domenico Ventrella, Luisa Giglio, Roberto Ferrise, Marco Moriondo, Anna Dalla Marta, Qunying Luo, Josef Eitzinger, Wilfried Mirschel, Hans-Joachim Weigel, Remy Manderscheid, Munir Hoffmann, Pavol Nejedlik, Muhammad Anjum Iqbal, Johannes Hösch. Assessing Uncertainties of Water Footprints Using an Ensemble of Crop Growth Models on Winter Wheat. Water. 2016; 8 (12):571.
Chicago/Turabian StyleKurt Christian Kersebaum; Joop Kroes; Anne Gobin; Jozef Takáč; Petr Hlavinka; Miroslav Trnka; Domenico Ventrella; Luisa Giglio; Roberto Ferrise; Marco Moriondo; Anna Dalla Marta; Qunying Luo; Josef Eitzinger; Wilfried Mirschel; Hans-Joachim Weigel; Remy Manderscheid; Munir Hoffmann; Pavol Nejedlik; Muhammad Anjum Iqbal; Johannes Hösch. 2016. "Assessing Uncertainties of Water Footprints Using an Ensemble of Crop Growth Models on Winter Wheat." Water 8, no. 12: 571.