Spatial quantification of vegetation density from terrestrial laser scanner data for characterization of 3D forest structure at plot level

International audiencePrecise description of forest 3D structure at plot level is required for sustainable ecosystem management. However, a detailed structure description from traditional field measurements is tedious. We propose an innovative method to quantify in 3D the spatial distribution of forest structure from terrestrial lidar data. The method rests on the hypothesis that the normalized number of laser returns within a given volume element is proportional to the density of vegetation material inside this volume. The developed model is based on analysis made inside Svoxels (spherical voxels) to compute a spatialized vegetation density index. The model was tested on two different scans of the same plot. The resulting vegetation density index well represents the vegetation structure as observed within the lidar point cloud. Quantitative analyses confirmed a global consistency of the results within and between scans. However, we observed a slight bias in the computed density indexes. It might be mainly explained by occlusions, which cause 1) a slight decrease of the density index with distance and 2) local differences in density index between scans.. Future work will focus on improving our algorithm and correcting biases. These results are promising for the development of quantitative measures of the 3D forest structure

Utilisation conjointe de trains d'ondes LiDAR vert et infrarouge pour la bathymétrie des eaux de très faible profondeurs

La bathymétrie et la topographie des surfaces immergées sont des connaissances essentielles pour la gestion durable des rivières et des espaces littoraux. Parmi les techniques permettant de les obtenir, le LiDAR bathymétrique apparaît prometteur par sa capacité à relever de grandes surfaces en un temps limité, avec une forte résolution spatiale et de manière continue entre zones émergées et immergées. Bien que certaines études aient porté sur la précision de cette technique dans les zones côtières de profondeur modérée, peu se sont intéressées aux eaux très peu profondes (<3m). Dans cette étude, une nouvelle méthode de traitement de formes d'ondes LiDAR pour les très faibles profondeurs est proposée. Cet algorithme s'appuie sur le traitement conjoint des trains d'ondes vert et proche-infrarouge (PIR). La densité et la précision des données résultantes sur les eaux côtières très peu profondes sont ensuite analysées. Les résultats de ces développements et analyses sont présentés sur des données acquises sur le Golfe du Morbihan (France) par le Service Hydrographique et Océanographique de la Marine (SHOM) en 2005 avec un système SHOALS qui fournit les formes d'ondes Raman, PIR et vert. Ce travail met l'accent sur la comparaison de la qualité entre les données bathymétriques livrées issues du traitement des signaux par l'opérateur et celles issues de l'algorithme de traitement proposé. Pour la validation des résultats, une méthode spécifique est utilisée ici afin de faciliter la comparaison de mesures altimétriques réalisées entre des points GPS de référence et des empreintes LiDAR (diamètre de l'ordre de 2m). Dans les très faibles profondeurs d'eau, l'algorithme proposé extrait 41% de mesures supplémentaires par rapport aux données livrées, avec un biais de mesure comparable (environ 5cm) et un écart-type des erreurs plus faible (26,1cm contre 41,1cm). 55% de ces mesures supplémentaires sont situés à une profondeur comprise entre 1,5m et 2m. De plus, l'algorithme proposé améliore la profondeur minimale détectable de 80cm par rapport aux données livrées (1m contre 1,8m)

New molecular marker technologies for pearl millet improvement

At a time when most of the world still viewed molecular technology as a luxury, for use only with major staple crops, a DFID-JIC-ICRISAT project anticipated as early as 1991 the application of molecular diagnostics in the breeding of orphan crops for developing countries

Copy Number Variation Affecting the Photoperiod-B1 and Vernalization-A1 Genes Is Associated with Altered Flowering Time in Wheat (Triticum aestivum)

The timing of flowering during the year is an important adaptive character affecting reproductive success in plants and is critical to crop yield. Flowering time has been extensively manipulated in crops such as wheat (Triticum aestivum L.) during domestication, and this enables them to grow productively in a wide range of environments. Several major genes controlling flowering time have been identified in wheat with mutant alleles having sequence changes such as insertions, deletions or point mutations. We investigated genetic variants in commercial varieties of wheat that regulate flowering by altering photoperiod response (Ppd-B1 alleles) or vernalization requirement (Vrn-A1 alleles) and for which no candidate mutation was found within the gene sequence. Genetic and genomic approaches showed that in both cases alleles conferring altered flowering time had an increased copy number of the gene and altered gene expression. Alleles with an increased copy number of Ppd-B1 confer an early flowering day neutral phenotype and have arisen independently at least twice. Plants with an increased copy number of Vrn-A1 have an increased requirement for vernalization so that longer periods of cold are required to potentiate flowering. The results suggest that copy number variation (CNV) plays a significant role in wheat adaptation

Identification of a Lacosamide Binding Protein Using an Affinity Bait and Chemical Reporter Strategy: 14-3-3 ζ

We have advanced a useful strategy to elucidate binding partners of ligands (drugs) with modest binding affinity. Key to this strategy is attaching to the ligand an affinity bait (AB) and a chemical reporter (CR) group, where the AB irreversibly attaches the ligand to the receptor upon binding and the CR group is employed for receptor detection and isolation. We have tested this AB&CR strategy using lacosamide ((R)-1), a low-molecular-weight antiepileptic drug. We demonstrate that using a (R)-lacosamide AB&CR agent ((R)-2) 14-3-3 ζ in rodent brain soluble lysates is preferentially adducted, adduction is stereospecific with respect to the AB&CR agent, and adduction depends upon the presence of endogenous levels of the small molecule metabolite xanthine. Substitution of lacosamide AB agent ((R)- 5) for (R)-2 led to the identification of the 14-3-3 ζ adduction site (K120) by mass spectrometry. Competition experiments using increasing amounts of (R)-1 in the presence of (R)-2 demonstrated that (R)-1 binds at or near the (R)-2 modification site on 14-3-3 ζ. Structure-activity studies of xanthine derivatives provided information concerning the likely binding interaction between this metabolite and recombinant 14-3-3 ζ. Documentation of the 14-3-3 ζ-xanthine interaction was obtained with isothermal calorimetry using xanthine and the xanthine analogue 1,7-dimethylxanthine

Genomic Approaches to Enhance Stress Tolerance for Productivity Improvements in Pearl Millet

Pearl millet [Pennisetum glaucum (L.) R. Br.], the sixth most important cereal crop (after rice, wheat, maize, barley, and sorghum), is grown as a grain and stover crop by the small holder farmers in the harshest cropping environments of the arid and semiarid tropical regions of sub-Saharan Africa and South Asia. Millet is grown on ~31 million hectares globally with India in South Asia; Nigeria, Niger, Burkina Faso, and Mali in western and central Africa; and Sudan, Uganda, and Tanzania in Eastern Africa as the major producers. Pearl millet provides food and nutritional security to more than 500 million of the world’s poorest and most nutritionally insecure people. Global pearl millet production has increased over the past 15 years, primarily due to availability of improved genetics and adoption of hybrids in India and expanding area under pearl millet production in West Africa. Pearl millet production is challenged by various biotic and abiotic stresses resulting in a significant reduction in yields. The genomics research in pearl millet lagged behind because of multiple reasons in the past. However, in the recent past, several efforts were initiated in genomic research resulting into a generation of large amounts of genomic resources and information including recently published sequence of the reference genome and re-sequencing of almost 1000 lines representing the global diversity. This chapter reviews the advances made in generating the genetic and genomics resources in pearl millet and their interventions in improving the stress tolerance to improve the productivity of this very important climate-smart nutri-cereal