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Accurate information of soil macronutrient contents and fertilizer macronutrient contents is the precondition of precision fertilization; however, how to detect soil and fertilizer information rapidly, reliably, and inexpensively remains a great challenge. Visible and near-infrared (VIS/NIR) diffuse reflectance spectroscopy proves to be an effective tool for extensive investigation of soil and fertilizer properties. This study first collected many soil and chemical fertilizer samples and performed both spectral scanning and chemical analysis. During the correlation between the collected VIS/NIR spectra and the measured data, different spectral pretreatment, sample selection, and wavelength optimization methods were applied for improving the accuracy and robustness of the prediction models. After appropriate spectral processing and selection of representative samples, both principal component regression and genetic algorithm (GA) can adequately reduce the number of variables and pick out the characteristic variables, which not only enhanced prediction speed but also greatly improved prediction accuracy. In particular, using GA-based models, organic matter content (OMC), total N and pH value in soil and N, P, and K contents in fertilizer can all be accurately predicted.

Univariate and multivariate analyses of strontium (Sr) and vanadium (V) elements in soil have been performed using laser-induced breakdown spectroscopy technology. Thirty-three samples were used as a calibration set, and 11 samples were used as a prediction set. The results demonstrated that the correlation coefficients of the calibration curves method were poor due to the matrix effect. Then, the multivariate models of partial least-squares regression and least squares support vector regression (LS-SVR) were used to construct models. The analysis accuracy was improved effectively by the LS-SVR method, and the correlation coefficient is 0.999 for Sr and 0.983 for V. The average relative errors for the prediction set are lower than 7.45% and 2.88% for Sr and V, respectively. The results indicated that the LIBS technique coupled with LS-SVR could be a reliable and accurate method in the quantitative determination of elemental Sr and V in complex matrices like soil.

Laser-induced breakdown spectroscopy (LIBS) is used to determine the total nitrogen (TN) and total phosphorus (TP) in soil. Quantitative determinations are conducted using the line intensity of the analyte element and element concentration. Calibration models are obtained using ten samples for TN and seven samples for TP. The rest samples are used to validate the results. Strong linear correlations are obtained from the determined TN and TP concentrations. LIBS is a powerful tool for analyzing soil samples to determine nutrient elements by selecting calibration and validation samples with similar matrix composition.

The on-line measurement of the main component contents is essential for production, detection and identification of compound fertilizer. Using developed VIS-NIR sensors for on-line measurement of the main component contents in compound fertilizer, primary results about nitrogen (N), phosphorus pentoxide (P2O5) and potassium oxide (K2O) were reported. A visible (VIS) and near infrared (NIR) spectrophotometer (Ocean Optics), with a measurement range of 360.18–2221.53 nm was used to measure fertilizer spectra in reflectance mode. By using principal component analysis (PCA) and mahalanobis distance method, 3 outlier samples were detected and eliminated from 174 samples firstly. Then these models of three components with the 124 samples in calibration set were established using principal component regress (PCR) and partial least squares regression (PLS) coupled respectively with the full cross-validation technique after preprocessing the original spectrum with different methods. These models were used to estimate the contents of N, P2O5 and K2O of the other 47 samples in predicted set. The research results showed that the method could be applied to rapid measurement to the main component contents in compound fertilizer. Compared with the traditional analysis method, the on-line measurement could do it rapidly, inexpensively and pollution-freely. It suggested the potential use of the VIS–NIR sensing system for on-line measurement in the production, detection and identification process of compound fertilizer. © (2015) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.

A 9-year field micro-plot experiment was conducted to investigate the use efficiency, residual effect, and fate of 15 N-labelled ryegrass green manure in soil-crop system, so as to offer useful information for reasonable application of green manures on meadow burozem. Results showed that high application rate (600g per plot) of 15 N-labelled ryegrass green manure resulted in reduction of percent recovery (PR) 15 N plant and PR 15 N soil by 25.0% and 12.8%, respectively, and elevation of percent loss (PL) 15 N by 31.2%, as compared with low application rate. The 15 N utilization and loss could be divided into three phases, i.e., high uptake and fast loss in the first and second growth seasons, low uptake and slow loss in the following four growth seasons, and little change in the last three growth seasons. This suggested that the green manure N had a long residual effect but its loss was faster at early phase, and thus, rational application of green manure was of considerable importance to reduce its N loss while improve its N use efficiency.

This paper analyzed the characteristics of laser-induced breakdown spectroscopy (LIBS) of metal element arsenic in soil using the Nd:YAG (wavelength: 1064 nm) laser as the excitation source, where the spectral signals were detected by the high resolved, wide spectral ECHELLE spectrograph and intensity charged coupled device (ICCD). The time evolution of the characteristic spectral line of arsenic was obtained by changing the delay time of ICCD at the same concentration and the gate of ICCD with wavelength of 228.8 nm of arsenic as the characteristic spectral line, from which a best delay time of 1 s and a gate width of 2 s were found. By measuring the intensities of the characteristic spectral line with different arsenic concentrations, it was demonstrated that the intensities of the spectral line increased with the concentration of arsenic under the condition of low concentration. From the results, the LIBS calibration curve of arsenic was obtained, and the detection limit of arsenic in soil at 45 mg/kg was obtained.