An indicator to evaluate the proportion of exogenous organic matter (EOM) remaining in soils over the long-term after application has been developed. A database was constructed with analytical data corresponding to 83 EOMs, including sludges, composts, animal wastes, mulches, plant materials and fertilizers. The data included results of proximal analysis (soluble, SOL, hemicellulose-, HEM, cellulose-, CEL, and lignin-like, LIC, fractions, in g kg-1 total organic matter) and of carbon (C) mineralization during long-term incubations under laboratory conditions (in g kg-1 exogenous organic C, EOC). The potential residual organic C after EOM application to soil was assessed from the extrapolation of the incubation results. Then, partial least square regression was used to relate EOM characteristics to the proportion of potentially residual organic C previously determined from the incubations. The biochemical fractions of EOM were not predictive enough to develop the indicator. The proportion of organic C mineralized during 3 days of incubation (C3d) was cumulated and appeared to be the most predictive variable of residual organic C. The proposed indicator of residual organic carbon in soils (expressed as g EOC kg-1) was IROC = 445 + 0.5 SOL - 0.2 CEL + 0.7 LIC - 2.3 C3d. The indicator was calculated for the main types of EOM applied to soils. When compared with the few field data of residual C measured in long-term field experiments, the values provided by the indicator seemed to be over-estimated (i.e. EOC degradation could be faster under field conditions than during laboratory incubations)
limitations of, near infrared reflectance spectroscopy applications in soil analysis: A review. Can. J. Soil Sci. 89: 531Á541. Near infrared reflectance spectroscopy (NIRS) is a cost-and time-effective and environmentally friendly technique that could be an alternative to conventional soil analysis methods. In this review, we focussed on factors that hamper the potential application of NIRS in soil analysis. The reported studies differed in many aspects, including sample preparation, reference methods, spectrum acquisition and pre-treatments, and regression methods. The most significant opportunities provided by NIRS in soil analysis include its potential use in situ, the determination of various biological, chemical, and physical properties using a single spectrum per sample, and an estimated reduction of analytical cost of at least 50%. Contradictory results among studies on NIRS utilisation in soil analysis are partly related to variations in sample preparation and reference methods. The following calibration statistics appear to be most appropriate for comparing NIRS performance across soil attributes: (i) coefficient of determination (r 2 ), (ii) ratio of performance deviation (RPD), (iii) coefficient of regression (b), and (iv) ratio of the standard error of prediction (SEP) to the standard error of the reference method (SER), i.e., the ratio of standard errors (RSE). Further investigations on issues such as (i) RSE guidelines, (ii) correlation between NIRS spectrophotometers, (iii) correlation of different reference methods for a given attribute to soil spectra, (iv) identification of key factors affecting the accuracy of NIRS predictions, and (v) efficient use of spectral libraries are required to enhance the acceptability of NIRS as a soil analysis technique and to make it more user-friendly. Standardized guidelines are proposed for the assessment of the accuracy of NIRS predictions of soil attributes.
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