Genetic evaluation using multi-trait and random regression models in Simmental beef cattle

The Brazilian Association of Simmental and Simbrasil Cattle Farmers provided 29,510 records from 10,659 Simmental beef cattle; these were used to estimate (co)variance components and genetic parameters for weights in the growth trajectory, based on multi-trait (MTM) and random regression models (RRM). The (co)variance components and genetic parameters were estimated by restricted maximum likelihood. In the MTM analysis, the likelihood ratio test was used to determine the significance of random effects included in the model and to define the most appropriate model. All random effects were significant and included in the final model. In the RRM analysis, different adjustments of polynomial orders were compared for 5 different criteria to choose the best fit model. An RRM of third order for the direct additive genetic, direct permanent environmental, maternal additive genetic, and maternal permanent environment effects was sufficient to model variance structures in the growth trajectory of the animals. The (co)variance components were generally similar in MTM and RRM. Direct heritabilities of MTM were slightly lower than RRM and varied from 0.04 to 0.42 and 0.16 to 0.45, respectively. Additive direct correlations were mostly positive and of high magnitude, being highest at closest ages. Considering the results and that pre-adjustment of the weights to standard ages is not required, RRM is recommended for genetic evaluation of Simmental beef cattle in Brazil. ©FUNPEC-RP.

Applying machine learning based on multiscale classifiers to detect remote phenology patterns in Cerrado savanna trees

Plant phenology is one of the most reliable indicators of species responses to global climate change, motivating the development of new technologies for phenological monitoring. Digital cameras or near remote systems have been efficiently applied as multi-channel imaging sensors, where leaf color information is extracted from the RGB (Red, Green, and Blue) color channels, and the changes in green levels are used to infer leafing patterns of plant species. In this scenario, texture information is a great ally for image analysis that has been little used in phenology studies. We monitored leaf-changing patterns of Cerrado savanna vegetation by taking daily digital images. We extract RGB channels from the digital images and correlate them with phenological changes. Additionally, we benefit from the inclusion of textural metrics for quantifying spatial heterogeneity. Our first goals are: (1) to test if color change information is able to characterize the phenological pattern of a group of species; (2) to test if the temporal variation in image texture is useful to distinguish plant species; and (3) to test if individuals from the same species may be automatically identified using digital images. In this paper, we present a machine learning approach based on multiscale classifiers to detect phenological patterns in the digital images. Our results indicate that: (1) extreme hours (morning and afternoon) are the best for identifying plant species; (2) different plant species present a different behavior with respect to the color change information; and (3) texture variation along temporal images is promising information for capturing phenological patterns. Based on those results, we suggest that individuals from the same species and functional group might be identified using digital images, and introduce a new tool to help phenology experts in the identification of new individuals from the same species in the image and their location on the ground. © 2013 Elsevier B.V. All rights reserved.

Seasonal variation in leaf traits between congeneric savanna and forest trees in Central Brazil: Implications for forest expansion into savanna

The ecology of forest and savanna trees species will largely determine the structure and dynamics of the forest-savanna boundaries, but little is known about the constraints to leaf trait variation imposed by selective forces and evolutionary history during the process of savanna invasion by forest species. We compared seasonal patterns in leaf traits related to leaf structure, carbon assimilation, water, and nutrient relations in 10 congeneric species pairs, each containing one savanna species and one forest species. All individuals were growing in dystrophic oxisols in a fire-protected savanna of Central Brazil. We tested the hypothesis that forest species would be more constrained by seasonal drought and nutrient-poor soils than their savanna congeners. We also hypothesized that habitat, rather than phylogeny, would explain more of the interspecific variance in leaf traits of the studied species. We found that throughout the year forest trees had higher specific leaf area (SLA) but lower integrated water use efficiency than savanna trees. Forest and savanna species maintained similar values of predawn and midday leaf water potential along the year. Lower values were measured in the dry season. However, this was achieved by a stronger regulation of stomatal conductance and of CO2 assimilation on an area basis (A area) in forest trees, particularly toward the end of the dry season. Relative to savanna trees, forest trees maintained similar (P, K, Ca, and Mg) or slightly higher (N) leaf nutrient concentrations. For the majority of traits, more variance was explained by phylogeny, than by habitat of origin, with the exception of SLA, leaf N concentration, and A area, which were apparently subjected to different selective pressures in the savanna and forest environments. In conclusion, water shortage during extended droughts would be more limiting for forest trees than nutrient-poor soils. © 2013 Springer-Verlag Berlin Heidelberg.

Growth and carbon isotopes of Mediterranean trees reveal contrasting responses to increased carbon dioxide and drought

Forest dynamics will depend upon the physiological performance of individual tree species under more stressful conditions caused by climate change. In order to compare the idiosyncratic responses of Mediterranean tree species (Quercus faginea, Pinus nigra, Juniperus thurifera) coexisting in forests of central Spain, we evaluated the temporal changes in secondary growth (basal area increment; BAI) and intrinsic water-use efficiency (iWUE) during the last four decades, determined how coexisting species are responding to increases in atmospheric CO2 concentrations (Ca) and drought stress, and assessed the relationship among iWUE and growth during climatically contrasting years. All species increased their iWUE (ca. +15 to +21 %) between the 1970s and the 2000s. This increase was positively related to Ca for J. thurifera and to higher Ca and drought for Q. faginea and P. nigra. During climatically favourable years the study species either increased or maintained their growth at rising iWUE, suggesting a higher CO2 uptake. However, during unfavourable climatic years Q. faginea and especially P. nigra showed sharp declines in growth at enhanced iWUE, likely caused by a reduced stomatal conductance to save water under stressful dry conditions. In contrast, J. thurifera showed enhanced growth also during unfavourable years at increased iWUE, denoting a beneficial effect of Ca even under climatically harsh conditions. Our results reveal significant inter-specific differences in growth driven by alternative physiological responses to increasing drought stress. Thus, forest composition in the Mediterranean region might be altered due to contrasting capacities of coexisting tree species to withstand increasingly stressful conditions. © 2013 Springer-Verlag Berlin Heidelberg.

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.

Influence of potassium and sodium nutrition on leaf area components in Eucalyptus grandis trees

Background and Aims: Recent studies showed a positive tree response to Na addition in K-depleted tropical soils. Our study aimed to gain insight into the effects of K and Na fertilizations on leaf area components for a widely planted tree species. Methods: Leaf expansion rates, as well as nutrient, polyol and soluble sugar concentrations, were measured from emergence to abscission of tagged leaves in 1-year-old Eucalyptus grandis plantations. Leaf cell size and water status parameters were compared 1 and 2 months after leaf emergence in plots with KCl application (+K), NaCl application (+Na) and control plots (C). Results: K and Na applications enhanced tree leaf area by increasing both leaf longevity and the mean area of individual leaves. Higher cell turgor in treatments +K and +Na than in the C treatment resulting from higher concentrations of osmotica contributed to increasing both palisade cell diameters and the size of fully expanded leaves. Conclusions: Intermediate total tree leaf area in treatment +Na compared to treatments C and +K might result from the capacity of Na to substitute K in osmoregulatory functions, whereas it seemed unable to accomplish other important K functions that contribute to delaying leaf senescence. © 2013 Springer Science+Business Media Dordrecht.

Modelação e análise da vida útil (metrológica) de medidores tipo indução de energia elétrica ativa

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Diversidade de ácaros em indivíduos masculinos e femininos de Triplaris americana L. (Polygonaceae) e eficiência de seu pólen como alimento para Euseius citrifolius Denmark & Muma (Acari: Phytoseiidae)

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Comparação entre três critérios de amostragem para a avaliação da densidade básica da madeira de florestas implantadas de eucaliptos

Pós-graduação em Agronomia (Energia na Agricultura) - FCA

Avaliação não-destrutiva de madeiras para dormentes ferroviários

Pós-graduação em Agronomia (Energia na Agricultura) - FCA

Alterações químicas no sistema solo-planta após adubação com lodo de esgoto compostado e irrigação com água residuária em laranjeira ‘Valência’

Pós-graduação em Agronomia (Irrigação e Drenagem) - FCA

Crescimento e produção de bananeiras 'prata anã' e 'maçã' fertirrigadas com potássio

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Qualidade fisiológica de sementes, crescimento e eficiência do uso do fósforo de Corymbia citriodora Hill & Johnson

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Nutritional balance and yield for green manure orange trees

Intercropping could efficiently prevent soil nutrient losses caused by extensive agriculture. The present study aimed to assess the effect of green manure on the nutritional status of orange trees cultivar 'Pera' (Citrus sinensis (L.) Osbeck). The plants were grafted on 'Cravo' lime trees and were then planted in a 7x4m space. Four different treatments corresponding to the evaluated green manures were employed: jack bean (JB) (Canavalia ensiformis DC), lablab (LL) (Dolichos lablab L.), pigeon pea (PP) (Cajanus cajan L. Millsp), and Brachiaria (BQ) (Brachiaria brizantha Hochst ex A. Rich. Stapf) as control. The experimental design was in randomized blocks, in split-plot time, with six replicates, with four treatments (green manures) and two plants per evaluation. The nutritional status was assessed by using the DRIS method (Diagnosis and Recommendation Integrated System); the yield and the macro and micronutrient levels contained in green manures and in the control was also determined. The nutritional diagnosis indicated that, in the two years of experiment, plants treated with green manure showed better nutritional balance index compared to Brachiaria. This suggests that, over time, green manure can lead to better nutritional balance. Pigeon pea treatment showed the highest yields, compared to control, in the two evaluated crop cycles (2004/05 and 2005/06).

Imagens hiperespectrais no monitoramento da nutrição em citros

Pós-graduação em Agronomia (Energia na Agricultura) - FCA