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10 resultados, página 1 de 1
Efficacy of drought-tolerant and insect-protected transgenic TELA® maize traits in Nigeria
Yoseph Beyene (2023, [Artículo])
Stem Borer TELA® Hybrids CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA FALL ARMYWORMS GENOTYPE ENVIRONMENT INTERACTION STEM EATING INSECTS TRANSGENIC PLANTS MAIZE HYBRIDS
Potential of Omics to control diseases and pests in the Coconut tree
MIGUEL ALONSO TZEC SIMA Jean Wildort Félix María Inés Granados Alegría Mónica Aparicio Ortiz Dilery Juarez Monroy Damian Mayo Sarai Vivas-Lopez Rufino Gómez-Tah Blondy Beatriz Canto Canché Maxim Berezovski Ignacio Rodrigo Islas Flores (2022, [Artículo])
The coconut palm (Cocos nucifera L.) is a common crop in pantropical areas facing various challenges, one of them being the control of diseases and pests. Diseases such as bud rot caused by Phytophthora palmivora, lethal yellowing caused by phytoplasmas of the types 16SrIV-A, 16SrIV-D or 16SrIV-E, among others, and pests like the coconut palm weevil, Rhynchophorus vulneratus (Coleoptera: Curculionidae), and the horned beetle, Oryctes rhinocerus (Coleoptera: Scarabaeidae), are controlled by applying pesticides, pheromones and cultural control. These practices do not guarantee eradication since some causal agents have become resistant or are imbedded in infected tissues making them difficult to eradicate. This review condenses the current genomics, transcriptomics, proteomics and metabolomics studies which are being conducted with the aim of understanding the pathosystems associated with the coconut palm, highlighting the findings generated by omics studies that may become future targets for the control of diseases and pests in the coconut crop. © 2022 by the authors.
COCOS NUCIFERA L. OMICS PESTS INSECTS DISEASES PATHOGENS BIOLOGÍA Y QUÍMICA CIENCIAS DE LA VIDA BIOLOGÍA MOLECULAR BIOLOGÍA MOLECULAR DE PLANTAS BIOLOGÍA MOLECULAR DE PLANTAS
Alejandra Miranda Carrazco Yendi Navarro-Noya Bram Govaerts Nele Verhulst Luc Dendooven (2022, [Artículo])
Plant-associated microorganisms that affect plant development, their composition, and their functionality are determined by the host, soil conditions, and agricultural practices. How agricultural practices affect the rhizosphere microbiome has been well studied, but less is known about how they might affect plant endophytes. In this study, the metagenomic DNA from the rhizosphere and endophyte communities of root and stem of maize plants was extracted and sequenced with the “diversity arrays technology sequencing,” while the bacterial community and functionality (organized by subsystems from general to specific functions) were investigated in crops cultivated with or without tillage and with or without N fertilizer application. Tillage had a small significant effect on the bacterial community in the rhizosphere, but N fertilizer had a highly significant effect on the roots, but not on the rhizosphere or stem. The relative abundance of many bacterial species was significantly different in the roots and stem of fertilized maize plants, but not in the unfertilized ones. The abundance of N cycle genes was affected by N fertilization application, most accentuated in the roots. How these changes in bacterial composition and N genes composition might affect plant development or crop yields has still to be unraveled.
Bacterial Community Structure DArT-Seq Bacterial Community Functionality Genes Involved in N Cycling CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA AGRICULTURAL PRACTICES MAIZE RHIZOSPHERE STEMS NITROGEN FERTILIZERS
Genomic regions associated with resistance to three rusts in CIMMYT wheat line “Mokue#1”
Naeela Qureshi Ravi Singh sridhar bhavani (2023, [Artículo])
Genetic Analysis Leaf Rust CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA GENETICS RUSTS QUANTITATIVE TRAIT LOCI MAPPING DISEASE RESISTANCE STRIPE RUST STEM RUST
Yoseph Beyene (2023, [Objeto de congreso])
CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA MAIZE HYBRIDS PEST INSECTS RESEARCH
Gerald Blasch David Hodson Francelino Rodrigues (2023, [Artículo])
Very high (spatial and temporal) resolution satellite (VHRS) and high-resolution unmanned aerial vehicle (UAV) imagery provides the opportunity to develop new crop disease detection methods at early growth stages with utility for early warning systems. The capability of multispectral UAV, SkySat and Pleiades imagery as a high throughput phenotyping (HTP) and rapid disease detection tool for wheat rusts is assessed. In a randomized trial with and without fungicide control, six bread wheat varieties with differing rust resistance were monitored using UAV and VHRS. In total, 18 spectral features served as predictors for stem and yellow rust disease progression and associated yield loss. Several spectral features demonstrated strong predictive power for the detection of combined wheat rust diseases and the estimation of varieties’ response to disease stress and grain yield. Visible spectral (VIS) bands (Green, Red) were more useful at booting, shifting to VIS–NIR (near-infrared) vegetation indices (e.g., NDVI, RVI) at heading. The top-performing spectral features for disease progression and grain yield were the Red band and UAV-derived RVI and NDVI. Our findings provide valuable insight into the upscaling capability of multispectral sensors for disease detection, demonstrating the possibility of upscaling disease detection from plot to regional scales at early growth stages.
Very High Resolution Imagery Disease Detection Methods Early Growth Stages CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA UNMANNED AERIAL VEHICLES STEM RUST PHENOTYPING HIGH-THROUGHPUT PHENOTYPING WHEAT
Tallo: A global tree allometry and crown architecture database
Tommaso Jucker Jörg Fischer Jerome Chave David Coomes John Caspersen Arshad Ali Grace Jopaul Loubota Panzou Ted R. Feldpausch Daniel Falster Vladimir Andreevich Usoltsev Stephen Adu-Bredu Luciana Alves Mohammad Aminpour Bhely ANGOBOY Ilondea Niels Anten Cécile Antin yousef askari Rodrigo Muñoz Ayyappan Narayanan Patricia Balvanera Lindsay Banin Nicolas Barbier John J. Battles Hans Beeckman Yannick Enock Bocko Benjamin Bond_Lamberty Frans Bongers Samuel Bowers THOMAS BRADE Michiel van Breugel ARTHUR CHANTRAIN Rajeev Chaudhary JINGYU DAI Michele Dalponte Kangbéni Dimobe jean-christophe domec Jean-Louis Doucet Remko Duursma Moisés Enriquez KARIN Y. VAN EWIJK WILLIAM FARFAN_RIOS Adeline FAYOLLE ERIC FORNI David Forrester Hammad Gilani John Godlee Sylvie Gourlet-Fleury Matthias Haeni Jefferson Hall Jie He Andreas Hemp JOSE LUIS HERNANDEZ STEFANONI Steven Higgins ROBERT J. HOLDAWAY Kiramat Hussain Lindsay Hutley Tomoaki Ichie Yoshiko Iida Hai Jiang Puspa Raj Joshi Seyed Hasan Kaboli Maryam Kazempour Larsary Tanaka Kenzo Brian Kloeppel Takashi Kohyama Suwash Kunwar Shem Kuyah Jakub Kvasnica Siliang Lin Emily Lines Hongyan Liu CRAIG LORIMER Joel Loumeto Yadvinder Malhi Peter Marshall Eskil Mattsson Radim Matula Jorge Arturo Meave del Castillo Sylvanus Mensah XIANGCHENG MI Stephane MOMO Takoudjou Glenn Moncrieff Francisco Mora Sarath Nissanka Kevin O'Hara steven pearce Raphaël Pélissier Pablo Luis Peri Pierre Ploton Lourens Poorter mohsen javanmiri pour Hassan pourbabaei JUAN MANUEL DUPUY RADA Sabina Ribeiro Ryan Casey ANVAR SANAEI Jennifer Sanger Michael Schlund Giacomo Sellan Alexander Shenkin Bonaventure Sonké Frank Sterck Martin Svatek Kentaro Takagi Anna Trugman Farman Ullah Matthew Vadeboncoeur Ahmad Valipour Mark Vanderwel Alejandra Vovides Weiwei WANG Li Qiu Christian Wirth MURRAY WOODS Wenhua Xiang Fabiano de Aquino Ximenes Yaozhan Xu TOSHIHIRO YAMADA Miguel A. Zavala (2022, [Artículo])
Data capturing multiple axes of tree size and shape, such as a tree's stem diameter, height and crown size, underpin a wide range of ecological research—from developing and testing theory on forest structure and dynamics, to estimating forest carbon stocks and their uncertainties, and integrating remote sensing imagery into forest monitoring programmes. However, these data can be surprisingly hard to come by, particularly for certain regions of the world and for specific taxonomic groups, posing a real barrier to progress in these fields. To overcome this challenge, we developed the Tallo database, a collection of 498,838 georeferenced and taxonomically standardized records of individual trees for which stem diameter, height and/or crown radius have been measured. These data were collected at 61,856 globally distributed sites, spanning all major forested and non-forested biomes. The majority of trees in the database are identified to species (88%), and collectively Tallo includes data for 5163 species distributed across 1453 genera and 187 plant families. The database is publicly archived under a CC-BY 4.0 licence and can be access from: https://doi.org/10.5281/zenodo.6637599. To demonstrate its value, here we present three case studies that highlight how the Tallo database can be used to address a range of theoretical and applied questions in ecology—from testing the predictions of metabolic scaling theory, to exploring the limits of tree allometric plasticity along environmental gradients and modelling global variation in maximum attainable tree height. In doing so, we provide a key resource for field ecologists, remote sensing researchers and the modelling community working together to better understand the role that trees play in regulating the terrestrial carbon cycle. © 2022 The Authors. Global Change Biology published by John Wiley & Sons Ltd.
ALLOMETRIC SCALING CROWN RADIUS FOREST BIOMASS STOCKS FOREST ECOLOGY REMOTE SENSING STEM DIAMETER TREE HEIGHT BIOLOGÍA Y QUÍMICA CIENCIAS DE LA VIDA BIOLOGÍA VEGETAL (BOTÁNICA) ECOLOGÍA VEGETAL ECOLOGÍA VEGETAL
Naeela Qureshi Mandeep Randhawa Peng Zhang Urmil Bansal Harbans Bariana (2023, [Artículo])
Fluorescent in Situ Hybridization Genomic in Situ Hybridization Ug99 CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA MARKER-ASSISTED SELECTION STEM RUST TRANSLOCATION WHEAT
Javier A. Ceja-Navarro Fernando E. Vega Ulas Karaoz Zhao Hao Petr Kosina Francisco Infante Trent Northen Eoin Brodie (2023, [Artículo])
Antibiotic Frass Non Antibiotic CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA MICROBIAL FLORA PEST INSECTS HYPOTHENEMUS HAMPEI CAFFEINE