Prediction by near Infrared Spectroscopy of the Composition of Plant Raw Materials from the Organic Fertiliser Industry and of Crop Residues from Tropical Agrosystems

Abstract

The dynamics of carbon (C) and nitrogen (N) of plant residues and organic fertilisers are of great interest for agricultural and global warming studies. The proportion of the fractions obtained from biochemical analyses (fibres by sequential Van Soest analysis) can be used for predicting both C and N transformation of organic materials in soils. Considering the expensive and time-consuming Van Soest method, the principal aim of this study was to elaborate near infrared (NIR) calibrations for fibres, in order to use them for consecutive studies (for example, our works on transformation of added organics or TAO model). A wide set of organic fertilisers and their raw materials was sampled, including plant materials originating from temperate (especially Mediterranean) and tropical regions. The particular objective of this work was to build NIR calibrations for fibre fractions, along with C and N content, in plant materials used in the organic fertiliser industry and green house gases mitigating strategies. The second particular objective was to test for two levels of validation of the equations previously elaborated: (1) validation with a set of randomly chosen samples that was not considered during the calibration step, (2) extrapolation of the predictive capacity of the equations when applying them to outliers that were previously discarded. The fibres were the best predicted parameters, as R² = 0.95, 0.91, 0.97, 0.97 for neutral detergent soluble, hemicelluloses, cellulose and lignin, respectively, whereas the characteristics of total organic matter had R² varying from 0.87 (N Kjeldahl) to 0.94 (C Dumas). The accuracy of the calibrations developed for fibres was confirmed by the first level of validation, since the standard errors of prediction were close to the corresponding standard errors of cross-validation and the standard errors of calibration. Nevertheless, the calibrations developed for ash and C Dumas were not so good. Surprisingly, at the second level of validation, some outliers were not so badly predicted. This can illustrate the robustness of the calibrations for cellulose, lignin and, to a lesser extent, N Dumas which are key parameters for our modelling works on C and N transformation of added organics in soils.

Indicator of potential residual carbon in soils after exogenous organic matter application

“…Bruun et al (2005) found that NIR spectra and biochemical fractions were able to predict C mineralization patterns of plant materials equally well. However, when comparing NIR spectra of various materials, Thuriès et al (2005) showed that different models have to be constructed for crop residues and other EOMs.…”

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

“…NIR studies on plant materials (forages, litters, etc. ), which were developed earlier than on soils, often involve the determination of average spectra using several sub-samples, probably because plant samples are rather hard to grind and are not fi nely ground in general (for example, 1 mm preparation [29][30][31] ). Nevertheless, single NIR measurement was reported with rather fi nely ground plant samples (0.5 mm preparation 32 ).…”

La spectrométrie dans le proche infrarouge pour la caractérisation des ressources alimentaires

“…routine. L'erreur de prédiction (SEP) sur le NDF est de l'ordre de 1,50 % de la MS (Andueza et al, 2016) mais peut être plus élevée dans des bases d'étalonnage très hétérogènes (plusieurs espèces végétales ou mélanges ; par exemple Thuriès et al, 2005). L'erreur de prédiction sur l'ADF est généralement inférieure de 30 % à celle du NDF en valeur absolue, mais elle est plus forte en valeur relative (coefficient de variation) car les teneurs en NDF sont supérieures à l'ADF.…”