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Registros recuperados: 7
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Lamb meat tenderness prediction using neural networks and sensitivity analysis IPB - Escola Superior Agrária
Cortez, Paulo; Portelinha, Manuel; Rodrigues, Sandra; Cadavez, Vasco; Teixeira, A..
The assessment of quality is a key factor for the meat industry, where the aim is to fulfill the consumer’s needs. In particular, tenderness is considered the most important characteristic affecting consumer perception of taste. In this paper, a Neural Network Ensemble, with feature selection based on a Sensitivity Analysis procedure, is proposed to predict lamb meat tenderness. This difficult real-world problem is defined in terms of two regression tasks, by using instrumental measurements and a sensory panel. In both cases, the proposed solution outperformed other neural approaches and the Multiple Regression method.
Tipo: Article Palavras-chave: Regression; Multilayer perceptrons; Multiple regression; Meat quality; Ensembles; Data mining.
Ano: 2005 URL: http://hdl.handle.net/10198/865
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Models of mechanical cutting parameters in terms of moisture content and cross section area of sugarcane stalks CIGR Journal
Taghinezhad, Javad; Alimardani, Reza; Jafary, Ali.
The objective of this study was to find optimizing moisture content and cutting area of sugarcane stalk cutting parameters using multiple regressions and to verify the optimum levels of the variables.  The effect of moisture content and cutting section area on mechanical cutting properties of sugarcane stalks was studied using a linear blade cutting and UTM (Universal Testing Machine) size reduction device.  Data obtained in the laboratory were divided into four different groups in order to determine the peak force, cutting energy, ultimate stress and specific energy.  Additional criterions were also proposed and used as an indicator of the cutting performance.  These were the marginal cutting parameter (MCP) and return to scale (RTS).  The data obtained...
Tipo: Info:eu-repo/semantics/article Palavras-chave: Mechanical cutting; Moisture content; Sugarcane stalk; Ultimate stress; Cutting energy; Multiple regression.
Ano: 2014 URL: http://www.cigrjournal.org/index.php/Ejounral/article/view/2579
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Molecular markers associated with the agronomic traits in the medicinal plant lemon balm Biological Sciences
Safaei-Chaeikar, Sanam; Rahimi, Mehdi.
Finding association between molecular markers and agronomic traits provide an excellent tool for indirect selection of a trait of interest in the population. In this study, stepwise regression analysis was used to estimate associations between ISSR and RAPD markers with some agronomic traits in lemon balm ecotypes. The analysis of results revealed significant associations between the traits and some of the studied loci. For all the traits, more than one informative marker was detected. Totally,90informative markers, including 48 ISSR loci and 42 RAPD loci, were identified. The SA-R-10, UBC826-1, UBC812-9, UBC813-10, UBC825-4, OPA-01-15, OPC-04-7 and CS-56-8 markers or fragment showed a significant correlation with Essential oil percentage and controlled...
Tipo: Info:eu-repo/semantics/article Palavras-chave: Association analyses; Informative markers; Multiple regression; R square..
Ano: 2017 URL: http://periodicos.uem.br/ojs/index.php/ActaSciBiolSci/article/view/34309
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Multiple regression as a method for the selection of early maturing varieties Thai Agricultural
Singh, Joginder; Agarwal, K.N.; Sethi, A.S..
1 ill., 4 tables
Palavras-chave: Corn; Maize; Multiple regression; Selection; Early maturing varieties; ข้าวโพด; มัลติเปิล รีเกรสชั่น; การคัดเลือก; พันธุ์เบา.
Ano: 1972 URL: http://anchan.lib.ku.ac.th/agnet/handle/001/3894
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Selecao de descritores na caracterizacao e avaliacao preliminar de germoplasma de guandu. Repositório Alice
SANTOS, C. A. F.; OLIVEIRA, C. A. V.; MENEZES, E. A..
Na caracterizacao de acessos de bancos de germoplasmas, a pratica generalizada tem sido a observacao de um grande numero de descritores, sem avaliacao da contribuicao relativa de cada descritor para a discriminacao fenotipica ou explicacao de determinados caracteres. Para analisar os descritores importantes em guandu (Cajanus cajan (L.) Millsp.), foram caracterizados 54 acessos no ano de 1991 e 34 acessos no ano de 1992, em EMBRAPA-CPATSA, em Petrolina, PE, adotando-se a analise dos componentes principais para o conjunto das variaveis e a regressao multipla, tendo como variavel dependente a producao de graos (g/planta). Na analise dos componentes principais, foram considerados como descritores discriminantes os caracteres numero e sementes por vagem, peso...
Tipo: Artigo em periódico indexado (ALICE) Palavras-chave: Selecao; Germoplasma; Guandu; Descritor; Melhoramento genetico; Regressao multipla; Cajanus cajan; Germplasm; Descriptor; Selection; Pigeonpea; Multiple regression; Melhoramento genético; Genentic breeding.
Ano: 1995 URL: http://www.alice.cnptia.embrapa.br/handle/doc/133151
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Selecao de descritores na caracterizacao e avaliacao preliminar de germoplasma de guandu. Repositório Alice
SANTOS, C.A.F.; OLIVEIRA, C.A.B.; MENEZES, E.A..
Na caracterizacao de acessos de bancos de germoplasmas, a pratica generalizada tem sido a observacao de um grande numero de descritores, sem avaliacoes da contribuicao relativa de cada descritor para a discriminacao fenotipica ou explicacao de determinados caracteres. Para analisar os descritores importantes em guandu (Cajanus cajan (L.) Millsp.), foram caracterizados 54 acessos no ano de 1991 e 34 acessos no ano de 1992, na EMBRAPA-CPATSA, em Petrolina, PE, adotando-se a analise dos componentes principais para o conjunto das variaveis e a regressao multipla, tendo como variavel dependente a producao de graos (g/planta). Na analise dos componentes principais, foram considerados como descritores discriminantes os caracteres numero de sementes por vagem,...
Tipo: Artigo em periódico indexado (ALICE) Palavras-chave: Cajanus cajan; Componentes principais; Regressao multipla; Melhoramento genetico; Principal components; Multiple regression; Genetic breeding.
Ano: 1995 URL: http://www.alice.cnptia.embrapa.br/handle/doc/104257
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Using multiple regression, neural networks and supprot vector machines to predict lamb carcasses composition IPB - Escola Superior Agrária
Silva, Filipe; Cortez, Paulo; Cadavez, Vasco.
The objective of this work was to use a Data Mining (DM) approach to predict, using as predictors the carcass measurements taken at slaughter line, the composition of lamb carcasses. One hundred and twenty ve lambs of Churra Galega Bragan cana breed were slaughtered. During carcasses quartering, a caliper was used to perform subcutaneous fat measurements, over the maximum depth of longissimus muscle (LM), between the 12th and 13th ribs (C12), and between the 1st and 2nd lumbar vertebrae (C1). The Muscle (MP), Bone (BP), Subcutaneous Fat (SFP), Inter-Muscular Fat (IFP), and Kidney Knob and Channel Fat (KKCF) proportions of lamb carcasses were computed. We used the rminer R library and compared three regression techniques: Multiple Regression (MR), Neural...
Tipo: ConferenceObject Palavras-chave: Carcass; Multiple regression; Neural networks; Support vector machines; Tissue.
Ano: 2010 URL: http://hdl.handle.net/1822/10826
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