So far in this course we have dealt entirely with the evolution of characters that are controlled by simple Mendelian inheritance at a single locus. There are notes on the course website about gametic disequilibrium and how allele frequencies change at two loci simultaneously, but we didn’t discuss them. In every example we’ve considered we’ve imagined that we could understand something about evolution by examining the evolution of a single gene. That’s the domain of classical population genetics. For the next few weeks we’re going to be exploring a field that’s actually older than classical population genetics, although the approach we’ll be taking to it involves the use of population genetic machinery. If you know a little about the history of evolutionary biology, you may know that after the rediscovery of Mendel’s work in 1900 there was a heated debate between the “biometricians” (e.g., Galton and Pearson) and the “Mendelians” (e.g., de Vries, Correns, Bateson, and Morgan). Biometricians asserted that the really important variation in evolution didn’t follow Mendelian rules. Height, weight, skin color, and similar traits seemed to

Human biochemical genetics

A Metodologia Cientifica, mais do que uma disciplina, que em principio desperta a ideia de uma linha puramente teorica, deve ser encarada como um conjunto de procedimentos sistematicos e racionais, base da formacao tanto do estudioso quanto do profissional. Ambos atuam, alem da pratica, no mundo das ideias, ou seja, suas linhas basicas caminham pelo campo teorico, porem, o acumulo do conhecimento cientifico teorico, permite a sua aplicacao pratica no desenvolvimento tecnologico, alem de sua utilizacao nas atividades profissionais. Pode-se afirmar que a pratica nasce da concepcao sobre o que deve ser realizado e qualquer tomada de decisao fundamenta-se naquilo que se afigura como o mais logico, racional, eficiente e eficaz. Desta forma, deve-se encarar a Pesquisa Cientifica e o Metodo Cientifico, que fornece os subsidios para a sua realizacao, como fundamentais para o modelo de sociedade que estamos inseridos. Os alunos devem compreender a Metodologia da Pesquisa Cientifica como um instrumento que deve auxilia a humanidade a encontrar as respostas para os problemas que surgem em nossa vida cotidiana, alem da sua importância para a elaboracao do Trabalho Cientifico, que deve ser apresentado ao final do curso de Pos-Graduacao. Para atingir este objetivo, os alunos deverao produzir um resumo cientifico.

Metodologia da pesquisa científica

Best linear unbiased prediction (BLUP) is a standard method for estimating random effects of a mixed model. This method was originally developed in animal breeding for estimation of breeding values and is now widely used in many areas of research. It does not, however, seem to have gained the same popularity in plant breeding and variety testing as it has in animal breeding. In plants, application of mixed models with random genetic effects has up until recently been mainly restricted to the estimation of genetic and non- genetic components of variance, whereas estimation of genotypic values is mostly based on a model with fixed effects. This paper reviews recent developments in the application of BLUP in plant breeding and variety testing. These include the use of pedigree information to model and exploit genetic correlation among relatives and the use of flexible variance-covariance structures for genotype-by-environment interaction. We demonstrate that BLUP has good predictive accuracy compared to other procedures. While pedi- gree information is often included via the so-called numerator relationship matrix ðAÞ, we stress that it is frequently straightforward to exploit the same infor- mation by a simple mixed model without explicit reference to the A-matrix.

https://www.esalq.usp.br/departamentos/lce/arquivos/aulas/2012/LCE5872/Piepho%20et%20al.,%202008.pdf

BLUP for phenotypic selection in plant breeding and variety testing

Identifying and characterizing vascular plants in time and space is required in various disciplines, e.g. in forestry, conservation and agriculture. Remote sensing emerged as a key technology revealing both spatial and temporal vegetation patterns. Harnessing the ever growing streams of remote sensing data for the increasing demands on vegetation assessments and monitoring requires efficient, accurate and flexible methods for data analysis. In this respect, the use of deep learning methods is trend-setting, enabling high predictive accuracy, while learning the relevant data features independently in an end-to-end fashion. Very recently, a series of studies have demonstrated that the deep learning method of Convolutional Neural Networks (CNN) is very effective to represent spatial patterns enabling to extract a wide array of vegetation properties from remote sensing imagery. This review introduces the principles of CNN and distils why they are particularly suitable for vegetation remote sensing. The main part synthesizes current trends and developments, including considerations about spectral resolution, spatial grain, different sensors types, modes of reference data generation, sources of existing reference data, as well as CNN approaches and architectures. The literature review showed that CNN can be applied to various problems, including the detection of individual plants or the pixel-wise segmentation of vegetation classes, while numerous studies have evinced that CNN outperform shallow machine learning methods. Several studies suggest that the ability of CNN to exploit spatial patterns particularly facilitates the value of very high spatial resolution data. The modularity in the common deep learning frameworks allows a high flexibility for the adaptation of architectures, whereby especially multi-modal or multi-temporal applications can benefit. An increasing availability of techniques for visualizing features learned by CNNs will not only contribute to interpret but to learn from such models and improve our understanding of remotely sensed signals of vegetation. Although CNN has not been around for long, it seems obvious that they will usher in a new era of vegetation remote sensing.

Review on Convolutional Neural Networks (CNN) in vegetation remote sensing

Agroindustrial and forestry residues, which are by-products of key industrial and economical activities, stand out as potential raw materials for the production of renewable fuels, chemicals and energy. The use of wastes is advantageous as their availability is not hindered by a requirement for arable land for the production of food and feed. In addition, waste utilization prevents its accumulation, which is of great environmental concern due to its potential for contamination of rivers and underground water. In Brazil, the agroindustry of corn (13767400 ha), sugarcane (7080920 ha), rice (2890930 ha), cassava (1894460 ha), wheat (1853220 ha), citrus (930591 ha), coconut (283205 ha), and grass (140000 ha) collectively occupies an area of 28840726 ha (FAOSTAT, http://www.faostat.fao.org/site/567/default.aspx#ancor) and generates 597 million tons of residue per year. By itself, this scale of operation calls for new solutions aiming for the appropriate utilization of these valuable resources. However, innovative dealings must be environmentally and economically acceptable and, most importantly, have social meaning. Indeed, great social benefits could draw from novel year-round activities as alternatives for the typical seasonal jobs in agroindustry. Considering the production of biomass ethanol, the abundance of feedstock near the site of processing must be taken into account, as low-density biomass involves significant handling and transportation costs. Within this context, the crushed stalk of sugar cane (bagasse) and straw are obvious choices, although bagasse is often burned for the production of steam (heat) and power/electricity in sugar-ethanol mills and important amounts of straw are needed to keep the soil nutrients balance. Other agricultural by-products of importance in Brazil, such as corn straw, wheat straw, rice straw and rice hulls, grass and forestry materials and residues from citrus, coconut and cassava processing, also deserve attention as local feedstock for the development of new and profitable activities. As each type of feedstock demands the development of tailor-made technology, the diversity of the aforementioned raw materials could allow for new solutions for the production of chemicals, fuels and energy in accordance with the local availability of these materials.

Biomass Residues in Brazil: Availability and Potential Uses

Brazil is an agricultural country, with 190 Mha of pastures sustaining 209 million cattle. Fewer than 10% of the cattle are fattened in feedlots, whereas cattle reared on pastures have a competitive advantage for export, eliminating the risks presented by the mad cow disease (bovine spongiform encephalopathy) and considerations related to animal welfare. Brazil has been the world’s largest exporter of beef since 2004 and has the largest commercial herd in the world. In 2011, 16.5% of its production was exported, and the livestock sector contributed 30.4% of the gross national product from agribusiness and 6.73% of the total GNP. Many forage breeding programs, mainly at Embrapa, have contributed to the development of improved pastures, and cultivars of Brachiaria brizantha, B. decumbens, B. humidicola and Panicum maximum are the main pastures used in the country. All have apomictic reproduction, which means there are few cultivars occupying very large, continuous areas, thus suggesting a risk to the productive system. Such is the case of B. brizantha cv. Marandu, which occupies around 50 Mha. The Brazilian tropical forage seed industry is also important, and Brazil is the main seed exporter, supplying all Latin American countries. Due to pasture degradation, around 8 Mha is renovated or recovered each year. Forages are also used and planted each year in integrated crop–livestock and integrated crop–livestock–forest systems. Nowadays, these systems occupy 4 Mha. Improved pastures are thus a major asset in Brazil not only for the beef production chain but also for the dairy industry.

The value of improved pastures to Brazilian beef production

Brazil has the largest commercial beef cattle herd and is the main beef exporter in the world. Cultivated pastures are the basis for the Brazilian beef production, and occupy an area of 101.4 million hectares. However, very few forage cultivars are commercially available, and the majority of these are of apomictic reproduction, thus genetically homogeneous. Tropical forage breeding is at its infancy, but much investment and efforts have been applied in the last three decades and some new cultivars have been released. In this paper, origin of different species, modes of reproduction, breeding programs and targets are discussed and the resulting new cultivars released are presented.

/pdf/breeding-tropical-forages-2rf3mh1mz0.pdf

Breeding tropical forages

As plantas forrageiras, base alimentar da bovinocultura de corte e de leite, sao de grande importância para o Brasil, pois a criacao de animais em pasto promoveu um diferencial qualitativo para a carne brasileira e colocou o Pais como maior exportador desse produto no mundo. O melhoramento de forrageiras tropicais, no Brasil e no mundo, e uma atividade recente, dos ultimos 30 anos, e demanda equipes multidisciplinares. Por limitacoes de germoplasma, de equipes com conhecimentos basicos e de metodos eficientes de triagem para avaliar os complexos criterios de merito, sao poucos os generos e especies trabalhados com o fim de responder a urgente demanda por diversificacao dos extensos monocultivos que se formaram no Brasil Central. Mesmo assim, os cultivares liberados, principalmente pela Embrapa, na sua maioria selecionados a partir da variabilidade natural, espelham o sucesso do metodo utilizado e respondem por mais de 70% do mercado de sementes forrageiras. Este trabalho apresenta um perfil do melhoramento de forrageiras tropicais e faz um resumo das atividades e perspectivas do melhoramento de Brachiaria spp., Panicum maximum e Stylosanthes spp.

/pdf/o-melhoramento-de-forrageiras-tropicais-no-brasil-4ka3el5q6d.pdf

O melhoramento de forrageiras tropicais no Brasil

O trabalho foi realizado com o objetivo de avaliar a producao de B. decumbens cv. Basilisk e B. brizantha, cultivares Marandu e Xaraes, sob diferentes niveis de sombreamento. Utilizou-se delineamento em blocos casualizados com esquema de parcelas subdivididas, considerando os niveis de sombreamento (0, 50, 70%) como parcela e as especies ou cultivares como subparcelas. Sementes das gramineas foram postas a germinar em bandejas e transplantadas (tres plântulas por vaso). Foram realizados quatro cortes em cada subparcela. Antes de cada corte, mediram-se a altura de planta e a area foliar de quatro folhas em cada planta e quantificou-se o numero de perfilhos vivos por vaso. Apos a colheita, as plantas foram separadas em lâmina, colmo + bainha e material morto para determinacao da producao de materia seca. Para producao de materia seca total, calcularam-se a producao media em cada um os cortes e a producao total. No ultimo corte, avaliou-se a massa seca de raizes. As interacoes significativas foram desdobradas adequadamente. O fator qualitativo foi submetido a comparacao de medias pelo teste Tukey e o quantitativo a analise de regressao linear. A excecao da producao media em quatro cortes e da producao de colmos e de material morto, observou-se interacao significativa para todas as outras variaveis. Independentemente do nivel de sombreamento, o cultivar Xaraes destacou-se positivamente na maioria das caracteristicas analisadas, enquanto, no nivel de 50% de sombreamento, o capim-braquiaria apresentou maior produtividade, em porcentagem de producao a pleno sol. Na avaliacao da porcentagem de folhas, destacou-se o capim-xaraes, seguido do capim-marandu. Independentemente da forrageira, o nivel de sombreamento teve efeito direto sobre o numero de perfilhos/planta, a producao de MS do sistema radicular, a area foliar e o valor SPAD.

http://www.scielo.br/pdf/rbz/v38n7/v38n7a04.pdf

Produção de gramíneas do gênero Brachiaria sob níveis de sombreamento

Apomixis is widely distributed among tropical forage grasses, and has long been merely regarded as an impediment to breeding. Panicum maximum is presented as the first opportunity for Brazilian geneticists to develop and test original breeding schemes adapted to an apomictic species. A large and representative germplasm of P. maximum has been introduced and is currently being evaluated. Basic knowledges on biology and reproduction are also available, which demonstrate an easy manipulation of apomixis and sexuality. Several limiting traits have already been detected during evaluation, which justify breeding attempts. An ideal scheme is given to transfer new qualities to already selected varieties.

/pdf/breeding-panicum-maximum-in-brazil-1-genetic-resources-modes-4j6mktk8dn.pdf

Liana Jank

Papers

The value of improved pastures to Brazilian beef production

Breeding tropical forages

O melhoramento de forrageiras tropicais no Brasil

Produção de gramíneas do gênero Brachiaria sob níveis de sombreamento

Breeding Panicum maximum in Brazil : 1. Genetic resources, modes of reproduction and breeding procedures