Evaluating soil quality indices in an agricultural region of Jiangsu Province, China

Qi, Yanbing; Darilek, Jeremy Landon; Huang, Biao; Zhao, Yongcun; Sun, Weixia; Gu, Zhen

doi:10.1016/j.geoderma.2008.12.015

Cited by 358 publications

(297 citation statements)

References 42 publications

(61 reference statements)

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“…For example, criteria can be developed and parameters measured and integrated to evaluate if a land area is suitable for development of irrigated agriculture. The MVIK method has been used to map the distribution of soil nutrients [10], define zones of soil pollutants [11], evaluate chemical health risks of groundwater [12], evaluate soil quality indices [6,13], classify soil degradation in agricultural lands [14], and assess groundwater quality for irrigated agriculture [15].…”

Section: Introductionmentioning

confidence: 99%

Field Scale Studies on the Spatial Variability of Soil Quality Indicators in Washington State, USA

Smith

Halvorson

2011

Applied and Environmental Soil Science

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Arable lands are needed for sustainable agricultural systems to support an ever-growing human population. Soil quality needs to be defined to assure that new land brought into crop production is sustainable. To evaluate soil quality, a number of soil attributes will need to be measured, evaluated, and integrated into a soil-quality index using the multivariable indicator kriging (MVIK) procedure. This study was conducted to determine the spatial variability and correlation of indicator parameters on a field scale with respect to soil quality and suitability for use with MVIK. The variability of the biological parameters decreased in the order of respiration > enzyme assays and qCO 2 > microbial biomass C. The distribution frequency of all parameters except respiration were normal although the spatial distribution across the landscape was highly variable. The biological parameters showed little correlation with each other when all data points were considered; however, when grouped in smaller sections, the correlations were more consistent with observed patterns across the field. To accurately assess soil quality, and arable land use, consideration of spatial and temporal variability, soil conditions, and other controlling factors must be taken into account.

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Section: Introductionmentioning

confidence: 99%

Field Scale Studies on the Spatial Variability of Soil Quality Indicators in Washington State, USA

Smith

Halvorson

2011

Applied and Environmental Soil Science

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“…El resultado obtenido en cada CP se le asignó como ponderador a los indicadores seleccionados en el respectivo CP (Andrews et al, 2002). En el MDS2 a los indicadores se les asignó como ponderador el valor de la comunalidad del AF (Qi et al, 2009;Yu-Dong et al, 2013). Los ponderadores de cada MDS se incluyeron en valor absoluto en los índices de calidad.…”

Section: Ponderación De Los Indicadores De La Calidad Del Suelounclassified

“…El núcleo con las mejores condiciones de calidad del suelo fue Ciudad Bolívar por tener el mejor índice promedio en las 10 fincas estudiadas en él, a diferencia de La Ceja-El Retiro que presentó el índice más bajo. Al comparar los valores de los índices obtenidos es evidente el gran impacto que tuvo la ponderación de los indicadores con la comunalidad de ellos en el ICS2 (Qi et al, 2009). Las diferencias entre los ICS fueron significativas estadísticamente al 95 %.…”

Section: Cálculo De Los íNdices De La Calidad Del Suelo (Ics)unclassified

“…Las mejores confirmando la importancia de los microorganismos del suelo en la calidad de las cosechas, como lo establecieron Qi et al (2009) y Yu-Dong et al (2013. Aunque se presentaron sólo dos correlaciones significativas entre el Mgf y la calidad de la taza, las correlaciones obtenidas entre Mgf y Sf con dicha calidad parecen indicar que el contenido de estos dos elementos en la hoja pueden llegar a ser unos buenos indicadores de la calidad de la taza que se va a tener.…”

Section: Evaluación De La Calidad De La Taza De Caféunclassified

“…Según Glover et al (2000), Andrews et al (2002), Rezai et al (2004), Qi et al (2009) y Yu-Dong et al (2013, el MDS para evaluar la calidad del suelo puede ser seleccionado utilizando la opinión de los expertos, las funciones de pedotransferencia o con procedimientos estadísticos multivariados. Luego de la selección del MDS, los indicadores son transformados, con funciones lineales o no lineales, a un sistema adimensional para ser incluidos en el índice de la calidad del suelo (ICS).…”

Section: Introductionunclassified

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Determinación De Dos Índices De La Calidad Del Suelo en La Calidad De La Taza De Café

Anaya-Gómez

Jaramillo

2017

Rev. Fac. Cienc.

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Se evaluaron algunas propiedades edáficas y foliares en 50 fincas cafeteras de seis municipios de Antioquia. Se determinaron dos índices de la calidad del suelo relacionados con la calidad de la taza de café mediante dos conjuntos de indicadores seleccionados por análisis de componentes principales (MDS1) y análisis de factores (MDS2). El contenido de azufre (S), la actividad enzimática (AE), el índice de Shanoon (ISh), la respirometría (CO2) y los contenidos foliares de N (Nf), Mg (Mgf) y S (Sf) fueron indicadores comunes a los dos índices. Los mejores índices se presentaron en Ciudad Bolívar, finca La Carolina: ICS1 (1,32) e ICS2 (4,32). Los índices más bajos estuvieron en Urrao: ICS1 (finca El Cadillal: 0,82) e ICS2 (fincas El Rosal y El Cadillal: 2,50). El mayor índice general promedio lo presentó el ICS2 (3,19) y el menor el ICS1 (1,05). Se presentaron diferencias significativas en los índices entre ellos y entre núcleos. Se recomienda el uso del ICS2 por ser mayor y requerir menos variables: más económico y fácil de determinar.

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Developing soil health scoring indices based on a comprehensive database under different land management practices in Florida

Amgain

Nan

Rabbany

et al. 2022

Agrosystems Geosci & Env

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A standardized soil health scoring system would be a beneficial tool for accessing and interpreting the status of soil health in Florida. However, because of the climate variability and diverse soil types, a soil health soring function designed in one location may not be useful for other places. In this study, we focused on developing scoring functions for Florida soil using a soil health indicator database under different land management practices across Florida. A soil health scoring index for 11 soil health indicators was calculated for 398 soil samples using comprehensive assessment of soil health (CASH), linear or nonlinear scoring function, and additive and weighted-additive methods. Based on communality and weights of total data sets (TDS), Mehlich-3 phosphorus (M3P) contributed the most, whereas pH contributed the least to the indices. The nonlinear scoring function had higher scores than other scoring functions. Only mixed cropping systems had significant changes in soil health indicators before and after treatment. The principal component analysis (PCA) showed that OM and M3P had the highest loading values compared with other indicators. Therefore, OM and M3P need to be considered if minimum number of indicators is to be measured while examining soil health indices pertinent to Florida soil types and land management practices. Overall, the findings of this study provide a foundation for creating and enhancing soil health indices in Florida.

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Evaluating soil quality indices in an agricultural region of Jiangsu Province, China

Cited by 358 publications

References 42 publications

Field Scale Studies on the Spatial Variability of Soil Quality Indicators in Washington State, USA

Field Scale Studies on the Spatial Variability of Soil Quality Indicators in Washington State, USA

Determinación De Dos Índices De La Calidad Del Suelo en La Calidad De La Taza De Café

Developing soil health scoring indices based on a comprehensive database under different land management practices in Florida

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