Fundamental Limits on Wavelength, Efficiency and Yield of the Charge Separation Triad

In an attempt to optimize a high yield, high efficiency artificial photosynthetic protein we have discovered unique energy and spatial architecture limits which apply to all light-activated photosynthetic systems. We have generated an analytical solution for the time behavior of the core three cofactor charge separation element in photosynthesis, the photosynthetic cofactor triad, and explored the functional consequences of its makeup including its architecture, the reduction potentials of its components, and the absorption energy of the light absorbing primary-donor cofactor. Our primary findings are two: First, that a high efficiency, high yield triad will have an absorption frequency more than twice the reorganization energy of the first electron transfer, and second, that the relative distance of the acceptor and the donor from the primary-donor plays an important role in determining the yields, with the highest efficiency, highest yield architecture having the light absorbing cofactor closest to the acceptor. Surprisingly, despite the increased complexity found in natural solar energy conversion proteins, we find that the construction of this central triad in natural systems matches these predictions. Our analysis thus not only suggests explanations for some aspects of the makeup of natural photosynthetic systems, it also provides specific design criteria necessary to create high efficiency, high yield artificial protein-based triads.

Upland rice yield as affected by previous summer crop rotation (soybean or upland rice) and glyphosate management on cover crops

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Influence of different extraction methods on the yield and linalool content of the extracts of Eugenia uniflora L.

This work has been developed using a sylvestral fruit tree, native to the Brazilian forest, the Eugenia uniflora L., one of the Mirtaceae family. The main goal of the analytical study was focused on extraction methods themselves. The method development pointed to the Clevenger extraction as the best yield in relation to SFE and Soxhlet. The SFE method presented a good yield but showed a big amount of components in the final extract, demonstrating low selectivity. The essential oil extracted was analyzed by GC/FID showing a large range of polarity and boiling point compounds, where linalool, a widely used compound, was identified. Furthermore, an analytical solid phase extraction method was used to clean it up and obtain separated classes of compounds that were fractionated and studied by GC/FlD and GUMS. (c) 2006 Elsevier B.V. All rights reserved.

Buffalos milk yield analysis using random regression models

Data comprising 1,719 milk yield records from 357 females (predominantly Murrah breed), daughters of 110 sires, with births from 1974 to 2004, obtained from the Programa de Melhoramento Genetic de Bubalinos (PROMEBUL) and from records of EMBRAPA Amazonia Oriental - EAO herd, located in Belem, Para, Brazil, were used to compare random regression models for estimating variance components and predicting breeding values of the sires. The data were analyzed by different models using the Legendre's polynomial functions from second to fourth orders. The random regression models included the effects of herd-year, month of parity date of the control; regression coefficients for age of females (in order to describe the fixed part of the lactation curve) and random regression coefficients related to the direct genetic and permanent environment effects. The comparisons among the models were based on the Akaike Infromation Criterion. The random effects regression model using third order Legendre's polynomials with four classes of the environmental effect were the one that best described the additive genetic variation in milk yield. The heritability estimates varied from 0.08 to 0.40. The genetic correlation between milk yields in younger ages was close to the unit, but in older ages it was low.

Genetic parameters estimate for milk and mozzarella cheese yield, fat and protein percentage in dairy buffaloes in Brazil

The aim of this study was analyze the (co)variance components and genetic and phenotypic relationships in the following traits: accumulated milk yield at 270 days (MY270,), observed until 305 days of lactation; accumulated milk yield at 270 days (MY270/A) and at 305 days (MY305), observed until 335 days of lactation; mozzarella cheese yield (MCY) and fat (FP) and protein (PP) percentage, observed until 335 days of lactation. The (co)variance components were estimated by Restricted Maximum Likelihood methodology in analyses single, two and three-traits using animal models. Heritability estimated for MY270, MY270/A, MY305, MCY, FP and PP were 0.22; 0.24, 0.25, 0.14, 0.29 and 0.40 respectively. The genetic correlations between MCY and the variables MY270, MY270/A, MY305, PP and FP was: 0.85; 1.00; 0.89; 0.14 and 0.06, respectively. This way, the selection for the production of milk in long period should increase MCY. However, in the search of animals that produce milk with quality, the genetic parameters suggest that another index should be composed allying these studied traits.

Variances of direct genetic effects, maternal genetic effects, and cytoplasmic inheritance effects for milk yield, fat yield, and fat percentage

Milk yield, fat yield, and fat percentage during the first three lactations were studied using New York Holsteins that were milked twice daily over a 305-d, mature equivalent lactation. Those data were used to estimate variances from direct and maternal genetic effects, cytoplasmic effects, sire by herd interaction, and cow permanent environmental effects. Cytoplasmic line was traced to the last female ancestor using DHI records from 1950 through 1991. Records were 138,869 lactations of 68,063 cows calving from 1980 through 1991. Ten random samples were based on herd code. Samples averaged 4926 dams and 2026 cytoplasmic lines. Model also included herd-year-seasons as fixed effects and genetic covariance for direct-maternal effects. Mean estimates of the effects of maternal genetic variances and direct-maternal covariances, as fractions of phenotypic variances, were 0.008 and 0.007 for milk yield, 0.010 and 0.010 for fat yield, and 0.006 and 0.025 for fat percentage, respectively. Average fractions of variance from cytoplasmic line were 0.011, 0.008, and 0.009 for milk yield, fat yield, and fat percentage. Removal of maternal genetic effects and covariance for maternal direct effects from the model increased the fraction of direct genetic variance by 0.014, 0.021, and 0.046 for milk yield, fat yield, and fat percentage; little change in the fraction was due to cytoplasmic line. Exclusion of cytoplasmic effects from the model increased the ratio of additive direct genetic variance to phenotypic variance by less than 2%. Similarly, when sire by herd interaction was excluded, the ratio of direct genetic variance to phenotypic variance increased 1% or less.

Genetic parameters estimates for milk, fat and protein yield analyzed by test day models for Murrah buffaloes in Brazil

The objectives of this study were to estimate genetic parameters for test-day milk, fat and protein yields, in Murrah buffaloes. In this study 4,757 complete lactations of Murrah buffaloes were analyzed. The (co) variance components were estimated by restricted maximum likelihood using MTDFREML software. The bi-trait animal test-day models included genetic additive direct and permanent environment effects, as random effects, and the fixed effects of contemporary group (herds-year-month of control) and age of the cow at calving as linear and quadratic covariable. The heritability estimate at first control was 0.19, increased until the third control (0.24), decreasing thereafter, reaching the lowest value at the ninth control (0.09). The highest heritability estimates for fat and protein yield were 0.23 (first control) and 0.33 (third control), respectively. For milk yield, genetic and phenotypic correlation estimates ranged from 0.37 to 0.99 and from 0.52 to 0.94, respectively. Genetic correlations were higher than phenotypic ones. For fat and protein yields, genetic correlation estimates ranged from 0.42 to 0.97.

Factors that cause genotype by environment interaction and use of a multiple-trait herd-cluster model for milk yield of Holstein cattle from Brazil and Colombia

Descriptive herd variables (DVHE) were used to explain genotype by environment interactions (G x E) for milk yield (MY) in Brazilian and Colombian production environments and to develop a herd-cluster model to estimate covariance components and genetic parameters for each herd environment group. Data consisted of 180,522 lactation records of 94,558 Holstein cows from 937 Brazilian and 400 Colombian herds. Herds in both countries were jointly grouped in thirds according to 8 DVHE: production level, phenotypic variability, age at first calving, calving interval, percentage of imported semen, lactation length, and herd size. For each DVHE, REML bivariate animal model analyses were used to estimate genetic correlations for MY between upper and lower thirds of the data. Based on estimates of genetic correlations, weights were assigned to each DVHE to group herds in a cluster analysis using the FASTCLUS procedure in SAS. Three clusters were defined, and genetic and residual variance components were heterogeneous among herd clusters. Estimates of heritability in clusters 1 and 3 were 0.28 and 0.29, respectively, but the estimate was larger (0.39) in Cluster 2. The genetic correlations of MY from different clusters ranged from 0.89 to 0.97. The herd-cluster model based on DVHE properly takes into account G x E by grouping similar environments accordingly and seems to be an alternative to simply considering country borders to distinguish between environments.

Alternative to peat for Agaricus brasiliensis yield

Casing layer is one of the most important components of Agaricus spp. production and it directly affects mushroom productivity, size and mass. The aim of this study was to evaluate potential raw materials as a casing layer and their effect on Agaricus brasiliensis productivity. Raw materials from Brazil with potential use were selected and characterized, and the most promising ones were tested as casing layers for mushroom yield. Evaluated raw materials included lime schist, vermiculite, eucalyptus sawdust, sand, São Paulo peat, Santa Catarina peat, subsoil and charcoal. Particle size, porosity and water absorption in relation to mushroom yield for casing layers were determined. Lime schist, an alternate casing layer to peat, is presented and the effects of the casing layer on the mushroom yield are discussed. © 2009 Elsevier Ltd. All rights reserved.

Test-day model for milk yield of dairy buffaloes in colombia

The test-day model is the preferred method for genetic evaluations in dairy cattle. For this study, 28372 test-day records of 1220 lactations from 1997 to 2009 were used. The (co)variance components for milk in test-day were estimated using a Uni and multiple-traits repeated animal model with the Restricted Maximum Likelihood method (REML). The Contemporary Group (herd, year, and season of parity) and the age of parity (linear and quadratic) fixed effects, and the additive genetic, permanent environmental, and residual random effects were included in the model. The heritabilities ranged between 0.06 and 0.45 during lactation. The genetic correlations were greater than 0.93. In conclusion, the test-day model is appropriate for the genetic evaluation of dairy buffaloes in Colombia.

Yield and phytochemical characterization of essential oil from Ocimum selloi B. obtained by hydrodistillation and supercritical fluid extraction

The yield and chemical composition of essential oils from leaves of Ocimum selloi B. submitted to organic and mineral fertilization, obtained by hydrodistillation and supercritical fluid extraction (SFE) were compared. Essential oil was extracted in a Clevenger-type apparatus for 2 h 30 min and analyzed by GC-MS (Shimadzu, QP 5050-DB-5 capillary column - 30 m × 0.25 mm × 0.25 μm). Carrier gas was helium (1.7 ml/min); split ratio: 1:30. Temperature program: 50°C, rising to 180°C at 5°C/min, 180°C, rising to 280°C at 10°C/min. Injector temperature: 240°C and detector temperature: 230°C. Identifications of chemical compounds were made by matching their mass spectra and Kovat's indices (IK) values with known compounds reported in the literature. An Applied Separations-apparatus (Speed SFE, model 7071, Allentown, PA, EUA) was used for SFE extractions. They were conducted at pressure 200 bar and temperature 30°C (20 min in static mode and 40 min in dynamic mode). The supercritical CO2 flow rate was (6.8±0.7)×10-5 kg-CO2/s. The essential oil collected was immersed in ethylene glycol bath (5°C). The yield of essential oils obtained by SFE was larger than hydrodistillation in both fertilization treatments (279 and 333% for organic and mineral fertilizations, respectively). There were no differences between the fertilization treatments. The amount of the volatile components showed by GC-MS chromatogram was highest in the essential oil obtained by hydrodistillation than SFE. The main volatile constituents of the essential oils were trans-anethole (Hydrodistillation: organic - 52.4%; mineral - 55.0%/ SFE: Hydrodistillation - 62.8%; mineral - 66.8%) and methyl-chavicol (Hydrodistillation: organic - 37.3%; mineral - 38.3%/ SFE: organic - 8.4%; mineral - 4.3%). A reduction of methyl-chavicol relative proportion of essential oil obtained by SFE was observed. Cys-anethole, α-copaene, trans-cariofilene, germacrene-D, β-selinene, biciclogermacrene and spathulenol were expressed only in hydrodistillation. The extraction of essential oil by SFE presented larger yield of essential oil than hydrodistillation technique, presenting, however, these essential oils, different phytochemical profiles.

Genetic parameters for test-day milk yield, 305-day milk yield, and lactation length in Guzerat cows

Milk production in tropical environments requires the use of crossbreeding systems including breeds well adapted to harsh conditions, but with lower productivities when compared to specialized breeds. Besides the genetic improvement for milk production, lactation lengths also need to be studied for most of these breeds. Accordingly, genetic parameters were estimated for 305-day cumulative milk yield (MY305), test-day milk yield (TDMY), and lactation length (LL) using information from the first lactations of 2816 Guzerat cows selected for milk production in 28 herds in Brazil. Contemporary groups were defined as herd, year and season of the test for TDMY, and as herd, year and season of calving for MY305 and LL. Variance components were estimated with the restricted maximum likelihood method under a multi-trait animal model. Heritabilities estimated for TDMY ranged from 0.16 to 0.24, and were 0.24 and 0.12 for MY305 and LL, respectively. Genetic correlations were high and positive, ranging from 0.51 to 0.99 among TDMY records, from 0.81 to 0.98 between each TDMY and MY305, and from 0.71 to 0.94 between each TDMY and LL. Genetic parameters obtained in this study indicated the possibility of using test-day records for the prediction of breeding values for milk yield in this population of the Guzerat breed. The use of TDMY as selection criteria would result in indirect gains in MY305 and LL. However, the highest response to selection for MY305 would be obtained by direct selection for this trait. © 2012 Elsevier B.V.

Multiple-trait random regression models for the estimation of genetic parameters for milk, fat, and protein yield in buffaloes

In this study, genetic parameters for test-day milk, fat, and protein yield were estimated for the first lactation. The data analyzed consisted of 1,433 first lactations of Murrah buffaloes, daughters of 113 sires from 12 herds in the state of São Paulo, Brazil, with calvings from 1985 to 2007. Ten-month classes of lactation days were considered for the test-day yields. The (co)variance components for the 3 traits were estimated using the regression analyses by Bayesian inference applying an animal model by Gibbs sampling. The contemporary groups were defined as herd-year-month of the test day. In the model, the random effects were additive genetic, permanent environment, and residual. The fixed effects were contemporary group and number of milkings (1 or 2), the linear and quadratic effects of the covariable age of the buffalo at calving, as well as the mean lactation curve of the population, which was modeled by orthogonal Legendre polynomials of fourth order. The random effects for the traits studied were modeled by Legendre polynomials of third and fourth order for additive genetic and permanent environment, respectively, the residual variances were modeled considering 4 residual classes. The heritability estimates for the traits were moderate (from 0.21-0.38), with higher estimates in the intermediate lactation phase. The genetic correlation estimates within and among the traits varied from 0.05 to 0.99. The results indicate that the selection for any trait test day will result in an indirect genetic gain for milk, fat, and protein yield in all periods of the lactation curve. The accuracy associated with estimated breeding values obtained using multi-trait random regression was slightly higher (around 8%) compared with single-trait random regression. This difference may be because to the greater amount of information available per animal. © 2013 American Dairy Science Association.

Comparison of factor-analytic and reduced rank models for test-day milk yield in Gyr dairy cattle (Bos indicus)

We analyzed 46,161 monthly test-day records of milk production from 7453 first lactations of crossbred dairy Gyr (Bos indicus) x Holstein cows. The following seven models were compared: standard multivariate model (M10), three reduced rank models fitting the first 2, 3, or 4 genetic principal components, and three models considering a 2-, 3-, or 4-factor structure for the genetic covariance matrix. Full rank residual covariance matrices were considered for all models. The model fitting the first two principal components (PC2) was the best according to the model selection criteria. Similar phenotypic, genetic, and residual variances were obtained with models M10 and PC2. The heritability estimates ranged from 0.14 to 0.21 and from 0.13 to 0.21 for models M10 and PC2, respectively. The genetic correlations obtained with model PC2 were slightly higher than those estimated with model M10. PC2 markedly reduced the number of parameters estimated and the time spent to reach convergence. We concluded that two principal components are sufficient to model the structure of genetic covariances between test-day milk yields. © FUNPEC-RP.

Biomass yield and calorific value of six clonal stands of Eucalyptus urophylla S. T. Blake cultivated in Northeastern Brazil

A demanda mundial por energia limpa e sustentável tem aumentado nos últimos anos. Uma das alternativas é a biomassa, incluindo os plantios florestais, com destaque, no Brasil, para o gênero Eucalyptus spp., que, atualmente, possui diversos clones selecionados para a produção de energia. Em razão da diferença na adaptação dos clones aos diferentes ambientes, há necessidade de estudos específicos para avaliar a produção de energia para determinada região. Objetivou-se, neste estudo, determinar dentre seis clones de Eucalyptus urophylla S. T. Blake analisados, aqueles com maior potencial para a produção de biomassa e energia para a região Centro Sul do Maranhão (Grajaú). Os clones foram avaliados com 41 meses de idade, plantados em espaçamento de 4 x 3 m, e distribuídos em delineamento inteiramente casualizado, com cinco repetições. Cada parcela experimental era composta por 100 árvores. Foram determinadas a produção e a alocação de biomassa de cada parte da árvore e o poder calorífico de casca e do lenho. Dos seis clones estudados, dois se destacaram tanto na produção de biomassa, quanto para a geração de energia, sendo superiores em até 27 % em comparação com o clone de menor rendimento.