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EFICIÊNCIA DO USO SIMULTÂNEO ENTRE DENDROGRAMA E AMMI NA SELEÇÃO DE PROGÊNIES DE AÇAZEIRO
Abstract
A expansão do consumo de polpa do fruto de açaizeiro precisa urgentemente de pesquisas para conseguir novos cultivares, visando atender o mercado em franco crescimento. Um grande dificultador é a quantidade de materiais genéticos que atrapalha o entendimento do resultado gráfico, portanto este trabalho teve como objetivo o uso simultâneo da análise multivariada, do agrupamento por dendrograma e da AMMI para identificar as superiores. Um total de 76 progênies foi avaliado em delineamento experimental de blocos ao acaso, duas repetições e cinco plantas por parcela. Avaliou-se: FV – número de cachos verdes em formação; FLF – número de lançamentos foliares por estipe e; TM - Tamanho do cacho. As conclusões foram de que o uso combinado da análise multivariada, o agrupamento pelo dendrograma e a análise gráfica AMMI, possibilita estudar quantitativo alto de progênies, tornando-se eficaz, importante e preciso; há variabilidade genética disponível com contribuições individuais distintas para a interação GxA, assim como também os efeitos ambientais; as progênies com maior destaque para estabilidade e adaptabilidade são P29, P55, P7, P8, P38, P5 e P24, não se adicionando progênie com base no modelo AMMI2, expandindo-se com o dendrograma para as progênies P72, P70, P9, P61, P62, P64 e P73; o distinto desempenho das progênies conforme os anos de avaliação, mostra que o desenvolvimento das plantas gera resposta aos fatores ambientais em função do estádio de desenvolvimento fenológico, tornando importante a pesquisa para se conhecer as exigências e respostas do açaizeiro.
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The objective of this article was to estimate the genetic variability and selection gain in the characters related with fruits in assai palms, 68 progenies collected in populations from Afuá city and planted in Amapá state were evaluated. The experiment was conducted in random blocks with two replications and four useful plants per plot. The following characters were evaluated: fruit longitudinal diameter (DLF), the fruit greatest transversal diameter (DTMA), the smallest fruit diameter (DTME); mass from one hundred fruits (P100) and, in bunches: total fruit mass (PTC). There are differences between progenies, denoting the possibility of selection gains. In general, the inheritabilities were medium or high for the characters, but always lower for PTC. The coefficient CVg/CVe was favorable in DTMA and DTME and unfavorable to PTC; the correlations between characters were positive and significant, the selection gain was 16.65% for PTC and from -1.29% to -7.60% in the other characters; the selected progenies were able to associate the desired values in the evaluated characters. The obtained conclusions were that there is high environmental contribution in the phenotypic manifestation of the progenies once the fruit metric dimensions had lower environmental effects and higher genetic effect; there is possibility of genetic gains which are important to breeding programs of this species using the characters simultaneously, although the values had been low, mainly due to the positive correlation presence, where there is preference for reduced fruit size with productivity increase.
Seedlings of açaí obtained from plant material native to floodplains (from Laranjeira and Muaná) and adapted to upland areas (cv. BRS-Pará and ecotype Hideo) were cultivated between March and October 2013 in a greenhouse, to test the hypothesis that water requirement for seedling production varies according to the origin of plant material. The seedlings were subjected to watering regimes corresponding to 40, 70, 100 and 130% of field capacity. Regardless of plant material, the production of vigorous seedlings was feasible only under irrigation of 100 and 130% of field capacity. The seedlings produced under 130% of field capacity showed higher plant height, stem diameter, number of leaves, total leaf area, leaf and root biomass, total plant biomass and root/shoot ratio than those produced under 100% of field capacity. The former also showed higher net CO2 assimilation rate, lower stomatal conductance and transpiration and higher instantaneous water use efficiency. In conclusion, the water requirement to produce vigorous seedlings of açaí does not vary within plant material and more vigorous seedlings are produced under irrigation of 130% of field capacity. © 2016, Departamento de Engenharia Agricola - UFCG/Cnpq. All rights reserved.
Acai (acai or assai) is one of the Amazon's most popular functional foods and widely used in the world. There are many benefits to its alleged use in the growing market for nutraceuticals. The acai extracts have a range of polyphenolic components with antioxidant properties, some of those present in greater quantity are orientin, isoorientin and vanillic acid, as well as anthocyanins cyanidin-3-glucoside and cyanidin-3-rutinoside. The presence of these substances is linked mainly to the antioxidant, anti- inflammatory, anti-proliferative and cardioprotective activities. Importantly, there are two main species of the Euterpe genus which produce acai. There are several differences between them but they are still quite unknown, from literature to producers and consumers. In this review are highlighted the chemical composition, botanical aspects, pharmacological, marketing and nutrition of these species based on studies published in the last five years in order to unify the current knowledge and dissimilarities between them.
Copyright © 2015 Elsevier Ltd. All rights reserved.
The analysis of genotype x environment interaction in plant breeding have been enlarged with new methodologies in the last decade, improving its efficiency on the selection of genotypes under different environmental conditions. The objective of this research was to analyze the yield and stability of twelve genotypes of rice, in eight environments, during the years 2005 and 2006 in Colombia. Completely randomized block designs with four replications were used. The phenotypic stability parameters and grouping of environments were estimated by the genotype-environment interaction study according to SREG (Sites Regression) method and its biplot graphic (GGE). The statistical analysis indicated significant differences (with 5% probability error) among genotypes and among environments. Also, it pointed out the significance (with 5% probability error) of the genotype-environment interaction, indicating different responses of genotypes confronted with different environments. In SREG method, the two first principal components of interactions explained 75.29% of the interaction. The genotypes 400094, 350361 and the variety Fedearroz were found as the highest yields. According to the biplot GGE graphic the environments La Libertad and Escobal were the ones with small variations during the years of study.
Oobjetivo deste trabalho foi avaliar a adaptabilidade e a estabilidade da produtividade de grãos de 20genótipos de feijão-caupi de porte semi-ereto, utilizando o modelo de efeitos aditivos principais e interação multiplicativa. Osensaios foram conduzidos em 16ambientes da Região Nordeste do Brasil. Osefeitos de genótipos, ambientes e da interação genótipo x ambiente, e os três primeiros eixos da análise de componentes principais (ACP) foram significativos. Osdois primeiros eixos da ACP explicaram juntos 55,11% da soma de quadrados da interação, correspondendo a 83,20% do padrão da interação genótipo x ambiente. Aslinhagens TE-97-321G-4, EVX-92-49E e EVX-63-10E apresentaram alta adaptabilidade, mas somente a última foi altamente previsível. Acultivar BRSGuariba e as linhagens EVX-92-49E e TE97-321G-4 expressam melhor potencial genético em ambientes de alta produtividade.
The objectives of this study were to determine the importance of simple and complex components of the interaction genotype × environment and to evaluate the adaptability and stability of Gália melon hybrids. Nine hybrids were tested in twelve environments of Rio Grande Norte State from 2000 to 2001. The experiments were carried out in a randomized complete block design with three replications. The statistical methods of Toler and Burrows, Wricke and AMMI (Additive Main effect and Multiplicative Interaction) were used to study the adaptability and stability. The complex component is responsible for most of the genotype × environment interaction for the yield and content of solids soluble of fruits. The environments associated with Mossoró and Assu municipalities are the most suitable to evaluate melon hybrids in the state. The hybrid DRG 1537 was the most likely to be grown in the Agro-industrial Complex Mossoró-Assu due to its stability, high productivity and high content of soluble solids.
Dietary intake of berry fruits has been demonstrated to positively impact human health. Interest in exploring new and exotic types of berries has grown in recent years. This article provides botanical descriptions and reviews the chemistry, biological activities, and commercialization of berry-producing plants from South America, specifically Aristotelia chilensis, Euterpe oleracea, Malpighia emarginata, Ugni molinae, Fragaria chiloensis, Rubus glaucus, Rubus adenotrichus, and Vaccinium floribundum. These species possess a rich and diversified composition of bioactive compounds with health-promoting properties. The most significant health benefits have been attributed to phenolic compounds and vitamin C, potentially protective against cardiovascular disease and cancer. Although both traditional folk medicine and composition of these berries suggest significant health benefits, few studies to date have investigated these potentials.
The interaction between genotypes and environment (GxE) can influence the selection process andrecommendation of peanut cultivars. The objective of this study was therefore to evaluate the influence of GxE interaction ofpeanut pod yield using AMMI. The yield of 18 peanut lines and the cultivars IAC Caiapo and Runner IAC 886 was assessedin 10 field trials in the state of São Paulo. Significant effects of genotypes, environments and GxE interactions were detected inthe analysis. The first AMMI principal component (IPCA1) explained 42.3% of the sum of squares of the GxE interaction.Sixteen of the twenty lines/cultivars under evaluation presented medium to high stability. Genotypes L127, L118, L123 line andRunner IAC 886 accounted for the greatest part of GxE interaction. Lines L132, L149 and L1-50P presented the higheststability and pod yields, above the overall mean, reflecting outstanding potential for cultivar recommendation.
Cultivar evaluation and mega-environment identification are among the most important objectives of multi-environment trials (MET). Although the measured yield is a combined result of effects of genotype (G), environment (E), and genotype x environment interaction (GE), only G and GE are relevant to cultivar evaluation and mega-environment identification. This paper presents a GGE (i.e., G + GE) biplot, which is constructed by the first two symmetrically scaled principal components (PC1 and PC2) derived from singular value decomposition of environment-centered MET data. The GGE biplot graphically displays G plus GE of a MET in a way that facilitates visual cultivar evaluation and mega-environment identification. When applied to yield data of the 1989 through 1998 Ontario winter wheat (Triticum aestivum L.) performance trials, the GGE biplots clearly identified yearly winning genotypes and their winning niches. Collective analysis of the yearly biplots suggests two winter wheat mega-environments in Ontario: a minor mega-environment (eastern Ontario) and a major one (southern and western Ontario), the latter being traditionally divided into three subareas. There were frequent crossover GE interactions within the major mega-environment but the location groupings were variable across years. It therefore could not be further divided into meaningful subareas. It was revealed that in most years PC1 represents a proportional cultivar response across locations, which leads to noncrossover GE interactions, while PC2 represents a disproportional cultivar response across locations, which is responsible for any crossover GE interactions. Consequently, genotypes with large PC1 scores tend to give higher average yield, and locations with large PC1 scores and near-zero PC2 scores facilitates identification of such genotypes.
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