Urban and livestock wastes in the tropics: Characterization and modeling of their transformations in soil to better choose their potential utilization

The exogenous organic materials (EOM) resulting from agricultural activities within the city are numerous. We present here descriptions of these EOMs, and have modeled management problems and competition in disposing and using them (e.g. agricultural recycling vs. production of renewable energies). In the Indian Ocean region (Madagascar and La Réunion Island), both the volume and variety of EOM are increasing. We have developed innovative methods (e.g. near infra-red spectroscopy [NIRS]) to characterize a large variety of tropical EOM and to evaluate the risks involved in either their agricultural or energy utilization. In order to represent the EOM from various origins and of different types, the development of models is carried out on several levels. On the one hand, NIRS models are presented to make use of the technique. Indeed, on a "simple" spectrum basis, one can make predictions of interesting parameters which are difficult to measure according to conventional methods. Many useful data to assess the scenarios of agricultural or energy valorization can thus be quickly produced at lower costs. On the other hand, we have developed models of EOM transformations in soils that are adapted to the tropics. These models can provide scenarios for the agricultural valorization of typical EOM, and can run with entry parameters which have been measured by conventional analyses, or resulting from NIRS models (double modeling). The various scenarios set out for either agricultural or energy utilization must be balanced against possible hazards due to trace elements and the release of N2O, a powerful greenhouse gas. (Texte intégral

Near infrared spectroscopy for predicting quality indices in the organic fertiliser industry

The carbon to nitrogen (C/N) ratio can provide information on the capacity of an organic input to be transformed into humus [1 - 3], but it is not sufficient in some cases [4]. The lignin/nitrogen (Lig/N) ratio is another parameter used when modelling the transformation of organic materials [5]. An alternative estimate of degradability is the percentage of organic matter which is potentially resistant to mineralization over a long period of time. This estimate of the potentially humified organic matter (PHOM), calculated from an established equation based on the chemical composition, is normalised [7]. Quality indicators to determine the total carbon (C), nitrogen (N) and lignin content are expensive and time-consuming. In this study we attempted to predict the PHOM index, the lignin/N ratio and the C/N ratio directly by near infrared (NIR) spectroscopy as a measure of the potential degradability of organic waste. (Résumé d'auteur

Intérêt des fumiers pour restaurer la fertilité des sols en zone semi-aride d'Afrique

Le maintien de la fertilité des sols tropicaux en zone semi-aride est conditionné par l'apport de matières minérales et organiques, mais des MO peu fermentescibles et riches en précurseurs d'humus. En plus de l'augmentation de la productivité, les effets attendus de ces MO, sont: une réduction du risque de sécheresse et de phytotoxicité, une augmentation: (i) de la valeur nutritionnelle des céréales, (ii) de la fixation de N2 des légumineuses, (iii) de la résistance des plantes aux maladies. On distingue en gros trois types de fumier: (1) les poudrettes de parc traditionnel, (2) le fumier de parc avec litière, (3) le fumier d'étable à stabulation composté. Pour améliorer l'efficacité du fumier, il faut intervenir à trois niveaux: (a) estimer son effet fertilisant et son effet amendement et vérifier si le processus de fermentation (compostage) s'est réalisé, (b) ajouter des compléments phosphatés et une biomasse riche en lignine, (c) définir le mode d'application au sol, la dose et la place dans la rotation de ce fumier. Les contraintes majeures à la production de fumier sont la ressource fourragère et le transport; cependant, un espoir est permis dans les zones cotonnières, avec l'apparition de la stabulation saisonnière au Mali ou des parcs d'hivernage au Burkina. (Résumé d'auteur

Near infrared spectroscopy predictions on heterogeneous databases

Faced to heterogeneous database questions, a NIR user is often answered: "you should work on more homogeneous data-sets". Nevertheless, as heterogeneity and variability is widespread among lots of agriculture areas, it is not always possible to have subsets which are at the same time homogeneous and large enough for calibration. It is therefore interesting to try calibration on heterogeneous databases before saying it is impossible... The major objective was to compare different strategies for NIR predictions. On one hand, build models from a data-set comprising different data-subsets, and on another hand, compare them to models based on the 'pure' data-subsets. The raw materials studied there originated from industrially pre-processed plant residues and other tropical plant residues, potentially utilisable in composting. Pure data-sets were (i) wet grape skins, (ii) dry grape skins, (iii) de-oiled grape pips, (iv) coffee cake, (v) cocoa cake, (vi) olive pulp, (vii) tropical plant residues samples. The parameter measured were Organic Matter OM (n= 30 to 56) and Total Nitrogen Kjeldahl TN (n=32 to 55) for the pure data-sets. The compiled data-set comprised 327 OM and 283 TN analyses. All samples were dried (40°C) ground (<1 mm sieve) and scanned on a NIRS 6500 (Foss NIRSystems) in ring cups. Spectra were corrected with SNVD 2,5,5 (WIN-ISI) mathematical pre-treatment and calibrations were performed using a modified partial least square regression (mPLS, WIN-ISI). The equations for OM had Standard Errors of Calibration (SEC) varying from 0.28 to 0.75 g 100 g-1 d.m., for the pure data-sets, and 0.94 for the compiled data-set. The equations for TN had SEC varying from 0.10 to 0.15 g 100 d.m., and 0.16 g 100 g-1 d.m., respectively. Standard Errors of Cross Validation (SECV) for OM varied from 0.44 to 1.27 g 100 g-1 d.m., and 1.07 g 100 g-1 d.m., respectively, whereas those of TN varied from 0.12 to 0.49 g 100 g-1 d.m., and 0.17 g 100 g-1 d.m., respectively. The corresponding SD/SECV ratios for OM varied from 1.3 to 3.9 for the pure data-sets, and equalled 2.8 for the compiled data-set. Those of TN varied from 1.4 to 3.7, and 3.1, respectively. Calibrations on pure data-sets seem to perform slightly better than that of the compilation. Nevertheless, models developed on the global data-set (made by compilation of the subsets, thus heterogeneous) had an acceptable predictive capacity and this strategy is therefore very useful. [Résumé d'auteur