Mapping the path to decarbonised agri-food products: a hybrid geographic information system and life cycle inventory methodology for assessing sustainable agriculture

Wayne Martindale; Ali Saeidan; Farajollah Tahernezhad-Javazm; Tom Æ Hollands; Linh Duong; Sandeep Jagtap

doi:10.1111/ijfs.17340

Mapping the path to decarbonised agri-food products: a hybrid geographic information system and life cycle inventory methodology for assessing sustainable agriculture

Wayne Martindale
, Ali Saeidan
, Farajollah Tahernezhad-Javazm
, Tom Æ Hollands
, Linh Duong
, Sandeep Jagtap

Lund University

Research output: Contribution to journal › Article › peer-review

4 Citations (Scopus)

86 Downloads (Pure)

Abstract

The development of a decarbonised food industry will depend on a sustainable agricultural system where embodied food product greenhouse gas emissions (GHG) can be associated with agricultural production. The method presented demonstrates how mapping agri-production can be used to calculate regional carbon footprints so GHG emission reduction is geographically strategic. Different agronomic and husbandry outcomes are mapped using Geographic Information Systems (GIS's) and carbon footprints are calculated using Life Cycle Inventory (LCI) libraries. The hybridised GIS-LCI approach reports unique insights for decarbonisation, demonstrating how farming practices can be further integrated to best deliver food security. We use the GIS-LCI method to show; (1), geography limits crop and livestock production types; (2), agri-product density data can be used to calculate a food system carbon footprint; and (3), GIS's can be used to focus food policy for sustainability.

Original language	English
Pages (from-to)	6078-6086
Number of pages	9
Journal	International Journal of Food Science and Technology
Volume	59
Issue number	9
Early online date	16 Jul 2024
DOIs	https://doi.org/10.1111/ijfs.17340
Publication status	Published online - 16 Jul 2024

Data Availability Statement

The data that support the findings of this study are available from the corresponding author upon reasonable request.

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 2 Zero Hunger

Keywords

Decarbonisation
food manufacturing
food security
food supply
sustainability

Access to Document

10.1111/ijfs.17340Licence: CC BY

ijfs17340Final published version, 2.36 MBLicence: CC BY

Cite this

Martindale, W., Saeidan, A., Tahernezhad-Javazm, F., Hollands, T. Æ., Duong, L., & Jagtap, S. (2024). Mapping the path to decarbonised agri-food products: a hybrid geographic information system and life cycle inventory methodology for assessing sustainable agriculture. International Journal of Food Science and Technology, 59(9), 6078-6086. Advance online publication. https://doi.org/10.1111/ijfs.17340

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abstract = "The development of a decarbonised food industry will depend on a sustainable agricultural system where embodied food product greenhouse gas emissions (GHG) can be associated with agricultural production. The method presented demonstrates how mapping agri-production can be used to calculate regional carbon footprints so GHG emission reduction is geographically strategic. Different agronomic and husbandry outcomes are mapped using Geographic Information Systems (GIS's) and carbon footprints are calculated using Life Cycle Inventory (LCI) libraries. The hybridised GIS-LCI approach reports unique insights for decarbonisation, demonstrating how farming practices can be further integrated to best deliver food security. We use the GIS-LCI method to show; (1), geography limits crop and livestock production types; (2), agri-product density data can be used to calculate a food system carbon footprint; and (3), GIS's can be used to focus food policy for sustainability.",

keywords = "Decarbonisation, food manufacturing, food security, food supply, sustainability",

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Martindale, W, Saeidan, A, Tahernezhad-Javazm, F, Hollands, TÆ, Duong, L & Jagtap, S 2024, 'Mapping the path to decarbonised agri-food products: a hybrid geographic information system and life cycle inventory methodology for assessing sustainable agriculture', International Journal of Food Science and Technology, vol. 59, no. 9, pp. 6078-6086. https://doi.org/10.1111/ijfs.17340

Mapping the path to decarbonised agri-food products: a hybrid geographic information system and life cycle inventory methodology for assessing sustainable agriculture. / Martindale, Wayne; Saeidan, Ali; Tahernezhad-Javazm, Farajollah et al.
In: International Journal of Food Science and Technology, Vol. 59, No. 9, 16.07.2024, p. 6078-6086.

Research output: Contribution to journal › Article › peer-review

TY - JOUR

T1 - Mapping the path to decarbonised agri-food products: a hybrid geographic information system and life cycle inventory methodology for assessing sustainable agriculture

AU - Martindale, Wayne

AU - Saeidan, Ali

AU - Tahernezhad-Javazm, Farajollah

AU - Hollands, Tom Æ

AU - Duong, Linh

AU - Jagtap, Sandeep

PY - 2024/7/16

Y1 - 2024/7/16

N2 - The development of a decarbonised food industry will depend on a sustainable agricultural system where embodied food product greenhouse gas emissions (GHG) can be associated with agricultural production. The method presented demonstrates how mapping agri-production can be used to calculate regional carbon footprints so GHG emission reduction is geographically strategic. Different agronomic and husbandry outcomes are mapped using Geographic Information Systems (GIS's) and carbon footprints are calculated using Life Cycle Inventory (LCI) libraries. The hybridised GIS-LCI approach reports unique insights for decarbonisation, demonstrating how farming practices can be further integrated to best deliver food security. We use the GIS-LCI method to show; (1), geography limits crop and livestock production types; (2), agri-product density data can be used to calculate a food system carbon footprint; and (3), GIS's can be used to focus food policy for sustainability.

AB - The development of a decarbonised food industry will depend on a sustainable agricultural system where embodied food product greenhouse gas emissions (GHG) can be associated with agricultural production. The method presented demonstrates how mapping agri-production can be used to calculate regional carbon footprints so GHG emission reduction is geographically strategic. Different agronomic and husbandry outcomes are mapped using Geographic Information Systems (GIS's) and carbon footprints are calculated using Life Cycle Inventory (LCI) libraries. The hybridised GIS-LCI approach reports unique insights for decarbonisation, demonstrating how farming practices can be further integrated to best deliver food security. We use the GIS-LCI method to show; (1), geography limits crop and livestock production types; (2), agri-product density data can be used to calculate a food system carbon footprint; and (3), GIS's can be used to focus food policy for sustainability.

KW - Decarbonisation

KW - food manufacturing

KW - food security

KW - food supply

KW - sustainability

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U2 - 10.1111/ijfs.17340

DO - 10.1111/ijfs.17340

M3 - Article

SN - 0950-5423

VL - 59

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EP - 6086

JO - International Journal of Food Science and Technology

JF - International Journal of Food Science and Technology

IS - 9

ER -

Martindale W, Saeidan A, Tahernezhad-Javazm F, Hollands TÆ, Duong L, Jagtap S. Mapping the path to decarbonised agri-food products: a hybrid geographic information system and life cycle inventory methodology for assessing sustainable agriculture. International Journal of Food Science and Technology. 2024 Jul 16;59(9):6078-6086. Epub 2024 Jul 16. doi: 10.1111/ijfs.17340

Mapping the path to decarbonised agri-food products: a hybrid geographic information system and life cycle inventory methodology for assessing sustainable agriculture

Abstract

Data Availability Statement

UN SDGs

Keywords

Access to Document

Other files and links

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Integrating hybrid structures and reinforcement learning into multi-objective evolutionary algorithms: enhancing efficiency and adaptability

Cite this

Mapping the path to decarbonised agri-food products: a hybrid geographic information system and life cycle inventory methodology for assessing sustainable agriculture

Abstract

Data Availability Statement

UN SDGs

Keywords

Access to Document

Other files and links

Fingerprint

Student theses

Integrating hybrid structures and reinforcement learning into multi-objective evolutionary algorithms: enhancing efficiency and adaptability

Cite this