Large-scale spatial variability of eight soil chemical properties within paddy fields

Duan, Liangxia; Li, Zhenwei; Xie, Huaming; Li, Zhiming; Zhang, Liang; Zhou, Qing

doi:10.1016/j.catena.2019.104350

Cited by 31 publications

(13 citation statements)

References 44 publications

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“…The CVs of pH, OM, and CEC were lower than 32%, indicating anthropogenic activities have little influence on these soil properties. The CV value of TN was 63.97%, which may be attributed to the different land-use types and fertilization patterns [ 40 ].…”

Section: Resultsmentioning

confidence: 99%

Metal(loid)s Spatial Distribution, Accumulation, and Potential Health Risk Assessment in Soil-Wheat Systems near a Pb/Zn Smelter in Henan Province, Central China

Liu

Ren

et al. 2022

IJERPH

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To understand the influence of Pb/Zn smelter on surrounding environment, 110 soil and 62 wheat grain samples (62 paired samples) were collected nearby a Pb/Zn smelter in Jiaozuo City, Henan Province, China. The content and spatial distribution of metal(loid)s in the soil-wheat system, and the potential health risk via consumption of wheat grains were determined. Results showed that the average content of Pb, Cd, As, Cu, Zn, and Ni in soil were 129.16, 4.28, 17.95, 20.43, 79.36, and 9.42 mg/kg, respectively. The content of Cd in almost all soil samples (99.1%) exceeded the national limitation of China (0.6 mg/kg). Spatial distribution analysis indicated that atmospheric deposition might be the main pollution source of Pb, Cd, As, and Zn in soil. In addition, the average content of Pb, Cd, As, Cu, Zn, and Ni in wheat grain were 0.62, 0.35, 0.10, 3.7, 35.77, and 0.15 mg/kg, respectively, with the average Pb and Cd content exceeding the national limitation of China. The average bioaccumulation factor of these metal(loid)s followed the following order: Zn (0.507) > Cu (0.239) > Cd (0.134) > Ni (0.024) > Pb (0.007) > As (0.006). Health risk assessment indicated that the average noncarcinogenic risk of children (6.78) was much higher than that of adults (2.83), and the carcinogenic risk of almost all wheat grain is higher than the acceptable range, with an average value of 2.43 × 10−2. These results indicated that humans who regularly consume these wheat grains might have a serious risk of noncarcinogenic and carcinogenic diseases.

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Section: Resultsmentioning

confidence: 99%

Metal(loid)s Spatial Distribution, Accumulation, and Potential Health Risk Assessment in Soil-Wheat Systems near a Pb/Zn Smelter in Henan Province, Central China

Liu

Ren

et al. 2022

IJERPH

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“…On the other hand, paddy soils studied in western Burkina Faso (all over the six sites) are particularly poor if compared for example to a study of more than 8 000 soils in Hunan Province (Duan et al . 2020), where average organic carbon was 1.972%, compared to 0.922% in our study, total nitrogen was 0.191%, higher than 0.072%, and total phosphorus was 0.71g.kg -1 , compared to 0.24g.kg -1 .…”

Section: Discussionmentioning

confidence: 88%

The impact of the rice production system (irrigated vs lowland) on root-associated microbiome from farmer’s fields in western Burkina Faso

Barro

Wonni

Simonin

et al. 2022

Preprint

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As a consequence of its potential applications for food safety, there is a growing interest in rice root-associated microbial communities, but some systems remain understudied. Here, we compare the assemblage of root-associated microbiota in rice sampled in 19 small farmers fields from irrigated and rainfed lowlands in western Burkina Faso, using an amplicon metabarcoding approach 16S (Prokaryotes, three plant sample per field) and ITS (fungi, one sample per field). In addition to the expected structure according to the root compartment (root vs. rhizosphere) and geographical zones, we show that the rice production system is a major driver of microbiome structure, both for prokaryotes and fungi. In irrigated systems, we found a higher diversity of prokaryotic communities from rhizosphere and more complex co-occurrence networks, compared to rainfed lowlands. Core taxa were different between the two systems, and indicator species were identified: mostly within Bacillaceae and Bradyrhizobiaceae families in rainfed lowlands, and within Burkholderiaceae and Moraxellaceae in irrigated areas. Finally, phylotypes assigned to putative phytobeneficial and pathogen species were found. Mycorrhizal fungi Glomeromycetes abundance was higher in rainfed lowlands. Our results highlight deep microbiome differences induced by contrasted rice production systems that should consequently be considered for potential microbial engineering applications.

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“…The soil alkali‐hydrolyzable N (available N) content was determined by the alkaline hydrolysis diffusion method (Xiong et al., 2008). Soil total K was determined by the sodium hydroxide fusion method at 720 °C followed by flame photometry measurement (Duan et al., 2020; ISSAS, 1978). Soil available K forms were extracted using 1 mol L −1 ammonium acetate and measured by flame photometry (Mi et al., 2019).…”

Section: Methodsmentioning

confidence: 99%

Prediction of multiple soil fertility parameters using VisNIR spectroscopy and PXRF spectrometry

Liu

Wang

Xiao

et al. 2021

Soil Science Soc of Amer J

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Visible and near-infrared (VisNIR) spectroscopy and portable X-ray fluorescence (PXRF) spectrometry are successful in estimating soil attributes. However, it is still necessary to investigate their performance in estimating soil fertility properties. In this study, for the soil fertility properties of soil organic C (SOC), available N, total P, available P, total K, and available K, the performance of using VisNIR and PXRF individually and combined, three data fusion methods (concatenation, model fusion and model averaging), and two modeling methods was evaluated. The results showed that combining VisNIR and PXRF did not substantially improve the prediction accuracy of SOC, total P, total K and available K. Using VisNIR alone could predict them well, achieving the best prediction in total K (R 2 = .90, ratio of performance to interquartile distance [RPIQ] = 5.08, and residual prediction deviation [RPD] = 3.13), followed by SOC (R 2 = .77, RPIQ = 2.05, and RPD = 2.10), total P (R 2 = .63, RPIQ = 2.35, and RPD = 1.64), and available K (R 2 = .53, RPIQ = 2.04, and RPD = 1.41). Both available N and available P were poorly estimated by all the methods proposed in this study. Although PXRF alone could predict total P, total K, and available K with acceptable accuracy, it did not perform well on SOC (R 2 < .32, RPIQ < 1.16, and RPD < 1.19). Hence, for the precision application of organic and NPK fertilizers, VisNIR is supposed to be the optimal way to rapidly obtain soil information.

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Large-scale spatial variability of eight soil chemical properties within paddy fields

Cited by 31 publications

References 44 publications

Metal(loid)s Spatial Distribution, Accumulation, and Potential Health Risk Assessment in Soil-Wheat Systems near a Pb/Zn Smelter in Henan Province, Central China

Metal(loid)s Spatial Distribution, Accumulation, and Potential Health Risk Assessment in Soil-Wheat Systems near a Pb/Zn Smelter in Henan Province, Central China

The impact of the rice production system (irrigated vs lowland) on root-associated microbiome from farmer’s fields in western Burkina Faso

Prediction of multiple soil fertility parameters using VisNIR spectroscopy and PXRF spectrometry

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