The environmental impacts of different organic rice management in Italy considering different productive scenarios.

Environmental assessment GHG gas LCA Organic farming Organic rice Oryza sativa L

Journal

The Science of the total environment
ISSN: 1879-1026
Titre abrégé: Sci Total Environ
Pays: Netherlands
ID NLM: 0330500

Informations de publication

Date de publication:
20 Dec 2022
Historique:
received: 27 06 2022
revised: 24 08 2022
accepted: 24 08 2022
pubmed: 4 9 2022
medline: 28 10 2022
entrez: 3 9 2022
Statut: ppublish

Résumé

Rice cultivation has a key role in food security worldwide; on the other hand, it has a high potential impact on the environment and human health, mainly due to the extensive pesticides use and greenhouse gas emissions caused by flooded cultivation. In Italy, the rice sector based mainly on high-input monoculture. The transition toward organic agriculture can improve the environmental performance of rice farming according to the actual European sustainable food production strategy. Through LCA methodology, the study aims to evaluate the variability of the environmental impacts and the mitigation potential of four management strategies suitable for organic rice production in North Italy and two production potential levels observed during three-year monitoring on 10 farms in the study area. The LCA analysis includes the wide range of agronomic realities that characterise this farming system, assessing the variation in environmental performance by exploring eight plausible and possible scenarios for organic rice. Results suggest a considerable potential of organic rice production to mitigate its impact on natural resources, depending on the chosen agricultural practices. In particular, six LCA indicators showed a potential of reduction over 40 %, shifting from the worst-performing management to the better one. Finally, the large variability of climate change impacts assessed, both in this study and in literature, is due to the corresponding existing large variability in terms of yield and available patterns of agricultural practices. Today the farmers could reach acceptable yield values thanks to more efficient management than in the past. The acknowledgement for that performances relates to the development of the farmers' know-how and to the productive improvement connected to the long-term processes which characterise the organic systems (e.g. generation of soil fertility based on biological fertility and stable humus components; lowering of weeds pressure through the gradual introduction of other crops in rotation).

Identifiants

pubmed: 36057306
pii: S0048-9697(22)05464-X
doi: 10.1016/j.scitotenv.2022.158365
pii:
doi:

Substances chimiques

Greenhouse Gases 0
Soil 0
Pesticides 0

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

158365

Informations de copyright

Copyright © 2022 Elsevier B.V. All rights reserved.

Déclaration de conflit d'intérêts

Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Auteurs

Valentina Vaglia (V)

Università Degli Studi di Milano, Department of Environmental Science and Policy (ESP), Via Celoria 2, Milano, MI 20133, Italy.

Jacopo Bacenetti (J)

Università Degli Studi di Milano, Department of Environmental Science and Policy (ESP), Via Celoria 2, Milano, MI 20133, Italy. Electronic address: jacopo.bacenetti@unimi.it.

Francesca Orlando (F)

Associazione Italiana di Agroecologia (AIDA).

Sumer Alali (S)

University of Brescia, Department of Civil, Environmental, Architectural Engineering and Mathematics (DICATAM), Agrofood Research Hub, via Branze 43, Brescia, BR 25123, Italy.

Ezio Bosso (E)

Università Degli Studi di Milano, Department of Environmental Science and Policy (ESP), Via Celoria 2, Milano, MI 20133, Italy.

Stefano Bocchi (S)

Università Degli Studi di Milano, Department of Environmental Science and Policy (ESP), Via Celoria 2, Milano, MI 20133, Italy.

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Classifications MeSH