Soil Salinity Effects on Crop Growth and Yield - Illustration of an Analysis and Mapping Methodology for Sugarcane

Wiegand, C. L.; Anderson, Gerald L.; Lingle, Sarah E.; Escobar, D. E.

doi:10.1016/s0176-1617(96)80274-4

Cited by 63 publications

(39 citation statements)

References 10 publications

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“…Cotton is largely cultivated on irrigated land, is therefore considered an ideal indirect indicator for soil salinity, so it has been used as salinity indicators in a variety of studies [31]. For example, based on the high correlations between the Normalized Difference Vegetation Index (NDVI) values of cotton, sugarcane crops and the EC, Wiegand et al [45,46] successfully assessed the severity and extent of soil salinity in terms of the economic impact on crop production and also distinguished saline soils from non-affected soils. This strong relationship most likely exists only where salinity is the major factor that causes crop yield variability; lands that suffer from soil salinity are likely to have other factors that affect yields as much or more than salinity, such as high or low temperatures, topography and land management.…”

Section: Crop Performancementioning

confidence: 99%

Soil Salinity Mapping and Monitoring in Arid and Semi-Arid Regions Using Remote Sensing Technology: A Review

Allbed¹,

Kumar²

2013

ARS

297

159

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Soil salinity is a serious environmental problem especially in arid and semiarid areas. It either occurs naturally or is human-induced. High levels of soil salinity negatively affect crop growth and productivity leading land degradation ultimately. Thus, it is important to monitor and map soil salinity at an early stage to enact effective soil reclamation program that helps lessen or prevent future increase in soil salinity. Remote sensing has outperformed the traditional method for assessing soil salinity offering more informative and professional rapid assessment techniques for monitoring and mapping soil salinity. Soil salinity can be identified from remote sensing data obtained by different sensors by way of direct indicators that refer to salt features that are visible at the soil surface as well as indirect indicators such as the presence of halophytic plant and assessing the performance level of salt-tolerant crops. The purposes of this paper are to 1) discuss some soil salinity indicators; 2) review the satellite sensors and methods used for remote monitoring, detecting and mapping of soil salinity, particularly in arid and semi-arid regions; 3) review various spectral vegetation and salinity indices that have been developed and proposed for soil salinity detection and mapping, with an emphasis on soil salinity mapping and assessment in arid and semi-arid regions; and 4) highlight the most important issues limiting the use of remote sensing for soil salinity mapping, particularly in arid and semi-arid regions.

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Section: Crop Performancementioning

confidence: 99%

Soil Salinity Mapping and Monitoring in Arid and Semi-Arid Regions Using Remote Sensing Technology: A Review

Allbed¹,

Kumar²

2013

ARS

297

159

View full text Add to dashboard Cite

show abstract

“…Remedial solutions require mapping of affected areas in space and time. This can be accomplished using remote sensing measurements which identify contaminated soils by their unusually high surface reflectance factors or by detecting reduced biomass or changes in spectral properties of plants growing in affected areas (Wiegand et al, 1992a;Wiegand et al, 1994;Wiegand et al, 1996;Wang et al, 2001;Wang et al, 2002a;Barnes et al, 2003 (p. 619, this issue)). Significant correlations exist between mid-season VIs and final yields of cotton and sorghum crops which are affected by salinity stress at sub-field spatial scales (Wiegand et al, 1994;Yang et al, 2000).…”

Section: Salinity Stressmentioning

confidence: 99%

Remote Sensing for Crop Management

Pinter¹,

Hatfield²,

Schepers³

et al. 2003

photogramm eng remote sensing

491

254

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“…The regression coefficients for sodicity and salinity were negative, because the soil sodicity and salinity can cause vegetation stress, obstructing crop growth and productivity (Maas, 1984;Abrol et al, 1988;Wiegand et al, 1996;Yamaguchi and Blumwald, 2005;Shabhax and Ashraf, 2013).…”

Section: Due To the Normalization Of The Response Andmentioning

confidence: 99%

Statistical estimation of crop yields for the Midwestern United States using satellite images, climate datasets, and soil property maps

Kim¹,

Cho²,

Hong³

et al. 2016

Korean Journal of Remote Sensing

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:In this paper, we described the statistical modeling of crop yields using satellite images, climatic datasets, soil property maps, and fertilizer data for the Midwestern United States during 2001-2012. Satellite images were obtained from the Moderate Resolution Imaging Spectroradiometer (MODIS), and climatic datasets were provided by the Parameter-elevation Regressions on Independent Slopes Model (PRISM) Climate Group. Soil property maps were derived from the Harmonized World Soil Database (HWSD). Our multivariate regression models produced quite good prediction accuracies, with differences of approximately 8-15% from the governmental statistics of corn and soybean yields. The unfavorable conditions of climate and vegetation in 2012 could have resulted in a decrease in yields according to the regression models, but the actual yields were greater than predicted. It can be interpreted that factors other than climate, vegetation, soil, and fertilizer may be involved in the negative biases. Also, we found that soybean yield was more affected by minimum temperature conditions while corn yield was more associated with photosynthetic activities. These two crops can have different potential impacts regarding climate change, and it is important to quantify the degree of the crop sensitivities to climatic variations to help adaptation by humans. Considering the yield decreases during the drought event, we can assume that climatic effect may be stronger than human adaptive capacity. Thus, further studies are demanded particularly by enhancing the data regarding human activities such as tillage, fertilization, irrigation, and comprehensive agricultural technologies.

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Soil Salinity Effects on Crop Growth and Yield - Illustration of an Analysis and Mapping Methodology for Sugarcane

Cited by 63 publications

References 10 publications

Soil Salinity Mapping and Monitoring in Arid and Semi-Arid Regions Using Remote Sensing Technology: A Review

Soil Salinity Mapping and Monitoring in Arid and Semi-Arid Regions Using Remote Sensing Technology: A Review

Remote Sensing for Crop Management

Statistical estimation of crop yields for the Midwestern United States using satellite images, climate datasets, and soil property maps

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