Patrícia Ferreira Ponciano Ferraz

Variabilidade espacial dos atributos da planta de uma lavoura cafeeira

Objetivou-se com esse trabalho caracterizar a estrutura e a magnitude da distribuicao espacial de atributos da planta em lavoura cafeeira e realizar o mapeamento desses atributos de forma a visualizar a distribuicao espacial, considerando a dependencia espacial destes atributos, demostrando a importância deste mapeamento. Este trabalho foi conduzido na fazenda Brejao no municipio de Tres Pontas, Minas Gerais, utilizando-se os seguintes atributos da planta: Produtividade, Indice de Maturacao, Enfolhamento, Forca de Desprendimento de Frutos Verde, Forca de Desprendimento de Frutos Maduros, Diferenca entre a Forca de Desprendimento de Frutos Verde e Maduros, Altura de Planta e Diâmetro de Copa amostrados em uma malha amostral de 100 pontos georreferenciados (64 pontos da malha base e 36 pontos de zoom). A analise destes dados por meio das tecnicas estatisticas e da geoestatistica possibilitaram caracterizar a variabilidade espacial dos atributos da planta em estudo, permitindo o mapeamento destas variaveis. Foi possivel observar a importância da cafeicultura de precisao no manejo de uma lavoura cafeeira tanto no gerenciamento da colheita quanto no acompanhamento do desenvolvimento da planta.

Predicting chick body mass by artificial intelligence‑based models

The objective of this work was to develop, validate, and compare 190 artificial intelligence-based models for predicting the body mass of chicks from 2 to 21 days of age subjected to different duration and intensities of thermal challenge. The experiment was conducted inside four climate-controlled wind tunnels using 210 chicks. A database containing 840 datasets (from 2 to 21-day-old chicks) - with the variables dry-bulb air temperature, duration of thermal stress (days), chick age (days), and the daily body mass of chicks - was used for network training, validation, and tests of models based on artificial neural networks (ANNs) and neuro-fuzzy networks (NFNs). The ANNs were most accurate in predicting the body mass of chicks from 2 to 21 days of age after they were subjected to the input variables, and they showed an R² of 0.9993 and a standard error of 4.62 g. The ANNs enable the simulation of different scenarios, which can assist in managerial decision-making, and they can be embedded in the heating control systems.

COMPORTAMENTO DE PINTINHOS SUBMETIDOS A ESTRESSE TÉRMICO

In the first week of a chick life, broilers are very sensitive to different conditions outside their thermoneutral zone. Thus, the goal of this study was to evaluate the behaviors and productive responses of broilers subjected to conditions of thermal comfort or challenge at different intensities (27, 30, 33 and 36oC) and durations (1, 2, 3 and 4 days starting on the second day of life). In the experiment, ten minutes of images from each hour of each treatment were analyzed to evaluate the key behaviors of the birds. Similar behavior at different dry-bulb air temperatures were identified by using Wards method of cluster analysis. These behaviors were grouped by dendograms in which the similarity of these data was qualified. Feed intake, water intake and body mass of these animals were evaluated and used to support the observed behaviors. Thus, a similar huddling behavior was observed in the birds from the 2nd to the 5th day of life subjected to 27oC and 30oC, while at 30oC and 33oC the behavior of accessing feeders and drinkers was also similar. Chicks subjected to 33oC presented the best performance, and at 30 and 36oC showed intermediate development.