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| Registros recuperados: 64 | |
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| Lourençoni,Dian; Abreu,Paulo G. de; Yanagi Junior,Tadayuki; Campos,Alessandro T.; Yanagi,Silvia de N. M.. |
| ABSTRACT The selection of the type of fuzzy systems pertinence curve allows a better representation of the mathematical model and a smaller simulation error. We aimed to study the effect of pertinence curves in fuzzy modeling of broiler performance, created in different production systems. For the development and testing of fuzzy models, three commercial aviaries (conventional, tunnel with negative pressure, and dark house) were evaluated over one year, totaling six lots per system. For the development of the model, the input variables were enthalpy in each rearing phase (initial: phases 1, 2, and 3; growth: phase 4; and final: phase 5) and the output variables were feed intake (FE), weight gain (GP), feed conversion (FE), and the productive efficiency... |
| Tipo: Info:eu-repo/semantics/article |
Palavras-chave: Poultry farming; Production performance; Artificial intelligence; Fuzzy logic. |
| Ano: 2019 |
URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0100-69162019000300265 |
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| Lourençoni,Dian; Yanagi Junior,Tadayuki; Yanagi,Silvia de N. M.; Abreu,Paulo G. de; Campos,Alessandro T.. |
| ABSTRACT Broiler chickens are homoeothermic animals, i.e., animals capable of maintaining their body temperature within quite narrow limits; therefore, climate change poses a great challenge to poultry. With this in mind, this research aims to evaluate the performance of broilers submitted to different commercial production systems and exposed to different future scenarios, taking into account the climate change trends. To achieve this objective, we developed and validated a fuzzy model able to predict the performance of a broiler as a function of enthalpy along its life stages. This model was developed and validated in part I of this article based on experimental data collected for one year in three aviaries: conventional, negative pressure, and dark... |
| Tipo: Info:eu-repo/semantics/article |
Palavras-chave: Broiler industry; Artificial intelligence; Climate change; Fuzzy system. |
| Ano: 2019 |
URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0100-69162019000100011 |
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| Abreu,Lucas H. P.; Yanagi Junior,Tadayuki; Campos,Alessandro T.; Lourençoni,Dian; Bahuti,Marcelo. |
| ABSTRACT Broiler chickens submitted to different intensities and durations of thermal stress are subject to variation in cloacal temperature and, consequently, to a decrease in performance. Given the complexity of these interactions, artificial intelligence is a useful methodology for decision-making. Thus, this study aimed to assess and predict, by means of a fuzzy model, the cloacal temperature of broiler chickens submitted to thermal stress in the second week of life, with varying durations and intensities, in climatized wind tunnels. Mamdani's inference and defuzzification methods by means of the center of gravity were used. One hundred and twenty rules were elaborated. The developed... |
| Tipo: Info:eu-repo/semantics/article |
Palavras-chave: Physiological response; Thermal environment; Mathematical modeling; Fuzzy logic. |
| Ano: 2019 |
URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0100-69162019000100018 |
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| Lourençoni,Dian; Yanagi Junior,Tadayuki; Abreu,Paulo G. de; Campos,Alessandro T.; Yanagi,Silvia de N. M.. |
| ABSTRACT Broiler chickens are classified as homoeothermic animals and require a production environment within well-defined thermal comfort intervals. Therefore, the development of algorithms (mathematical models) to control the environment that can be embedded in microcontrollers becomes necessary. Hence, this work aimed to develop a fuzzy model for predicting the productive performance of broiler chickens as a function of the thermal environment during the various breeding phases. The Mamdani inference and defuzzification methods were used, by means of the gravity center, to develop the fuzzy model. Two hundred and forty-three rules with weighting factors of 1.0 each were elaborated. Three commercial warehouses (conventional system, wind tunnel with... |
| Tipo: Info:eu-repo/semantics/article |
Palavras-chave: Poultry farming; Productive performance; Artificial intelligence; Fuzzy logic. |
| Ano: 2019 |
URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0100-69162019000100001 |
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| El Hourany, Roy; Abboud-abi Saab, Marie; Faour, Ghaleb; Mejia, Carlos; Crepon, Michel; Thiria, Sylvie. |
| We present a new method to identify phytoplankton functional types (PFTs) in the Mediterranean Sea from ocean color data (GlobColour data in the present study) and AVHRR sea surface temperature. The principle of the method is constituted by two very fine clustering algorithms, one mapping the relationship between the satellite data and the pigments and the other between the pigments and the PFTs. The clustering algorithms are constituted of two efficient self-organizing maps, which are neural network classifiers. We were able to identify and estimate the percentage of six PFTs: haptophytes, chlorophytes, cryptophytes, Synechococcus, Prochlorococcus, and diatoms. We found that these PFTs present a peculiar variability due to the complex physical and... |
| Tipo: Text |
Palavras-chave: Phytoplankton; Secondary phytoplankton pigments; Self-organizing maps; Classification; Mediterranean Sea; Remote sensing. |
| Ano: 2019 |
URL: https://archimer.ifremer.fr/doc/00589/70145/68135.pdf |
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| Farcy, Patrick; Durand, Dominique; Charria, Guillaume; Painting, Suzanne J.; Tamminem, Timo; Collingridge, Kate; Grémare, Antoine J.; Delauney, Laurent; Puillat, Ingrid. |
| The coastal area is the most productive and dynamic environment of the world ocean, offering significant resources and services for mankind. As exemplified by the UN Sustainable Development Goals, it has a tremendous potential for innovation and growth in blue economy sectors. Due to the inherent complexity of the natural system, the answers to many scientific and societal questions are unknown, and the impacts of the cumulative stresses imposed by anthropogenic pressures (such as pollution) and climate change are difficult to assess and forecast. A major challenge for the scientific community making observations of the coastal marine environment is to integrate observations of Essential Ocean Variables for physical, biogeochemical, and biological... |
| Tipo: Text |
Palavras-chave: European Research Infrastructure; JERICO and JERICO-NEXT; Coastal essential ocean variables; Coastal observatories; High frequency; Physics; Biogeochemistry and biology. |
| Ano: 2019 |
URL: https://archimer.ifremer.fr/doc/00514/62595/66955.pdf |
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| Howell, Kerry L.; Davies, Jaime S.; Allcock, A. Louise; Braga-henriques, Andreia; Buhl-mortensen, Pål; Carreiro-silva, Marina; Dominguez-carrió, Carlos; Durden, Jennifer M.; Foster, Nicola L.; Game, Chloe A.; Hitchin, Becky; Horton, Tammy; Hosking, Brett; Jones, Daniel Ob; Mah, Christopher; Laguionie Marchais, Claire; Menot, Lenaick; Morato, Telmo; Pearman, Tabitha R. R.; Piechaud, Nils; Ross, Rebecca E.; Ruhl, Henry A.; Saeedi, Hanieh; Stefanoudis, Paris V.; Taranto, Gerald H.; Thompson, Michael B.; Taylor, James R.; Tyler, Paul; Vad, Johanne; Victorero, Lissette; Vieira, Rui P.; Woodall, Lucy C.; Xavier, Joana R.; Wagner, Daniel. |
| Video and image data are regularly used in the field of benthic ecology to document biodiversity. However, their use is subject to a number of challenges, principally the identification of taxa within the images without associated physical specimens. The challenge of applying traditional taxonomic keys to the identification of fauna from images has led to the development of personal, group, or institution level reference image catalogues of operational taxonomic units (OTUs) or morphospecies. Lack of standardisation among these reference catalogues has led to problems with observer bias and the inability to combine datasets across studies. In addition, lack of a common reference standard is stifling efforts in the application of |
| Tipo: Text |
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| Ano: 2019 |
URL: https://archimer.ifremer.fr/doc/00602/71408/69862.pdf |
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| Araújo Júnior,Carlos Alberto; Souza,Pábulo Diogo de; Assis,Adriana Leandra de; Cabacinha,Christian Dias; Leite,Helio Garcia; Soares,Carlos Pedro Boechat; Silva,Antonilmar Araújo Lopes da; Castro,Renato Vinícius Oliveira. |
| Abstract: The objective of this work was to compare methods of obtaining the site index for eucalyptus (Eucalyptus spp.) stands, as well as to evaluate their impact on the stability of this index in databases with and without outliers. Three methods were tested, using linear regression, quantile regression, and artificial neural network. Twenty-two permanent plots from a continuous forest inventory were used, measured in trees with ages from 23 to 83 months. The outliers were identified using a boxplot graphic. The artificial neural network showed better results than the linear and quantile regressions, both for dominant height and site index estimates. The stability obtained for the site index classification by the artificial neural network was also... |
| Tipo: Info:eu-repo/semantics/article |
Palavras-chave: Eucalyptus; Artificial intelligence; Dominant height; Forest inventory; Forest modelling; Non-sampling errors. |
| Ano: 2019 |
URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0100-204X2019000103200 |
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| Ferreira, Lucas Borges; Duarte, Anunciene Barbosa; Cunha, Fernando França da; Fernandes Filho, Elpídio Inácio. |
| Estimation of reference evapotranspiration (ETo) is very relevant for water resource management. The Penman-Monteith (PM) equation was proposed by the Food and Agriculture Organization (FAO) as the standard method for estimation of ETo. However, this method requires various weather data, such as air temperature, wind speed, solar radiation and relative humidity, which are often unavailable. Thus, the objective of this study was to compare the performance of multivariate adaptive regression splines (MARS) and alternative equations, in their original and calibrated forms, to estimate daily ETo with limited weather data. Daily data from 2002 to 2016 from 8 Brazilian weather stations were used. ETo was estimated using empirical equations, PM equation with... |
| Tipo: Info:eu-repo/semantics/article |
Palavras-chave: Data driven; Irrigation scheduling; Agrometeorology; Artificial intelligence.; Agrometeorologia. |
| Ano: 2019 |
URL: http://periodicos.uem.br/ojs/index.php/ActaSciAgron/article/view/39880 |
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| Azevedo, Camila Ferreira; Nascimento, Moysés; Fontes, Vitor Cunha; Silva, Fabyano Fonseca e; Resende, Marcos Deon Vilela de; Cruz, Cosme Damião. |
| GenomicLand is free software intended for prediction and genomic association studies based on the R software. This computational tool has an intuitive interface and supports large genomic databases, without requiring the user to use the command line. GenomicLand is available in English, can be downloaded from the Internet (https://licaeufv.wordpress.com/), and requires the Windows or Linux operating system. The software includes statistical procedures based on mixed models, Bayesian inference, dimensionality reduction and artificial intelligence. Examples of data files that can be processed by GenomicLand are available. The examples are useful to learn about the operation of the modules... |
| Tipo: Info:eu-repo/semantics/article |
Palavras-chave: Statistical analysis; Genomic analysis; Molecular markers; Biometrics.. |
| Ano: 2019 |
URL: http://periodicos.uem.br/ojs/index.php/ActaSciAgron/article/view/45361 |
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| Azevedo, Camila Ferreira; Nascimento, Moysés; Fontes, Vitor Cunha; Silva, Fabyano Fonseca e; Resende, Marcos Deon Vilela de; Cruz, Cosme Damião. |
| GenomicLand is free software intended for prediction and genomic association studies based on the R software. This computational tool has an intuitive interface and supports large genomic databases, without requiring the user to use the command line. GenomicLand is available in English, can be downloaded from the Internet (https://licaeufv.wordpress.com/), and requires the Windows or Linux operating system. The software includes statistical procedures based on mixed models, Bayesian inference, dimensionality reduction and artificial intelligence. Examples of data files that can be processed by GenomicLand are available. The examples are useful to learn about the operation of the modules... |
| Tipo: Info:eu-repo/semantics/article |
Palavras-chave: Statistical analysis; Genomic analysis; Molecular markers; Biometrics.. |
| Ano: 2019 |
URL: http://periodicos.uem.br/ojs/index.php/ActaSciAgron/article/view/45361 |
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| Ferreira, Lucas Borges; Duarte, Anunciene Barbosa; Cunha, Fernando França da; Fernandes Filho, Elpídio Inácio. |
| Estimation of reference evapotranspiration (ETo) is very relevant for water resource management. The Penman-Monteith (PM) equation was proposed by the Food and Agriculture Organization (FAO) as the standard method for estimation of ETo. However, this method requires various weather data, such as air temperature, wind speed, solar radiation and relative humidity, which are often unavailable. Thus, the objective of this study was to compare the performance of multivariate adaptive regression splines (MARS) and alternative equations, in their original and calibrated forms, to estimate daily ETo with limited weather data. Daily data from 2002 to 2016 from 8 Brazilian weather stations were used. ETo was estimated using empirical equations, PM equation with... |
| Tipo: Info:eu-repo/semantics/article |
Palavras-chave: 5.01.05.00-0 data driven; Irrigation scheduling; Agrometeorology; Artificial intelligence. Agrometeorologia. |
| Ano: 2019 |
URL: http://periodicos.uem.br/ojs/index.php/ActaSciAgron/article/view/39880 |
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| Abreu,Lucas H. P.; Yanagi Junior,Tadayuki; Bahuti,Marcelo; Hernández-Julio,Yamid F.; Ferraz,Patrícia F. P.. |
| ABSTRACT Due to a number of factors involving the thermal environment of a broiler cutting installation and its interaction with the physiological and productive responses of birds, artificial intelligence has been shown to be an interesting methodology to assist in the decision-making process. For this reason, the main aim of this work was to develop an artificial neural network (ANN) to predict feed conversion (FC), water consumption (Cwater), and cloacal temperature (tclo) of broilers submitted to different air dry-bulb temperatures (24, 27, 30, and 33°C) and durations (1, 2, 3, and 4 days) of thermal stress in the second week of the production cycle. Relative humidity and wind speed... |
| Tipo: Info:eu-repo/semantics/article |
Palavras-chave: Poultry; Thermal stress; Artificial intelligence. |
| Ano: 2020 |
URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0100-69162020000100001 |
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| Abdalla, Saleh; Abdeh Kolahchi, Abdolnabi; Adusumilli, Susheel; Aich Bhowmick, Suchandra; Alou-font, Eva; Amarouche, Laiba; Andersen, Ole Baltazar; Antich, Helena; Aouf, Lotfi; Arbic, Brian; Armitage, Thomas; Arnault, Sabine; Artana, Camila; Aulicino, Giuseppe; Ayoub, Nadia; Badulin, Sergei; Baker, Steven; Banks, Chris; Bao, Lifeng; Barbetta, Silvia; Barceló-llull, Bàrbara; Barlier, François; Basu, Sujit; Bauer-gottwein, Peter; Becker, Matthias; Beckley, Brian; Bellefond, Nicole; Belonenko, Tatyana; Benkiran, Mounir; Benkouider, Touati; Bennartz, Ralf; Benveniste, Jérôme; Bercher, Nicolas; Berge-nguyen, Muriel; Bettencourt, Joao; Blarel, Fabien; Blazquez, Alejandro; Blumstein, Denis; Bonnefond, Pascal; Borde, Franck; Bouffard, Jérôme; Boy, François; Boy, Jean-paul; Brachet, Cédric; Brasseur, Pierre; Braun, Alexander; Brocca, Luca; Brockley, David; Brodeau, Laurent; Brown, Shannon; Bruinsma, Sean; Bulczak, Anna; Buzzard, Sammie; Cahill, Madeleine; Calmant, Stéphane; Calzas, Michel; Camici, Stefania; Cancet, Mathilde; Capdeville, Hugues; Carabajal, Claudia Cristina; Carrere, Loren; Cazenave, Anny; Chassignet, Eric P.; Chauhan, Prakash; Cherchali, Selma; Chereskin, Teresa; Cheymol, Cecile; Ciani, Daniele; Cipollini, Paolo; Cirillo, Francesca; Cosme, Emmanuel; Coss, Steve; Cotroneo, Yuri; Cotton, David; Couhert, Alexandre; Coutin-faye, Sophie; Crétaux, Jean-françois; Cyr, Frederic; D’ovidio, Francesco; Darrozes, José; David, Cedric; Dayoub, Nadim; De Staerke, Danielle; Deng, Xiaoli; Desai, Shailen; Desjonqueres, Jean-damien; Dettmering, Denise; Di Bella, Alessandro; Díaz-barroso, Lara; Dibarboure, Gerald; Dieng, Habib Boubacar; Dinardo, Salvatore; Dobslaw, Henryk; Dodet, Guillaume; Doglioli, Andrea; Domeneghetti, Alessio; Donahue, David; Dong, Shenfu; Donlon, Craig; Dorandeu, Joël; Drezen, Christine; Drinkwater, Mark; Du Penhoat, Yves; Dushaw, Brian; Egido, Alejandro; Erofeeva, Svetlana; Escudier, Philippe; Esselborn, Saskia; Exertier, Pierre; Fablet, Ronan; Falco, Cédric; Farrell, Sinead Louise; Faugere, Yannice; Femenias, Pierre; Fenoglio, Luciana; Fernandes, Joana; Fernández, Juan Gabriel; Ferrage, Pascale; Ferrari, Ramiro; Fichen, Lionel; Filippucci, Paolo; Flampouris, Stylianos; Fleury, Sara; Fornari, Marco; Forsberg, Rene; Frappart, Frédéric; Frery, Marie-laure; Garcia, Pablo; Garcia-mondejar, Albert; Gaudelli, Julia; Gaultier, Lucile; Getirana, Augusto; Gibert, Ferran; Gil, Artur; Gilbert, Lin; Gille, Sarah; Giulicchi, Luisella; Gómez-enri, Jesús; Gómez-navarro, Laura; Gommenginger, Christine; Gourdeau, Lionel; Griffin, David; Groh, Andreas; Guerin, Alexandre; Guerrero, Raul; Guinle, Thierry; Gupta, Praveen; Gutknecht, Benjamin D.; Hamon, Mathieu; Han, Guoqi; Hauser, Danièle; Helm, Veit; Hendricks, Stefan; Hernandez, Fabrice; Hogg, Anna; Horwath, Martin; Idžanović, Martina; Janssen, Peter; Jeansou, Eric; Jia, Yongjun; Jia, Yuanyuan; Jiang, Liguang; Johannessen, Johnny A.; Kamachi, Masafumi; Karimova, Svetlana; Kelly, Kathryn; Kim, Sung Yong; King, Robert; Kittel, Cecile M.m.; Klein, Patrice; Klos, Anna; Knudsen, Per; Koenig, Rolf; Kostianoy, Andrey; Kouraev, Alexei; Kumar, Raj; Labroue, Sylvie; Lago, Loreley Selene; Lambin, Juliette; Lasson, Léa; Laurain, Olivier; Laxenaire, Rémi; Lázaro, Clara; Le Gac, Sophie; Le Sommer, Julien; Le Traon, Pierre-yves; Lebedev, Sergey; Léger, Fabien; Legresy, Benoı̂t; Lemoine, Frank; Lenain, Luc; Leuliette, Eric; Levy, Marina; Lillibridge, John; Liu, Jianqiang; Llovel, William; Lyard, Florent; Macintosh, Claire; Makhoul Varona, Eduard; Manfredi, Cécile; Marin, Frédéric; Mason, Evan; Massari, Christian; Mavrocordatos, Constantin; Maximenko, Nikolai; Mcmillan, Malcolm; Medina, Thierry; Melet, Angelique; Meloni, Marco; Mertikas, Stelios; Metref, Sammy; Meyssignac, Benoit; Michaël, Ablain; Minster, Jean-françois; Moreau, Thomas; Moreira, Daniel; Morel, Yves; Morrow, Rosemary; Moyard, John; Mulet, Sandrine; Naeije, Marc; Nerem, Robert Steven; Ngodock, Hans; Nielsen, Karina; Nilsen, Jan Even Øie; Niño, Fernando; Nogueira Loddo, Carolina; Noûs, Camille; Obligis, Estelle; Otosaka, Inès; Otten, Michiel; Oztunali Ozbahceci, Berguzar; P. Raj, Roshin; Paiva, Rodrigo; Paniagua, Guillermina; Paolo, Fernando; Paris, Adrien; Pascual, Ananda; Passaro, Marcello; Paul, Stephan; Pavelsky, Tamlin; Pearson, Christopher; Penduff, Thierry; Peng, Fukai; Perosanz, Felix; Picot, Nicolas; Piras, Fanny; Poggiali, Valerio; Poirier, Étienne; Ponce De León, Sonia; Prants, Sergey; Prigent, Catherine; Provost, Christine; Pujol, M-isabelle; Qiu, Bo; Quilfen, Yves; Rami, Ali; Raney, R. Keith; Raynal, Matthias; Remy, Elisabeth; Rémy, Frédérique; Restano, Marco; Richardson, Annie; Richardson, Donald; Ricker, Robert; Ricko, Martina; Rinne, Eero; Rose, Stine Kildegaard; Rosmorduc, Vinca; Rudenko, Sergei; Ruiz, Simón; Ryan, Barbara J.; Salaün, Corinne; Sanchez-roman, Antonio; Sandberg Sørensen, Louise; Sandwell, David; Saraceno, Martin; Scagliola, Michele; Schaeffer, Philippe; Scharffenberg, Martin G.; Scharroo, Remko; Schiller, Andreas; Schneider, Raphael; Schwatke, Christian; Scozzari, Andrea; Ser-giacomi, Enrico; Seyler, Frederique; Shah, Rashmi; Sharma, Rashmi; Shaw, Andrew; Shepherd, Andrew; Shriver, Jay; Shum, C.k.; Simons, Wim; Simonsen, Sebatian B.; Slater, Thomas; Smith, Walter; Soares, Saulo; Sokolovskiy, Mikhail; Soudarin, Laurent; Spatar, Ciprian; Speich, Sabrina; Srinivasan, Margaret; Srokosz, Meric; Stanev, Emil; Staneva, Joanna; Steunou, Nathalie; Stroeve, Julienne; Su, Bob; Sulistioadi, Yohanes Budi; Swain, Debadatta; Sylvestre-baron, Annick; Taburet, Nicolas; Tailleux, Rémi; Takayama, Katsumi; Tapley, Byron; Tarpanelli, Angelica; Tavernier, Gilles; Testut, Laurent; Thakur, Praveen K.; Thibaut, Pierre; Thompson, Luanne; Tintoré, Joaquín; Tison, Céline; Tourain, Cédric; Tournadre, Jean; Townsend, Bill; Tran, Ngan; Trilles, Sébastien; Tsamados, Michel; Tseng, Kuo-hsin; Ubelmann, Clément; Uebbing, Bernd; Vergara, Oscar; Verron, Jacques; Vieira, Telmo; Vignudelli, Stefano; Vinogradova Shiffer, Nadya; Visser, Pieter; Vivier, Frederic; Volkov, Denis; Von Schuckmann, Karina; Vuglinskii, Valerii; Vuilleumier, Pierrik; Walter, Blake; Wang, Jida; Wang, Chao; Watson, Christopher; Wilkin, John; Willis, Josh; Wilson, Hilary; Woodworth, Philip; Yang, Kehan; Yao, Fangfang; Zaharia, Raymond; Zakharova, Elena; Zaron, Edward D.; Zhang, Yongsheng; Zhao, Zhongxiang; Zinchenko, Vadim; Zlotnicki, Victor. |
| In 2018 we celebrated 25 years of development of radar altimetry, and the progress achieved by this methodology in the fields of global and coastal oceanography, hydrology, geodesy and cryospheric sciences. Many symbolic major events have celebrated these developments, e.g., in Venice, Italy, the 15th (2006) and 20th (2012) years of progress and more recently, in 2018, in Ponta Delgada, Portugal, 25 Years of Progress in Radar Altimetry. On this latter occasion it was decided to collect contributions of scientists, engineers and managers involved in the worldwide altimetry community to depict the state of altimetry and propose recommendations for the altimetry of the future. This paper summarizes contributions and recommendations that were collected and... |
| Tipo: Text |
Palavras-chave: Satellite altimetry; Oceanography; Sea level; Coastal oceanography; Cryospheric sciences; Hydrology. |
| Ano: 2021 |
URL: https://archimer.ifremer.fr/doc/00688/79999/82978.pdf |
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| Sousa,Ithalo Coelho de; Nascimento,Moysés; Silva,Gabi Nunes; Nascimento,Ana Carolina Campana; Cruz,Cosme Damião; Silva,Fabyano Fonseca e; Almeida,Dênia Pires de; Pestana,Kátia Nogueira; Azevedo,Camila Ferreira; Zambolim,Laércio; Caixeta,Eveline Teixeira. |
| ABSTRACT Genomic selection (GS) emphasizes the simultaneous prediction of the genetic effects of thousands of scattered markers over the genome. Several statistical methodologies have been used in GS for the prediction of genetic merit. In general, such methodologies require certain assumptions about the data, such as the normality of the distribution of phenotypic values. To circumvent the non-normality of phenotypic values, the literature suggests the use of Bayesian Generalized Linear Regression (GBLASSO). Another alternative is the models based on machine learning, represented by methodologies such as Artificial Neural Networks (ANN), Decision Trees (DT) and related possible refinements such as Bagging, Random Forest and Boosting. This study aimed to... |
| Tipo: Info:eu-repo/semantics/article |
Palavras-chave: Hemileia vastatrix; Statistical learning; Plant breeding; Artificial intelligence. |
| Ano: 2021 |
URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0103-90162021000401102 |
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| Brazil leads the way in terms of digitalization in agriculture, and, according to studies conducted by McKinsey, in 2019, the Brazilian agriculturists were, in average, the heaviest users of digital media for their transactions. During the covid-19 pandemic, in 2020, Brazil has grown 10 percentage points, moving from 36% to 46% of agriculturists who use some digital media, surpassing American and European producers who presented a usage rate of 31% and 22%, respectively. The growth of digitalization in agriculture places our country in a distinguished position that can facilitate competitiveness and the future of the agriculture and livestock industry, bringing new tools and approaches to the diversity of Brazilian agriculture and food systems, which have... |
| Tipo: Livros |
Palavras-chave: Agtechs; Agribusiness; Innovation adoption. |
| Ano: 2022 |
URL: http://www.infoteca.cnptia.embrapa.br/infoteca/handle/doc/1143152 |
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| Registros recuperados: 64 | |
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