910 resultados para Apple extract
Resumo:
2011
Resumo:
2011
Resumo:
The obtaining of a compact plant, with less vigor and high productivity, equivalent to a conventional plant, constitutes a strong tendency in the current horticulture, aiming at a raising of the fruit production at the same planted area. One of the techniques that have had success nowadays is the interstem use. This study was developed in a commercial orchard of Randon Agro Silvo Pastoril S.A. (RASIP), located in the Rio Grande do Sul state, Brazil. The purpose of this work was to evaluate the vegetative and productive development of apple trees of 'Imperial Gala' with different lengths of EM-9 interstem. The treatments consisted of five interstem lengths: 10, 15, 20, 25, 30 cm. In the seventh year of implantation the following parameters were evaluated: the height of the plant, the diameter of the 'Imperial Gala' 5 cm above the second graft point, the volume of the tree-head (height, width and length), the number of bud per branch, and the number of fruits per lineal centimeter of branch. Through this study it could be concluded that the greater interstem (30 cm) presented better indices with relation of vigor control. However, the number of fruits per lineal centimeter of branch with the interstem of 10 cm offered only significant superiority, when compared with the interstem of 30 cm. Using interstem technique allows to gather the benefits of the rootstock 'Marubakaido' and to control excessive vigour with the interstem EM-9.
Resumo:
2011
Resumo:
Grapholita molesta (Busck) is one of the main pests of apple trees, and lives on their shoots and fruits. In southern Brazil, the insect is also found on old branches and structures similar to aerial roots, so-called burrknots. This study evaluated the development and population growth potential of G. molesta fed on burrknots, compared with apple fruit cultivar. Fuji and a corn-based artiÞcial diet. The study was carried out in the laboratory under controlled temperature (25 1C), relative humidity (7010%), and photophase (16 h). The biological parameters of the immature and adult stages were determined, and a fertility life table was constructed. Insects fed on burrknots showed a longer duration and a lower survival for the egg-to-adult period (29.3 d and 22.5%) compared with those that fed on apples (25.1 d and 30.0%) and artiÞcial diet (23.9 d and 54.8%). Insects reared on aerial roots had a lower pupal weight (10.0 mg) compared with those reared on either artiÞcial diet (13.7 mg) or apple cultivar. Fuji (12.4 mg). The fecundity and longevity of males and females did not signiÞcantly differ for the three foods. Based on the fertility life table, insects reared on burrknots had the lowest net reproductive rate (Ro), intrinsic rate of population growth (rm) and finite rate of increase, compared with insects reared on artiÞcial diet and apple fruit. Burrknots support the development of the complete cycle of G. molesta, which allows populations of this pest to increase in orchards.
Resumo:
2010
Resumo:
2011
Resumo:
Abstract. This study was aimed to determine the influences of turmeric extract supplementation on water holding capacity, cooking loss, pH value and tenderness of broiler chicken meat Data analysis was subject to completely randomized design 5 treatments namely T0, T1, T2, T3 and T4 containing non-turmeric extract, 100 mg/kgBW/day, 200 mg/kgBW/day, 300 mg/kgBW/day and 400 mg/kgBW/day, respectively. Each unit of experiment administered 3 heads with four replications. The results indicated no effect from turmeric extract supplementation on water holding capacity, cooking loss, pH value and tenderness of broiler chicken meat. The average treatments of T0, T1, T2, T3, T4 had water holding capacities of 39.86, 37.58, 36.41, 36.94, respectively; cooking losses of 26.00, 27.58, 27.57, 27.11, and 27.49%, respectively; tenderness of 1.97, 1.95, 1.63, 1.77 and 1.99 Nmm, respectively, and final Body weights of 1,618.5, 1,568, 1,692.5, 1,651.75 and 1,462 g/head, respectively. However, a highly significant influence was observed on the pH values of 6.46, 6.04, 6.21, 6.08 and 5.98. The results indicated that none of the turmeric extract supplementation increased water holding capacity, cooking losses, tenderness and body weight. Key words: broiler, cooking loss, pH values, tenderness, water holding capacity, turmeric Abstrak. Penelitian ini bertujuan untuk mengetahui pengaruh pemberian ekstrak kunyit terhadap daya ikat air, susut masak, nilai pH dan keempukan daging ayam broiler. Manfaat penelitian yaitu tersedianya informasi ilmiah tentang ekstrak kunyit terhadap danging ayam broiler. Perlakuan yang diterapkan adalah T0 tanpa ekstrak kunyit, T1 100, T2 200, T3 300, dan T4 400 mg/kgBB/hari. Data analisis yang digunakan adalah rancangan acak lengkap yang terdiri dari 5 perlakuan dan 4 replikasi. Setiap unit percobaan terdiri dari 3 ekor. Hasil penelitian menunjukkan tidak ada pengaruh pemberian ekstrak kunyit terhadap daya ikat air, susut masak, dan keempukan daging ayam broiler. Rataan untuk perlakuan T0, T1, T2, T3, T4 pada Daya Ikat Air masing–masing 39,86; 37,58; 36,41; 36,94; 34,78%; susut masak 26,00; 27,58; 27,57; 27,11; 27,49%, keempukan 1,97; 1,95; 1,63; 1,77; 1,99 Nmm, dan bobot badan akhir 1.618,5; 1.568; 1.692,5; 1.651,75; 1.462g/ekor. Namun, memberikan pengaruh sangat nyata pada nilai pH 6,46; 6,04; 6,21; 6,08; 5,98. Hasil  menunjukkan bahwa pemberian ekstrak kunyit tidak meningkatkan daya ikat air, susut masak, keempukan dan bobot badan. Kata Kunci : Broiler, Susut Masak, pH, Keempukan, Daya Ikat Air, Kunyit
Resumo:
The occurrence and levels of airborne polycyclic aromatic hydrocarbons and volatile organic compounds in selected non-industrial environments in Brisbane have been investigated as part of an integrated indoor air quality assessment program. The most abundant and most frequently encountered compounds include, nonanal, decanal, texanol, phenol, 2-ethyl-1-hexanol, ethanal, naphthalene, 2,6-tert-butyl-4-methyl-phenol (BHT), salicylaldehyde, toluene, hexanal, benzaldehyde, styrene, ethyl benzene, o-, m- and pxylenes, benzene, n-butanol, 1,2-propandiol, and n-butylacetate. Many of the 64 compounds usually included in the European Collaborative Action method of TVOC analysis were below detection limits in the samples analysed. In order to extract maximum amount of information from the data collected, multivariate data projection methods have been employed. The implications of the information extracted on source identification and exposure control are discussed.
Resumo:
The measurement of Cobb angles from radiographs is routine practice in spinal clinics. The technique relies on the use and availability of specialist equipment such as a goniometer, cobbometer or protractor. The aim of this study was to validate the use of i-Phone (Apple Inc) combined with Tilt Meter Pro software as compared to a protractor in the measurement of Cobb angles. Between November 2008 and December 2008 20 patients were selected at random from the Paediatric Spine Research Groups Database. A power calculation was performed which indicated if n=240 measurements the study had a 96% chance of detecting a 5 degree difference between groups. All patients had idiopathic scoliosis with a range of curve types and severities. The study found the i-Phone combined with Tilt Meter Pro software offers a faster alternative to the traditional method of Cobb angle measurement. The use of i-Phone offers a more convenient way of measuring Cobb angles in the outpatient setting. The intra-observer repeatability of the iPhone is equivalent to the protractor in the measurement of Cobb angles.
Resumo:
Music composition using prominent broadcast speeches across the whole twentieth century in commemoration of the centenary of Marconi's first transatlantic radio transmission. The work is based on creating music from the found objects of melody derived from spoken intonation. Recordings of the speeches are accompanied throughout by live instrumental music.
Resumo:
Peer to peer systems have been widely used in the internet. However, most of the peer to peer information systems are still missing some of the important features, for example cross-language IR (Information Retrieval) and collection selection / fusion features. Cross-language IR is the state-of-art research area in IR research community. It has not been used in any real world IR systems yet. Cross-language IR has the ability to issue a query in one language and receive documents in other languages. In typical peer to peer environment, users are from multiple countries. Their collections are definitely in multiple languages. Cross-language IR can help users to find documents more easily. E.g. many Chinese researchers will search research papers in both Chinese and English. With Cross-language IR, they can do one query in Chinese and get documents in two languages. The Out Of Vocabulary (OOV) problem is one of the key research areas in crosslanguage information retrieval. In recent years, web mining was shown to be one of the effective approaches to solving this problem. However, how to extract Multiword Lexical Units (MLUs) from the web content and how to select the correct translations from the extracted candidate MLUs are still two difficult problems in web mining based automated translation approaches. Discovering resource descriptions and merging results obtained from remote search engines are two key issues in distributed information retrieval studies. In uncooperative environments, query-based sampling and normalized-score based merging strategies are well-known approaches to solve such problems. However, such approaches only consider the content of the remote database but do not consider the retrieval performance of the remote search engine. This thesis presents research on building a peer to peer IR system with crosslanguage IR and advance collection profiling technique for fusion features. Particularly, this thesis first presents a new Chinese term measurement and new Chinese MLU extraction process that works well on small corpora. An approach to selection of MLUs in a more accurate manner is also presented. After that, this thesis proposes a collection profiling strategy which can discover not only collection content but also retrieval performance of the remote search engine. Based on collection profiling, a web-based query classification method and two collection fusion approaches are developed and presented in this thesis. Our experiments show that the proposed strategies are effective in merging results in uncooperative peer to peer environments. Here, an uncooperative environment is defined as each peer in the system is autonomous. Peer like to share documents but they do not share collection statistics. This environment is a typical peer to peer IR environment. Finally, all those approaches are grouped together to build up a secure peer to peer multilingual IR system that cooperates through X.509 and email system.
Resumo:
Experience plays an important role in building management. “How often will this asset need repair?” or “How much time is this repair going to take?” are types of questions that project and facility managers face daily in planning activities. Failure or success in developing good schedules, budgets and other project management tasks depend on the project manager's ability to obtain reliable information to be able to answer these types of questions. Young practitioners tend to rely on information that is based on regional averages and provided by publishing companies. This is in contrast to experienced project managers who tend to rely heavily on personal experience. Another aspect of building management is that many practitioners are seeking to improve available scheduling algorithms, estimating spreadsheets and other project management tools. Such “micro-scale” levels of research are important in providing the required tools for the project manager's tasks. However, even with such tools, low quality input information will produce inaccurate schedules and budgets as output. Thus, it is also important to have a broad approach to research at a more “macro-scale.” Recent trends show that the Architectural, Engineering, Construction (AEC) industry is experiencing explosive growth in its capabilities to generate and collect data. There is a great deal of valuable knowledge that can be obtained from the appropriate use of this data and therefore the need has arisen to analyse this increasing amount of available data. Data Mining can be applied as a powerful tool to extract relevant and useful information from this sea of data. Knowledge Discovery in Databases (KDD) and Data Mining (DM) are tools that allow identification of valid, useful, and previously unknown patterns so large amounts of project data may be analysed. These technologies combine techniques from machine learning, artificial intelligence, pattern recognition, statistics, databases, and visualization to automatically extract concepts, interrelationships, and patterns of interest from large databases. The project involves the development of a prototype tool to support facility managers, building owners and designers. This final report presents the AIMMTM prototype system and documents how and what data mining techniques can be applied, the results of their application and the benefits gained from the system. The AIMMTM system is capable of searching for useful patterns of knowledge and correlations within the existing building maintenance data to support decision making about future maintenance operations. The application of the AIMMTM prototype system on building models and their maintenance data (supplied by industry partners) utilises various data mining algorithms and the maintenance data is analysed using interactive visual tools. The application of the AIMMTM prototype system to help in improving maintenance management and building life cycle includes: (i) data preparation and cleaning, (ii) integrating meaningful domain attributes, (iii) performing extensive data mining experiments in which visual analysis (using stacked histograms), classification and clustering techniques, associative rule mining algorithm such as “Apriori” and (iv) filtering and refining data mining results, including the potential implications of these results for improving maintenance management. Maintenance data of a variety of asset types were selected for demonstration with the aim of discovering meaningful patterns to assist facility managers in strategic planning and provide a knowledge base to help shape future requirements and design briefing. Utilising the prototype system developed here, positive and interesting results regarding patterns and structures of data have been obtained.
Resumo:
Marketers and commercial media alike are confronted by shifts in the social relations of media production and consumption in the global services economy, including the challenge of capturing, managing and commercialising media-user productivity. This trajectory of change in media cultures and economies is described here as ‘mass conversation’. Two media texts and a new media object provide a starting point for charting the ascendance and social impact of mass conversation. Apple’s 1984 television commercial, which launched the Macintosh computer, inverted George Orwell’s dystopian vision of the social consequences of panoptic communications systems. It invoked a revolutionary rhetoric to anticipate the social consequences of a new type of interactivity since theorised as ‘intercreativity’. This television commercial is contrasted with another used in Nike’s 2006 launch of its Nike+ (Apple iPod) system. The Nike+ online brand community is also used to consider how a multiplatform brand channel is seeking to manage the changing norms and practices of consumption and end-user agency. This analysis shows that intercreativity modifies the operations of ‘Big Brother’ but serves the more mundane than revolutionary purpose of generating commercial value from the affective labour of end-users.
Resumo:
Experience plays an important role in building management. “How often will this asset need repair?” or “How much time is this repair going to take?” are types of questions that project and facility managers face daily in planning activities. Failure or success in developing good schedules, budgets and other project management tasks depend on the project manager's ability to obtain reliable information to be able to answer these types of questions. Young practitioners tend to rely on information that is based on regional averages and provided by publishing companies. This is in contrast to experienced project managers who tend to rely heavily on personal experience. Another aspect of building management is that many practitioners are seeking to improve available scheduling algorithms, estimating spreadsheets and other project management tools. Such “micro-scale” levels of research are important in providing the required tools for the project manager's tasks. However, even with such tools, low quality input information will produce inaccurate schedules and budgets as output. Thus, it is also important to have a broad approach to research at a more “macro-scale.” Recent trends show that the Architectural, Engineering, Construction (AEC) industry is experiencing explosive growth in its capabilities to generate and collect data. There is a great deal of valuable knowledge that can be obtained from the appropriate use of this data and therefore the need has arisen to analyse this increasing amount of available data. Data Mining can be applied as a powerful tool to extract relevant and useful information from this sea of data. Knowledge Discovery in Databases (KDD) and Data Mining (DM) are tools that allow identification of valid, useful, and previously unknown patterns so large amounts of project data may be analysed. These technologies combine techniques from machine learning, artificial intelligence, pattern recognition, statistics, databases, and visualization to automatically extract concepts, interrelationships, and patterns of interest from large databases. The project involves the development of a prototype tool to support facility managers, building owners and designers. This Industry focused report presents the AIMMTM prototype system and documents how and what data mining techniques can be applied, the results of their application and the benefits gained from the system. The AIMMTM system is capable of searching for useful patterns of knowledge and correlations within the existing building maintenance data to support decision making about future maintenance operations. The application of the AIMMTM prototype system on building models and their maintenance data (supplied by industry partners) utilises various data mining algorithms and the maintenance data is analysed using interactive visual tools. The application of the AIMMTM prototype system to help in improving maintenance management and building life cycle includes: (i) data preparation and cleaning, (ii) integrating meaningful domain attributes, (iii) performing extensive data mining experiments in which visual analysis (using stacked histograms), classification and clustering techniques, associative rule mining algorithm such as “Apriori” and (iv) filtering and refining data mining results, including the potential implications of these results for improving maintenance management. Maintenance data of a variety of asset types were selected for demonstration with the aim of discovering meaningful patterns to assist facility managers in strategic planning and provide a knowledge base to help shape future requirements and design briefing. Utilising the prototype system developed here, positive and interesting results regarding patterns and structures of data have been obtained.