1,721,022 research outputs found

    Greenhouse gas emissions from soil cultivated with vegetables in crop rotation under integrated, organic and organic conservation management in a Mediterranean environment

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    A combination of organic and conservation approaches have not been widely tested, neither considering agronomic implications nor the impacts on the environment. Focussing on the effect of agricultural practices on greenhouse gas (GHG) emissions from soil, the hypothesis of this research is that the organic conservation system (ORG+) may reduce emissions of N2O, CH4 and CO2 from soil, compared to an integrated farming system (INT) and an organic (ORG) system in a two-year irrigated vegetable crop rotation set up in 2014, in a Mediterranean environment. The crop rotation included: Savoy cabbage (Brassica oleracea var. sabauda L. cv. Famosa), spring lettuce (Lactuca sativa L. cv. Justine), fennel (Foeniculum vulgare Mill. cv. Montebianco) and summer lettuce (L. sativa cv. Ballerina). Fluxes from soil of N2O, CH4 and CO2 were measured from October 2014 to July 2016 with the flow-through non-steady state chamber technique using a mobile instrument equipped with high precision analysers. Both cumulative and daily N2O emissions were mainly lower in ORG+ than in INT and ORG. All the cropping systems acted as a sink of CH4, with no significant differences among treatments. The ORG and ORG+ systems accounted for higher cumulative and daily CO2 emissions than INT, maybe due to the stimulating effect on soil respiration of organic material (fertilizers/plant biomass) supplied in ORG and ORG+. Overall, the integration of conservation and organic agriculture showed a tendency for higher CO2 emissions and lower N2O emissions than the other treatments, without any clear results on its potential for mitigating GHG emissions from soil

    Il contributo delle colture dedicate al settore delle agroenergie in Toscana: sviluppo di un modello previsionale a base GIS

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    La metodologia adottata, basata sullo sviluppo di un geodatabase di tipo vettoriale, opportunamente supportato da un software dedicato alla gestione (PostgreSQL), ha consentito di sviluppare un modello dinamico e versatile in grado di interrogare simultaneamente più strati informativi secondo criteri e regole definite dall’utente e di elaborare il risultato rispetto ad unità territoriali di dettaglio minimo. Il modello consente di definire scenari differenti in virtù: i) dei fattori che incidono sulla adattabilità delle diverse specie alle condizioni pedoclimatiche del territorio; ii) delle classi di uso del suolo che si ipotizza di convertire alla produzione di colture dedicate; iii) della quota parte di superficie che si intende destinare alla loro produzione. Lo scenario proposto, elaborato considerando le effettive possibilità di inserimento delle colture da energia nel contesto agricolo regionale, prevede una distinzione tra specie da biomassa e specie per la produzione di bio-carburanti; alle prime si è ipotizzato di destinare circa il 10% delle superfici potenzialmente convertibili (seminativi in asciutto con pendenze inferiori al 15%), mentre alle seconde è stato assegnato il 20% della restante superficie. I risultati mostrano differenze sensibili nella distribuzione delle specie considerate nei diversi areali della Toscana, in conseguenza del loro livello di adattabilità, evidenziando anche la possibilità di coprire le superfici potenzialmente convertibili con opportune combinazioni di colture. Le specie che sembrano presentare le maggiori prospettive di diffusione sono state la canna, fra le specie ligno-cellulosiche, e il girasole e la colza, fra le colture destinate alla produzione di biocarburanti di prima generazione. Le produzioni di energia ottenibili sulla base dello scenario ipotizzato evidenziano come, anche attraverso il recupero dei molti ettari usciti recentemente dall’utilizzo agricolo, potrebbe essere possibile ridurre la dipendenza della regione dalle importazioni di energia elettrica e soddisfare buona parte degli obiettivi previsti dal PIER (Piano di Indirizzo Energetico Regionale) riguardo all’installazione di nuovi impianti alimentati a biomasse entro il 2020

    Competition for light affects alfalfa biomass production more than its nutritive value in an olive-based alley-cropping system

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    Cropping among trees with perennial legumes is one option for increasing agro-ecosystem services, such as improving the nitrogen supply and increasing soil protection by herbaceous vegeta-tion. Moreover, cropping under the canopy of olive trees should diversify the farm production, compared to the traditional fallow management. Among perennial legumes, alfalfa (Medicago sativa L.) produces abundant biomass under Mediterranean rainfed condition. Based on this, a two-year field experiment was implemented in southern Tuscany in a rainfed olive orchard to test the competition for light effects on alfalfa biomass production and nutritive value. Light availability under the tree canopy was measured by hemispherical photos. In both years, the alfalfa yield of under-canopy varied according to the tree presence. A significant relationship between biomass production and light availability was recorded. The nutritive value of under-canopy alfalfa was similar to that of the open-grown alfalfa. However, same significant differences did however occur, between shaded and sole crop. When differences were found, under-canopy herbage was characterised by a higher content of crude protein and a lower content of fibre with respect to open-grown. In a hilly silvoarable olive orchard, alfalfa biomass accumulation was reduced mainly due to scarce light availability, therefore tree management such as pruning and plantation layout can enhance the herbage productivity. Studying shade tolerant forage legumes in order to enhance the yield and nutritive value of herbage production in rainfed agroforestry systems is essential

    Going Beyond Counting First Authors in Author Co-citation Analysis

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    The present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
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