Plant regeneration from proroplasts of alfalfa (Medicago sativa) via somatic embryogenesis Regeneração de plantas a partir de protoplastos de alfafa (Medicago sativa) via embriogênese somática

Alfalfa is one of the most frequently studied species from the production of tissue culture-derived embryos point of view. In this study, five alfalfa cultivars were analyzed with reference to their ability to regenerate plants from protoplast cultures via somatic embryogenesis. Plant regeneration from leaf-derived protoplasts isolated from the cultivar Rangelander was achieved using a protocol defined for alfalfa cell suspension-derived embryogenesis. Because of its high efficiency, this procedure is recommended for protoplast electroporation-mediated genetic transformation of alfalfa.<br>A alfafa é uma das espécies mais freqüentemente estudadas do ponto de vista da produção de embriões somáticos derivados da cultura de tecidos. Neste trabalho, cinco cultivares de alfafa foram analisados com referência à capacidade de regenerar plantas a partir de culturas de protoplastos via embriogênese somática. Regeneração de plantas a partir de protoplastos isolados de folhas da cultivar Rangelander foi obtida usando-se um protocolo definido para embriogênese somática derivada de suspensões celulares de alfafa. Em função da sua alta eficiência, recomenda-se o uso deste procedimento para transformação genética de alfafa mediada por eletroporação de protoplastos

Near infrared spectroscopy of faeces to evaluate the nutrition and physiology of herbivores

Near infrared (NIR) spectroscopy, usually in reflectance mode, has been applied to the analysis of faeces to measure the concentrations of constituents such as total N, fibre, tannins and delta C-13. In addition, an unusual and exciting application of faecal NIR [F.NIR] analyses is to directly predict attributes of the diet of herbivores such as crude protein and fibre contents, proportions of plant species and morphological components, diet digestibility and voluntary DM intake. This is an unusual application of NIR spectroscopy insofar as the spectral measurements are made, not on the material of interest [i.e. the diet), but on a derived material (i.e. faeces). Predictions of diet attributes from faecal spectra clearly depend on there being sufficient NIR spectral information in the diet residues present in faeces to describe the diet, although endogenous components of faeces such as undigested debris of micro-organisms from the rumen and Large intestine and secretions into the gastrointestinal tract wilt also contribute spectral information. Spectra of forage and of faeces derived from the forage are generally similar and the observed differences are principally in the spectral regions associated with constituents of forages known to be of low, or of high, digestibility. Some diet components (for example, ureal which are likely to be entirely digested apparently cannot be predicted from faecal NIR spectra because they cannot contribute to faecal spectra except through modifying the microbial and endogenous components. The errors and robustness of F.NIR calibrations to predict the crude protein concentration and digestibility of the diet of herbivores are generally comparable with those to directly predict the same attributes in forage from NIR spectra of the forage. Some attributes of the animal, such as species, gender, pregnancy status and parasite burden have been successfully discriminated into classes based on their faecal NIR spectra. Such discrimination was likely associated with differences in the diet selected and/or differences in the metabolites excreted in the faeces. NIR spectroscopy of faeces has usually involved scanning dried and ground samples in monochromators in the 400-2500nm or 1100-2500nm ranges. Results satisfactory for the purpose have also been reported for dried and ground faeces scanned using a diode array instrument in the 800-1700nm range and for wet faeces and slurries of excreta scanned with monochromators. Chemometric analysis of faecal spectra has generally used the approaches established for forage analysis. The capacity to predict many attributes of the diet, and some aspects of animal physiology, from NIR spectra of faeces is particularly useful to study the quality and quantity of the diet selected by both domestic and feral grazing herbivores and to enhance production and management of both herbivores and their grazing environment

Near infrared reflectance spectroscopy for estimating soil characteristics valuable in the diagnosis of soil fertility

Soil fertility diagnostics rely not only upon measurement of available nutrients but also upon the soil’s ability to retain these nutrients. Near-infrared reflectance spectroscopy (NIRS) is a rapid and non-destructive analytical technique which allows to simultaneously estimate standard soil characteristics and does not require use of chemicals. Previous studies showed that NIRS could be used in local contexts to predict soil properties. The main goal of our research is to build a methodological framework for the use of NIRS at a more global scale. The specific goals of this study were (i) to identify the best spectra treatment and processing –LOCAL versus GLOBAL regression- methods, (ii) to compare NIRS performances to standard chemical protocols and (iii) to evaluate the ability of NIRS to predict soil total organic carbon (TOC), total Nitrogen (TN), clay content and cationic exchange capacity (CEC) for a wide range of soil conditions. We scanned 1,300 samples representative of main soil types of Wallonia under crop, grassland or forest. Various sample preparations were tested prior to NIRS measurements. The most appropriate options were selected according to ANOVA analysis and multiple means comparisons of the spectra principal components. Fifteen pre-treatments were applied to a calibration set and the prediction accuracy was evaluated for GLOBAL and LOCAL modified partial least square (MPLS) regression models. The LOCAL MPLS calibrations showed very encouraging results for all the studied characteristics. On average, for crop soil samples, the prediction coefficient of variation (CVp) was close to 15% for TOC content, 7% for TN content, and 10% for clay content and CEC. The comparisons of repeatability and reproducibility of both NIRS and standard methods showed that NIRS is as reliable as reference methods. Prediction accuracy and technique repeatability allow the use of NIRS within the framework of the soil fertility evaluation and its replacement of standard protocols. LOCAL MPLS can be applied within global datasets, such as the International global soil spectral library. However, the performance of LOCAL MPLS is linked to the number of similar spectra in the dataset and more standard measurements are needed to characterize the least widespread soils