A PCR based method to detect Russula spp. in soil samples and Limodorum abortivum roots in Mediterranean environments

Aim of study. Orchidaceae has the largest number of species of any family in the plant kingdom. This family is subject to a high risk of extinction in natural environments, such as natural parks and protected areas. Recent studies have shown the prevalence of many species of orchids to be linked to fungal soil diversity, due to their myco-heterotrophic behaviour. Plant communities determine fungal soil diversity, and both generate optimal conditions for orchid development. Area of study. The work was carried out in n the two most important natural parks in Alicante (Font Roja and Sierra Mariola), in South-eastern of Spain. Material and Methods. We designed a molecular tool to monitor the presence of Russula spp. in soil and orchids roots, combined with phytosociological methods. Main results. Using a PCR-based method, we detected the presence in the soil and Limodorum abortivum orchid roots of the mycorrhizal fungi Russula spp. The species with highest coverage was Quercus rotundifolia in areas where the orchid was present. Research highlights. We present a useful tool based on PCR to detect the presence of Russula spp. in a natural environment. These results are consistent with those obtained in different studies that linked the presence of the mycorrhizal fungi Russula spp. in roots of the species Limodorum and the interaction between these fungal species and Quercus ilex trees in Mediterranean forest environments.

Dispersivity Determination Through a Modeling Approach From a Tracer Test Based on Total Br Concentration in Soil Samples

Determination of reliable solute transport parameters is an essential aspect for the characterization of the mechanisms and processes involved in solute transport (e.g., pesticides, fertilizers, contaminants) through the unsaturated zone. A rapid inexpensive method to estimate the dispersivity parameter at the field scale is presented herein. It is based on the quantification by the X-ray fluorescence solid-state technique of total bromine in soil, along with an inverse numerical modeling approach. The results show that this methodology is a good alternative to the classic Br− determination in soil water by ion chromatography. A good agreement between the observed and simulated total soil Br is reported. The results highlight the potential applicability of both combined techniques to infer readily solute transport parameters under field conditions.

Contribution to Real-Time Estimation of Crop Phenological States in a Dynamical Framework Based on NDVI Time Series: Data Fusion With SAR and Temperature

In this study, a methodology based in a dynamical framework is proposed to incorporate additional sources of information to normalized difference vegetation index (NDVI) time series of agricultural observations for a phenological state estimation application. The proposed implementation is based on the particle filter (PF) scheme that is able to integrate multiple sources of data. Moreover, the dynamics-led design is able to conduct real-time (online) estimations, i.e., without requiring to wait until the end of the campaign. The evaluation of the algorithm is performed by estimating the phenological states over a set of rice fields in Seville (SW, Spain). A Landsat-5/7 NDVI series of images is complemented with two distinct sources of information: SAR images from the TerraSAR-X satellite and air temperature information from a ground-based station. An improvement in the overall estimation accuracy is obtained, especially when the time series of NDVI data is incomplete. Evaluations on the sensitivity to different development intervals and on the mitigation of discontinuities of the time series are also addressed in this work, demonstrating the benefits of this data fusion approach based on the dynamic systems.