Your browser doesn't support javascript.
loading
Mostrar: 20 | 50 | 100
Resultados 1 - 1 de 1
Filtrar
Mais filtros

Base de dados
Ano de publicação
Tipo de documento
Intervalo de ano de publicação
1.
Sci Total Environ ; 929: 172661, 2024 Jun 15.
Artigo em Inglês | MEDLINE | ID: mdl-38649059

RESUMO

The study's objective was to evaluate the status of converted degraded land into productive agricultural models by improving the physicochemical properties of the soil, soil organic matter (SOM), soil organic carbon (SOC) fractions (active and passive), and microbial biomass carbon (MBC), while also generating carbon (C) credit for additional farmers' income. Six models were analyzed, namely: (1) Arjun forest-based agroecosystems (AFBAE); (2) Lemon grass-based agroecosystems (LGBAE); (3) Legume-cereal-moong-based agroecosystems (LCMBAE); (4) Bael-black mustard-based agroecosystems (BMBAE); (5) Guava-wheat-based agroecosystems (GWBAE), and (6) Custard apple -lentil -based agroecosystems (CALBAE). These models were replicated three times in a randomized block design (RBD). Soil samples were collected from the study area at two depths (0-0.30 and 0.30-0.60 m). At a 0-0.30 m depth, the highest bulk density (ρb) of 1.50 Mg m-3 was observed in LCMBAE, while the lowest ρb of 1.43 Mg m-3 was recorded in BMBAE. The soil organic carbon (SOC) and SOC stock values exhibited a range of 4.2-7.7 g kg-1 and 19.0-33.4 Mg ha-1, respectively. In the AFBAE, the highest levels of 163.1 % MBC were found over LCMBAE. At a 0-0.30 m depth, the recalcitrant index (RI) and lability index (LI) ranged from 0.35-0.46 to 1.97-2.11, respectively. Additionally, the AFBAE exhibited the highest total biomass accumulation (39.23 Mg ha-1), carbon dioxide (CO2) biosequestration (287.9 Mg ha-1), and the total social cost of CO2 at US$ 277 ha-1. Furthermore, in the AFBAE, there was a 198.1 % increase in total C credit (US$ 161 ha-1) compared to LCMBAE (US$ 54 ha-1). However, at 0.30-0.60 m depths, GWBAE and CALBAE were statistically equivalent (p ≤ 0.05) in total C stocks. Principal component analysis (PCA) reveals that component-1 accounts for 77.4 % of the variability, while component-2 contributes 18.6 %. This article aimed to convert the degraded land into a sustainable agricultural module by increasing SOC and CO2 biosequestration and producing more C-credit, or climate currency, on underutilized land.

SELEÇÃO DE REFERÊNCIAS
DETALHE DA PESQUISA