Abstract The objective of this work was to develop an index of adequacy to minimum biosecurity conditions (IAB) to express the external biosecurity level of pig farms in the state of Santa Catarina, Brazil. Pig farms of producers registered in the database of Companhia Integrada de Desenvolvimento Agrícola de Santa Catarina were sampled through an online questionnaire, with 76 questions on farm identification, production system, relationship with the agroindustry, herd size, and external biosecurity. One hundred questionnaires were answered by the farmers, showing the existence, partial existence, or absence of biosecurity practices, with scores of 1.0, 0.5, and 0.0, respectively, used to calculate the IAB of each farm. The farrow to weaning farms were grouped into three categories of production units (farrow to finishing, farrow to rearing, or farrow to weaning) and two of relationships with the production chain (integrated or independent). The investments necessary to achieve the ideal biosecurity practices were estimated. The farms with a low IAB (< 40%) represented 33% of the total, and the remaining 67% of the farms were classified with a medium or high index, evidencing a good external biosecurity. The IAB can be used to measure the biosecurity of pig farms and, based on their classification, to support the design of intervention plans.

Resumo O objetivo deste trabalho foi desenvolver um índice de adequação às condições mínimas de biossegurança (IAB) para expressar o nível de biossegurança externa de granjas suinícolas, no estado de Santa Catarina, Brasil. Foram amostradas granjas de produtores registrados no banco de dados da Companhia Integrada de Desenvolvimento Agrícola de Santa Catarina, por meio de questionário online com 76 perguntas sobre identificação da granja, sistema de produção, relação com a agroindústria, tamanho do rebanho e biossegurança externa. Foram respondidos 100 questionários pelos produtores, tendo mostrado a existência, a existência parcial ou a ausência de práticas de biossegurança, com pontuações de 1,0, 0,5 e 0,0, respectivamente, utilizadas para calcular o IAB de cada granja. As granjas de produção foram agrupadas em três categorias de unidades de produção (ciclo completo, creche ou desmame) e duas de relação com a cadeia produtiva (integrada ou independente). Estimaram-se os investimentos necessários para atingir as práticas ideais de biossegurança. As granjas com baixo IAB (< 40%) representaram 33% do total, e o restante das 67% propriedades foram classificadas com índice médio ou alto, tendo evidenciado boa biossegurança externa. O IAB pode ser usado para medir a biosseguridade de granjas suinícolas e, com base na classificação delas, apoiar a elaboração de planos de intervenção.

ABSTRACT: Among the species related to sugarcane, Saccharum spontaneum (L.) is a wild species with the greatest potential as a source of genetic variation to cope with biomass production in harsh environments. Due to its high yield, early vigor, ratooning ability, low input requirements and tolerance to various biotic and abiotic stresses, sugarcane breeders have shown interest in its contribution, as a donor of genes, to the development of high biomass energy canes. The conservation, evaluation and utilization of the genetic variability of S. spontaneum available in germplasm collections are critical for breeding, but, given the aggressive rhizomatous growth habit and the ability to propagate via seed dispersal, S. spontaneum is classified as a noxious weed in several nations, including the U.S.A. As a result, field trials are restrictive and few phenotypic analyses have been carried out on these collections. In the present study, a subset of 130 S. spontaneum accessions obtained from the World Collection of Sugarcane and Related Grasses in Miami, FL has been characterized phenotypically - with either morphological and agronomic traits (including composition analysis) or reaction to abiotic stress and genotypically - molecular markers (Simple Sequence Repeats - SSR). Using these data, a core collection has been established, genotypes with positive agronomic traits have been identified and are being used as parents for hybridization crosses, aimed at genetic improvement of sugarcane and energycane.

O objetivo desse trabalho foi avaliar o uso de Redes Neurais Artificiais (RNA) na seleção dentro de famílias de cana-de-açúcar. O melhor modelo de RNA não apresentou erro, sendo capaz de classificar corretamente todos os genótipos, ou seja, a rede tomou a mesma decisão de seleção realizada pelo melhorista durante a aplicação do BLUP individual simulado (BLUPIS), demonstrando a capacidade de aprendizado da RNA a partir das entradas e saídas informadas nas fases de treinamento e validação. Tendo em vista que a seleção via RNA facilita a identificação dos melhores indivíduos e visando desenvolver uma nova estratégia de seleção dentro das melhores famílias, de forma a garantir que os melhores genótipos da população sejam avaliados nas próximas fases do programa de melhoramento, recomendamos, ranquear as famílias via BLUP, selecionar as melhores e realizar a seleção individual via RNA, a partir das informações coletadas em nível individual nas melhores famílias.

The objective of this study was to evaluate Artificial Neural Networks (ANN) applied in an selection process within sugarcane families. The best ANN model produced no mistake, but was able to classify all genotypes correctly, i.e., the network made the same selective choice as the breeder during the simulation individual best linear unbiased predictor (BLUPIS), demonstrating the ability of the ANN to learn from the inputs and outputs provided in the training and validation phases. Since the ANN-based selection facilitates the identification of the best plants and the development of a new selection strategy in the best families, to ensure that the best genotypes of the population are evaluated in the following stages of the breeding program, we recommend to rank families by BLUP, followed by selection of the best families and finally, select the seedlings by ANN, from information at the individual level in the best families.