New methodology for the characterization of endoglucanase activity and its application on the Trichoderma longibrachiatum cellulolytic complex

The cellulolytic complex of Trichoderma longibrachiatum was separated in nine fractions using FPLC. The avicelase, cellobiase, carboxymethylcellulase, and endoglucanase activities of these fractions were characterized. The endoglucanase activity was measured by a method that allows the determination of the variation in the degree of polymerization of the insoluble celluloses. This method, which is based on the measurement of the reducing power of the insoluble fibers, is proposed as a tool for the identification and characterization of the endoglucanases. Using this technique and H3PO4-swollen cotton as substrate, the kinetic parameters of two proteins that showed high specific endoglucanase activity (pI = 5.25; Mr = 55 kDa; and pI = 4.70; Mr = 70 kDa) were determined. The measurement of the degree of polymerization variation during digestion of Sigmacell gives evidence that the endoglucanase activity is located at the beginning of the reaction.JNICT -Junta Nacional de Investigação Científica e Tecnológicainfo:eu-repo/semantics/publishedVersio

Effect of purified trichoderma reesei cellulases on formation of cotton powder from cotton fabric

The mode of action of monocomponent purified Trichoderma reesei cellobiohydrolases (CBHI and CBHII) and endoglucanases (EGI and EGII) on cotton fabrics was studied by analyzing the weight loss of the fabric, the reducing sugars, the soluble oligosaccharides and the molecular weight of the cotton powder formed. The impact of mechanical action on these factors was also evaluated. EGI and EGII released the highest amounts of reducing sugars and soluble oligosaccharides in both treatments with or without additional mechanical action. After cellulase treatment without additional mechanical action, all of the cellulases were found to have reduced the molecular weight of cotton poplin powder. When mechanical action was combined with enzyme treatments, only EGII reduced the molecular weight. The weight loss of EG-treated fabrics was clearly higher than the weight loss of CBH-treated fabrics with both low and high mechanical action levels

A process-based model of conifer forest structure and function with special emphasis on leaf lifespan

We describe the University of Sheffield Conifer Model (USCM), a process-based approach for simulating conifer forest carbon, nitrogen, and water fluxes by up-scaling widely applicable relationships between leaf lifespan and function. The USCM is designed to predict and analyze the biogeochemistry and biophysics of conifer forests that dominated the ice-free high-latitude regions under the high pCO2 “greenhouse” world 290–50 Myr ago. It will be of use in future research investigating controls on the contrasting distribution of ancient evergreen and deciduous forests between hemispheres, and their differential feedbacks on polar climate through the exchange of energy and materials with the atmosphere. Emphasis is placed on leaf lifespan because this trait can be determined from the anatomical characteristics of fossil conifer woods and influences a range of ecosystem processes. Extensive testing of simulated net primary production and partitioning, leaf area index, evapotranspiration, nitrogen uptake, and land surface energy partitioning showed close agreement with observations from sites across a wide climatic gradient. This indicates the generic utility of our model, and adequate representation of the key processes involved in forest function using only information on leaf lifespan, climate, and soils

Coupling Sentinel-2 images and STICS crop model to map soil hydraulic properties

Introduction - The characterization of soil hydraulic properties such as the soil water storage capacity (SWC) is essential in hydrology or agronomy to establish the soil water balance and thus represent the hydrological functioning of a territory and/or the dynamics of a crop. SWC spatial variability is often strong resulting from heterogeneity in texture and structure as well as soil depth. ln situ measurement of SWC is expensive, destructive and cannot be considered over a large area as it requires very large sampling plans. This study aims to develop a method to characterize SWC based on sentinel 2 images, yield map and the STICS model. The challenge is then to analyze how a model such as STICS, which involves a very large number of parameters, can be used in an operational context. This leads to define an inversion strategy that takes the main factors of variation into account. Material and Methods - The study was conducted on durum wheat crops in the Avignon region (South-Eastern France). A set of 7 plots was monitored, 6 of which were cultivated by a farmer equipped with a yield monitoring device and 1 on the INRA research centre. Remote sensing data were acquired by sentinel 2 satellites. The LAI and FAPAR were calculated using a neural network applied to the 2, 4 and 8 bands at the resolution of 10 m. Field observations were made in pits (3 to 5 pits per plot) where soil depth and texture were systematically observed. The parameterization of the soil moisture initialization in STICS model was set up at the beginning of September depending on the previous crop. Prior to the inversion method design, a sensitivity analysis was made using the Morris method considering soil thickness, SWC in unit layer, sowing depth, sowing density, soil initialization (water and nitrogen) and organic nitrogen content. The inversion was done using the GLUE method a Bayesian approach, which allows exploring the parameter field within an a priori distribution. Results - The influence of each investigated factor on foliar development varies over time. The crop establishment parameters are more influential at the beginning of the crop cycle. The influence of parameters related to SWC is mainly expressed at the end of the crop cycle with a difference in the rate of LAI senescence and the crop yield. Over the rest of the cycle, ail the parameters have an influence with nevertheless a relative importance of each parameter that change according to the climatic years. Ali the investigated parameters had a significant effect on the annual yield. lt is therefore important to have an inversion method that can separate the effects of the different parameters. The value of the SWC is the main factor influencing the calculation of yield and leaf development, while the way in which the SWC is established is less important. Thus, we can li mit the number of parameters to be calibrated by focusing either on the soil thickness or the SWC per unit horizon, according to the a priori knowledge we have on the soil. Concerning the parameter used for the crop installation parameters, even if the effects of the two parameters are strongly correlated, there is an adding value in maintaining the estimation of both parameters. Finally, for the soil nitrogen effect, the determination of the two parameters, the initial soil nitrogen and the soil organic nitrogen, is not necessary. The initial nitrogen content of the soil is sufficient to represent the influence of the soil with regard to nitrogen nutrition. Comparing the inverted SWC to field measurements, we showed that the SWC was well characterized, in particular, when the soil has strong heterogeneities. Sorne spatial structures that do not coïncide with the reality in the ground. This might be because STICS model do not simulate crop diseases or deficiencies in fertilizing elements. To li mit the detection of those erroneous spatial structures, we simulated crop development in a different climatic year using the determined SWC. Conclusions - This study showed that the inverse use of the STICS model with time series of Leaf Area Index (LAI) retrieved from remote sensing enable mapping the soil water storage capacity (SWC), in particular in water stress conditions. However, other factors might affect foliar dynamic and yield that led ta artefacts in SWC determination. Crop models offer a mean ta consider part of those factors and the STICS model is particularly able to represent the quality of the crop installation and the nitrogen supply together with constraints on water supply. This was possible in an operational context, where most of the model parameters were set to default parameters. Multi-year analysis might be a mean to limit residual artefacts generated by pest and plant diseases. The study also underlines the importance of having high frequency Sentinel-2 images, as it allows capturing short feature as the senescence rate, which appears as an important proxy of the availability of water in the soil

Treatment of cotton with an alkaline Bacillus spp cellulase : activity towards crystalline cellulose

We analysed the influence of several enzymatic treatment processes using an alkaline cellulase enzyme from Bacillus spp. on the sorption properties of cotton fabrics. Although cellulases are commonly applied in detergent formulations due to their anti-redeposition and depilling benefits, determining the mechanism of action of alkaline cellulases on cotton fibres requires a deeper understanding of the morphology and structure of cotton fibres in terms of fibre cleaning. The accessibility of cellulose fibres was studied by evaluating the iodine sorption value and by fluorescent-labelled enzyme microscopy; the surface morphology of fabrics was analysed by scanning microscopy. The action of enzyme hydrolysis over short time periods can produce fibrillation on cotton fibre surface without any release of cellulosic material. The results indicate that several short consecutive treatments were more effective in increasing the fibre accessibility than one long treatment. In addition, no detectable hydrolytic activity, in terms of reducing sugar production, was found.This work is funded by European Union funds through the Marie Curie Fellowships (MEST-CT-2005-019885) from the Sixth Framework Programme (FP6)

Estimating soil water holding capacity using Sentinel2 images and yield map

The Sentinel 2 satellite mission offers the possibility of having a frequent global coverage with high spatial resolution. This is an unprecedented opportunity to follow the dynamics of plant canopies (NDVI, fapar, LAI, chlorophyll) and to observe spatio-temporal variations that can be related to the interactions of plant covers with the environment. In addition, recent advances in technologies have offered the possibility to accurately map crop yield. This paper presents and evaluates a modelling approach for estimating soil water holding capacity parameters at 10 meters spatial resolution. The method is based on an inverse use of the STICS crop model and easily accessible input data including yield maps, time series of Leaf Area Index derived from Sentinel 2 observations, farming practices and a priori knowledge on soils. In order to have a good representation of the interactions between yield and foliar development, parameters describing crop variety in STICS crop model have first been calibrated. The main parameters describing the crop stand establishment have also been calibrated. Finally, the soil water holding capacity has been estimated. This method was applied on different wheat fields located in the South of France and on the plateau of Castilla La Mancha in Spain. The results were compared to the measurements of soil water holding capacity. The comparisons showed that simulated maps accurately fit the measurements in high water stress areas. The model was able to reproduce the critical water stress that seriously hindered the wheat growth and the final yields. These results demonstrate the benefit of using time series of Sentinel 2 data. The proposed approach can be applied in different agronomical, pedologic and climatic conditions to support farmer's decisions in a precision farming approach