Evaluation of kraft cooking behaviour for different hardwood species

In this study six wood species (birch, chestnut, oak, beech, poplar and eucalyptus) were analysed separately. Lignin content, Polysaccharides content (cellulose and hemicelluloses), Yield, Hexenuronic acids were evaluated for three cooking temperatures (140ºC, 150ºC and 160ºC) and different cooking times. Common cooking conditions were applied and temperature program included cold impregnation, a plateau at 110°C (2.5 hours) to perform initial delignification separately followed by a second plateau at cooking temperature. The results of PCA show that the almost all parameters (excluding hexenuronic acids) are well correlated between them (total variance: 62%). For Eucalyptus and poplar species the hemicelluloses content aren’t well correlated with the previously parameter, caused by the difference observed for the higher temperatures. In some samples was observed that xylans are partially resistant and their elimination is only partial (30 to 40%) in the early stage of cooking. For the highest cooking time there were observed a significant difference between the three temperatures studied. Chestnut and oak wood species present a different behaviour compared with the other species, caused by their similar anatomical and chemical structure. For the 160º of cooking temperature in the second plateau was the poplar, beech and birch that present a different performance

Evaluation of kraft cooking behaviour for six different softwoods species

The main goal of this paper is to observe de differences of behaviour between six softwoods species during the kraft cooking sequence, knowing that morphological, physicochemical and hygroscopic characters are different. Six wood species (Scots pine, maritime pine, Aleppo pine, black pine, Douglas fir and Spruce) were analysed separately. Different parameters were evaluated (Lignin content, Polysaccharides content (cellulose and hemicelluloses), Yield, Hexenuronic acids) and for each wood species three temperatures (150ºC, 160ºC and 170ºC) and different cooking times, allowing to study the behaviour of the wood species. Common cooking conditions were applied and temperature program included cold impregnation, a plateau at 110°C during 2.5 hours to perform initial delignification separately followed by a second plateau at cooking temperature. Non-uniform cooking behaviour was observed; chestnut and oak trees consumed much more caustic soda and had a lower yield in the initial phase of the cook. It was possible conclude that in a genera way, the behaviour of the six softwoods is highly homogeneous, for the three temperatures studied. Data analysis was made with Principal component analysis (PCA) and ANOVA. The results of PCA show that all parameters: Yield (Y), Klason lignin (L), cellulose content (C), and effective residual alkali (EA) are well correlated. The cellulose content was negatively correlated with the other factors. The hexenuronic acids (HA) and hemicelluloses content was well correlated witch other. The coking time in the 2nd plateau influence all factors. Moreover, the three different temperatures are very similar they present statically differences with Tukey’s test (P<0.05). For the highest cooking time all parameter present lower values. The time on the 2nd plateau do not influence the yield and the delignification

Metals recovery from spent Zn-MnO2 batteries by Hydrometallurgy

A hydrometallurgical process for recycling spent Zn-MnO2 batteries was developed, involving leaching with sulfuric acid, purification by precipitation and metals separation for further recovery. Leaching of zinc oxide was easily attained while for manganese oxide was rather difficult depending on temperature and acid concentration. At 90ºC and with the liquid/solid ratio of 20 L/kg, more than 95% of zinc is recovered in 30 minutes with 0.5M H2SO4. To attain similar recovery for manganese, higher levels of acid concentration and time are needed (e.g 0.7 M and 2 hours). After leaching a purification step is necessary to remove iron co-dissolved through Fe(III) precipitation. Separation of zinc from manganese by solvent extraction with 1M DEHPA follows in the process route. The countercurrent multistage separation diagram developed allows the production of a zinc electrolyte with 120 g/L Zn and 0.005 g/L Mn, and a raffinate with 16 g/L Mn and 0.013 g/L Zn

Caracterização funcional do transcriptoma de amendoim forrageiro.

O uso do amendoim forrageiro em consórcios com gramíneas nas pastagens e como cobertura verde, consorciado com culturas comerciais, tem crescido nos últimos anos. A análise do genoma funcional permite a identificação de genes de interesse agronômico. Assim, o objetivo deste trabalho foi realizar a anotação funcional de genes do transcriptoma de folhas de Arachis pintoi. Dos 98.432 transcritos analisados, 69% apresentaram correspondências com o banco de dados de proteínas do National Center of Biotechnology Information. As classes função molecular (36%) e processo biológico (35,8%) representaram a maioria dos termos de Gene Ontology atribuídos, enquanto o componente celular (28,2%) apresentou menor número. A análise de expressão diferencial identificou 1.550 e 1.357 genes com maior nível de expressão nas cultivares Amarillo e Belomonte, respectivamente. A análise de enriquecimento dos genes mostrou que 55,63% pertencem à classe componente celular, seguida por função molecular (26,48%) e processo biológico (20,89%). Esses resultados são o primeiro relato de anotação funcional de A. pintoi que irá fornecer uma importante fonte de informação para avanços nos estudos de expressão, silenciamento e edição gênica nos programas de melhoramento de Arachis.Editores técnicos: Rodrigo Souza Santos; Fabiano Marçal Estanislau

Genomic prediction applied to high-biomass sorghum for bioenergy production.

The increasing cost of energy and finite oil and gas reserves have created a need to develop alternative fuels from renewable sources. Due to its abiotic stress tolerance and annual cultivation, high-biomass sorghum (Sorghum bicolor L. Moench) shows potential as a bioenergy crop. Genomic selection is a useful tool for accelerating genetic gains and could restructure plant breeding programs by enabling early selection and reducing breeding cycle duration. This work aimed at predicting breeding values via genomic selection models for 200 sorghum genotypes comprising landrace accessions and breeding lines from biomass and saccharine groups. These genotypes were divided into two sub-panels, according to breeding purpose. We evaluated the following phenotypic biomass traits: days to flowering, plant height, fresh and dry matter yield, and fiber, cellulose, hemicellulose, and lignin proportions. Genotyping by sequencing yielded more than 258,000 single-nucleotide polymorphism markers, which revealed population structure between subpanels. We then fitted and compared genomic selection models BayesA, BayesB, BayesC?, BayesLasso, Bayes Ridge Regression and random regression best linear unbiased predictor. The resulting predictive abilities varied little between the different models, but substantially between traits. Different scenarios of prediction showed the potential of using genomic selection results between sub-panels and years, although the genotype by environment interaction negatively affected accuracies. Functional enrichment analyses performed with the marker-predicted effects suggested several interesting associations, with potential for revealing biological processes relevant to the studied quantitative traits. This work shows that genomic selection can be successfully applied in biomass sorghum breeding programs

A mixed model QTL analysis for sugarcane multiple-harvest-location trial data

Sugarcane-breeding programs take at least 12 years to develop new commercial cultivars. Molecular markers offer a possibility to study the genetic architecture of quantitative traits in sugarcane, and they may be used in marker-assisted selection to speed up artificial selection. Although the performance of sugarcane progenies in breeding programs are commonly evaluated across a range of locations and harvest years, many of the QTL detection methods ignore two- and three-way interactions between QTL, harvest, and location. In this work, a strategy for QTL detection in multi-harvest-location trial data, based on interval mapping and mixed models, is proposed and applied to map QTL effects on a segregating progeny from a biparental cross of pre-commercial Brazilian cultivars, evaluated at two locations and three consecutive harvest years for cane yield (tonnes per hectare), sugar yield (tonnes per hectare), fiber percent, and sucrose content. In the mixed model, we have included appropriate (co)variance structures for modeling heterogeneity and correlation of genetic effects and non-genetic residual effects. Forty-six QTLs were found: 13 QTLs for cane yield, 14 for sugar yield, 11 for fiber percent, and 8 for sucrose content. In addition, QTL by harvest, QTL by location, and QTL by harvest by location interaction effects were significant for all evaluated traits (30 QTLs showed some interaction, and 16 none). Our results contribute to a better understanding of the genetic architecture of complex traits related to biomass production and sucrose content in sugarcane