Didier Brunet

Determination of total carbon and nitrogen content in a range of tropical soils using near infrared spectroscopy: influence of replication and sample grinding and drying

Near infrared (NIR) reflectance spectroscopy has been receiving increased attention for the rapid and inexpensive determination of soil properties and of total carbon (Ct) and nitrogen content (Nt) in particular. However, methodological aspects such as sample grinding and drying or replication have not been addressed extensively. The objectives of the paper were, thus, to assess how NIR predictions of Ct and Nt were affected by sample grinding (2 mm sieving vs. 0.2 mm grinding), drying (air-drying vs oven-drying at 40°C during 24 h) and replication (use of one to six sub-samples to determine average spectra). This was performed on a range of tropical soils that differed widely in mineralogy (low and high activity clay soils, allophanic soils) and texture (sandy to clayey). The accuracy of the NIR predictions of Ct and Nt was higher with oven-dried compared to air-dried samples and, more markedly, with 0.2 mm ground compared to 2 mm sieved samples. Replication had a positive effect on NIR predictions when 2 mm sieved samples were used, especially for air-dried samples, but this effect was not clear with 0.2 mm ground samples. Thus, the most accurate predictions of Ct and Nt were obtained with oven-dried finely ground samples, with limited response to sample replication. Accurate predictions were, however, also obtained with four replicates on oven-dried 2 mm sieved samples. Acceptable and less tedious results could, thus, be achieved when replacing fine grinding by replication. Even with this procedure, the r2 between predicted (NIR) and measured (reference) values was 0.9 and the ratio of standard error of prediction to mean (CV%) was 20% which can be considered satisfactory for the heterogeneous sample set under study.

Determination of soil content in chlordecone (organochlorine pesticide) using near infrared reflectance spectroscopy (NIRS).

Chlordecone is a toxic organochlorine insecticide that was used in banana plantations until 1993 in the French West Indies. This study aimed at assessing the potential of near infrared reflectance spectroscopy (NIRS) for determining chlordecone content in Andosols, Nitisols and Ferralsols from Martinique. Using partial least square regression, chlordecone content conventionally determined through gas chromatography-mass spectrometry could be correctly predicted by NIRS (Q(2) = 0.75, R(2) = 0.82 for the total set), especially for samples with chlordecone content <12 mg kg(-1) or when the sample set was rather homogeneous (Q(2) = 0.91, R(2) = 0.82 for the Andosols). Conventional measures and NIRS predictions were poorly correlated for chlordecone content >12 mg kg(-1), nevertheless ca. 80% samples were correctly predicted when the set was divided into three or four classes of chlordecone content. Thus NIRS could be considered a time- and cost-effective method for characterising soil contamination by chlordecone.

Cast production and NIR spectral signatures of Aporrectodea caliginosa fed soil with different amounts of half-decomposed Populus nigra litter

Sub-adult individuals of Aporrectodea caliginosa were incubated for 16xa0weeks under laboratory cultures in a soil treated with 0%, 10% or 50% of a Populus nigra half-decomposed leaves, respectively. Growth was maximum in the 50% organic matter treatment and cocoon production occurred. Average soil ingestion rates decreased from 1.56xa0g/g−1 fresh weight of worm per day−1 in control soil to 1.17 and 0.5xa0g, respectively, in treatments with 10% and 50% half-decomposed litter. Surface casts never comprised more than 10% of total cast production. Near-infrared spectrometry (NIRS)signatures of digested and non-ingested soil significantly differed and showed a rather constant effect of digestion, independent of the organic matter content (pu2009<u20090.01). These results confirm the value of NIRS spectral signatures as indicators of the origin of soil aggregates and biological processes involved in soil aggregation.

Comparing near and Mid-Infrared Reflectance Spectroscopy for Determining Properties of Malagasy Soils, Using Global or LOCAL Calibration:

Nowadays, near infrared (NIR) and mid-infrared (mid-IR) reflectance spectroscopy are recognised useful approaches for quantifying soil properties, cost and time effectively. The aim of this work was to compare predictions of soil carbon (C) and nitrogen (N) content, C/N ratio, substrate-induced respiration (SIR) and denitrifying enzyme activity (DEA) using NIR and mid-IR spectroscopy over a diverse set of 360 Malagasy topsoils. Partial least square regression was used for fitting NIR and mid-IR spectra to conventional data through procedures of calibration either global (one prediction model for all samples) or LOCAL (one prediction model per sample). Prediction accuracy was assessed according to validation (r2), standard error of prediction (SEP) in proportion to the mean and ratio of standard deviation to SEP (RPD). Using both NIR and mid-IR spectroscopy, global calibration over the whole sample set yielded predictions that were excellent for C and N (r2 > 0.9, SEP <20%, RPD ⩾ 3), good for C/N, acceptable for SIR, but poor for DEA. LOCAL calibration improved C/N and SIR predictions with both NIR and mid-IR spectroscopy, while DEA prediction became acceptable with NIR spectroscopy only. Additional improvement was achieved when LOCAL calibration was carried out over the fine-textured sub-set, especially for SIR (r2 > 0.9, SEP < 20%, RPD > 3). In contrast, LOCAL calibration over the coarse-textured sub-set was clearly not useful for improving prediction accuracy. NIR outperformed mid-IR spectroscopy whatever the variable, the calibration procedure and the sample set (except for SIR over the coarse-textured sub-set, where both similar), suggesting its possible superiority for tropical soils.

Near infrared reflectance spectroscopy applied to model the transformation of added organic materials in soil

Raw, mixed and composted organic materials (OM) from agricultural and urban wastes were subjected to biochemical analyses, near infrared (NIR) reflectance spectroscopy and laboratory incubations. Respiration during incubations was accurately predicted using a decomposition model [transformation of added organic materials, (TAO)] of very labile, intermediary resistant, and stable OM fractions. Calibrations using NIR spectra were developed to determine the very labile and stable fractions of OM used to predict three-month OM mineralisation in soil. This study has confirmed that OM decomposition is mainly driven by OM quality on a short-term basis. The wavelengths contributing heavily to the prediction of very labile and stable OM components and molecular functions of these fractions were identified. The resulting TAO–NIR spectroscopy model is an efficient tool to study the degradation of natural molecules and its management for plant growth and sustainability of ecosystems. As a sub-model of a more complex C cycle model, it can instantaneously simulate labile and stable fractions of various organic inputs in soil and, as a non-destructive and easily portable spectroscopic method, could be used to assess C dynamics on a regional scale.