Distribuição temporal e espacial do besouro-verde-do-açaizeiro [Macraspis pseudochrysis (Coleoptera: Scarabaeidae: Rutelini)] em açaizeiros de várzea em Mazagão, Amapá.

Em diferentes regiões do Estado do Amapá, foi verificada recentemente a ocorrência do besouro-verde-do-açaizeiro (Macraspis pseudochrysis Landin), derrubando as inflorescências de açaizeiro (Euterpe oleracea) em várzeas, provocando preocupação aos produtores, uma vez que a ação deste inseto poderia influenciar na formação de frutos. Com o objetivo de avaliar a distribuição temporal e espacial de M. pseudochrysis, foram realizadas amostragens mensais em inflorescências de E. oleracea em várzea no Campo Experimental da Embrapa Amapá em Mazagão, Amapá. Os açaizeiros eram provenientes de duas regiões do estuário amazônico que apresentam produção de frutos em épocas distintas do ano. A população 1 foi representada por açaizeiros que têm a produção de frutos no período chuvoso do ano (abril a agosto) e a população 2 foi composta por açaizeiros do tipo açaí de verão tendo sua produção de frutos no período de estiagem (agosto a dezembro). No período de maio a outubro de 2011 foram registrados 271 indivíduos de M. pseudochrysis em toda a área experimental. Na população 1 a maior densidade foi obtida em maio, apresentando 3 indivíduos/inflorescência. A população 2 apresentou densidade mais alta em julho com 4 indivíduos/inflorescência. Na maioria das ocasiões de amostragem o padrão de distribuição espacial foi agregado em ambas as populações.bitstream/item/100960/1/CPAF-AP-2014-BPD-82-Besouro-acai-DG3comCGPE.pd

Apícolas.

Neste capítulo foram destacadas espécies vegetais reconhecidamente importantes para a produção de mel no semi-árido. Essa atividade tem grande expressão no contexto sócio-econômico da população da região; e é feita em muitas vezes sob a forma extrativista, sem um planejamento racional prévio que vise à otimização dos recursos dos principais atores desse processo abelhas e plantas

An extensive experimental evaluation of automated machine learning methods for recommending classification algorithms

This paper presents an experimental comparison among four automated machine learning (AutoML) methods for recommending the best classification algorithm for a given input dataset. Three of these methods are based on evolutionary algorithms (EAs), and the other is Auto-WEKA, a well-known AutoML method based on the combined algorithm selection and hyper-parameter optimisation (CASH) approach. The EA-based methods build classification algorithms from a single machine learning paradigm: either decision-tree induction, rule induction, or Bayesian network classification. Auto-WEKA combines algorithm selection and hyper-parameter optimisation to recommend classification algorithms from multiple paradigms. We performed controlled experiments where these four AutoML methods were given the same runtime limit for different values of this limit. In general, the difference in predictive accuracy of the three best AutoML methods was not statistically significant. However, the EA evolving decision-tree induction algorithms has the advantage of producing algorithms that generate interpretable classification models and that are more scalable to large datasets, by comparison with many algorithms from other learning paradigms that can be recommended by Auto-WEKA. We also observed that Auto-WEKA has shown meta-overfitting, a form of overfitting at the meta-learning level, rather than at the base-learning level

Aptidão agrícola das terras do Matopiba.

Este trabalho está inserido no Projeto Especial Plano Estratégico de Atuação da Embrapa na Região do Matopiba, financiado pela Embrapa (Projeto SEG/IDEARE 05.13.25.009.00.00), e tem como objetivo avaliar a aptidão agrícola das terras do Matopiba, na escala 1:500.000, com base em informações pedoclimáticas disponíveis consubstanciadas por verificação in situ por meio de campanhas de campo para validação das interpretações de aptidão agrícola.bitstream/item/134012/1/DOC-179-Matopiba.pd

Kinetin and nitrogen in agronomic characteristics of soybean.

The objective of this work was to evaluate the application of kinetin associated with nitrogen in coverage on the agronomic characteristics and soybean yield. In the 2016/2017 harvest, a 6x2 factorial scheme was used, six doses of kinetin (0; 0.30; 0.60; 0.90; 1.20; 1.50 g ha−1) and two doses of N (20 and 40 kg ha−1) and in the 2017/2018 harvest, factorial scheme 5x2 was used, five doses of kinetin (0; 0.25; 0.75; 1.00; 1.25 g ha−1) and two doses of N (20 and 40 kg ha−1). Agronomic plant height characteristics, first pod insertion height, number of grains per plant, number of pods per plant, number of grains per pod, number of grains per pod, hundred-grain mass and grain yield were evaluated. The use of N alone and associated with kinetin increased the number of pods and grains in the 2016/2017 harvest. In the 2017/2018 crop, kinetin caused a reduction of 8.9% at plant height and N caused an increase in plant height and first pod insertion and reduced the number of pods and grains per plant, grains per pods and productivity

Environmental variables in the G x E interaction in soybean in the semiarid.

The objective of the present work was to evaluate the infl uence of environmental variables on the interaction between genotypes and environments and to identify adapted and stable genotypes for grain seed yield. Twenty-one cultivars were evaluated in randomized blocks with four replications in the years 2016, 2017, and 2018 in the northeastern semi-arid region of Brazil, for seed yield and oil content

Survivorship of Anopheles darlingi (Diptera: Culicidae) in Relation with Malaria Incidence in the Brazilian Amazon

We performed a longitudinal study of adult survival of Anopheles darlingi, the most important vector in the Amazon, in a malarigenous frontier zone of Brazil. Survival rates were determined from both parous rates and multiparous dissections. Anopheles darlingi human biting rates, daily survival rates and expectation of life where higher in the dry season, as compared to the rainy season, and were correlated with malaria incidence. The biting density of mosquitoes that had survived long enough for completing at least one sporogonic cycle was related with the number of malaria cases by linear regression. Survival rates were the limiting factor explaining longitudinal variations in Plasmodium vivax malaria incidence and the association between adult mosquito survival and malaria was statistically significant by logistic regression (P<0.05). Survival rates were better correlated with malaria incidence than adult mosquito biting density. Mathematical modeling showed that P. falciparum and P. malariae were more vulnerable to changes in mosquito survival rates because of longer sporogonic cycle duration, as compared to P. vivax, which could account for the low prevalence of the former parasites observed in the study area. Population modeling also showed that the observed decreases in human biting rates in the wet season could be entirely explained by decreases in survival rates, suggesting that decreased breeding did not occur in the wet season, at the sites where adult mosquitoes were collected. For the first time in the literature, multivariate methods detected a statistically significant inverse relation (P<0.05) between the number of rainy days per month and daily survival rates, suggesting that rainfall may cause adult mortality