Assessing soil key fertility attributes using a portable X-ray fluorescence : a simple method to overcome matrix effect

The matrix effect is one of the challenges to be overcome for a successful analysis of soil samples using X-ray fluorescence (XRF) sensors. This work aimed at evaluation of a simple modeling approach consisted of Compton normalization (CN) and multivariate regressions (e.g., multiple linear regressions (MLR) and partial least squares regression (PLSR)) to overcome the soil matrix effect, and subsequently improve the prediction accuracy of key soil fertility attributes. A portable XRF was used for analyzing 102 soil samples collected from two agricultural fields with contrasting soil matrices. Using the intensity of emission lines as input, preprocessing methods included with and without the CN. Univariate regression models for the prediction of clay, cation exchange capacity (CEC), and exchangeable (ex-) K and Ca were compared with the corresponding MLR models to assess matrix effect mitigation. The MLR and PLSR models improved the prediction results of the univariate models for both preprocessing methods, proving to be promising strategies for mitigating the matrix effect. In turn, the CN also mitigated part of the matrix effect for ex-K, ex-Ca, and CEC predictions, by improving the predictive performance of these elements when used in univariate and multivariate models. The CN has not improved the prediction accuracy of clay. The prediction performances obtained using MLR and PLSR were comparable for all evaluated attributes. The combined use of CN with multivariate regressions (MLR or PLSR) achieved excellent prediction results for CEC (R-2= 0.87), ex-K (R-2 >= 0.94), and ex-Ca (R-2 >= 0.96), whereas clay predictions were comparable with and without CN (0.89 <= R-2 <= 0.92). We suggest using multivariate regressions (MLR or PLSR) combined with the CN to remove the soil matrix effects and consequently result in optimal prediction results of the studied key soil fertility attributes. The prediction performance observed for this solution showed comparable results to the approach based on the preprogrammed measurement package tested (Geo Exploration package, Bruker AXS, Madison, WI, USA)

Effect of X-ray tube configuration on measurement of key soil fertility attributes with XRF

The successful use of energy-dispersive X-ray fluorescence (ED-XRF) sensors for soil analysis requires the selection of an optimal procedure of data acquisition and a simple modelling approach. This work aimed at assessing the performance of a portable XRF (XRF) sensor set up with two different X-ray tube configurations (combinations of voltage and current) to predict nine key soil fertility attributes: (clay, organic matter (OM), cation exchange capacity (CEC), pH, base saturation (V), and extractable nutrients (P, K, Ca, and Mg). An XRF, operated at a voltage of 15 kV (and current of 23 mu A) and 35 kV (and current of 7 mu A), was used for analyzing 102 soil samples collected from two agricultural fields in Brazil. Two different XRF data analysis scenarios were used to build the predictive models: (i) 10 emission lines of 15 keV spectra (EL-15), and (ii) 12 emission lines of 35 keV spectra (EL-35). Multiple linear regressions (MLR) were used for model calibration, and the models' prediction performance was evaluated using different figures of merit. The results show that although X-ray tube configuration affected the intensity of the emission lines of the different elements detected, it did not influence the prediction accuracy of the studied key fertility attributes, suggesting that both X-ray tube configurations tested can be used for future analyses. Satisfactory predictions with residual prediction deviation (RPD) >= 1.54 and coefficient of determination (R-2) >= 0.61 were obtained for eight out of the ten studied soil fertility attributes (clay, OM, CEC, V, and extractable K, Ca, and Mg). In addition, simple MLR models with a limited number of emission lines was effective for practical soil analysis of the key soil fertility attributes (except pH and extractable P) using XRF. The simple and transparent methodology suggested also enables future researches that seek to optimize the XRF scanning time in order to speed up the XRF analysis in soil samples

Combined use of Vis-NIR and XRF sensors for tropical soil fertility analysis : assessing different data fusion approaches

Visible and near infrared (vis-NIR) diffuse reflectance and X-ray fluorescence (XRF) sensors are promising proximal soil sensing (PSS) tools for predicting soil key fertility attributes. This work aimed at assessing the performance of the individual and combined use of vis-NIR and XRF sensors to predict clay, organic matter (OM), cation exchange capacity (CEC), pH, base saturation (V), and extractable (ex-) nutrients (ex-P, ex-K, ex-Ca, and ex-Mg) in Brazilian tropical soils. Individual models using the data of each sensor alone were calibrated using multiple linear regressions (MLR) for the XRF data, and partial least squares (PLS) regressions for the vis-NIR data. Six data fusion approaches were evaluated and compared against individual models using relative improvement (RI). The data fusion approaches included (i) two spectra fusion approaches, which simply combined the data of both sensors in a merged dataset, followed by support vector machine (SF-SVM) and PLS (SF-PLS) regression analysis; (ii) two model averaging approaches using the Granger and Ramanathan (GR) method; and (iii) two data fusion methods based on least squares (LS) modeling. For the GR and LS approaches, two different combinations of inputs were used for MLR. The GR2 and LS2 used the prediction of individual sensors, whereas the GR3 and LS3 used the individual sensors prediction plus the SF-PLS prediction. The individual vis-NIR models showed the best results for clay and OM prediction (RPD >= 2.61), while the individual XRF models exhibited the best predictive models for CEC, V, ex-K, ex-Ca, and ex-Mg (RPD >= 2.57). For eight out of nine soil attributes studied (clay, CEC, pH, V, ex-P, ex-K, ex-Ca, and ex-Mg), the combined use of vis-NIR and XRF sensors using at least one of the six data fusion approaches improved the accuracy of the predictions (with RI ranging from 1 to 21%). In general, the LS3 model averaging approach stood out as the data fusion method with the greatest number of attributes with positive RI (six attributes; namely, clay, CEC, pH, ex-P, ex-K, and ex-Mg). Meanwhile, no single approach was capable of exploiting the synergism between sensors for all attributes of interest, suggesting that the selection of the best data fusion approach should be attribute-specific. The results presented in this work evidenced the complementarity of XRF and vis-NIR sensors to predict fertility attributes in tropical soils, and encourage further research to find a generalized method of data fusion of both sensors data. Keywords Author Keywords

The use of scattered radiation in x-ray fluorescence analysis of soil and plant materials

The isolated atom model of X-ray scatter was used to develop a new analytical strategy for internal standardisation in X-ray fluorescence spectrometry. The method which was applicable to both geological and biological materials, defined quantitatively, by how much and within what limitations, various calibration techniques could improve analyses, for particular elements in specific materials. The analytical strategy was based on a modified peak-to-background ratio equation, where the background intensity was raised by an exponent T. The variable T, combined as special cases, all existing analytical strategies which used scattered X-rays and the simple linear calibration where T = O. Variation in T was evaluated using extensive computer processing of matrix data for typical soil and plant materials. It was found that values of T varied with analyte, scatter wavelength, type of scatter, and the matrix component contributing to mass absorption error. The procedure developed to select the optimum calibration strategy, for any combination of mass absorption errors in soil and plant analysis, showed: (i) how much each interfering component contributed to both initial and final analyte error, (ii) which value of T, for various scatter wavelengths and types of scatter, gave optimum reduction in analyte error, and, (iii) if any improvement over the various strategies commonly used, could be achieved. Consequent limitations of some analytical methods which have been proposed in the literature were discussed. Extremely variable matrices were specially prepared to test the method for zinc and zirconium analysis. The improvement in quality of matrix compensation was as predicted from theory. Values of T were tabulated for analysis of various groups of elements in soil and plant materials and situations were described where successful calibration using scattered radiation was most unlikely. The methods developed were among those used to analyse soils and metalliferous sewage sludge in an experimental programme designed to establish for local conditions (i) maximum permissible sewage sludge application rates and, (ii) the effect of sludge application on pasture production and quality. Although the digested sludge contained useful amounts of plant and animal nutrients, metal content was too high to permit its indiscriminate use as a soil additive. The metal contents were not high enough however to prohibit the judicious utilisation of the sludge within prescribed limits. Highly significant results from both glasshouse and field trials showed that chromium contamination of sludge could decrease pasture production. It appeared that chromium may have blocked plant uptake of nutrient cations. With the sludge chromium concentration at about 0.5%, and the total sludge application at the recommended level of 250 t/ha, no deleterious effects were likely, provided a good supply of nutrient cations was maintained in the soil. Zinc was found to be the limiting contaminant in herbage, and copper concentrations were near the upper safety limits. Potassium deficiency was probably a greater pastoral constraint than was metal toxicity. No other elements were found in herbage, in concentrations likely to be injurious to animal health, or restrictive to plant yield

Soil Contamination and Risk Assessments on Selected Dumpsites within the Basement Complex and Sedimentary Formations of Ogun State, South-western Nigeria

The concentrations of inorganic elements in soils of Saje, Ita-Oshin, Premier, and Oke-Diya dumpsites were determined using an X-Ray Fluorescence spectrometer to assess the soil quality through chronological changes with depths. A soil core sampler collects 56 samples at 20, 40, 60, and 80 cm depths. Saje showed high mean concentrations of Ca, K, Fe, Rb, and Ti at all depths, while Oke-Diya revealed high mean concentrations of Ca, K, Fe, Rb, Ti, Mn, Zn, V, Cr, and Ni at all depths. These concentrations were in a closed range suggesting a build-up of elements in the soil profiles. Oke-Diya had the highest pollution index, followed by Saje, and the contaminations were from anthropogenic and geologic sources. The mean concentrations of Fe, Zn, Ni, Mn, Ti, K, and Ca were high at all depths in Ita-Oshin, and in Premier, the mean concentrations of K and Fe were high at all depths. Premier had the lowest pollution index. Ita-Oshin and Premier enrichment factors showed geologic sources. Saje and Oke-Diya revealed unacceptable non-carcinogenic risks for adults and children, and Ita-Oshin and Premier recorded acceptable limits. Saje and Oke-Diya samples had high carcinogenic risks for adults due to Cr, Pb, and As. Elements Cr and As in Ita-Oshin, and Pb in Premier evinced unacceptable carcinogenic risks for adults. Saje, Oke-Diya, and Premier indicated unacceptable carcinogenic risks for children due to Cr. The study showed toxins build-up in the soil system, and the study areas are not suitable for growing crops and sinking water wells for agricultural and domestic uses

Evaluating solubility, aggregation and sorption of nanosilver particles and silver ions in soils

Engineered nanoparticles (ENPs) are used in so many different products. ENPs are released into different environmental compartments. Silver nanoparticle (AgNP) is one of the most used ENPs. AgNPs may cause damage to the environment due to their toxicity and wide exposure. In this thesis possible exposure ways of AgNPs to the environment was reported. Also sorption-solubility and aggregation of AgNPs and AgNO3 based on the different concentration of Ag and pH function in clayey and sandy soil was investigated. Results showed that sorption of both silver nanoparticles and silver ions by the soils were increased with increasing pH. Silver (nano/ion) sorption ratio in clayey treatment was slightly higher than sandy one. It can be due to having higher CEC value and finer texture in clay in comparison with sand. Partitioning between nanosilver and free silver ions was investigated by help of ultrafiltration. It can be concluded that a significant fraction of the silver nanoparticles were oxidized and transformed to free Ag+ during the oxic experimental conditions. The aggregation of AgNPs and silver ions was investigated based on the different concentration of silver in a constant pH. Aggregation of silver nanoparticulate by help of SEM and XRD were identified in 2.5 ppm concentration of AgNPs in sandy soil. No aggregation was found at low concentration of silver nanoparticles. No silver aggregated spot could be recognized at 6.7, 0.65 and 0.05 ppm concentration of silver in silver nitrate polluted soil samples

Silicate-Solubilizing Bacteria in Louisiana Soils: Identification, Profiling, and Functions in Crop Production

Studies were conducted to determine the potential of silicate-solubilizing bacteria (SSB) as biostimulant in Louisiana rice (Oryza sativa L.) production systems. Isolation and profiling of SSB in Louisiana soils; evaluation on its effects on the silicon (Si) uptake and productivity of rice using various carriers derived from slag, rice hull, and sugarcane (Officinarum spp.) bagasse; and development of a feasible approach of incorporating SSB to the rice production system were conducted. Results showed that numerous bacteria isolated from Louisiana soils can solubilize silicate and produce multiple plant growth-promoting compounds. These potential SSBs were identified into four genera: Aeromonas, Bacillus, Enterobacter, and Pseudomonas. In the greenhouse, the differences in agronomic variables and Si nutrition of rice were evident between Commerce silt loam and Gigger silt loam soil. While Si addition did not result in a significant grain yield increase, there was a significant improvement observed on rice Si uptake. The survival test confirmed the presence of SSB in the different carriers, thus the observed improvement on straw Si content of rice can be associated with the use of SSB-inoculated carriers. Even so, this did not significantly increase rice biomass and grain yield. The lack of rice yield response to Si addition and SSB inoculation was partly explained by the high initial Si availability in both soil types. The semi-quantitative evaluation of silica bodies distribution on the leaf surface of rice (treated with wollastonite and SSB using different carriers) via SEM-EDX further confirmed that the soil type had greater influence than Si addition and SSB inoculation on rice Si nutrition. More silica bodies were observed on the leaf surface of rice planted in Commerce silt loam than in Gigger silt loam. In the laboratory, the highest population of SSB was 5.0 x 106 CFU g-1 (log number of cells, 6.70) obtained in bagasse + soil carrier at 150 days after inoculation with a final population of 4.6 x 106 CFU g-1 at 180 days after inoculation (log number of cells, 6.66). The fluorescent microscopy analysis showed that the green fluorescence protein tagged-SSB can colonize the root tissues of the two-week-old rice seedlings indicating its ability to survive when used as a seed treatment, which is a very practical and efficient application method of potential bioinoculant to the field in the future. Future research will focus on (1) determining the optimum concentration of SSB to be inoculated in different carriers, and (2) evaluating the benefits of SSB application in varying field conditions

Environmental and farm management effects on food nutrient concentrations and yields of East African staple food crops

Hidden hunger affects two billion people worldwide, particularly children and pregnant women. Human health and well-being are dependent on the quality and quantity of food consumed, particularly of plant-based foods. Plants source their nutrients from the soil. Essential nutrients for both, plants and humans, therefore, predominantly originate from the soil. Very little is known about the influence of environmental factors (e.g. soil types and abiotic factors, such as weather), or farm management choices (e.g. fertilisation or agrobiodiversity), on nutrient concentrations of edible crop parts. The main aim of this thesis was, therefore, to analyse the effects of soil fertility, farm management, and abiotic factors such as drought, on the quantity (yields) and quality (nutrient concentrations) of essential macro- (Mg, P, S, K, Ca) and micronutrients (Fe, Zn, Mn and Cu), of the edible parts of three East African staple food crops, i.e. maize (Zea mays L.), cassava (Manihot esculenta} Crantz), and matooke (East African Highland Banana (Musa acuminata Colla)), and discuss the resulting implications for food and nutrition security. Two research areas were selected in East Africa, one with a high fertility soil (Kapchorwa, Uganda - Nitisol) and one with a low fertility soil (Teso South, Kenya Ferralsol). In each region, 72 households were randomly selected, and leaf and edible crop parts, and soil samples collected on three fields per household, organised by distance (closest, mid-distance, and farthest field). Maize and cassava were collected in Teso South, maize and matooke were collected in Kapchorwa. Yields, fertilizer usage and species richness (SR) and diversity (SD) were recorded per field. The total nutrient concentrations were measured in all samples collected (soils and plant parts). A drought occurring in the second rain season of 2016 provided the opportunity to analyse water stress effects on crop quantity and quality (Chapter 2). Edible part samples and yields collected in both seasons were compared. Soil chemical and physical properties, together with farm management variables, were compared to edible part nutrient concentrations and yields using a Canonical Correspondence Analysis (CCA) (Chapter 3). To understand the strength of association between the measurements routinely done by agronomists (leaf measurement) and nutritionists (edible part measurement), samples of each crop were collected, and were compared to each other and to yields, using a bivariate linear mixed model (Chapter 4). During the severe drought, nutrient concentrations in Kapchorwa decreased significantly from normal to drought season in both crops. In contrast, during the moderate drought in Teso South, nutrient concentrations increased significantly in both crops. Lacking nutrient phloem mobility is suggested to play a vital role in mobilisation of micronutrients (Fe, Mn, and Cu), as shown by their decreased concentration under severe drought in the yields of both crops in Kapchorwa (Chapter 2). Soil type had a very strong effect on food nutrient concentrations. Maize grain nutrient concentrations and yields, for example, were significantly higher for all nutrients measured on higher fertility soils. Maize grain had the highest correlations with soil factors. In contrast, corresponding correlations to management factors were much weaker (Chapter 3). Concerning the comparison of nutrient concentrations in different plant parts, low phloem mobile nutrients Ca, Mn, Fe, Zn, and Cu showed the largest differences in correlations between leaves and edible parts. In the same comparison, perennial crops (matooke and cassava) showed lower correlations between leaves and edible parts, than annual crops (maize) (Chapter 4). Environmental factors, such as drought impacted food nutrient concentrations. Severe drought caused a potential double-burden for consumers, decreasing both yields and nutrient concentrations, particularly of micronutrients. Considering food nutrient concentrations, apart from yield, as response variables in agronomic trials (e.g. fertilisation or soil improvement strategies) would contribute towards discounting the notion that crops growing on fertile soils always produce healthy and high-quality foods. Leaves may provide information on plant health, however, do not provide enough information to gauge both yields and food quality, particularly regarding micronutrients. The results also showed that measuring the edible part is vital to assessing food quality, particularly due to the observed effects of nutrient mobility, affecting particularly micronutrients and Ca. Ending hunger and improving food and nutrition security for all, particularly when confronted with global change issues such as degrading soils and a changing climate, requires a collaborative effort by all disciplines concerned.Weltweit leiden zwei Milliarden Menschen an verborgenem Hunger. Die Qualität und die Quantität der konsumierten Nahrung, besonders die der pflanzlichen Nahrung, beeinflusst die Gesundheit und das Wohlbefinden der Menschen. Pflanzen nehmen ihre Nährstoffe aus dem Boden auf. Folglich stammen die essentiellen Makro- und Mikronährstoffe für Pflanzen und damit auch für den Menschen überwiegend aus dem Boden. Es bestehen große Wissenslücken, inwieweit Umweltfaktoren (z.B. abiotische Faktoren wie Bodentyp und Wetter) und das betriebliche Management, die Nährstoffkonzentration im essbaren Pflanzenteil beeinflussen. Das Forschungsziel dieser Arbeit war, den Einfluss der Bodenfruchtbarkeit, des Betriebsmanagements sowie abiotischer Faktoren auf die Erträge (Quantität) und die Nährstoffkonzentrationen (Qualität, essentielle Makro- (Mg, P, S, K, Ca), und Mikronährstoffen (Fe, Zn, Mn, Cu)) dreier ostafrikanischer Grundnahrungsmittel, und zwar Mais (Zea mays L.), Maniok (Manihot esculenta Crantz) und Matooke (ostafrikanische Hochlandbanane (Musa acuminata Colla)), zu analysieren und daraus resultierende Implikationen für die Nahrungs- und Ernährungssicherung zu diskutieren. Zwei Forschungsgebiete mit unterschiedlicher Bodenfruchtbarkeit wurden in Ostafrika ausgewählt (hohe Bodenfruchtbarkeit: Kapchorwa, Uganda Nitisole; niedrige Bodenfruchtbarkeit: Teso South, Kenia Ferralsole). Auf landwirtschaftliche Betrieben wurden Proben der Blätter, der essbaren Pflanzenteile und Bodenproben gesammelt, und deren Nährstoffkonzentrationen gemessen. Mais- und Maniokproben wurden in Teso South gesammelt. Mais- und Matookeproben wurden in Kapchorwa gesammelt. Erträge, Düngeaufwand, Artenreichtum und -diversität wurden je Feld gemessen. Eine eingetretene Dürre in der zweiten Regenperiode 2016 ermöglichte es, die Ertragsquantität und -qualität unter Trockenstress zu analysieren (Kapitel 2). Einflüsse der Bodenchemie und Bodenphysik sowie des betrieblichen Managements wurden mit den Nährstoffkonzentrationen im essbaren Pflanzenteil und den Erträgen unter Anwendung der Kanonischen Korrespondenz-Analyse (CCA) ermittelt (Kapitel 3). Die Nährstoffgehalte der Blätter und der essbaren Pflanzenteile wurden mit den Erträgen durch ein bivariates lineares gemischtes Modell verglichen, um damit die Ergebnisse der gängigen Messmethoden der Agrar- (Blätter) und Ernährungswissenschaften (essbare Pflanzenteile) zu vergleichen, Unterschiede zu identifizieren, und Implikationen für die Nahrungs- und Ernährungssicherung abzuleiten (Kapitel 4). Die Nährstoffgehalte in der intensiven Dürreperiode in Kapchorwa hatten, verglichen mit der normalen Regenzeit, in beiden Pflanzen signifikant abgenommen. Konträr dazu hatten die Nährstoffgehalte in Teso South während der moderaten Dürre in beiden Pflanzen signifikant zugenommen. Die niedrigen Mikronährstoffkonzentrationen im essbaren Pflanzenteil während der intensiven Dürreperiode (Fe, Mn und Cu) lassen darauf schließen, dass die niedrige Nährstoffmobilität im Phloem hierfür verantwortlich war (Kapitel 2). Auch der Bodentyp hatte einen starken Effekt auf die Nährstoffkonzentrationen im essbaren Pflanzenteil. Die Konzentrationen aller gemessenen Nährstoffe im Maiskorn sind auf den fruchtbareren Böden signifikant höher als auf nährstoffärmeren Böden. Die Nährstoffkonzentrationen im Maiskorn korrelierten am stärksten mit den Bodeneigenschaften und am wenigsten mit Managementfaktoren. Der Vergleich der Nährstoffkonzentrationen zwischen Blättern und essbaren Pflanzenteilen zeigten, dass die wenig phloemmobilen Nährstoffe (Ca, Mn, Fe, und Cu) die größten Korrelationsunterschiede aufweisen. Die mehrjährigen Pflanzen (Matooke und Maniok) zeigten dabei eine niedrigere Korrelation zwischen den Pflanzenteilen als die einjährige Pflanze (Mais) (Kapitel 4). Umweltfaktoren, wie zum Beispiel die starke Dürre führte zu Nährstoff- (besonders die der Mikronährstoffe) und Ertragseinbußen, welches damit eine doppelte Belastung der Bevölkerung bedeutete. Würden in agrarwissenschaftlichen Versuchen neben den Erträgen die Nährstoffkonzentrationen des essbaren Teils der Pflanze erhoben werden, könnte man der gängigen Annahme, dass nur auf fruchtbaren Böden gesunde und qualitativ hochwertige Nahrung produziert wird, relativieren. Die Analyse der Blätter gibt Auskunft über die Pflanzengesundheit und den Ertrag, erlaubt aber keine Rückschlüsse über die Ertragsqualität, vor allem nicht in Bezug auf Mikronährstoffe und Ca. Umwelt- und Managementfaktoren haben einen bedeutenden Einfluss auf die Nährstoffkonzentrationen und könnten damit die Nahrungs- und Ernährungssicherheit erheblich beeinflussen. Eine Steigerung der Nahrungs- und Ernährungssicherheit und damit ein Ende des weltweiten Hungerns, gerade auch im Kontext wachsender Herausforderungen einhergehend mit der Klimakrise und einer zunehmenden Bodendegradierung, verlangen einen kollaborativen Einsatz aller beteiligten Disziplinen