Development of a Quality Index to Evaluate the Impact of Abiotic Stress in Saline Soils in the Geothermal Zone of Los Negritos, Michoacán, Mexico

In recent years, salinity-induced soil quality impairment and the misuse of management practices have led to the reduced productivity of agroecosystems. This has prompted a search for simple and effective agricultural management strategies that improve the sustainability of agricultural production t...

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Published in:Agronomy (Basel) 2023-06, Vol.13 (6), p.1650
Main Authors: Bahena-Osorio, Yanely, Franco-Hernández, Marina Olivia, Pueyo, José J., Vásquez-Murrieta, María Soledad
Format: Article
Language:English
Subjects:
abiotic stress
Agricultural ecosystems
Agricultural management
Agricultural production
Agriculture
Carbon
Cation exchange
Cation exchanging
Corn
Correlation analysis
Datasets
Electrical conductivity
Indicator organisms
Indicators
Lithium
minimum dataset
Nitrogen
Phosphatase
principal component analysis
Principal components analysis
Quality assessment
Quality management
Rainy season
Saline soils
Salinity
Soil fertility
soil properties
Soil quality
soil quality indicators
Soil stresses
Soils, Salts in
Variables
Variance analysis
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Summary:In recent years, salinity-induced soil quality impairment and the misuse of management practices have led to the reduced productivity of agroecosystems. This has prompted a search for simple and effective agricultural management strategies that improve the sustainability of agricultural production through soil quality assessments. In this context, the objective of this study was to establish an integrated soil quality index (SQI) by assessing the influence of different types of abiotic stress in two different seasons, using physical, chemical and biological indicators at three sites in the geothermal zone of “Los Negritos”, Michoacán, Mexico. Thirty-nine indicators related to soil fertility attributes and C, N, P, and S cycling—identified as the total dataset (TDS)—were evaluated. Principal component analysis (PCA) and the Spearman correlation matrix (r2 ≥ 0.6) were used to calculate the SQI using an integrated quality index (IQI) equation, with the indicators total nitrogen (TN), cation exchange capacity (CEC), lithium (Li), and zinc (Zn) identified as the minimum dataset (MDS). Significantly higher SQI values related to the better performance of soil functions were detected during the rainy season.
ISSN:2073-4395
2073-4395
DOI:10.3390/agronomy13061650