Selection of tomato progenies F2:3 for resistance to bacterial wilt via mixed modeling

Bacterial wilt is among the major diseases of tomatoes and is currently considered the most important in Brazil. The development of resistant cultivars is the strategy that presents greater efficiency and viability, being the mixed modeling approach allows the selection of genetic materials with major accuracy. This work defines strategies for the development and selection of segregating strains F2:3 from the estimation of genetic parameters and individual mean components using mixed models. A greenhouse experiment was conducted in a randomized complete block design with four replicates, in which the resistance of 43 progenies F2:3 segregants obtained from the F2 generation from the cross between the parents was evaluated, having as parents Yoshimatsu (Resistant) and IPA-7 (Susceptible). Components of variance and genetic parameters were estimated, followed by ranking by additive genetic values. The selection of F2:3 progenies resistant to bacterial wilt was more effective when the household information was used. Mixed model procedures for the selective accuracy of 77.98%, verified efficiency in the selection of F2:3 progenies resistant to bacterial wilt evaluated at 20 days after inoculation. A total of 240 resistant and moderately resistant individual progenies were selected with severity scores between 1 and 2.49. Families presented the new averages between 1.0 and 2.87, making 23 families F2:3 that will continue the tomato breeding program

Herança da resistência do Feijão-Caupi ao Cowpea severe mosaic virus e Cowpea aphid-borne mosaic vírus: Inheritance of cowpea resistance to Cowpea severe mosaic virus and Cowpea aphid-borne mosaic virus

Foi avaliada a herança da resistência da variedade CNC-0434 ao Cowpea severe mosaic virus (CPSMV) e da linhagem TVu-966 ao Cowpea aphid-borne mosaic virus (CABMV) por meio de retrocruzamentos. Foram realizados dois experimentos, o primeiro com CNC-0434, Sempre Verde Salgueiro e as gerações F1, F2, RC11 e RC21, avaliados quanto à resistência ao CPSMV. No segundo, foram avaliados os genitores TVu-966, Sempre Verde Salgueiro e as gerações F1, F2, RC11 e RC21, avaliados quanto à resistência ao CABMV. As plantas foram avaliadas por inspeção visual aos 10, 20 e 30 dias após a inoculação quanto ao surgimento e desenvolvimento dos sintomas para cada um dos vírus, classificando-as como resistentes ou suscetíveis. A herança da resistência ao CPSMV em CNC-0434 é controlada por um único gene homozigoto recessivo com dois alelos. A herança da resistência ao CABMV em TVu-966 é controlada por um único gene homozigoto recessivo com dois alelos. A avaliação das plantas pode ser realizada aos dez dias após a inoculação. As duas variedades podem ser utilizadas como genitores doadores nos programas de melhoramento visando à resistência a estes vírus

Correlações em componentes de produção de feijão-caupi cultivado em ambiente de sequeiro na Zona da Mata Norte de Pernambuco: Correlations in production components of cowpea cultivated in rainfed environment in Zona da Mata Norte of Pernambuco

O feijão-caupi é uma leguminosa de grande importância socioeconômica para a região Nordeste do Brasil, sendo responsável pela geração de emprego e renda para muitas comunidades rurais. Para o desenvolvimento de novas variedades mais produtivas faz-se necessário a obtenção de informações sobre o controle genético da produção de grãos e de seus componentes primários. Desta forma, objetivou-se avaliar as correlações entre características morfoagronômicas do feijão-caupi a fim de auxiliar na seleção de genótipos superiores. O experimento foi conduzido na Estação Experimental do Instituto Agronômico de Pernambuco (IPA), em Goiana–PE. O delineamento experimental foi em blocos casualizados, com quatro repetições. Foram avaliados: início de floração, número de vagem/pedúnculo, número de vagem/planta, comprimento de vagem, peso de dez vagens, peso dos grãos de dez vagens, índice de grãos, rendimento de grãos/hectare. Existe um alto componente genético na expressão fenotípica dos caracteres avaliados, com grande probabilidade de ganhos genéticos através de ciclos de seleção para o melhoramento da cultura e entre os caracteres avaliados o número de vagem por planta, o peso de vagem e o peso de grãos por vagem são mais indicados para a seleção de genótipos promissores para o melhoramento

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear un derstanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5–7 vast areas of the tropics remain understudied.8–11 In the American tropics, Amazonia stands out as the world’s most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepre sented in biodiversity databases.13–15 To worsen this situation, human-induced modifications16,17 may elim inate pieces of the Amazon’s biodiversity puzzle before we can use them to understand how ecological com munities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple or ganism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region’s vulnerability to environmental change. 15%–18% of the most ne glected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lostinfo:eu-repo/semantics/publishedVersio

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear understanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5,6,7 vast areas of the tropics remain understudied.8,9,10,11 In the American tropics, Amazonia stands out as the world's most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepresented in biodiversity databases.13,14,15 To worsen this situation, human-induced modifications16,17 may eliminate pieces of the Amazon's biodiversity puzzle before we can use them to understand how ecological communities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple organism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region's vulnerability to environmental change. 15%–18% of the most neglected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lost

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear understanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5,6,7 vast areas of the tropics remain understudied.8,9,10,11 In the American tropics, Amazonia stands out as the world's most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepresented in biodiversity databases.13,14,15 To worsen this situation, human-induced modifications16,17 may eliminate pieces of the Amazon's biodiversity puzzle before we can use them to understand how ecological communities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple organism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region's vulnerability to environmental change. 15%–18% of the most neglected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lost

ATLANTIC EPIPHYTES: a data set of vascular and non-vascular epiphyte plants and lichens from the Atlantic Forest

Epiphytes are hyper-diverse and one of the frequently undervalued life forms in plant surveys and biodiversity inventories. Epiphytes of the Atlantic Forest, one of the most endangered ecosystems in the world, have high endemism and radiated recently in the Pliocene. We aimed to (1) compile an extensive Atlantic Forest data set on vascular, non-vascular plants (including hemiepiphytes), and lichen epiphyte species occurrence and abundance; (2) describe the epiphyte distribution in the Atlantic Forest, in order to indicate future sampling efforts. Our work presents the first epiphyte data set with information on abundance and occurrence of epiphyte phorophyte species. All data compiled here come from three main sources provided by the authors: published sources (comprising peer-reviewed articles, books, and theses), unpublished data, and herbarium data. We compiled a data set composed of 2,095 species, from 89,270 holo/hemiepiphyte records, in the Atlantic Forest of Brazil, Argentina, Paraguay, and Uruguay, recorded from 1824 to early 2018. Most of the records were from qualitative data (occurrence only, 88%), well distributed throughout the Atlantic Forest. For quantitative records, the most common sampling method was individual trees (71%), followed by plot sampling (19%), and transect sampling (10%). Angiosperms (81%) were the most frequently registered group, and Bromeliaceae and Orchidaceae were the families with the greatest number of records (27,272 and 21,945, respectively). Ferns and Lycophytes presented fewer records than Angiosperms, and Polypodiaceae were the most recorded family, and more concentrated in the Southern and Southeastern regions. Data on non-vascular plants and lichens were scarce, with a few disjunct records concentrated in the Northeastern region of the Atlantic Forest. For all non-vascular plant records, Lejeuneaceae, a family of liverworts, was the most recorded family. We hope that our effort to organize scattered epiphyte data help advance the knowledge of epiphyte ecology, as well as our understanding of macroecological and biogeographical patterns in the Atlantic Forest. No copyright restrictions are associated with the data set. Please cite this Ecology Data Paper if the data are used in publication and teaching events. © 2019 The Authors. Ecology © 2019 The Ecological Society of Americ

Catálogo Taxonômico da Fauna do Brasil: setting the baseline knowledge on the animal diversity in Brazil

The limited temporal completeness and taxonomic accuracy of species lists, made available in a traditional manner in scientific publications, has always represented a problem. These lists are invariably limited to a few taxonomic groups and do not represent up-to-date knowledge of all species and classifications. In this context, the Brazilian megadiverse fauna is no exception, and the Catálogo Taxonômico da Fauna do Brasil (CTFB) (http://fauna.jbrj.gov.br/), made public in 2015, represents a database on biodiversity anchored on a list of valid and expertly recognized scientific names of animals in Brazil. The CTFB is updated in near real time by a team of more than 800 specialists. By January 1, 2024, the CTFB compiled 133,691 nominal species, with 125,138 that were considered valid. Most of the valid species were arthropods (82.3%, with more than 102,000 species) and chordates (7.69%, with over 11,000 species). These taxa were followed by a cluster composed of Mollusca (3,567 species), Platyhelminthes (2,292 species), Annelida (1,833 species), and Nematoda (1,447 species). All remaining groups had less than 1,000 species reported in Brazil, with Cnidaria (831 species), Porifera (628 species), Rotifera (606 species), and Bryozoa (520 species) representing those with more than 500 species. Analysis of the CTFB database can facilitate and direct efforts towards the discovery of new species in Brazil, but it is also fundamental in providing the best available list of valid nominal species to users, including those in science, health, conservation efforts, and any initiative involving animals. The importance of the CTFB is evidenced by the elevated number of citations in the scientific literature in diverse areas of biology, law, anthropology, education, forensic science, and veterinary science, among others