Jean-Luc Chotte

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.

Changes in bacterial communities and Azospirillum diversity in soil fractions of a tropical soil under 3 or 19 years of natural fallow

Abstract The effects of 3 and 19xa0yr natural fallows on soil structure and soil bacteria were assessed by aggregate size fractionation of a tropical sandy soil (0–10xa0cm). Bulk unfractionated soil and fractions including particulate coarse organic residues (COR), and four fractions (>2000, 50–2000, 2–50 and 50xa0μm), suggesting that these microhabitats were favourable to active N2 fixers. In contrast, more than 70% of the N2 fixing microorganisms and 90% of the recovered Azospirillum were isolated from the dispersible clay fraction (0–2xa0μm). Diversity of Azospirillum species was assessed by hybridisation with specific genetic probes on colonies within each fraction. This approach revealed the abundance of Azospirillum irakense in the 3xa0yr fallow soil fractions only and a selective effect of fallow on Azospirillum brasilense/Azospirillum amazonense genomic species in the 19xa0yr fallow soil. These changes would remain hidden, if the investigation had been restricted to the unfractionated soil.

Morphological aspects of microorganism habitats in a vertisol

Abstract Chotte, J.L., Villemin, G., Guillore, P. and Jocteur Monrozier, L., 1994. Morphological aspects of microorganism habitats in a vertisol. In: A.J. Ringrose-Voase and G.S. Humphreys (Editors), Soil Micromorphology: Studies in Management and Genesis. Proc. IX Int. Working Meeting on Soil Micromorphology, Townsville, Australia, July 1992. Developments in Soil Science 22, Elsevier, Amsterdam, pp. 395–403.

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.

Multiscale MAS modelling to simulate the soil environment: Application to soil ecology

Abstract Soils are important components of ecosystem and their functioning is of great importance for human well-being. Describing, understanding, foreseeing, and controlling biological activities and functions in soil in the context of global change are major objectives for scientists. Modelling soil bioturbation by soil engineers is of great importance although it is faced with the difficulty to describe the soil physical environment. Creating a model of a soil leads to complexity problems: a soil is a multi-scale heterogeneous, three-dimensional and dynamic environment that cannot be modelled and simulated without defining a suitable and optimized representation and taking assumptions about the studied system. An approach based on fractal theory (often used in soil sciences) was chosen to model such a real complex environment; it was integrated into a multi-agent system (MAS). MAS allows to simulate situated agents (earthworms) in an virtual world. The originality of this present MAS is that it is based on a dynamic environment which builds itself, on demand, according to an abstract canvas tree and agent movements. The aim of this paper is to present this approach and its originality, and to describe the model and the simulator. A theoretical view of the approach is given and applied to a case study: the impact of earthworms on soil structure and organic matter dynamics.

Effects of Organic and Inorganic Applications on Soil Bacterial and Fungal Microbial Communities Diversity and Impacts of Earthworms on Microbial Diversity in the Kabete Long-Term Trial, Kenya

Soil fertility decline is increasingly leading to reduced food production worldwide. Over 70% of small holder farmers in the central highlands of Kenya are using crop manure, animal wastes and inorganic fertilizers to increase their farms’ fertility and subsequent productivity. The dilemma with these practices is that less is known on the impact of these resources on the below ground biodiversity particularly the microbial communities which play a key role in determining soil quality. A study was carried out on a 32 year old long-term trial in Kabete, Kenya. These soils were treated with organic (maize stover at 10 t ha−, farmyard manure at 10 t ha−) and inorganic fertilizers (120 kg N, 52.8 kg P plus farmyard manure at 10 t ha−1 (N2P2 + FYM), 120 kg N, 52.8 kg P plus maize stover at 10 t ha−1 (N2P2 + R), 120 kg N, 52.8 kg P (N2P2), and a control (Nil and fallow) for over 30 years. We examined 16S rRNA gene and 28S rRNA gene fingerprints of bacterial and fungal communities, respectively, by PCR amplification and denaturing gradient gel electrophoresis (PCR-DGGE) separation. Bacterial community structure and diversity were negatively affected by N2P2, as evidenced by changes in the PCR-DGGE banding patterns. Bacterial community structure in the N2P2-treated soil was more closely related to the bacterial structure in the untreated soil (fallow and Nil) than that in soils treated with a combination of inorganic and organic or inorganic fertilizers alone. For the fungal community the negative effect of N2P2 alone was not as adverse as for the bacterial community structure since the soils treated with N2P2 were closely related to those treated with N2P2 + FYM and N2P2 + maize stover. However, soils treated with organic inputs clustered away from soils amended with inorganic inputs. Organic inputs had a positive effect on both fungal and bacterial community structures with or without chemical fertilizers. Results from this study suggested that bacterial and fungal community structure was closely related to agro-ecosystem management practices conducted for over the past 30 years.