Economic and environmental evaluation of site-specific tillage in a maize crop in NE Italy

Science of The Total Environment

Cammarano

et al. 2016

Self Cite

144

Agronomic input and management practices have traditionally been applied uniformly on agricultural fields despite the presence of spatial variability of soil properties and landscape position. When spatial variability is ignored, uniform agronomic management can be both economically and environmentally inefficient. The objectives of this study were to: i) identify optimal N fertilizer rates using an integrated spatio-temporal analysis of yield and site-specific N rate response; ii) test the sensitivity of site specific N management to nitrate leaching in response to different N rates; and iii) demonstrate the environmental benefits of variable rate N fertilizer in a Nitrate Vulnerable Zone. This study was carried out on a 13.6 ha field near the Venice Lagoon, northeast Italy over four years (2005–2008). We utilized a validated crop simulation model to evaluate crop response to different N rates at specific zones in the field based on localized soil and landscape properties under rainfed conditions. The simulated rates were: 50 kg N ha− 1 applied at sowing for the entire study area and increasing fractions, ranging from 150 to 350 kg N ha− 1 applied at V6 stage. Based on the analysis of yield maps from previous harvests and soil electrical resistivity data, three management zones were defined. Two N rates were applied in each of these zones, one suggested by our simulation analysis and the other with uniform N fertilization as normally applied by the producer. N leaching was lower and net revenue was higher in the zones where variable rates of N were applied when compared to uniform N fertilization. This demonstrates the efficacy of using crop models to determine variable rates of N fertilization within a field and the application of variable rate N fertilizer to achieve higher profit and reduce nitrate leaching

Section: Discussionmentioning

confidence: 85%

Section: Crop Growth Model and Simulation Scenariosmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Environmental and economic benefits of variable rate nitrogen fertilization in a nitrate vulnerable zone

Basso

Science of The Total Environment

Cammarano

et al. 2016

Self Cite

144

“…SALUS has been widely used (Basso and Ritchie, 2015) and successfully validated for Italian agricultural systems and environmental conditions by Basso et al (2007Basso et al ( , 2010Basso et al ( , 2011Basso et al ( , 2011bBasso et al ( , 2016.…”

Section: The Salus Modelmentioning

confidence: 99%

Evaluating the impact of soil conservation measures on soil organic carbon at the farm scale

Pezzuolo

Computers and Electronics in Agriculture

Sartori

et al. 2017

Self Cite

a b s t r a c tNo-tillage (NT) is considered the least invasive conservation agriculture technique and has shown to be the effective in increasing soil C stocks, and reducing losses compared to others tillage systems. In Italy, the Veneto Region was the first to establish a subsidies scheme aimed at promoting the adoption of NT practices. This program encourages farmers to perform direct seeding, alternate autumn and winter crops and maintain soil cover throughout the year by leaving crop residues or sowing cover crops.The goals of this study were to: (i) compare the CO 2 emission and soil C sequestration patterns of agricultural soils under CT and NT management practices in the Veneto region and (ii) analyse the potential mid-term benefits (2010-2025) of NT management in terms of soil organic C dynamics and CO 2 balance. Agronomic data and soil organic carbon levels were measured from 2010 to 2014 in eight farms in the Veneto region that had adopted CT and NT techniques. Field measurements were used to calibrate first and then validate the SALUS model to compare the mid-term impact of CT and NT practices using climate projections. SOC carbon pools in the model were initialized using the procedure described in Basso et al. (2011c). This is the first study to employ a model using such an extensive dataset at the farm level to assess the CT and NT strategies within this region.Results of this research will assist farmers and policy makers in the region to define the tillage systems most suited to improve soil C stocks and thereby minimize CO 2 emissions from agricultural soils. Overall, simulations indicated that SOC stocks can decrease under both CT and NT regimes, however SOC oxidation rates were substantially lower under NT. Critically, the greatest reduction in CO 2 emission was observed when NT was adopted in soil with high levels of SOM. This highlights the benefits of NT adoption in terms of soil fertility preservation and CO 2 emissions mitigation.

“…The optimum N fertilization is known to vary within the same field and with each growing season as a result of the heterogeneity of soil properties, as well as inter-and intra-annual climatic patterns (Basso et al, 2012b). Furthermore, the decision-making process linked to N management remains complex because even if a spatial map of soil properties exists, the decision regarding the amount of N fertilizer to apply must be made without any prior knowledge of future weather conditions (Basso et al, 2011b). Consequently, experimentally determining how plant characteristics, either individually or in combination, affect crop performance under a wide range of growing conditions is an intractable task (Hoogeboom et al, 2004).…”

Section: Introductionmentioning

confidence: 99%

Assessing and modeling economic and environmental impact of wheat nitrogen management in Belgium

Environmental Modelling & Software

Basso

Bodson

et al. 2016

a b s t r a c tFuture progress in wheat yield will rely on identifying genotypes and management practices better adapted to the fluctuating environment. Nitrogen (N) fertilization is probably the most important practice impacting crop growth. However, the adverse environmental impacts of inappropriate N management (e.g., lixiviation) must be considered in the decision-making process. A formal decisional algorithm was developed to tactically optimize the economic and environmental N fertilization in wheat. Climatic uncertainty analysis was performed using stochastic weather time-series (LARS-WG). Crop growth was simulated using STICS model. Experiments were conducted to support the algorithm recommendations: winter wheat was sown between 2008 and 2014 in a classic loamy soil of the Hesbaye Region, Belgium (temperate climate). Results indicated that, most of the time, the third N fertilization applied at flag-leaf stage by farmers could be reduced. Environmental decision criterion is most of the time the limiting factor in comparison to the revenues expected by farmers.