Selecting optimal hyperspectral bands to discriminate nitrogen status in durum wheat: a comparison of statistical approaches.

Hyperspectral data can provide prediction of physical and chemical vegetation properties, but data handling, analysis, and interpretation still limit their use. In this study, different methods for selecting variables were compared for the analysis of on-the-ground hyperspectral signatures of wheat grown under a wide range of nitrogen supplies. Spectral signatures were recorded at the end of stem elongation, booting, and heading stages in 100 georeferenced locations, using a 512-channel portable spectroradiometer operating in the 325-1075-nm range. The following procedures were compared: (i) a heuristic combined approach including lambda-lambda R(2) (LL R(2)) model, principal component analysis (PCA), and stepwise discriminant analysis (SDA); (ii) variable importance for projection (VIP) statistics derived from partial least square (PLS) regression (PLS-VIP); and (iii) multiple linear regression (MLR) analysis through maximum R-square improvement (MAXR) and stepwise algorithms. The discriminating capability of selected wavelengths was evaluated by canonical discriminant analysis. Leaf-nitrogen concentration was quantified on samples collected at the same locations and dates and used as response variable in regressive methods. The different methods resulted in differences in the number and position of the selected wavebands. Bands extracted through regressive methods were mostly related to response variable, as shown by the importance of the visible region for PLS and stepwise. Band selection techniques can be extremely useful not only to improve the power of predictive models but also for data interpretation or sensor design.

Integration of electromagnetic induction sensor data in soil sampling scheme optimization using simulated annealing.

Soil survey is generally time-consuming, labor-intensive, and costly. Optimization of sampling scheme allows one to reduce the number of sampling points without decreasing or even increasing the accuracy of investigated attribute. Maps of bulk soil electrical conductivity (EC a ) recorded with electromagnetic induction (EMI) sensors could be effectively used to direct soil sampling design for assessing spatial variability of soil moisture. A protocol, using a field-scale bulk EC a survey, has been applied in an agricultural field in Apulia region (southeastern Italy). Spatial simulated annealing was used as a method to optimize spatial soil sampling scheme taking into account sampling constraints, field boundaries, and preliminary observations. Three optimization criteria were used. the first criterion (minimization of mean of the shortest distances, MMSD) optimizes the spreading of the point observations over the entire field by minimizing the expectation of the distance between an arbitrarily chosen point and its nearest observation; the second criterion (minimization of weighted mean of the shortest distances, MWMSD) is a weighted version of the MMSD, which uses the digital gradient of the grid EC a data as weighting function; and the third criterion (mean of average ordinary kriging variance, MAOKV) minimizes mean kriging estimation variance of the target variable. The last criterion utilizes the variogram model of soil water content estimated in a previous trial. The procedures, or a combination of them, were tested and compared in a real case. Simulated annealing was implemented by the software MSANOS able to define or redesign any sampling scheme by increasing or decreasing the original sampling locations. The output consists of the computed sampling scheme, the convergence time, and the cooling law, which can be an invaluable support to the process of sampling design. The proposed approach has found the optimal solution in a reasonable computation time. The use of bulk EC a gradient as an exhaustive variable, known at any node of an interpolation grid, has allowed the optimization of the sampling scheme, distinguishing among areas with different priority levels.

A multisensor approach coupled with multivariate statistics and geostatistics for assessing the status of land degradation: The case of soils contaminated in a former outdoor shooting range.

Soil contamination in outdoor shooting ranges (OSRs) is a major threat for human health, particularly when, after the end of activities, the land is used for recreational areas or agricultural production. The status of land degradation of an OSR in southern Italy was assessed using a multisensor approach. It was based on: i) proximal sensors, including electromagnetic induction (EMI) for measuring soil electrical conductivity (ECa) and magnetic susceptibility (MSa), γ-ray spectrometry for K, eU and eTh analyses and ultrasonic penetrometry detecting cone index (CI) data representative of soil's strength, ii) field surveys on soil thickness (ST), and iii) laboratory analyses of potentially-toxic-elements (PTEs) by portable X-ray fluorescence spectrometry and polycyclic aromatic hydrocarbons (PAHs) by gas-chromatography. Spatial variability of measurements was modelled and mapped using geostatistical methods. The most densely measured covariate (i.e., the ECa of the topsoil) was used within kriging with external drift to improve the PTEs predictions. The PTEs maps were complemented by maps of spatial uncertainty. A robust multivariate principal component analysis (rPCA) was applied to proximal sensor and laboratory data and allowed to identify associations of PAHs, lead, CI with the topsoil ECa along the first component (PC1), highlighting the correlation between land anthropogenic effects and EMI measures; while the association between the ST (estimating the depth of underground travertine hard-layers) and the bottom soil ECa and MSa along the second component (PC2) evidenced the influence of soil stratigraphy on the EMI measures. This study demonstrates that the simultaneous use of different proximal sensors associated with laboratory analysis can allow to assess and model the spatial variability of the land degradation status of an OSR, including soil compaction, organic and inorganic contamination. The correlation between EMI data with the PTEs content highlights the potential of this technique in the field of soil contamination.

Site-specific management of salt affected soils: A case study from Egypt.

In Egypt all agricultural practices are generally applied uniformly without taking spatial variability into consideration, which is not efficient and may be more expensive than site-specific management approach. This is based on accurate assessment of within-field variation and on field delineation into homogeneous zones to be submitted to differential management. Multivariate geostatistics allows to assess and model the spatial variation of a set of soil attributes influencing management. The objective of this paper was to propose an approach for determining spatially variable rate application (VRA) of leaching water, to control soil salinity, and of fertilizer to improve productivity while reducing environmental impact. The research was conducted in an experimental 3.1-ha field in Egypt and the following soil attributes were measured: electrical conductivity (ECe), available nitrogen (N), available phosphorus (P), available potassium (K) and organic matter content (OM). Ordinary cokriging was applied to produce thematic maps of soil attributes and the appropriateness of the linear model of coregionalization was evaluated with cross-validation. Spatial maps of the five soil variables were classified into three isofrequencies classes and the mean values were calculated for each class. These values were then compared with critical reference values to assess the local soil requirements for reducing soil salinity and/or improving soil fertility. The results showed that the estimations of soil attributes were unbiased and accurate. Only for ECe and available nitrogen site-specific management would be preferable because it would reduce the agricultural costs for both soil reclamation (saving water used to leach salts) and improvement of soil N fertility in comparison with the traditional uniform methods. The proposed approach, though producing encouraging results, would require improvements in the determination of the threshold values used to plan salt leaching and soil fertilization.

A rare case of primary thyroid amyloidosis.

INTRODUCTION: Amyloid goiter is due to the deposition of amyloid in the thyroid, resulting with enlargement of the gland and compressive symptoms. CASE: We herein present a case of a 45-year-old male patient who complained of a big swelling in the neck. Ultrasound showed an enlarged thyroid gland with mediastinal involvement. The multinodular appearance was consistent with the diagnosis of multinodular goiter. He had a history of multiple myeloma but no sign of systemic amyloidosis. DISCUSSION: Thyroid gland was removed and the histopathological examination revealed a diffuse deposition of amyloid associated with metaplastic lipomatosis of the stroma. CONCLUSIONS: The treatment of choice in patients with amyloid goiter is total thyroidectomy to solve compression symptoms.