Precision of Predicting Soil Salinity Based on Vegetation Categories of Abandoned Lands

Tóth, Tibor; Matsumoto, Satoshi; Mao, Ruifeng; Yin, Yanfeng

doi:10.1097/00010694-199509000-00007

Cited by 15 publications

(10 citation statements)

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“…The mean annual transpiration is 2138.6 mm, the mean annual air temperature is 12.3°C with the maximum and minimum mean monthly air temperature being 26.6°C (July) and -4.3°C (January), respectively, and with 184 frost-free days a year. The total salt content is over 0.8% at 0-10 cm and remained essentially constant at around 0.5% at depths below 40 cm in the saline soil of this region (Tóth et al 1995, Mao et al 2002. The depth of the groundwater table to surface is 5.6-6.0 m during the maize cropping season.…”

Section: Site and Soilmentioning

confidence: 86%

Effects of nitrogen fertilizer application rates on nitrate nitrogen distribution in saline soil in the Hai River Basin, China

Yin

Mao

2007

J Soils Sediments

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Conclusions. Nitrogen fertilizer application increased NO 3--N concentration and stock in 0-100cm soil profile and changed NO 3 --N distribution during maize cropping season. And nitrogen fertilizer application promoted movement of NO 3 --N down the soil profile and increased N loss. But effects of nitrogen fertilization application rate on above-ground dry matter production and grain yield were non-linear. Recommendations and Perspectives.A strictly controlled, site-specific, long-term fertilization study will be set up for the determination of biochemical processes of soil NO 3 --N and for the effective N fertilizer management of the saline soil areas. --N) accumulation is related closely to NO 3 -leaching, which is an important issue in groundwater pollution, especially in intensive agricultural areas with saline soils where volumes of water are used in irrigation to avoid salt accumulation in the root zone. However, in the saline environment in Hai River Basin, China, the importance of detailed research into NO 3 --N distribution in the root zone has not been adequately recognized. Considering the impacts of eco-environmental system N and crop production, the present study aimed at contributing to an understanding of the effects of N application rate on soil NO 3 --N distribution, NO 3 --N residue, N loss, and maize (Zea mays L.) yield in this region.

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Section: Site and Soilmentioning

confidence: 86%

Effects of nitrogen fertilizer application rates on nitrate nitrogen distribution in saline soil in the Hai River Basin, China

Yin

Mao

2007

J Soils Sediments

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“…Fisher's least significant difference (LSD) was used to test the significance of means that were considered significantly different at a = 0.05 probability level. Canonical correlation analysis (CCA) was also run to determine the extent to which the variation of SOCP could be attributed to site variables (Töth et al, 1995;Dieleman et al, 2000;Tan et al, 2003).…”

Section: Discussionmentioning

confidence: 99%

Relationships between surface soil organic carbon pool and site variables

et al. 2004

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“…The CCA was run to identify the dominant associations between a set of independent variables ( j) and a set of soil dependent properties (k) and to determine the extent to which the variation of soil properties could be attributed to independent variables (Dieleman et al, 2000;Töth et al, 1995).…”

Section: Discussionmentioning

confidence: 99%

“…The standardized canonical coefficients (SCC) for each canonical variable can be used to interpret associations between two sets of variables, and the magnitude and sign of the coefficient indicate the importance and direction of respective variables in the relationship (Dieleman et al, 2000;Töth et al, 1995). The first three canonical variates of two sets of variables for all pedons are expressed by their original variables as follows because their respective correlations are significant (P Ͻ 0.0001), as previously mentioned.…”

Section: Associations Among Soil Properties and Site Variablesmentioning

confidence: 99%

Identifying Associations Among Soil and Site Variables Using Canonical Correlation Analysis

et al. 2003

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Alfisols are the predominant soil resource in Ohio. An understanding of the relationships among their soil and site variables will help in planning judicious future land use to maintain soil quality and sustain agriculture. The objective of this study was to identify associations and their significance between dependent variables of surface horizons of Alfisols (consisting of bulk density, base saturation, CEC, pH, Munsell value and chroma) and descriptive variables (including drainage class, elevation, sand, slope gradient, soil organic carbon) using canonical correlation analysis (CCA). The association of SOC concentration with bulk density was found to be the most important relationship among the selected variables, followed by the association of soil clay content with CEC. The association of drainage class and Munsell chroma was identified as being dominant and significant from the third pair of canonical variates. Despite pronounced variations in the means of all selected variables among land uses, these associations and their significance were consistently confirmed, regardless of land use, and were responsible for about 60% of the variance within each set of variables. Additional associations could be identified from other canonical variates but were less explicit and varied widely among land uses. As a means of identifying associations and the order of their importance among multivariates, the CCA has become a promising technique for simplifying, and simultaneously analyzing, two sets of complex data consisting of biotic and abiotic variables. (Soil Science 2003;168:376-382)

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Precision of Predicting Soil Salinity Based on Vegetation Categories of Abandoned Lands

Cited by 15 publications

References 0 publications

Effects of nitrogen fertilizer application rates on nitrate nitrogen distribution in saline soil in the Hai River Basin, China

Effects of nitrogen fertilizer application rates on nitrate nitrogen distribution in saline soil in the Hai River Basin, China

Relationships between surface soil organic carbon pool and site variables

Identifying Associations Among Soil and Site Variables Using Canonical Correlation Analysis

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