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1.
Sci Total Environ ; 838(Pt 2): 156181, 2022 Sep 10.
Artigo em Inglês | MEDLINE | ID: mdl-35618131

RESUMO

Viticulture is gradually shifting to more sustainable production systems and a fair number of studies aim at assessing the environmental impacts of different technologies and techniques adopted in the wine production through the Life Cycle Assessment approach. The main environmental issues identified are on water, soil and energy use, management of organic and inorganic solid waste streams, greenhouse gas emissions and use of chemicals. Precision viticulture (PV) techniques can play an important role in the sustainable use of water and fertilizers in grape production, thanks to the site-specific application of these inputs, improving yield and quality of grapes while minimizing negative effects on the environment. However, PV often implies investments and additional management costs. The objective of this study is to compare different strategies for the management of water and fertilizers in vineyards, ranging from the conventional ones to the most technologically advanced, to assess their sustainability both from an economic and an environmental point of view. Six scenarios have been explored, considering different irrigation water supply systems, and irrigation and fertilizer management strategies. A multidisciplinary approach, including Life Cycle Assessment, economic assessment and multivariate analysis was used to assess the sustainability of the different vineyard management approaches. The results show the higher economic and environmental sustainability for the scenario considering irrigation water supplied from an irrigation consortium, a variable rate drip irrigation system for irrigation and fertigation. Finally, also according to PCA results, at least for the scenarios explored in the study, the introduction of PV technologies led to the reduction of environmental impacts and to the increase in economic advantages, which showed to be inversely correlated.


Assuntos
Fertilizantes , Vitis , Agricultura/métodos , Fazendas , Fertilizantes/análise , Solo , Água
2.
J Environ Manage ; 86(1): 272-81, 2008 Jan.
Artigo em Inglês | MEDLINE | ID: mdl-17296259

RESUMO

The weights of evidence (WofE) modeling technique has been used to analyze both natural and anthropogenic factors influencing the occurrence of high nitrate concentrations in groundwater resources located in the central part of the Po Plain (Northern Italy). The proposed methodology applied in the Lodi District combines measurements of nitrate concentrations, carried out by means of a monitoring net of 69 wells, with spatial data representing both categorical and numerical variables. These variables describe either potential sources of nitrate and the relative ease with which it may migrate towards groundwater. They include population density, nitrogen fertilizer loading, groundwater recharge, soil protective capacity, vadose zone permeability, groundwater depth, and saturated zone permeability. Once conditional dependence problems among factors have been solved and validation tests performed, the statistical approach has highlighted negative and positive correlations between geoenvironmental factors and nitrate concentration in groundwater. These results have been achieved analysing the calculated statistical parameters (weights, contrasts, normalized contrasts) of each class by which each factor has been previously subdivided. This has permitted to outline: the overall influence each factor has on the presence/absence of nitrate; the range of their values mostly influencing this presence/absence; the most and least critical combination of factor classes existing in each specific zone; areas where the influence of impacting factor classes is reduced by the presence of not impacting factor classes. This last aspect could represent an important support for a correct land use management to preserve groundwater quality.


Assuntos
Modelos Teóricos , Nitratos/análise , Poluentes Químicos da Água/análise , Abastecimento de Água/análise , Teorema de Bayes , Monitoramento Ambiental/estatística & dados numéricos , Itália
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