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Yang, John; Hammer, Richard; Thompson, Allen L.; Blanchar, R. W.

doi:10.1023/a:1022801322245

Cited by 23 publications

(7 citation statements)

References 13 publications

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“…The relationships between soil productivity indexes and corn yield have been discussed by numerous researchers (Gantzer and McCarty 1987;Myers et al 2000). Furthermore, as a simple and mature soil productivity evaluation model, the PI has been used to predict some other agronomic crops, such as soybean (Rijsberman and Wolman 1985;Yang et al 2003), wheat (Wilson et al 1991;Thompson et al 1992), and sorghum (Rijsberman and Wolman 1985;Mulengera and Payton 1999), around the world. Almost all of those studies found a good relationship between soil productivity indexes and crop yields, where a high soil productivity index value corresponds to high crop yields in all crops.…”

Section: Modification and Validation Of Soil Productivity Modelmentioning

confidence: 99%

A new method to calculate soil loss tolerance for sustainable soil productivity in farmland

Duan

Shi

et al. 2016

Agron. Sustain. Dev.

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Soil loss tolerance (T) is a widely used concept for assessing potential risks of soil erosion and is a criterion for assessing the effectiveness of soil and water conservation projects. However, current approaches for calculating T values lack a strong scientific basis, and few practicable methods are available. Many questions remain regarding which parameters, such as planning periods and offset damages, should be included in calculating T values. Here, we developed a new method to calculate soil loss tolerance as a function of the soil productivity index (SPI) for farmland. To achieve sustainable soil productivity in farmland, erosion rates leading to SPI values lower than the lower boundary of soil productivity (SPI0) are not tolerable and must be controlled by soil conservation measures. We applied this method in the Red River Basin of China based on the investigation of typical soil profiles and crop yields. Our results show that the T values in the Red River Basin ranged from 0.91 to 10.24 t ha −1 a −1. The SPI0 and the lowest limit of soil loss tolerance (T1) were 0.4 and 0.91 t ha −1 a −1 , respectively. Here, we demonstrate that, when determining T values in farmland, (1) the soil formation rate and offset damage should not be core items, (2) the "planning period" concept should be replaced by "sustainability", (3) the management objective of T should be the sustainability of the soil resource, and (4) the T values of farmland should be determined according to soil productivity. We provide a reasonable and feasible method to determine T for farmland, which will help maintain the sustainability of soil productivity.

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Section: Modification and Validation Of Soil Productivity Modelmentioning

confidence: 99%

A new method to calculate soil loss tolerance for sustainable soil productivity in farmland

Duan

Shi

et al. 2016

Agron. Sustain. Dev.

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“…In the past few years, ZnGa 2 O 4 nanowires and thin films have been synthesized using various methods such as solid-state reaction [ 7 , 15 , 16 ], sputtering [ 8 ], sol–gel processing [ 17 ], electrophoresis [ 18 ], pulsed laser deposition [ 19 ], thermal evaporation [ 20 , 21 ], and chemical vapor deposition [ 22 - 26 ]. However, the synthesis of hierarchical ZnGa 2 O 4 nanostructures has not been investigated yet.…”

Section: Introductionmentioning

confidence: 99%

Synthesis of ZnGa2O4 Hierarchical Nanostructure by Au Catalysts Induced Thermal Evaporation

et al. 2010

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In this paper, ZnGa2O4 hierarchical nanostructures with comb-like morphology are fabricated by a simple two-step chemical vapor deposition (CVD) method: first, the Ga2O3 nanowires were synthesized and employed as templates for the growth of ZnGa2O4 nanocombs; then, the as-prepared Ga2O3 nanowires were reacted with ZnO vapor to form ZnGa2O4 nanocombs. Before the reaction, the Au nanoparticles were deposited on the surfaces of Ga2O3 nanowires and used as catalysts to control the teeth growth of ZnGa2O4 nanocombs. The as-prepared ZnGa2O4 nanocombs were highly crystallized with cubic spinel structure. From the photoluminescence (PL) spectrum, a broad band emission in the visible light region was observed of as-prepared ZnGa2O4 nanocombs, which make it promising application as an optical material.

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“…Surface soil textures are silty clay loam to silty clay (Young and Geller, 1995). Variations in claypan profi le properties across the landscape greatly infl uence the profi le water holding capacity ( Jiang et al, 2007b), hydraulic conductivity (Th ompson et al, 1991;Yang et al, 2003;Jiang et al, 2007a), and plant root development (Wang et al, 2003;Myers et al, 2007).…”

mentioning

confidence: 99%

Reflectance Spectroscopy Detects Management and Landscape Differences in Soil Carbon and Nitrogen

Chaudhary

Sudduth

Kitchen

et al. 2012

Soil Science Society of America Journal

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Many studies have calibrated visible and near-infrared (VNIR) diffuse reflectance spectroscopy (DRS) to various soil properties; however, few studies have used VNIR DRS to detect treatment differences in controlled experiments. Therefore, our objective was to investigate the ability of VNIR DRS to detect treatment differences in topsoil organic C (SOC) and total N (TN) compared with standard dry combustion analysis. A long-term (since 1991) experiment in central Missouri, where cropping systems were replicated across a typical claypan soil landscape was studied. Soil samples from two depths (0-5 and 5-15 cm) were obtained in 2008 at summit, backslope, and footslope positions for three grain cropping systems. Estimates of SOC by VNIR DRS using oven-dried soil samples and an independent calibration set were very good, with /?2 = 0.87 and RMSE = 2.4 g k §-\ Estimates of TN were somewhat less accurate {R^ = 0.79, RMSE = 0.24 g kg-i). Field-moist VNIR DRS results were also good, but with 13 to 17% higher RMSE. Trends in differences among treatment means were very similar for dry combustion, oven-dry soil VNIR, and field-moist VNIR. Dry combustion was best at separating treatment means, followed by dry soil VNIR and field-moist VNIR. Differences among methods were relatively minor for 0-to 5-cm depth samples but more pronounced for 5-to 15-cm samples. Efficiency of the VNIR method, particularly when applied to field-moist soil, suggests that it deserves consideration as a tool for determining near-surface SOC and TN differences in field experiments.

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Cited by 23 publications

References 13 publications

A new method to calculate soil loss tolerance for sustainable soil productivity in farmland

A new method to calculate soil loss tolerance for sustainable soil productivity in farmland

Synthesis of ZnGa2O4 Hierarchical Nanostructure by Au Catalysts Induced Thermal Evaporation

Reflectance Spectroscopy Detects Management and Landscape Differences in Soil Carbon and Nitrogen

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