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One challenge in predicting soil parameters using in situ visible and near infrared spectroscopy is the distortion of the spectra due to soil moisture. External parameter orthogonalization (EPO) is a mathematical method to remove unwanted variability from spectra. We created two different EPO correction matrices based on the difference between spectra collected in situ and, respectively, spectra collected from the same soil samples after drying and sieving and after drying, sieving and finely grinding. Spectra from 134 soil samples recorded with two different spectrometers were split into calibration and validation sets and the two EPO corrections were applied. Clay, organic carbon and total nitrogen content were predicted by partial least squares regression for uncorrected and EPO-corrected spectra using models based on the same type of spectra ("within domain") as well as using laboratory-based models to predict in situ collected spectra ("cross-domain"). Our results show that the within-domain prediction of clay is improved with EPO corrections only for the research grade spectrometer, with no improvement for the other parameters. For the cross-domain predictions, there was a positive effect from both EPO corrections on all parameters. Overall, we also found that in situ collected spectra provided an equally successful prediction as laboratory-based spectra. [ABSTRACT FROM AUTHOR]

There is a growing interest in developing agricultural practices that can improve crop performance while preserving natural resources. Plant biostimulants are thought to play a role in reaching this goal, in particular by increasing the nitrogen use efficiency. However, a notable research gap exists concerning the effects of foliar applications of natural zeolites as plant biostimulants on crop performance. To address this knowledge gap, a greenhouse experiment was set up in order to study the response of maize and wheat traits, specifically the biomass productivity and nitrogen uptake, as well as the response of soil extracellular enzymes to the foliar applications of a natural zeolite in combination with different levels of nitrogen fertilization, that is, 100%, 75%, and 50% of the optimal dose. Foliar application of zeolite in wheat and maize plants led to an increase in root nitrogen concentration of about 10%, particularly at the lowest nitrogen fertilization rate. This response was accompanied by an increase in aboveground to belowground uptake nitrogen ratio. Furthermore, there was a significant reduction of about 20% in root biomass in both crops with zeolite application across the entire nitrogen fertilization gradient. These plant-level responses were associated with a significant increase in the activity of carbon-degrading and nitrogen-degrading enzymes at the soil level in response to zeolite applications. Our findings provide a compelling proof-of-concept for the beneficial effects of foliar-applied zeolite as a biostimulant for crops, emphasizing the critical need for additional field research to validate our greenhouse results. [ABSTRACT FROM AUTHOR]

Peatlands are found on all continents, covering 3% of the global land area. However, the spatial extent and causes of metal enrichment in peatlands is understudied and no attempt has been made to evaluate global patterns of metal enrichment in bog and fen peatlands, despite that certain metals and rare earth elements (REE) arise from anthropogenic sources. We analyzed 368 peat cores sampled in 16 countries across five continents and measured metal and other element concentrations at three depths down to 70 cm as well as estimated cumulative atmospheric S deposition (1850–2009) for each site. Sites were assigned to one of three distinct broadly recognized peatland categories (bog, poor fen, and intermediate-to-moderately rich fen) that varied primarily along a pH gradient. Metal concentrations differed among peatland types, with intermediate-to-moderately rich fens demonstrating the highest concentrations of most metals. Median enrichment factors (EFs; a metric comparing natural and anthropogenic metal deposition) for individual metals were similar among bogs and fens (all groups), with metals likely to be influenced by anthropogenic sources (As, Cd, Co, Cu, Hg, Pb, and Sb) demonstrating median enrichment factors (EFs) > 1.5. Additionally, mean EFs were substantially higher than median values, and the positive correlation (< 0.40) with estimated cumulative atmospheric S deposition, confirmed some level of anthropogenic influence of all pollutant metals except for Hg that was unrelated to S deposition. Contrary to expectations, high EFs were not restricted to pollutant metals, with Mn, K and Rb all exhibiting elevated median EFs that were in the same range as pollutant metals likely due to peatland biogeochemical processes leading to enrichment of these nutrients in surface soil horizons. The global patterns of metal enrichment in bogs and fens identified in this study underscore the importance of these peatlands as environmental archives of metal deposition, but also illustrates that biogeochemical processes can enrich metals in surface peat and EFs alone do not necessarily indicate atmospheric contamination. [ABSTRACT FROM AUTHOR]

The application of visible and near-infrared (vis–NIR) spectroscopy to characterize soil samples has gained growing interest as a fast and cost-effective methodology forsoil fertility assessment.In orderto profit from the full potential of vis–NIR spectroscopy, the acquisition of soil spectra directly in-situ would increase the possibility to obtain data rapidly and at a high spatial and temporal resolution. In the present study, we test and propose the best practice to characterize a set of fertility-related parameters (i.e. texture, organic carbon, pH, cation exchange capacity and major nutrients) of agricultural soils by measuring vis–NIR spectra in the field. To reach this goal, we compare the spectra obtained from different scanning positions with two portable spectrometers, that is, a micro-electromechanical systems (MEMS)-based spectrometer and a research-grade vis–NIR spectrometer. On the basis of 134 soil sampling points, vis–NIR spectra were recorded from: (1) the cutaway side of a soil sample collected with an Edelman auger to a depth of 20 cm, (2) the raw soil surface, as well as (3) the cleaned and smoothed soil surface. Partial least squares regression (PLSR) calibration models were built for the selected soil parameters, scanning positions and different spectral pretreatments for both spectrometers. The model performance was evaluated based on the ratio of performance to interquartile range (RPIQ), the R2 , the root mean squared error (RMSE) and Lin's concordance correlation coefficient (CCC). Overall, the following soil parameters were successfully predicted: clay, sand, pH, organic carbon, cation exchange capacity, total nitrogen and exchangeable magnesium. In contrast, total and exchangeable Ca, K and P, as well as total Mg could not be predicted at a satisfactory level for both the spectrometers. The best scanning position for the successfully calibrated models was along the cutaway sides of the Edelman auger. Although the research-grade spectrometer gave better performance indicators for most of the parameters, the calibrations with the MEMS-based spectrometer still resulted in satisfactory predictions. Based on these findings, the proposed best practice for obtaining in-situ soil vis–NIR scans is to scan along the cutaway sides of a soil core using at least five replicate scans. [ABSTRACT FROM AUTHOR]