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Prof. Alessia Perego
Department of Agricultural and Environmental Sciences, University of Milan, Italy

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0 soil organic carbon
0 Conservation agriculture
0 Nitrate Leaching
0 Crop Modeling
0 N<sub>2</sub>O emissions

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soil organic carbon
Conservation agriculture
Nitrate Leaching
N<sub>2</sub>O emissions

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Short Biography

Alessia Perego is an associate professor in Field Crops and Experimental at the University of Milan since 2020. She has expertise in modelling and monitoring of agro-environmental variables (crop yield, nitrate leaching, ammonia and nitrous oxide emissions, soil organic carbon) in conventional and conservation agriculture. Her research activity mainly concerns the experimental and modeling evaluation of the agronomic management of cropping systems and the strategies that can be implemented to minimize their impact on the agroecosystem.

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Journal article
Published: 19 July 2021 in Sustainability
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Proximal sensing represents a growing avenue for precision fertilization and crop growth monitoring. In the last decade, precision agriculture technology has become affordable in many countries; Global Positioning Systems for automatic guidance instruments and proximal sensors can be used to guide the distribution of nutrients such as nitrogen (N) fertilization using real-time applications. A two-year field experiment (2017–2018) was carried out to quantify maize yield in response to variable rate (VR) N distribution, which was determined with a proximal vigour sensor, as an alternative to a fixed rate (FR) in a cereal-livestock farm located in the Po valley (northern Italy). The amount of N distributed for the FR (140 kg N ha−1) was calculated according to the crop requirement and the regional regulation: ±30% of the FR rate was applied in the VR treatment according to the Vigour S-index calculated on-the-go from the CropSpec sensor. The two treatments of N fertilization did not result in a significant difference in yield in both years. The findings suggest that the application of VR is more economically profitable than the FR application rate, especially under the hypothesis of VR application at a farm scale. The outcome of the experiment suggests that VR is a viable and profitable technique that can be easily applied at the farm level by adopting proximal sensors to detect the actual crop N requirement prior to stem elongation. Besides the economic benefits, the VR approach can be regarded as a sustainable practice that meets the current European Common Agricultural Policy.

ACS Style

Calogero Schillaci; Tommaso Tadiello; Marco Acutis; Alessia Perego. Reducing Topdressing N Fertilization with Variable Rates Does Not Reduce Maize Yield. Sustainability 2021, 13, 8059 .

AMA Style

Calogero Schillaci, Tommaso Tadiello, Marco Acutis, Alessia Perego. Reducing Topdressing N Fertilization with Variable Rates Does Not Reduce Maize Yield. Sustainability. 2021; 13 (14):8059.

Chicago/Turabian Style

Calogero Schillaci; Tommaso Tadiello; Marco Acutis; Alessia Perego. 2021. "Reducing Topdressing N Fertilization with Variable Rates Does Not Reduce Maize Yield." Sustainability 13, no. 14: 8059.

Journal article
Published: 07 June 2021 in Carbon Balance and Management
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Background Legacy data are unique occasions for estimating soil organic carbon (SOC) concentration changes and spatial variability, but their use showed limitations due to the sampling schemes adopted and improvements may be needed in the analysis methodologies. When SOC changes is estimated with legacy data, the use of soil samples collected in different plots (i.e., non-paired data) may lead to biased results. In the present work, N = 302 georeferenced soil samples were selected from a regional (Sicily, south of Italy) soil database. An operational sampling approach was developed to spot SOC concentration changes from 1994 to 2017 in the same plots at the 0–30 cm soil depth and tested. Results The measurements were conducted after computing the minimum number of samples needed to have a reliable estimate of SOC variation after 23 years. By applying an effect size based methodology, 30 out of 302 sites were resampled in 2017 to achieve a power of 80%, and an α = 0.05. A Wilcoxon test applied to the variation of SOC from 1994 to 2017 suggested that there was not a statistical difference in SOC concentration after 23 years (Z = − 0.556; 2-tailed asymptotic significance = 0.578). In particular, only 40% of resampled sites showed a higher SOC concentration than in 2017. Conclusions This finding contrasts with a previous SOC concentration increase that was found in 2008 (75.8% increase when estimated as differences of 2 models built with non-paired data), when compared to 1994 observed data (Z = − 9.119; 2-tailed asymptotic significance < 0.001). This suggests that the use of legacy data to estimate SOC concentration dynamics requires soil resampling in the same locations to overcome the stochastic model errors. Further experiment is needed to identify the percentage of the sites to resample in order to align two legacy datasets in the same area.

ACS Style

Calogero Schillaci; Sergio Saia; Aldo Lipani; Alessia Perego; Claudio Zaccone; Marco Acutis. Validating the regional estimates of changes in soil organic carbon by using the data from paired-sites: the case study of Mediterranean arable lands. Carbon Balance and Management 2021, 16, 1 -15.

AMA Style

Calogero Schillaci, Sergio Saia, Aldo Lipani, Alessia Perego, Claudio Zaccone, Marco Acutis. Validating the regional estimates of changes in soil organic carbon by using the data from paired-sites: the case study of Mediterranean arable lands. Carbon Balance and Management. 2021; 16 (1):1-15.

Chicago/Turabian Style

Calogero Schillaci; Sergio Saia; Aldo Lipani; Alessia Perego; Claudio Zaccone; Marco Acutis. 2021. "Validating the regional estimates of changes in soil organic carbon by using the data from paired-sites: the case study of Mediterranean arable lands." Carbon Balance and Management 16, no. 1: 1-15.

Review
Published: 04 March 2021
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Mediterranean and humid subtropical climate is characterized by hot summer and cold to mild winter with a medium-low soil organic carbon (SOC) content and high risk of land desertification. Recent EU policies pointed out the need to preserve the SOC stock and to enhance its accumulation by promoting the adoption of conservation agriculture (CA) as an efficient action for climate change adaptation and mitigation. The meta-analysis is a powerful data analysis tool, which can be useful to evaluate the effectiveness of CA in increase SOC in comparison with conventional agriculture. In fact, this topic has been addressed by several published articles even though the methodology shortcomings make sometimes difficult to draw reliable conclusions about the contribution of CA. In our work, we applied a robust methodology to comply with the meta-analytic assumptions, such as an independence of effect sizes and weighting, as well as the requirement to use no predictive functions like pedotransfer. Therefore, the present meta-analysis defines a conservative and replicable approach to deal with soil carbon data, explaining the differences between conventional (control) and CA management (treatment) in terms of SOC stock accumulation in the first 0-0.3 m layer. A defined methodology was developed to summarize carbon data within a unique soil layer taking into account the real variance and correlation between different initial soil carbon layers. A final database of 49 studies has been used to summarize the effect and to explain the heterogeneity across studies, including also several pedoclimatic moderators in the analysis. An overall positive effect of about 13 % change in SOC accumulation was found due to CA practices compared to control. To better explain the data variability, we created two different groups of studies ("low carbon in control, LC" and "high carbon in control", HC) base on the amount of SOC in control (with 40 Mg ha-1 as a threshold). This method leads to more reliable conclusions that it is more likely to find a response to CA management in soil with low carbon content rather than in soil that have more than 40 t C stock ha-1 . A positive correlation was also found between clay soils with high carbon content in control and carbon sequestration event though the texture classification did not explain data variability. Agronomic management plays an essential role in inducing C accumulation under CA in both LC and HC groups, especially with high residue retention during long-term experiments (0.21 Mg C ha-1 yr-1 for the whole database). We also found that climatic and geographical moderators can explain the variability among the effect sizes, like the absolute value of latitude or the precipitation during the year, even though the different continent or climate Köppen classification did not give significant results.

ACS Style

Tommaso Tadiello; Marco Acutis; Alessia Perego; Calogero Schillaci; Elena Valkama. Can Conservation Agriculture Enhance Soil Organic Carbon Sequestration In Mediterranean And Humid Subtropical Climates? A Meta-Analysis. 2021, 1 .

AMA Style

Tommaso Tadiello, Marco Acutis, Alessia Perego, Calogero Schillaci, Elena Valkama. Can Conservation Agriculture Enhance Soil Organic Carbon Sequestration In Mediterranean And Humid Subtropical Climates? A Meta-Analysis. . 2021; ():1.

Chicago/Turabian Style

Tommaso Tadiello; Marco Acutis; Alessia Perego; Calogero Schillaci; Elena Valkama. 2021. "Can Conservation Agriculture Enhance Soil Organic Carbon Sequestration In Mediterranean And Humid Subtropical Climates? A Meta-Analysis." , no. : 1.

Preprint content
Published: 04 March 2021
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Legacy data are frequently unique sources of data for the estimation of past soil properties. With the rising concerns about greenhouse gases (GHG) emission and soil degradation due to intensive agriculture and climate change effects, soil organic carbon (SOC) concentration might change heavily over time.

When SOC changes is estimated with legacy data, the use of soil samples collected in different plots (i.e., non-aligned data) may lead to biased results. The sampling schemes adopted to capture SOC variation usually involve the resampling of the original sample using a so called paired-site approach.

In the present work, a regional (Sicily, south of Italy) soil database, consisting of N=302 georeferenced soil samples from arable land collected in 1993 [1], was used to select coinciding sites to test a former temporal variation (1993-2008) obtained by a comparison of models built with data sampled in non-coinciding locations [2]. A specific sampling strategy was developed to spot SOC concentration changes from 1994 to 2017 in the same plots at the 0-30 cm soil depth and tested.

To spot SOC changes the minimum number of samples needed to have a reliable estimate of SOC variation after 23 years has been estimated. By applying an effect size based methodology, 30 out of 302 sites were resampled in 2017 to achieve a power of 80%, and an a=0.05.

After the collection of the 30 samples, SOC concentration in the newly collected samples was determined in lab using the same method

A Wilcoxon test applied to the variation of SOC from 1994 to 2017 suggested that there was not a statistical difference in SOC concentration after 23 years (Z = -0.556; 2-tailed asymptotic significance = 0.578). In particular, only 40% of resampled sites showed a higher (not always significant) SOC concentration than in 2017.

This finding contrasts with a previous SOC concentration increase that was found in 2008 (75.8% increase when estimated as differences of 2 models built with non-aligned data) [2], when compared to 1994 observed data (Z = -9.119; 2-tailed asymptotic significance < 0.001).

Such a result implies that the use of legacy data to estimate SOC concentration changes need soil resampling in the same locations to overcome the stochastic model errors. Further experiment is needed to identify the percentage of the sites to resample in order to align two legacy datasets in the same area.

Bibliography

[1]Schillaci C, et al.,2019. A simple pipeline for the assessment of legacy soil datasets: An example and test with soil organic carbon from a highly variable area. CATENA.

[2]Schillaci C, et al., 2017. Spatio-temporal topsoil organic carbon mapping of a semi-arid Mediterranean region: The role of land use, soil texture, topographic indices and the influence of remote sensing data to modelling. Sci Total Environ. 

ACS Style

Calogero Schillaci; Sergio Saia; Aldo Lipani; Alessia Perego; Claudio Zaccone; Marco Acutis. Matching legacy estimation of soil organic carbon changes from non-paired data with measured values in paired soil samples after two decades: a case study. 2021, 1 .

AMA Style

Calogero Schillaci, Sergio Saia, Aldo Lipani, Alessia Perego, Claudio Zaccone, Marco Acutis. Matching legacy estimation of soil organic carbon changes from non-paired data with measured values in paired soil samples after two decades: a case study. . 2021; ():1.

Chicago/Turabian Style

Calogero Schillaci; Sergio Saia; Aldo Lipani; Alessia Perego; Claudio Zaccone; Marco Acutis. 2021. "Matching legacy estimation of soil organic carbon changes from non-paired data with measured values in paired soil samples after two decades: a case study." , no. : 1.

Preprint content
Published: 23 March 2020
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Barley is a widespread crop in the Mediterranean area and in temperate climates. Barley impact in the food chain is very important for its value as food and feed. The societal demand is for more productive varieties, which can be able to cope with the current and future climate scenarios. Change in climate is expected to result in more adverse conditions for the barley growth and alter land suitability in its growing regions, such as the Mediterranean basin. In this context, laboratory and modelling activities for the so-called “in silico ideotyping” can be effectively carried out to design new germplasms and to define optimal field management practices. As a first step to reach this objective, we collate the available scientific research about the identification of optimal phenotypic traits for the adaptation to harsh environments. In the framework of the GENDIBAR project (Utilization of local genetic diversity for studying barley adaptation to harsh environments and for pre-breeding; PRIMA European Funding Programme), a bibliometric analysis was carried out in the SCOPUS database with the aim to find published papers about barley adaptation in relation to changing climate. The initial query was (barley AND climate AND adaptation); it contained few keywords and resulted in less than 200 publications. By adding (barley AND ideotyping OR barley AND phenotyping), the search reached 450 records. The most comprehensive search was achieved by adding another OR condition (Barley AND future climate OR climate change) that yielded more than 1000 results. Although these records seemed relevant, a deeper analysis showed that less than 5% of these studies are of real interest and moreover the manual screening of the abstracts of all records will require around a month of work. The second query represents a compromise between the simplest query (barley AND climate AND adaptation) and the last query made by three conditions bonded together. This literature search approach highlighted the results of manipulative experiments and modelling studies for deriving phenotyping and agronomic traits to address in-silico ideotyping design. However, the search outcome suggests that there is a gap of knowledge about the barley phenotypic traits needed to cope with climate change in the semi-arid and arid regions of the Mediterranean basin. This approach is expected to further provide useful information for the development of land suitability models, as well as for barley breeding.

ACS Style

Agostino Fricano; Erica Mica; Raffaella Battaglia; Alessandro Tondelli; Calogero Schillaci; Alessia Perego. Barley ideotyping for the adaptation to heat stress in the Mediterranean basin. A bibliometric search approach. 2020, 1 .

AMA Style

Agostino Fricano, Erica Mica, Raffaella Battaglia, Alessandro Tondelli, Calogero Schillaci, Alessia Perego. Barley ideotyping for the adaptation to heat stress in the Mediterranean basin. A bibliometric search approach. . 2020; ():1.

Chicago/Turabian Style

Agostino Fricano; Erica Mica; Raffaella Battaglia; Alessandro Tondelli; Calogero Schillaci; Alessia Perego. 2020. "Barley ideotyping for the adaptation to heat stress in the Mediterranean basin. A bibliometric search approach." , no. : 1.

Preprint content
Published: 23 March 2020
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Conservation agriculture (CA) involves complex and interactive processes that ultimately determine soil C storage, making it difficult to identify clear patterns, particularly, when the results originate from many experimental studies. To solve these problems, we used the ARMOSA process-based crop model to simulate the contribution of different CA components (minimum soil disturbance, permanent soil cover with crop residues and/or cover crops, and diversification of plant species) to soil organic carbon (SOC) sequestration at 0-30 cm soil depth and to compare it with SOC evolution under conventional agricultural practices. We simulated SOC changes in two sites located in Central Asia (Almalybak, Kazakhstan) and Southern Europe (Lombriasco, Italy), which have contrasting soils, organic carbon contents, climates, crops and management intensity.  Simulations were carried out for the current (1998-2017) and future climatic scenarios (period 2020-2040, scenario Representative Concentration Pathway 6.0).

Five cropping systems were simulated: conventional systems under ploughing at 25-30 cm with monoculture and  residues removed (Conv–R) or residues retained (Conv+R); no-tillage (NT) with residue retained and crop monocultures; CA and CA with a cover crop, Italian ryegrass (CA+CC). In Conv–R, Conv+R and NT, the simulated monocultures were spring barley in Almalybak and maize in Lombriasco. In CA and CA+CC, crop rotations were winter wheat - winter wheat - spring barley - chickpea in Almalybak; maize - winter wheat - soybean in Lombriasco, together with Italian ryegrass in the +CC options.

In Lombriasco, conventional systems led to SOC decline of 170-350 kg ha-1 yr-1, whereas, NT and CA prevented the decline and kept it on the slightly positive level under both climate scenarios. A low rate of SOC increase most likely stems from, in addition to climates, the low silt-clay fraction (34%), and thus, more vulnerable to mineralization and decay.

In Almalybak, SOC loss in conventional systems was 480-560 kg ha-1 yr-1 under current climate, and NT prevented the loss only under current climate, but not under the future climate scenario. In contrast, CA allowed for the annual C sequestration of 300 kg ha-1 and up to 620 kg ha-1 with cover crops. Under the future climate scenario, the model predicted somewhat less C sequestration under CA, probably, due to the reduction of residue biomass. Particularly, in Southern Kazakhstan, CA has the largest potential for C sequestration under both climate scenarios, twice exceeding the objectives of the “4 per 1000” initiative. This initiative claims that an annual growth rate of 0.4% in the soil carbon stocks, or 4‰ per year, in the first 30-40 cm of soil, would significantly reduce the CO2 concentration in the atmosphere related to human activities.

ACS Style

Marco Acutis; Elena Valkama; Gulya Kunypiyaeva; Muratbek Karabayev; Rauan Zhapayev; Erbol Zhusupbekov; Alessia Perego; Calogero Schillaci; Dario Sacco; Barbara Moretti; Carlo Grignani. SOC modelling and cropping system managements in contrasting climatic conditions. 2020, 1 .

AMA Style

Marco Acutis, Elena Valkama, Gulya Kunypiyaeva, Muratbek Karabayev, Rauan Zhapayev, Erbol Zhusupbekov, Alessia Perego, Calogero Schillaci, Dario Sacco, Barbara Moretti, Carlo Grignani. SOC modelling and cropping system managements in contrasting climatic conditions. . 2020; ():1.

Chicago/Turabian Style

Marco Acutis; Elena Valkama; Gulya Kunypiyaeva; Muratbek Karabayev; Rauan Zhapayev; Erbol Zhusupbekov; Alessia Perego; Calogero Schillaci; Dario Sacco; Barbara Moretti; Carlo Grignani. 2020. "SOC modelling and cropping system managements in contrasting climatic conditions." , no. : 1.

Preprint content
Published: 10 March 2020
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To improve nitrogen fertilization is well known that vegetation indices can offer a picture of the nutritional status of the crop. In this study, field management information (maize sowing and harvesting dates, tillage, fertilization) and estimated vegetation indices VI (Sentinel 2 derived Leaf Area Index LAI, Normalized Difference Vegetation Index NDVI, Fraction of Photosynthetic radiation fPAR) were analysed to develop a batch-mode VIs routine to manage high dimensional temporal and spatial data for Decision Support Systems DSS in precision agriculture, and to optimize the maize N fertilization in the field. The study was carried out in maize (2017-2018) on a farm located in Mantua (northern Italy); the soil is a Vertic Calciustepts with a fine silty texture with moderate content of carbonates. A collection of Sentinel 2 images (with <25% cloud cover) were processed using Graph Processing Tool (GPT). This tool is used through the console to execute Sentinel Application Platform (SNAP) raster data operators in batch-mode. The workflow applied on the Sentinel images consisted in: resampling each band to 10m pixel size, splitting data into subsets according to the farm boundaries using Region of Interest (ROI). Biophysical Operator based on Biophysical Toolbox was used to derive LAI, fPAR for the estimation of maize vegetation indices from emergence until senescence. Yield data were acquired with a volumetric yield sensing in a combine harvester. Fertilization plans were then calculated for each field prior to the side-dressing fertilization. The routine is meant as a user-friendly tool to obtain time series of assimilated VIs of middle and high spatial resolution for field crop fertilization. It also overcomes the failures of the open source graphic user interface of SNAP. For the year 2018, yield data were related to the 34 LAI derived from Sentinel 2a products at 10 m spatial resolution (R2=0.42). This result underlined a trend that can be further studied to define a cluster strategy based on soil properties. As a further step, we will test whether spatial differences in assimilated VIs, integrated with yield data, can guide the nitrogen top-dress fertilization in quantitative way more accurately than a single image or a collection of single images.

ACS Style

Calogero Schillaci; Edoardo Tomasoni; Marco Acutis; Alessia Perego. Data assimilation of remote sensing data for farm scale maize fertilization in northern Italy. 2020, 1 .

AMA Style

Calogero Schillaci, Edoardo Tomasoni, Marco Acutis, Alessia Perego. Data assimilation of remote sensing data for farm scale maize fertilization in northern Italy. . 2020; ():1.

Chicago/Turabian Style

Calogero Schillaci; Edoardo Tomasoni; Marco Acutis; Alessia Perego. 2020. "Data assimilation of remote sensing data for farm scale maize fertilization in northern Italy." , no. : 1.

Preprint content
Published: 10 March 2020
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Conservative Agriculture (CA) practices are recognized to enhance soil organic carbon stock and in turn to mitigate the effect of climate change. One of the CA principles is to integrate cover crops (CC) into the cropping systems. The termination of CC before the cash crop sowing and the weeds control are the most critical aspects to manage in the CA. The technique currently adopted by farmers for the termination of CC implies the use of Glyphosate. However, the European Commission is currently discussing the possibility of banning the use of this herbicide due to the negative effects on human health and the agro-environment. The disk harrow (DH) or the roller-crimper (RC) can be adopted in CA as an alternative to the use of Glyphosate for the devitalization of CC, their incorporation into the soil (in the case of the disk harrow), and the reduction of weed pressure on the subsequent cash crop.

From November 2017 to October 2019, soil organic carbon (SOC, g kg-1) and crop biomass production were observed in a 2-year field experiment located in Lodi (northern Italy), in which minimum tillage (MT) has been applied for the last 5 years. The soil was loamy and SOC was 16.2 g kg-1 at the beginning of the experiment. The winter CC was barley (from November to May) and the cash crop was soybean (from June to October). The experiment consisted in three treatments replied for two consecutive years in a randomized block design: Glyphosate spray + DH + sowing + hoeing (MT-GLY); DH + sowing + hoeing (MT-ORG); RC + sod seeding (NT-ORG).

At the end of 2019, SOC resulted in a higher increase in MT-GLY (+15%) and in MT-ORG (+14%) than in NT-ORG (+6%; p<0.01). This was due to the fact that CC litter in NT-ORG was not in direct contact with soil particles and the process of immobilization was lower than in the other treatments.

Moreover, the increase in SOC resulted positively correlated to the CC biomass (2018+2019), which was significantly lower in NT-ORG. In particular, no differences of soybean and CC between the three treatments were observed at the end of 2018, but MT-GLY resulted in significantly higher CC and soybean biomass at the end of the second year (+32%, p<0.01). MT-GLY allows to stock more carbon via photosynthesis that in turn results in higher SOC content.

However, if we consider the tractor fuel consumption (for Glyphosate spray, DH, RC, hoeing), along with the biomass production, the carbon sequestration did not vary between the three treatments.

Further studies are needed for the definition of optimized field management practices to reduce the passage of machinery while increasing crop production and SOC.

ACS Style

Alessia Perego; Marco Acutis; Calogero Schillaci. Alternatives to Glyphosate in conservation agriculture: effects on carbon sequestration in a field experiment in northern Italy. 2020, 1 .

AMA Style

Alessia Perego, Marco Acutis, Calogero Schillaci. Alternatives to Glyphosate in conservation agriculture: effects on carbon sequestration in a field experiment in northern Italy. . 2020; ():1.

Chicago/Turabian Style

Alessia Perego; Marco Acutis; Calogero Schillaci. 2020. "Alternatives to Glyphosate in conservation agriculture: effects on carbon sequestration in a field experiment in northern Italy." , no. : 1.

Preprint content
Published: 10 March 2020
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Mediterranean areas are vulnerable and at high risk of desertification, although harboring high fractions of the global biodiversity. Resilience of these (agro)ecosystem strongly relies on soil preservation, and thus the reduction of both the sediment and soil organic carbon (SOC) losses. However, SOC dynamic is understudied in the Mediterranean areas, especially in the arid and semiarid regions [1].

Here we are summarizing the known and unknown of the SOC modelling in a highly variable Mediterranean area, namely Sicily (southern Italy). In addition, we highlight main research needs to increase the reliability of the estimation of the SOC change in time.

A total of 6674 soil samples were taken in various sampling campaigns from the 1993 to the 2008 from various depths (of which only 20% with soil bulk density [SBD] information) from both agricultural and forest lands on a 25,711-km2 area [2]. Such database was used for SOC modelling through various procedures including classification and regression trees (CARTs) and Least Absolute Shrinkage and Selection Operator (LASSO) [3-5].

Modelling SOC stock estimated with an already developed pedotransfer (R2 = 0,3) function for SBD consisted in a high uncertainty, with a ratio between the model mean absolute error and the modelled 90th percentile higher than 26.9%, suggesting that SBD information or its reliable prediction is a prerequisite for SOC stock modelling in these areas, especially in agricultural land. In addition, taking into account the sampling campaign almost doubled the r squared of the CART models, which on average outcompeted the kriging and LASSO methods for the prediction certainty.

When modelling the time-variation of the SOC concentration through the use of non-paired samples [5], the closer of which was few km apart, a mean SOC variation was highlighted, and the model yielded high pseudo-R2 (0.63–0.69) and low uncertainty (s.d. < 0.76 g C kg−1). However, these s.d. can be used only to highlight strong variations at a relatively low resolution (i.e. 1-km), especially if data are not collected with the same sampling scheme. The variation found in the aforementioned work [5] likely depended on a change of both the sampling scheme and land use rather than an accumulation or loss of SOC in a given land use.

Thus, measuring SOC concentration and SBD in time-paired sites appears as a prerequisite to detect a SOC change in a given land use, especially if taking into account that the most important SOC predictors throughout the experiments were rainfall and temperatures and climate change is likely to differentially affect each site. To overcome such a lack, a time paired-sampling was performed in 2017 in 30 sites in the arable land, providing evidence that the increases estimated from the 1993 to 2008 were not evident when resampling the 10% of the 1993’s sites in field with continuous arable land use.

 

Reference: [1] Schillaci et al. DOI: 10.3301/ROL.2018.68; [2] Schillaci et al. DOI: 10.1016/j.catena.2018.12.015; [3] Veronesi and Schillaci DOI: 10.1016/j.ecolind.2019.02.026; [4] Lombardo et al. DOI: 10.1016/j.geoderma.2017.12.011; [5] Schillaci et al. DOI: 10.1016/j.scitotenv.2017.05.239

ACS Style

Sergio Saia; Calogero Schillaci; Aldo Lipani; Alessia Perego; Marco Acutis. Achievements and challenges of the modelling of soil organic carbon in a highly variable Mediterranean area. 2020, 1 .

AMA Style

Sergio Saia, Calogero Schillaci, Aldo Lipani, Alessia Perego, Marco Acutis. Achievements and challenges of the modelling of soil organic carbon in a highly variable Mediterranean area. . 2020; ():1.

Chicago/Turabian Style

Sergio Saia; Calogero Schillaci; Aldo Lipani; Alessia Perego; Marco Acutis. 2020. "Achievements and challenges of the modelling of soil organic carbon in a highly variable Mediterranean area." , no. : 1.

Journal article
Published: 05 August 2019 in Agronomy
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The agricultural area in the Po Valley is prone to high nitrous oxide (N2O) emissions as it is characterized by irrigated maize-based cropping systems, high amounts of nitrogen supplied, and elevated air temperature in summer. Here, two monitoring campaigns were carried out in maize fertilized with raw digestate in a randomized block design in 2016 and 2017 to test the effectiveness of the 3, 4 DMPP inhibitor Vizura® on reducing N2O-N emissions. Digestate was injected into 0.15 m soil depth at side-dressing (2016) and before sowing (2017). Non-steady state chambers were used to collect N2O-N air samples under zero N fertilization (N0), digestate (D), and digestate + Vizura® (V). Overall, emissions were significantly higher in the D treatment than in the V treatment in both 2016 and 2017. The emission factor (EF, %) of V was two and four times lower than the EF in D in 2016 and 2017, respectively. Peaks of NO3-N generally resulted in N2O-N emissions peaks, especially during rainfall or irrigation events. The water-filled pore space (WFPS, %) did not differ between treatments and was generally below 60%, suggesting that N2O-N emissions were mainly due to nitrification rather than denitrification.

ACS Style

Marcello Ermido Chiodini; Alessia Perego; Marco Carozzi; Marco Acutis. The Nitrification Inhibitor Vizura® Reduces N2O Emissions When Added to Digestate before Injection under Irrigated Maize in the Po Valley (Northern Italy). Agronomy 2019, 9, 431 .

AMA Style

Marcello Ermido Chiodini, Alessia Perego, Marco Carozzi, Marco Acutis. The Nitrification Inhibitor Vizura® Reduces N2O Emissions When Added to Digestate before Injection under Irrigated Maize in the Po Valley (Northern Italy). Agronomy. 2019; 9 (8):431.

Chicago/Turabian Style

Marcello Ermido Chiodini; Alessia Perego; Marco Carozzi; Marco Acutis. 2019. "The Nitrification Inhibitor Vizura® Reduces N2O Emissions When Added to Digestate before Injection under Irrigated Maize in the Po Valley (Northern Italy)." Agronomy 9, no. 8: 431.

Research article
Published: 03 December 2018 in Agronomy for Sustainable Development
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Herbicide resistance is a major weed control issue that threatens the sustainability of rice cropping systems. Its epidemiology at large scale is largely unknown. Several rice weed species have evolved resistant populations in Italy, including multiple resistant ones. The study objectives were to analyze the impact in Italian rice fields of major agronomic factors on the epidemiology of herbicide resistance and to generate a large-scale resistance risk map. The Italian Herbicide Resistance Working Group database was used to generate herbicide resistance maps. The distribution of resistant weed populations resulted as not homogeneous in the area studied, with two pockets where resistance had not been detected. To verify the situation, random sampling was done in the pockets where resistance had never been reported. Based on data from 230 Italian municipalities, three different statistics, stepwise discriminant analysis, stepwise logistic regression, and neural network, were used to correlate resistance distribution in the main Italian rice growing area with seeding type, rotation rate, and soil texture. Through the integration of complaint monitoring, mapping, and neural network analyses, we prove that a high risk of resistance evolution is associated with traditional rice cropping systems with intense monoculture rates and where water-seeding is widespread. This is the first study that determines the degree of association between herbicide resistance and a few important predictors at large scale. It also demonstrates that resistance is present in areas where it had never been reported through extensive complaint monitoring. However, these resistant populations cause medium-low density infestations, likely not alarming rice farmers. This highlights the importance of integrated agronomic techniques at cropping system level to prevent the diffusion and impact of herbicide resistance or limit it to an acceptable level. The identification of concise, yet informative, agronomic predictors of herbicide resistance diffusion can significantly facilitate effective management and improve sustainability.

ACS Style

Elisa Mascanzoni; Alessia Perego; Niccolò Marchi; Laura Scarabel; Silvia Panozzo; Aldo Ferrero; Marco Acutis; Maurizio Sattin. Epidemiology and agronomic predictors of herbicide resistance in rice at a large scale. Agronomy for Sustainable Development 2018, 38, 68 .

AMA Style

Elisa Mascanzoni, Alessia Perego, Niccolò Marchi, Laura Scarabel, Silvia Panozzo, Aldo Ferrero, Marco Acutis, Maurizio Sattin. Epidemiology and agronomic predictors of herbicide resistance in rice at a large scale. Agronomy for Sustainable Development. 2018; 38 (6):68.

Chicago/Turabian Style

Elisa Mascanzoni; Alessia Perego; Niccolò Marchi; Laura Scarabel; Silvia Panozzo; Aldo Ferrero; Marco Acutis; Maurizio Sattin. 2018. "Epidemiology and agronomic predictors of herbicide resistance in rice at a large scale." Agronomy for Sustainable Development 38, no. 6: 68.

Journal article
Published: 09 November 2018 in Agricultural Systems
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An evaluation of the effect of the conservation agriculture (CA) on agro-environmental aspects is needed at the farm scale in intensive production systems, which are likely prone to reduce soil fertility. Here, as part of the HelpSoil LIFE+ Project and involving 20 farms in the Po valley (Northern Italy), we have estimated the soil organic carbon (SOC) content, SOC stock, crop yield, biological fertility, soil biodiversity, and economic efficiency under different agricultural systems (CA and conventional, CvtA) at the beginning (March 2014) and end (October 2016) of the experimental period. CA was mostly represented by no-till practice (NT) coupled with the cultivation of winter cover crops. Minimum tillage (MT) was considered as CA or CvtA practice according to the farm design. The CA practices have been implemented on the monitored farms at different times (Long-term = before 2006, Medium-term = between 2006 and 2013, Short-term = after 2013). A direct comparison between CA and CvtA of soil-related variables, yields, and costs was performed on 14 out of the 20 farms; data were statistically treated with a linear mixed model. Overall, CA resulted in significantly higher SOC content, SOC stock, biological fertility, QBS-ar, and earthworms for the Medium-term group. Considering the effect of tillage practices observed on the 20 farms, SOC content was the highest in NT for the Long-term group. The biological fertility index was higher in NT and MT compared to CvtA within the Long-term and Medium-term groups in 2016. QBS-ar was the higher in MT and NT than CvtA for the Long-term and Medium-Term groups. The number of earthworms was the highest under NT for the Long-term group. Maize, winter wheat, and soybeans yields were generally 1 t ha−1 higher in CvtA than in CA, but this did not reach statistical significance. The cost for herbicides was 18% more expensive in NT, whereas the fuel consumption and total costs for weeding operations did not differ between NT and CvtA. The overall outcome of the analysis was that CA is a viable solution for intensive farms in the monitored area, but further skills need still to be acquired in to enhance its economic feasibility.

ACS Style

A. Perego; A. Rocca; Valentina Cattivelli; Vincenzo Tabaglio; Andrea Fiorini; S. Barbieri; Calogero Schillaci; M.E. Chiodini; S. Brenna; Marco Acutis. Agro-environmental aspects of conservation agriculture compared to conventional systems: A 3-year experience on 20 farms in the Po valley (Northern Italy). Agricultural Systems 2018, 168, 73 -87.

AMA Style

A. Perego, A. Rocca, Valentina Cattivelli, Vincenzo Tabaglio, Andrea Fiorini, S. Barbieri, Calogero Schillaci, M.E. Chiodini, S. Brenna, Marco Acutis. Agro-environmental aspects of conservation agriculture compared to conventional systems: A 3-year experience on 20 farms in the Po valley (Northern Italy). Agricultural Systems. 2018; 168 ():73-87.

Chicago/Turabian Style

A. Perego; A. Rocca; Valentina Cattivelli; Vincenzo Tabaglio; Andrea Fiorini; S. Barbieri; Calogero Schillaci; M.E. Chiodini; S. Brenna; Marco Acutis. 2018. "Agro-environmental aspects of conservation agriculture compared to conventional systems: A 3-year experience on 20 farms in the Po valley (Northern Italy)." Agricultural Systems 168, no. : 73-87.

Journal article
Published: 01 January 2018 in Agricultural Systems
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Crop growth simulation models can differ greatly in their treatment of key processes and hence in their response to environmental conditions. Here, we used an ensemble of 26 process-based wheat models applied at sites across a European transect to compare their sensitivity to changes in temperature (−2 to +9°C) and precipitation (−50 to +50%). Model results were analysed by plotting them as impact response surfaces (IRSs), classifying the IRS patterns of individual model simulations, describing these classes and analysing factors that may explain the major differences in model responses. The model ensemble was used to simulate yields of winter and spring wheat at four sites in Finland, Germany and Spain. Results were plotted as IRSs that show changes in yields relative to the baseline with respect to temperature and precipitation. IRSs of 30-year means and selected extreme years were classified using two approaches describing their pattern.The expert diagnostic approach (EDA) combines two aspects of IRS patterns: location of the maximum yield (nine classes) and strength of the yield response with respect to climate (four classes), resulting in a total of 36 combined classes defined using criteria pre-specified by experts. The statistical diagnostic approach (SDA) groups IRSs by comparing their pattern and magnitude, without attempting to interpret these features. It applies a hierarchical clustering method, grouping response patterns using a distance metric that combines the spatial correlation and Euclidian distance between IRS pairs. The two approaches were used to investigate whether different patterns of yield response could be related to different properties of the crop models, specifically their genealogy, calibration and process description. Although no single model property across a large model ensemble was found to explain the integrated yield response to temperature and precipitation perturbations, the application of the EDA and SDA approaches revealed their capability to distinguish: (i) stronger yield responses to precipitation for winter wheat than spring wheat; (ii) differing strengths of response to climate changes for years with anomalous weather conditions compared to period-average conditions; (iii) the influence of site conditions on yield patterns; (iv) similarities in IRS patterns among models with related genealogy; (v) similarities in IRS patterns for models with simpler process descriptions of root growth and water uptake compared to those with more complex descriptions; and (vi) a closer correspondence of IRS patterns in models using partitioning schemes to represent yield formation than in those using a harvest index. Such results can inform future crop modelling studies that seek to exploit the diversity of multi-model ensembles, by distinguishing ensemble members that span a wide range of responses as well as those that display implausible behaviour or strong mutual similarities

ACS Style

Stefan Fronzek; Nina Pirttioja; Timothy R. Carter; Marco Bindi; Holger Hoffmann; Taru Palosuo; Margarita Ruiz-Ramos; Fulu Tao; Miroslav Trnka; Marco Acutis; Senthold Asseng; Piotr Baranowski; Bruno Basso; Per Bodin; Samuel Buis; Davide Cammarano; Paola Deligios; Marie-France Destain; Benjamin Dumont; Frank Ewert; Roberto Ferrise; Louis François; Thomas Gaiser; Petr Hlavinka; Ingrid Jacquemin; Kurt Christian Kersebaum; Chris Kollas; Jaromir Krzyszczak; Ignacio Lorite; Julien Minet; M Ines Minguez; Manuel Montesino; Marco Moriondo; Christoph Müller; Claas Nendel; Isik Öztürk; Alessia Perego; Alfredo Rodríguez; Alex C. Ruane; Françoise Ruget; Mattia Sanna; Mikhail Semenov; Cezary Sławiński; Pierre Stratonovitch; Iwan Supit; Katharina Waha; Enli Wang; Lianhai Wu; Zhigan Zhao; Reimund Rötter. Classifying multi-model wheat yield impact response surfaces showing sensitivity to temperature and precipitation change. Agricultural Systems 2018, 159, 209 -224.

AMA Style

Stefan Fronzek, Nina Pirttioja, Timothy R. Carter, Marco Bindi, Holger Hoffmann, Taru Palosuo, Margarita Ruiz-Ramos, Fulu Tao, Miroslav Trnka, Marco Acutis, Senthold Asseng, Piotr Baranowski, Bruno Basso, Per Bodin, Samuel Buis, Davide Cammarano, Paola Deligios, Marie-France Destain, Benjamin Dumont, Frank Ewert, Roberto Ferrise, Louis François, Thomas Gaiser, Petr Hlavinka, Ingrid Jacquemin, Kurt Christian Kersebaum, Chris Kollas, Jaromir Krzyszczak, Ignacio Lorite, Julien Minet, M Ines Minguez, Manuel Montesino, Marco Moriondo, Christoph Müller, Claas Nendel, Isik Öztürk, Alessia Perego, Alfredo Rodríguez, Alex C. Ruane, Françoise Ruget, Mattia Sanna, Mikhail Semenov, Cezary Sławiński, Pierre Stratonovitch, Iwan Supit, Katharina Waha, Enli Wang, Lianhai Wu, Zhigan Zhao, Reimund Rötter. Classifying multi-model wheat yield impact response surfaces showing sensitivity to temperature and precipitation change. Agricultural Systems. 2018; 159 ():209-224.

Chicago/Turabian Style

Stefan Fronzek; Nina Pirttioja; Timothy R. Carter; Marco Bindi; Holger Hoffmann; Taru Palosuo; Margarita Ruiz-Ramos; Fulu Tao; Miroslav Trnka; Marco Acutis; Senthold Asseng; Piotr Baranowski; Bruno Basso; Per Bodin; Samuel Buis; Davide Cammarano; Paola Deligios; Marie-France Destain; Benjamin Dumont; Frank Ewert; Roberto Ferrise; Louis François; Thomas Gaiser; Petr Hlavinka; Ingrid Jacquemin; Kurt Christian Kersebaum; Chris Kollas; Jaromir Krzyszczak; Ignacio Lorite; Julien Minet; M Ines Minguez; Manuel Montesino; Marco Moriondo; Christoph Müller; Claas Nendel; Isik Öztürk; Alessia Perego; Alfredo Rodríguez; Alex C. Ruane; Françoise Ruget; Mattia Sanna; Mikhail Semenov; Cezary Sławiński; Pierre Stratonovitch; Iwan Supit; Katharina Waha; Enli Wang; Lianhai Wu; Zhigan Zhao; Reimund Rötter. 2018. "Classifying multi-model wheat yield impact response surfaces showing sensitivity to temperature and precipitation change." Agricultural Systems 159, no. : 209-224.

Journal article
Published: 11 December 2017 in Italian Journal of Agronomy
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The evaluation of commercial hybrids under limited water availability is of primary importance to assess Sorghum bicolor (Moench) as potential multipurpose bioenergy crop in Mediterranean drought prone environments. Ten genotypes were grown during three growing seasons (2010, 2011 and 2012) in open field trials and in pot experiments (2014). Phenological traits, biomass production, fibre content and biomass chemical composition were measured under irrigated and rainfed conditions. Differences in biomass production among the ten genotypes varied across years. In a three-year experiment significant differences were found among the ten genotypes in terms of duration of vegetative growth (P

ACS Style

Alessandra Fracasso; Alessia Perego; Stefano Amaducci. Characterisation of ten commercial sorghum genotypes grown under water-limited conditions for bioenergy production in Mediterranean environment. Italian Journal of Agronomy 2017, 12, 1 .

AMA Style

Alessandra Fracasso, Alessia Perego, Stefano Amaducci. Characterisation of ten commercial sorghum genotypes grown under water-limited conditions for bioenergy production in Mediterranean environment. Italian Journal of Agronomy. 2017; 12 (4):1.

Chicago/Turabian Style

Alessandra Fracasso; Alessia Perego; Stefano Amaducci. 2017. "Characterisation of ten commercial sorghum genotypes grown under water-limited conditions for bioenergy production in Mediterranean environment." Italian Journal of Agronomy 12, no. 4: 1.

Journal article
Published: 01 August 2017 in European Journal of Agronomy
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This study presents results from a major grassland model intercomparison exercise, and highlights the main challenges faced in the implementation of a multi-model ensemble prediction system in grasslands. Nine, independently developed simulation models linking climate, soil, vegetation and management to grassland biogeochemical cycles and production were compared in a simulation of soil water content (SWC) and soil temperature (ST) in the topsoil, and of biomass production. The results were assessed against SWC and ST data from five observational grassland sites representing a range of conditions – Grillenburg in Germany, Laqueuille in France with both extensive and intensive management, Monte Bondone in Italy and Oensingen in Switzerland – and against yield measurements from the same sites and other experimental grassland sites in Europe and Israel. We present a comparison of model estimates from individual models to the multi-model ensemble (represented by multi-model median: MMM). With calibration (seven out of nine models), the performances were acceptable for weekly-aggregated ST (R2 > 0.7 with individual models and >0.8–0.9 with MMM), but less satisfactory with SWC (R2 < 0.6 with individual models and < ∼ 0.5 with MMM) and biomass (R2 < ∼0.3 with both individual models and MMM). With individual models, maximum biases of about −5 °C for ST, −0.3 m3 m−3 for SWC and 360 g DM m−2 for yield, as well as negative modelling efficiencies and some high relative root mean square errors indicate low model performance, especially for biomass. We also found substantial discrepancies across different models, indicating considerable uncertainties regarding the simulation of grassland processes. The multi-model approach allowed for improved performance, but further progress is strongly needed in the way models represent processes in managed grassland systems

ACS Style

Renáta Sándor; Z. Barcza; Marco Acutis; Luca Doro; D. Hidy; Martin Köchy; J. Minet; E. Lellei-Kovács; S. Ma; Alessia Perego; S. Rolinski; F. Ruget; Mattia Sanna; G. Seddaiu; L. Wu; G. Bellocchi. Multi-model simulation of soil temperature, soil water content and biomass in Euro-Mediterranean grasslands: Uncertainties and ensemble performance. European Journal of Agronomy 2017, 88, 22 -40.

AMA Style

Renáta Sándor, Z. Barcza, Marco Acutis, Luca Doro, D. Hidy, Martin Köchy, J. Minet, E. Lellei-Kovács, S. Ma, Alessia Perego, S. Rolinski, F. Ruget, Mattia Sanna, G. Seddaiu, L. Wu, G. Bellocchi. Multi-model simulation of soil temperature, soil water content and biomass in Euro-Mediterranean grasslands: Uncertainties and ensemble performance. European Journal of Agronomy. 2017; 88 ():22-40.

Chicago/Turabian Style

Renáta Sándor; Z. Barcza; Marco Acutis; Luca Doro; D. Hidy; Martin Köchy; J. Minet; E. Lellei-Kovács; S. Ma; Alessia Perego; S. Rolinski; F. Ruget; Mattia Sanna; G. Seddaiu; L. Wu; G. Bellocchi. 2017. "Multi-model simulation of soil temperature, soil water content and biomass in Euro-Mediterranean grasslands: Uncertainties and ensemble performance." European Journal of Agronomy 88, no. : 22-40.

Journal article
Published: 01 May 2016 in European Journal of Agronomy
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The expansion of biogas production from anaerobic digestion in the Po Valley (Northern Italy) has stimulated the cultivation of dedicated biomass crops, and maize in particular. A mid-term experiment was carried out from 2006 to 2010 on a silt loamy soil in Northern Italy to compare water use and energy efficiency of maize and sorghum cultivation under rain fed and well-watered treatments and at two rates of nitrogen fertilization. The present work hypothesis were: (i) biomass sorghum, for its efficient use of water and nitrogen, could be a valuable alternative to maize for biogas production; (ii) reduction of irrigation level and (iii) application of low nitrogen fertilizer rate increase the efficiency of bioenergy production. Water treatments, a rain fed control (I0) and two irrigation levels (I1 and I2; only one in 2006 and 2009), were compared in a split–split plot design with four replicates. Two fertilizer rates were also tested: low (N1, 60 kg ha−1 of nitrogen; 0 kg ha−1 of nitrogen in 2010) and high (N2, 120 kg ha−1 of nitrogen; 100 kg ha−1 of nitrogen in 2010). Across treatments, sorghum produced more aboveground biomass than maize, respectively 21.6 Mg ha−1 and 16.8 Mg ha−1 (p < 0.01). In both species, biomass yield was lower in I0 than in I1 and I2 (p < 0.01), while I1 and I2 did differ significantly. Nitrogen level never affected biomass yield. Water use efficiency was generally higher in sorghum (52 kg ha−1 mm−1) than in maize (38 kg ha−1 mm−1); the significant interaction between crop and irrigation revealed that water use efficiency did not differ across water levels in sorghum, whereas it significantly increased from I0 and I1 to I2 in maize (p < 0.01). The potential methane production was similar in maize and sorghum, while it was significantly lower in I0 (16505 MJ ha−1) than in I1 and I2 (21700 MJ ha−1). The only significant effect of nitrogen fertilization was found in the calculation of energy efficiency (ratio of energy output and input) that was higher in N1 than in N2 (p < 0.01). These results support the hypothesis that (i) sorghum should be cultivated rather than maize to increase energy efficiency, (ii) irrigation level should replace up to 36% of ETr and (iii) nitrogen fertilizer rate should be minimized to maximize the efficiency in biomass production for anaerobic digestion in the Po Valley.

ACS Style

Stefano Amaducci; Michele Colauzzi; Ferdinando Battini; Alessandra Fracasso; Alessia Perego. Effect of irrigation and nitrogen fertilization on the production of biogas from maize and sorghum in a water limited environment. European Journal of Agronomy 2016, 76, 54 -65.

AMA Style

Stefano Amaducci, Michele Colauzzi, Ferdinando Battini, Alessandra Fracasso, Alessia Perego. Effect of irrigation and nitrogen fertilization on the production of biogas from maize and sorghum in a water limited environment. European Journal of Agronomy. 2016; 76 ():54-65.

Chicago/Turabian Style

Stefano Amaducci; Michele Colauzzi; Ferdinando Battini; Alessandra Fracasso; Alessia Perego. 2016. "Effect of irrigation and nitrogen fertilization on the production of biogas from maize and sorghum in a water limited environment." European Journal of Agronomy 76, no. : 54-65.

Journal article
Published: 17 April 2016 in Agriculture, Ecosystems & Environment
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Nitrous oxide (N2O) emissions from a specific environment vary with agricultural management and pedoclimatic conditions. Therefore a 2-year field experiment was carried out to compare N2O emissions from contrasting fertilizer (cattle slurry, compost, digestate, ammonium nitrate, unfertilized control) and tillage treatments (conventional, CT, and minimum, MT) under a rotation of forage and bioenergy crops in Piacenza (Po Valley, Northern Italy). Field N2O emissions were measured during four monitoring campaigns (late spring 2011, summer and autumn 2012, and summer 2013), while the cumulative fluxes over the same campaign were estimated with the SPACSYS model, calibrated with data collected in a lysimeter experiment and validated with field data. The interaction between fertilizer and tillage resulted in significant differences of N2O emissions (P < 0.05). In CT, ammonium nitrate and slurry showed the largest emissions, while in MT emissions were lower under digestate, compost, and slurry than under ammonium nitrate. The annual cumulative emissions from ammonium nitrate application estimated by the model were 20% and 33% higher than the emissions from organic fertilizer treatments in CT and MT respectively. The highest peaks of emissions occurred in summer when the cumulative N2O emissions were 24% higher (from June to August, 8.3 kg N2O-N ha−1, P < 0.01) than those predicted in the remaining part of the year (6.3 kg N2O-N ha−1). The reduced tillage resulted in an overall significant reduction of the annual N2O emissions (−12%), from 16 kg N2O-N ha−1 y−1 in CT to 14.2 kg N2O-N ha−1 y−1 in MT. Nitrogen fertilization caused peaks of N2O emissions when the soil water content reached a critical value of 0.29 m3 m−3 that corresponded to a water filled pore space of 50%. The emission factors (fertilizer-derived N lost as N2O) calculated in this work largely exceed the default value of 1% proposed by IPCC: it was 2.1% under CT, 3.5% with ammonium nitrate and 1.6% when slurry was applied. Besides reduced tillage and fertilization with treated slurry (compost and digestate) also reduced irrigation is likely to reduce the absolute emissions rate of N2O in the study area.

ACS Style

Alessia Perego; L. Wu; G. Gerosa; A. Finco; M. Chiazzese; S. Amaducci. Field evaluation combined with modelling analysis to study fertilizer and tillage as factors affecting N2O emissions: A case study in the Po valley (Northern Italy). Agriculture, Ecosystems & Environment 2016, 225, 72 -85.

AMA Style

Alessia Perego, L. Wu, G. Gerosa, A. Finco, M. Chiazzese, S. Amaducci. Field evaluation combined with modelling analysis to study fertilizer and tillage as factors affecting N2O emissions: A case study in the Po valley (Northern Italy). Agriculture, Ecosystems & Environment. 2016; 225 ():72-85.

Chicago/Turabian Style

Alessia Perego; L. Wu; G. Gerosa; A. Finco; M. Chiazzese; S. Amaducci. 2016. "Field evaluation combined with modelling analysis to study fertilizer and tillage as factors affecting N2O emissions: A case study in the Po valley (Northern Italy)." Agriculture, Ecosystems & Environment 225, no. : 72-85.

Journal article
Published: 29 February 2016 in GCB Bioenergy
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A wealth of data and information on the cultivation of perennial biomass crops has been collected, but direct comparisons between herbaceous and woody crops are rare. The main objective of this research was to compare the biomass yield, the energy balance and the biomass quality of six perennial bioenergy crops: Populus spp., Robinia pseudoacacia, Salix spp. and Arundo donax, Miscanthus ×giganteus, Panicum virgatum, grown in two marginal environments. For giant reed and switchgrass two levels of nitrogen fertilization were applied annually (0-100 kg ha−1). Nitrogen fertilization did not affect biomass or energy production of giant reed, thus it significantly reduced the Energy Return On Investment (EROI) (from 73 to 27). In switchgrass, nitrogen fertilization significantly increased biomass production and the capacity of this crop to respond to water availability, making it a favorable option when only biomass production is a target. Net Energy Gain (NEG) was higher for herbaceous crops than for woody crops. In Casale, EROI calculated for poplar and willow (7, on average) was significantly lower than that of the other crops (14, on average). In Gariga, the highest EROI was calculated for miscanthus (98), followed by no-fertilized giant reed and switchgrass (82 and 73, respectively). Growing degree days10 during the cropping season had no effect on biomass production in any of the studied species, though water availability from May to August was a major factor affecting biomass yield in herbaceous crops. Overall, herbaceous crops had the highest ranking for bioenergy production due to their high biomass yield, high net energy gain (NEG) and their biomass quality that renders them suitable to both biochemical and thermochemical conversion. Miscanthus in particular had the highest EROI in both locations (16 and 98, in Casale and Gariga), while giant reed had the highest NEG on the silty-loam soil of Gariga. This article is protected by copyright. All rights reserved.

ACS Style

Stefano Amaducci; Gianni Facciotto; Sara Bergante; Alessia Perego; Paolo Serra; Andrea Ferrarini; Carlo Chimento. Biomass production and energy balance of herbaceous and woody crops on marginal soils in the Po Valley. GCB Bioenergy 2016, 9, 31 -45.

AMA Style

Stefano Amaducci, Gianni Facciotto, Sara Bergante, Alessia Perego, Paolo Serra, Andrea Ferrarini, Carlo Chimento. Biomass production and energy balance of herbaceous and woody crops on marginal soils in the Po Valley. GCB Bioenergy. 2016; 9 (1):31-45.

Chicago/Turabian Style

Stefano Amaducci; Gianni Facciotto; Sara Bergante; Alessia Perego; Paolo Serra; Andrea Ferrarini; Carlo Chimento. 2016. "Biomass production and energy balance of herbaceous and woody crops on marginal soils in the Po Valley." GCB Bioenergy 9, no. 1: 31-45.

Journal article
Published: 01 January 2016 in Science of The Total Environment
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Fontanile is a Po Valley (Italy) quasi-natural lowland spring built in the middle age. This paper identifies options for the conservation of the Fontanile water dependent ecosystem, using scenarios and simulations, and exploring different policy options. Three modeling analysis have been performed: the first was carried out for estimating groundwater contamination and recharge from above, the second for evaluating the function of vegetative filter strip on the surface water quality and the last one for testing pesticide drift reduction due to the vegetative filter strip. Uncertainty characterization included climate change projections. Despite the nitrate concentration in water could favorite the eutrophication phenomena, this not occurs because of the low phosphate concentration in water and of the presence of arboreal shade. Therefore, the protection strategies must focus on sustaining desirable water quantity conditions. Water saving and conservation technologies that improve the agricultural productivity but reduce the Fontanile water flow and large buffer strips that have a limited efficacy due to the Fontanile hydrological settings can be judged as ecological traps. Inefficient irrigation systems, good agricultural practices, integrated pest management and arboreal filter strip can preserve the quality of those ecosystems.

ACS Style

Matteo Balderacchi; Alessia Perego; Giovanni Lazzari; Rafael Muñoz-Carpena; Marco Acutis; Alex Laini; Andrea Giussani; Mattia Sanna; David Kane; Marco Trevisan. Avoiding social traps in the ecosystem stewardship: The Italian Fontanile lowland spring. Science of The Total Environment 2016, 539, 526 -535.

AMA Style

Matteo Balderacchi, Alessia Perego, Giovanni Lazzari, Rafael Muñoz-Carpena, Marco Acutis, Alex Laini, Andrea Giussani, Mattia Sanna, David Kane, Marco Trevisan. Avoiding social traps in the ecosystem stewardship: The Italian Fontanile lowland spring. Science of The Total Environment. 2016; 539 ():526-535.

Chicago/Turabian Style

Matteo Balderacchi; Alessia Perego; Giovanni Lazzari; Rafael Muñoz-Carpena; Marco Acutis; Alex Laini; Andrea Giussani; Mattia Sanna; David Kane; Marco Trevisan. 2016. "Avoiding social traps in the ecosystem stewardship: The Italian Fontanile lowland spring." Science of The Total Environment 539, no. : 526-535.

Journal article
Published: 01 November 2015 in Industrial Crops and Products
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A collection of 24 clones of Arundo donax, from different geographical areas in Italy, Europe, and China, were evaluated during the first 3 years from transplant. A field trial with 3 replicates was set up in the Po valley (northern Italy) in a sandy loam soil. At harvest, at the end of the second and third year after plantation, biomass yield, average stem number, average stem diameter, and single plant area were determined for each clone. For a selection of clones, chemical analysis and biochemical methane potential (BMP) were also performed. A large variation among clones was found for all the biometric parameters considered and also for biomass yield. It was interesting to note that some clones, while achieving similar biomass yield, had contrasting growth patterns, with some clones producing just a few large stems and others producing many thin ones. As a consequence, a different number of stems per plant area was also found among clones. Chemical analysis highlighted a significant difference among clones for ash (from 5.3% to 8.1%), lignin (from 6.9% to 10.6%), and hemicellulose (from 25.1% to 29.2%) content, while cellulose content was on average 43.4%. BMP ranging from 147 ml g(-1) VS to 243 ml g(-1) VS and was partially affected by lignin and ash content. (C) 2015 Elsevier B.V. All rights reserved.A collection of 24 clones of Arundo donax, from different geographical areas in Italy, Europe, and China, were evaluated during the first 3 years from transplant. A field trial with 3 replicates was set up in the Po valley (northern Italy) in a sandy loam soil. At harvest, at the end of the second and third year after plantation, biomass yield, average stem number, average stem diameter, and single plant area were determined for each clone. For a selection of clones, chemical analysis and biochemical methane potential (BMP) were also performed. A large variation among clones was found for all the biometric parameters considered and also for biomass yield. It was interesting to note that some clones, while achieving similar biomass yield, had contrasting growth patterns, with some clones producing just a few large stems and others producing many thin ones. As a consequence, a different number of stems per plant area was also found among clones. Chemical analysis highlighted a significant difference among clones for ash (from 5.3% to 8.1%), lignin (from 6.9% to 10.6%), and hemicellulose (from 25.1% to 29.2%) content, while cellulose content was on average 43.4%. BMP ranging from 147 ml g(-1) VS to 243 ml g(-1) VS and was partially affected by lignin and ash content

ACS Style

Stefano Amaducci; Alessia Perego. Field evaluation of Arundo donax clones for bioenergy production. Industrial Crops and Products 2015, 75, 122 -128.

AMA Style

Stefano Amaducci, Alessia Perego. Field evaluation of Arundo donax clones for bioenergy production. Industrial Crops and Products. 2015; 75 ():122-128.

Chicago/Turabian Style

Stefano Amaducci; Alessia Perego. 2015. "Field evaluation of Arundo donax clones for bioenergy production." Industrial Crops and Products 75, no. : 122-128.