Search results for "62"

showing 10 items of 970 documents

Effect of pulp cell number and assimilate availability on dry matter accumulation rate in a banana fruit (Musa sp. AAA group 'Grande Naine' (Cavendis…

2001

Fruit position on the bunch (inflorescence) is an important part of variability in banana fruit weight at harvest, as fruits at the bottom of the bunch (distal fruits) are approx. 40% smaller than those at the top (proximal fruits). In this study, the respective roles of cell number and cell filling rate in the development of pulp dry weight are estimated. To this end, the source/sink ratio in the plant was altered at different stages of fruit development. Leaf shading (reducing resource availability), bunch bagging (increasing sink activity by increasing fruit temperature), and bunch trimming (decreasing sink size by fruit pruning), applied once cell division had finished, showed that the …

0106 biological sciencesCell numberFruit developmentF62 - Physiologie végétale - Croissance et développementPlant ScienceBiology01 natural sciencesSink (geography)[SDV.BV.BOT] Life Sciences [q-bio]/Vegetal Biology/Botanics03 medical and health sciencesFilling rateCelluleDry weightstomatognathic systemBananeDry matterPulpe de fruitshttp://aims.fao.org/aos/agrovoc/c_3126Croissancehttp://aims.fao.org/aos/agrovoc/c_4993ComputingMilieux_MISCELLANEOUS030304 developmental biology2. Zero hunger0303 health sciencesgeographygeography.geographical_feature_categoryhttp://aims.fao.org/aos/agrovoc/c_1418BANANIERfungifood and beveragesMusaECOPHYSIOLOGIE[SDV.BV.BOT]Life Sciences [q-bio]/Vegetal Biology/BotanicsTempératurehttp://aims.fao.org/aos/agrovoc/c_921Relation source puitsstomatognathic diseaseshttp://aims.fao.org/aos/agrovoc/c_3394http://aims.fao.org/aos/agrovoc/c_7657AgronomyInflorescencehttp://aims.fao.org/aos/agrovoc/c_806http://aims.fao.org/aos/agrovoc/c_34110Shading010606 plant biology & botanyDéveloppement biologique
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Calibrating Expert Assessments Using Hierarchical Gaussian Process Models

2020

Expert assessments are routinely used to inform management and other decision making. However, often these assessments contain considerable biases and uncertainties for which reason they should be calibrated if possible. Moreover, coherently combining multiple expert assessments into one estimate poses a long-standing problem in statistics since modeling expert knowledge is often difficult. Here, we present a hierarchical Bayesian model for expert calibration in a task of estimating a continuous univariate parameter. The model allows experts' biases to vary as a function of the true value of the parameter and according to the expert's background. We follow the fully Bayesian approach (the s…

0106 biological sciencesComputer sciencepäätöksentekoRECONCILIATIONInferencecomputer.software_genre01 natural sciencesSTOCK ASSESSMENTenvironmental management010104 statistics & probabilityJUDGMENTSELICITATIONkalakantojen hoito111 Mathematicstilastolliset mallitReliability (statistics)Applied Mathematicsgaussiset prosessitfisheries sciencebias correctionexpert elicitationPROBABILITY62P1260G15symbols62F15Statistics and ProbabilityarviointimenetelmätBayesian probabilityenvironmental management.Bayesian inferenceMachine learningHEURISTICSsymbols.namesakeasiantuntijatMANAGEMENT0101 mathematicsGaussian processGaussian processCATCH LIMITSbusiness.industrybayesilainen menetelmä010604 marine biology & hydrobiologyUnivariateExpert elicitationOPINIONSupra BayesArtificial intelligenceHeuristicsbusinessFISHERIEScomputerBayesian Analysis
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Genetic and phenotypic variation of the malaria vector Anopheles atroparvus in southern Europe

2011

Abstract Background There is a growing concern that global climate change will affect the potential for pathogen transmission by insect species that are vectors of human diseases. One of these species is the former European malaria vector, Anopheles atroparvus. Levels of population differentiation of An. atroparvus from southern Europe were characterized as a first attempt to elucidate patterns of population structure of this former malaria vector. Results are discussed in light of a hypothetical situation of re-establishment of malaria transmission. Methods Genetic and phenotypic variation was analysed in nine mosquito samples collected from five European countries, using eight microsatell…

0106 biological sciencesEntomologylcsh:Arctic medicine. Tropical medicinelcsh:RC955-962PopulationBiology010603 evolutionary biology01 natural sciencesGene flowlcsh:Infectious and parasitic diseases03 medical and health sciencesSDG 3 - Good Health and Well-beingAnophelesGenetic variationGeneticsSDG 13 - Climate ActionAnimalsWings Animallcsh:RC109-216educationEcology Evolution Behavior and Systematics030304 developmental biologySDG 15 - Life on LandMorphometrics0303 health scienceseducation.field_of_studyGenetic diversity[SDV.GEN.GPO]Life Sciences [q-bio]/Genetics/Populations and Evolution [q-bio.PE]GeographyResearchAnophelesGenetic Variationbiology.organism_classification3. Good healthEurope[SDV.GEN.GA]Life Sciences [q-bio]/Genetics/Animal geneticsInfectious DiseasesEvolutionary biologyInsect ScienceMicrosatelliteParasitologyMicrosatellite RepeatsMalaria Journal
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Paysandisia archon: Taxonomy, distribution, biology and life cycle

2017

The taxonomic position of the family Castniidae within the order Lepidoptera has changed over time. Initially, it was classified in the superfamily Sesioidea, and then it was grouped in a large assemblage including the Cossoidea, Sesioidea, and Zygaenoidea. Recent studies have included it in the superfamily Cossoidea. In Europe, the palm borer moth (PBM) Paysandisia archon is the only species of the Castniidae. This moth, native to South America (Argentina and Uruguay), was first reported in Europe (France and Spain) in 2001, but it is believed to have been introduced before 1995 on palm trees imported from Argentina. Since then, the moth has been reported in Belgium, Bulgaria, Cyprus Islan…

0106 biological sciencesIdentificationPlante hôteDistribution géographiquePaysandisia archonCossoideahttp://aims.fao.org/aos/agrovoc/c_25231http://aims.fao.org/aos/agrovoc/c_15807SesioideaIntroduced speciesArecaceaeArecaceaeCastniidae010603 evolutionary biology01 natural scienceshttp://aims.fao.org/aos/agrovoc/c_8812Biologie animalehttp://aims.fao.org/aos/agrovoc/c_5083http://aims.fao.org/aos/agrovoc/c_4317http://aims.fao.org/aos/agrovoc/c_4698Palm borer Phoenix morphologyhttp://aims.fao.org/aos/agrovoc/c_11621Physiologie du développementbiologyEcologyTaxonomiebiology.organism_classificationH10 - Ravageurs des plantesPupaLepidoptera010602 entomologyhttp://aims.fao.org/aos/agrovoc/c_3791Settore AGR/11 - Entomologia Generale E ApplicataCycle de développementhttp://aims.fao.org/aos/agrovoc/c_29176http://aims.fao.org/aos/agrovoc/c_4268Zygaenoideahttp://aims.fao.org/aos/agrovoc/c_7631
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Long-term mineral fertiliser use and maize residue incorporation do not compensate for carbon and nutrient losses from a Ferralsol under continuous m…

2015

9 pages; International audience; It has been repeatedly argued that mineral fertiliser application combined with in situ retention of crop residue biomass can sustain long-term productivity of West African soils. Using 20-year experimental data from southern Togo, a biannual rainfall area, we analysed the effect of two rates of mineral NPK fertiliser application to maize–cotton rotation on the long-term dynamics of soil C and nutrient contents, as compared with two control treatments. Mineral fertiliser treatments consisted of application to both maize (first season) and cotton (second season) the research-recommended NPK rates (Fertiliser-RR) and 1.5 times these rates (Fertiliser-1.5 RR). …

0106 biological sciencesRésidu de récolteCrop residueRotation culturalehttp://aims.fao.org/aos/agrovoc/c_27870[SDV.SA.AGRO]Life Sciences [q-bio]/Agricultural sciences/AgronomySoil fertility management01 natural sciencesSoil managementCrop rotationF01 - Culture des plantesSoil pHhttp://aims.fao.org/aos/agrovoc/c_10795http://aims.fao.org/aos/agrovoc/c_356572. Zero hungerSub-Saharan Africahttp://aims.fao.org/aos/agrovoc/c_166http://aims.fao.org/aos/agrovoc/c_718204 agricultural and veterinary sciencesPE&RCTillageRendement des cultureshttp://aims.fao.org/aos/agrovoc/c_8504http://aims.fao.org/aos/agrovoc/c_3335P33 - Chimie et physique du solCarbonehttp://aims.fao.org/aos/agrovoc/c_7170[ SDV.SA.SDS ] Life Sciences [q-bio]/Agricultural sciences/Soil studySoil Science[SDV.SA.SDS]Life Sciences [q-bio]/Agricultural sciences/Soil studyZea maysFertilisationMatière organique du solhttp://aims.fao.org/aos/agrovoc/c_10176[ SDV.SA.AGRO ] Life Sciences [q-bio]/Agricultural sciences/AgronomyFertilité du solhttp://aims.fao.org/aos/agrovoc/c_7801Propriété physicochimique du solhttp://aims.fao.org/aos/agrovoc/c_1301http://aims.fao.org/aos/agrovoc/c_16118GossypiumP35 - Fertilité du solSowingFarm Systems Ecology Group15. Life on landCrop rotationAgronomySoil water040103 agronomy & agricultureEngrais minéral0401 agriculture forestry and fisheriesEnvironmental scienceSoil fertilityAgronomy and Crop Sciencehttp://aims.fao.org/aos/agrovoc/c_6662F04 - Fertilisation010606 plant biology & botanyField Crops Research
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Hierarchical log Gaussian Cox process for regeneration in uneven-aged forests

2021

We propose a hierarchical log Gaussian Cox process (LGCP) for point patterns, where a set of points x affects another set of points y but not vice versa. We use the model to investigate the effect of large trees to the locations of seedlings. In the model, every point in x has a parametric influence kernel or signal, which together form an influence field. Conditionally on the parameters, the influence field acts as a spatial covariate in the intensity of the model, and the intensity itself is a non-linear function of the parameters. Points outside the observation window may affect the influence field inside the window. We propose an edge correction to account for this missing data. The par…

0106 biological sciencesStatistics and ProbabilityFOS: Computer and information sciences62F15 (Primary) 62M30 60G55 (Secondary)MCMCGaussianBayesian inferenceMarkovin ketjutStatistics - Applications010603 evolutionary biology01 natural sciencesCox processMethodology (stat.ME)010104 statistics & probabilitysymbols.namesakeregeneraatio (biologia)Applied mathematicsApplications (stat.AP)0101 mathematicsLaplace approximationStatistics - MethodologyGeneral Environmental ScienceParametric statisticsMathematicsspatial random effectsbayesilainen menetelmäMarkov chain Monte CarloFunction (mathematics)15. Life on landMissing dataMonte Carlo -menetelmätcompetition kernelLaplace's methodKernel (statistics)symbolstree regenerationpuustometsänhoitomatemaattiset mallitStatistics Probability and Uncertainty
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Assessment of genetically modified maize Bt11 x MIR162 x 1507 x GA21 and three subcombinations independently of their origin, for food and feed uses …

2018

In this opinion, the GMO Panel assessed the four-event stack maize Btll x MIR162 x 1507 x GA21 and three of its subcombinations, independently of their origin. The GMO Panel previously assessed the four single events and seven of their combinations and did not identify safety concerns. No new data on the single events or the seven subcombinations leading to modification of the original conclusions were identified. Based on the molecular, agronomic, phenotypic and compositional characteristics, the combination of the single events in the four-event stack maize did not give rise to food/feed safety issues. Based on the nutritional assessment of the compositional characteristics of maize Btll …

0106 biological sciencesVeterinary (miscellaneous)[SDV]Life Sciences [q-bio]Context (language use)Plant Science010501 environmental sciencesBiology01 natural sciencesMicrobiologyGA21Plant scienceEnvironmental safetyinsect resistant and herbicide tolerantmaize (Zea mays)15070105 earth and related environmental sciences2. Zero hungerGenetically modified maizebusiness.industryGMOMIR162Bt11BiotechnologyGenetically modified organismScientific OpinionAnimal Science and ZoologyParasitologybusiness010606 plant biology & botanyFood Science
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Vegetation structure and greenness in Central Africa from Modis multi-temporal data.

2013

African forests within the Congo Basin are generally mapped at regional scale as broad-leaved evergreen forests, with a main distinction between terra-firme and swamp forests types. At the same time, commercial forest inventories, as well as national maps, have highlighted a strong spatial heterogeneity of forest types. A detailed vegetation map generated using consistent methods is needed to inform decision makers about spatial forest organisation and theirs relationships with environmental drivers in the context of global change. We propose a multi-temporal remotely sensed data approach to characterize vegetation types using vegetation index annual profiles. The classifications identified…

0106 biological scienceshttp://aims.fao.org/aos/agrovoc/c_28568Time Factors010504 meteorology & atmospheric sciencesDatabases FactualRainEcological Parameter Monitoringhttp://aims.fao.org/aos/agrovoc/c_900018001 natural sciencesTrees[ SDE ] Environmental Sciencesremote sensinghttp://aims.fao.org/aos/agrovoc/c_3062K01 - Foresterie - Considérations généralesDynamique des populationsForêt tropicale humidehttp://aims.fao.org/aos/agrovoc/c_6498http://aims.fao.org/aos/agrovoc/c_29008geography.geographical_feature_categoryCentral AfricaEcologyInventaire forestierVegetationArticlesClassificationSpatial heterogeneity[ SDE.MCG ] Environmental Sciences/Global ChangesDeciduoushttp://aims.fao.org/aos/agrovoc/c_7976CongoP31 - Levés et cartographie des solsForêt[SDE]Environmental SciencesSeasonshttp://aims.fao.org/aos/agrovoc/c_1432General Agricultural and Biological Scienceshttp://aims.fao.org/aos/agrovoc/c_34911Research ArticleF40 - Écologie végétaleTélédétectionClimate Change[SDE.MCG]Environmental Sciences/Global ChangesSpectroscopie infrarougeContext (language use)69Typologie010603 evolutionary biologySwampGeneral Biochemistry Genetics and Molecular BiologyCarbon Cycle[ SDU.ENVI ] Sciences of the Universe [physics]/Continental interfaces environmentHumansAfrica Centralhttp://aims.fao.org/aos/agrovoc/c_1666http://aims.fao.org/aos/agrovoc/c_1344http://aims.fao.org/aos/agrovoc/c_8176[SDU.ENVI]Sciences of the Universe [physics]/Continental interfaces environmenthttp://aims.fao.org/aos/agrovoc/c_6111Ecosystem0105 earth and related environmental sciencesChangement climatiquegeographyCartographiehttp://aims.fao.org/aos/agrovoc/c_24174Enhanced vegetation index15. Life on landEvergreenVégétationStructure du peuplement13. Climate actionCouvert forestierPhysical geographyU30 - Méthodes de recherchehttp://aims.fao.org/aos/agrovoc/c_1653tropical rainforestTropical rainforest
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Las almadrabas del Reino de Valencia entre finales del siglo XVI e inicios del XVII

2018

0210-9093 553 Estudis: Revista de historia moderna 500918 2018 44 6623952 Las almadrabas del Reino de Valencia entre finales del siglo XVI e inicios del XVII Vidal BonavilaUNESCO::HISTORIAJudit 107 133:HISTORIA [UNESCO]Revista de historia moderna 500918 2018 44 6623952 Las almadrabas del Reino de Valencia entre finales del siglo XVI e inicios del XVII Vidal Bonavila [0210-9093 553 Estudis]
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Creiximent de la població, mortalitat, natalitat i migracions a les comarques de Tarragona (1700-1860)

2018

0210-9093 553 Estudis: Revista de historia moderna 500918 2018 44 6623956 Creiximent de la poblacióUNESCO::HISTORIAmortalitat:HISTORIA [UNESCO]natalitat i migracions a les comarques de Tarragona (1700-1860) Ferrer i AlòsRevista de historia moderna 500918 2018 44 6623956 Creiximent de la població [0210-9093 553 Estudis]Llorenç 197 223
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