Literature DB >> 35809110

Milk carbon footprint of silvopastoral dairy systems in the Northern Peruvian Amazon.

Deysi Ruiz-Llontop1, José Velarde-Guillén1, Eduardo Fuentes1, Melisa Prudencio1, Carlos Gómez2.   

Abstract

The objective of this study was to estimate the carbon footprint (CF) of milk production (in kg of CO2 equivalents (CO2e) per kg of fat and protein corrected milk (FPCM)) in dairy farms of the San Martín region, in the Peruvian Amazon. A cradle-to-farm gate characterization and analysis were carried out on eight representative dairy farms. Greenhouse gas (GHG) emissions were estimated using equations, following the 2019 refinement of the 2006 IPCC Guidelines. The results showed an average milk production of 9.7 ± 0.82 L milk/cow/day, Gyr x Holstein crosses as the predominant breed, use of cultivated grasses such as Brachiaria brizantha, living fences (Guazuma ulmifolia Lam) as the predominant silvopastoral arrangement, and low level of external inputs such as feed or grain additives. In relation to CF, an average value of 2.26 ± 0.49 kg CO2e/kg FPCM was obtained, with enteric fermentation being the most important source (1.81 ± 0.51 kg CO2e/kg FPCM), followed by manure management, land use, and energy/transport (0.26 ± 0.06, 0.14 ± 0.04, and 0.05 ± 0.04 kg CO2e/kg FPCM, respectively). Differences were found between farmers, obtaining lower CF values (1.76 vs 3.09 kg CO2e/kg FPCM) on farms with better feed quality, higher production levels, and a higher percentage of lactating animals compared to dry cows. It is concluded that dairy farms in the Peruvian Amazon region can reduce their emissions if they improve their current feeding practices.
© 2022. The Author(s), under exclusive licence to Springer Nature B.V.

Entities:  

Keywords:  Carbon dioxide; Dairy cattle; Grazing systems; Life cycle assessment; Methane; Nitrous oxide

Mesh:

Substances:

Year:  2022        PMID: 35809110     DOI: 10.1007/s11250-022-03224-5

Source DB:  PubMed          Journal:  Trop Anim Health Prod        ISSN: 0049-4747            Impact factor:   1.893


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