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ADOPT: a tool for predicting adoption of agricultural innovations AgEcon
Kuehne, Geoff; Llewellyn, Rick S.; Pannell, David J.; Wilkinson, Roger; Dolling, P.; Ewing, Michael A..
A wealth of evidence exists about the adoption of new practices and technologies in agriculture but there does not appear to have been any attempt to simplify this vast body of research knowledge into a model to make quantitative predictions across a broad range of contexts. This is despite increasing demand from research, development and extension agencies for estimates of likely extent of adoption and the likely timeframes for project impacts. This paper reports on the reasoning underpinning the development of ADOPT (Adoption and Diffusion Outcome Prediction Tool). The tool has been designed to: 1) predict an innovation‘s likely peak extent of adoption and likely time for reaching that peak; 2) encourage users to consider the influence of a structured...
Tipo: Conference Paper or Presentation Palavras-chave: Adoption; Diffusion; Prediction; Research and Development/Tech Change/Emerging Technologies.
Ano: 2011 URL: http://purl.umn.edu/100570
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Agrometeorological models for groundnut crop yield forecasting in the Jaboticabal, São Paulo State region, Brazil Agronomy
Moreto, Victor Brunini; Rolim, Glauco de Souza.
Forecast is the act of estimating a future event based on current data. Ten-day period (TDP) meteorological data were used for modeling: mean air temperature, precipitation and water balance components (water deficit (DEF) and surplus (EXC) and soil water storage (SWS)). Meteorological and yield data from 1990-2004 were used for calibration, and 2005-2010 were used for testing. First step was the selection of variables via correlation analysis to determine which TDP and climatic variables have more influence on the crop yield. The selected variables were used to construct models by multiple linear regression, using a stepwise backwards process. Among all analyzed models, the following was notable: Yield = - 4.964 x [SWS of 2° TDP of December of the...
Tipo: Info:eu-repo/semantics/article Palavras-chave: Agrometeorologia 5.01.05.00-0 crop model; Water balance; Prediction; Production. agrometeorologia.
Ano: 2015 URL: http://periodicos.uem.br/ojs/index.php/ActaSciAgron/article/view/19766
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Artificial neural networks compared with Bayesian generalized linear regression for leaf rust resistance prediction in Arabica coffee. Repositório Alice
SILVA, G. N.; NASCIMENTO, M.; SANT'ANNA, I. de C.; CRUZ, C. D.; CAIXETA, E. T.; CARNEIRO, P. C. S.; ROSADO, R. D. S.; PESTANA, K. N.; ALMEIDA, D. P. de; OLIVEIRA, M. da S..
The objective of this work was to evaluate the use of artificial neural networks in comparison with Bayesian generalized linear regression to predict leaf rust resistance in Arabica coffee (Coffea arabica). This study used 245 individuals of a F2 population derived from the self-fertilization of the F1 H511-1 hybrid, resulting from a crossing between the susceptible cultivar Catuaí Amarelo IAC 64 (UFV 2148-57) and the resistant parent Híbrido de Timor (UFV 443-03). The 245 individuals were genotyped with 137 markers. Artificial neural networks and Bayesian generalized linear regression analyses were performed. The artificial neural networks were able to identify four important markers belonging to linkage groups that have been recently mapped, while the...
Tipo: Artigo em periódico indexado (ALICE) Palavras-chave: Inteligência artificial; Predição; Coffea arabica; Hemileia vastatrix; Marcador molecular; Coffea arabica; Hemileia vastatrix; Artificial intelligence; Genetic markers; Prediction.
Ano: 2017 URL: http://www.alice.cnptia.embrapa.br/handle/doc/1069618
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Artificial neural networks compared with Bayesian generalized linear regression for leaf rust resistance prediction in Arabica coffee PAB
Silva,Gabi Nunes; Nascimento,Moysés; Sant’Anna,Isabela de Castro; Cruz,Cosme Damião; Caixeta,Eveline Teixeira; Carneiro,Pedro Crescêncio Souza; Rosado,Renato Domiciano Silva; Pestana,Kátia Nogueira; Almeida,Dênia Pires de; Oliveira,Marciane da Silva.
Abstract: The objective of this work was to evaluate the use of artificial neural networks in comparison with Bayesian generalized linear regression to predict leaf rust resistance in Arabica coffee (Coffea arabica). This study used 245 individuals of a F2 population derived from the self-fertilization of the F1 H511-1 hybrid, resulting from a crossing between the susceptible cultivar Catuaí Amarelo IAC 64 (UFV 2148-57) and the resistant parent Híbrido de Timor (UFV 443-03). The 245 individuals were genotyped with 137 markers. Artificial neural networks and Bayesian generalized linear regression analyses were performed. The artificial neural networks were able to identify four important markers belonging to linkage groups that have been recently mapped,...
Tipo: Info:eu-repo/semantics/article Palavras-chave: Coffea arabica; Hemileia vastatrix; Artificial intelligence; Molecular markers; Prediction.
Ano: 2017 URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0100-204X2017000300186
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Assessing Future Ecosystem Services: a Case Study of the Northern Highlands Lake District, Wisconsin Ecology and Society
Peterson, Garry D; McGill University; garry.peterson@mcgill.ca; Beard Jr., T. Douglas; Wisconsin Department of Natural Resources; BEARDT@dnr.state.wi.us; Beisner, Beatrix E; University of Wisconsin-Madison; bebeisner@facstaff.wisc.edu; Bennett, Elena M; University of Wisconsin-Madison; embennett@wisc.edu; Carpenter, Stephen R; University of Wisconsin-Madison; srcarpen@wisc.edu; Cumming, Graeme; University of Florida; cummingg@wec.ufl.edu; Dent, C. Lisa; University of Wisconsin-Madison; ldent@facstaff.wisc.edu,; Havlicek, Tanya D; University of Wisconsin-Madison; TDHAVLIC@students.wisc.edu.
The Northern Highlands Lake District of Wisconsin is in transition from a sparsely settled region to a more densely populated one. Expected changes offer benefits to northern Wisconsin residents but also threaten to degrade the ecological services they rely on. Because the future of this region is uncertain, it is difficult to make decisions that will avoid potential risks and take advantage of potential opportunities. We adopt a scenario planning approach to cope with this problem of prediction. We use an ecological assessment framework developed by the Millennium Ecosystem Assessment to determine key social and ecological driving forces in the Northern Highlands Lake District. From these, we describe three alternative scenarios to the year 2025 in which...
Tipo: Peer-Reviewed Reports Palavras-chave: Northern Highlands Lake District; Wisconsin; Assessment; Ecosystem services; Freshwater; Futures; Prediction; Scenario planning.
Ano: 2003
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Body Height and Its Estimation Utilizing Arm Span Measurements in Serbian Adults International Journal of Morphology
Popovic,Stevo; Bjelica,Dusko; Molnar,Slavko; Jaksic,Damjan; Akpinar,Selcuk.
Anthropologists recognized the tallness of nations in the Dinaric Alps long time ago. As the modern Serbians fall more into the Dinaric racial classification than any other does, the purpose of this study was to examine the body height in Serbian adults as well as the relationship between arm span as an alternative to estimating the body height, which vary in different ethnic and racial groups. The nature and scope of this study analyzes 394 students (318 men, aged 20.13±1.47 and 76 women, aged 19.59±1.46) from the University of Novi Sad to be subjects. The anthropometric measurements were taken according to the protocol of the ISAK. Means and standard deviations were obtained. A comparison of means of body heights and arm spans within each gender group...
Tipo: Journal article Palavras-chave: Prediction; Standing height; Stature; Armspan; Serbia.
Ano: 2013 URL: http://www.scielo.cl/scielo.php?script=sci_arttext&pid=S0717-95022013000100043
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Changing business environment: implications for farming AgEcon
Malcolm, Bill.
The natural, technological, economic, political and social environment in which farmers farm constantly changes. History has lessons about change in agriculture and about farmers coping with change, though the future is unknowable and thus always surprising. The implication for farm operation is to prepare, do not predict.
Tipo: Article Palavras-chave: Preparation; Prediction; Farm management; Uncertainty; Farm Management.
Ano: 2012 URL: http://purl.umn.edu/122904
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Climate warming and sea level rise. OceanDocs
Yue, Jun; Dong, Yue; Wu, Sangyun; Geng, Xiushan; Zhao, Changrong.
Based on a large number of actual data, the author believe that the modern global warming and sea level rise resulted from climate warming after the cold front of the Little Ice Age about 200 years ago and the developmnet of the sea level rise phase. In the past 30 years, the rate of sea level rise was increasing, which is under the background of the average temperature uplift 0.2F°(0.11 °C)every 10 years in succession from the 1980s to the past 10 years this century. On the basis of the absolute and relative sea-level rise rate that was calculated from the tidal data during the same period at home and abroad in the last 30 years, in accordance with the resolutions of the 2010 climate conference in Cancun, at the same time, considering the previous...
Tipo: Journal Contribution Palavras-chave: Global warming; Sea level variations; Prediction; Evaluation.
Ano: 2012 URL: http://hdl.handle.net/1834/5832
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Comparing the artificial neural network with parcial least squares for prediction of soil organic carbon and pH at different moisture content levels using visible and near-infrared spectroscopy Rev. Bras. Ciênc. Solo
Tekin,Yücel; Tümsavas,Zeynal; Mouazen,Abdul Mounem.
Visible and near infrared (vis-NIR) spectroscopy is widely used to detect soil properties. The objective of this study is to evaluate the combined effect of moisture content (MC) and the modeling algorithm on prediction of soil organic carbon (SOC) and pH. Partial least squares (PLS) and the Artificial neural network (ANN) for modeling of SOC and pH at different MC levels were compared in terms of efficiency in prediction of regression. A total of 270 soil samples were used. Before spectral measurement, dry soil samples were weighed to determine the amount of water to be added by weight to achieve the specified gravimetric MC levels of 5, 10, 15, 20, and 25 %. A fiber-optic vis-NIR spectrophotometer (350-2500 nm) was used to measure spectra of soil samples...
Tipo: Info:eu-repo/semantics/other Palavras-chave: Modeling; Prediction; Vis-NIR.
Ano: 2014 URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0100-06832014000600014
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Comparison of Regression and Neural Networks Models to Estimate Solar Radiation Chilean J. Agric. Res.
Bocco,Mónica; Willington,Enrique; Arias,Mónica.
The incident solar radiation on soil is an important variable used in agricultural applications; it is also relevant in hydrology, meteorology and soil physics, among others. To estimate this variable, empirical models have been developed using several parameters and, recently, prognostic and prediction models based on artificial intelligence techniques such as neural networks. The aim of this work was to develop linear models and neural networks, multilayer perceptron, to estimate daily global solar radiation and compare their efficiency in its application to a region of the Province of Salta, Argentina. Relative sunshine duration, maximum and minimum temperature, rainfall, binary rainfall and extraterrestrial solar radiation data for the period...
Tipo: Journal article Palavras-chave: Modeling; Prediction; Linear regression; Multilayer perceptron.
Ano: 2010 URL: http://www.scielo.cl/scielo.php?script=sci_arttext&pid=S0718-58392010000300010
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Determining the pathogenicity of CFTR missense variants: Multiple comparisons of in silico predictors and variant annotation databases Genet. Mol. Biol.
Michels,Marcus; Matte,Ursula; Fraga,Lucas Rosa; Mancuso,Aline Castello Branco; Ligabue-Braun,Rodrigo; Berneira,Elias Figueroa Rodrigues; Siebert,Marina; Sanseverino,Maria Teresa Vieira.
Abstract Pathogenic variants in the Cystic Fibrosis Transmembrane Conductance Regulator gene (CFTR) are responsible for cystic fibrosis (CF), the commonest monogenic autosomal recessive disease, and CFTR-related disorders in infants and youth. Diagnosis of such diseases relies on clinical, functional, and molecular studies. To date, over 2,000 variants have been described on CFTR (~40% missense). Since few of them have confirmed pathogenicity, in silico analysis could help molecular diagnosis and genetic counseling. Here, the pathogenicity of 779 CFTR missense variants was predicted by consensus predictor PredictSNP and compared to annotations on CFTR2 and ClinVar. Sensitivity and specificity analysis was divided into modeling and validation phases using...
Tipo: Info:eu-repo/semantics/article Palavras-chave: CFTR; Missense variant; Prediction; Bioinformatics; Cystic fibrosis.
Ano: 2019 URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S1415-47572019000400560
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Development and evaluation of neural network models to estimate daily solar radiation at Córdoba, Argentina. Repositório Alice
BOCCO, M.; OVANDO, G.; SAYAGO, S..
The objective of this work was to develop neural network models of backpropagation type to estimate solar radiation based on extraterrestrial radiation data, daily temperature range, precipitation, cloudiness and relative sunshine duration. Data from Córdoba, Argentina, were used for development and validation. The behaviour and adjustment between values observed and estimates obtained by neural networks for different combinations of input were assessed. These estimations showed root mean square error between 3.15 and 3.88 MJ m-2 d-1. The latter corresponds to the model that calculates radiation using only precipitation and daily temperature range. In all models, results show good adjustment to seasonal solar radiation. These results allow inferring the...
Tipo: Artigo em periódico indexado (ALICE) Palavras-chave: Modelling; Prediction; Backpropagation neural networks; Modelagem; Predição; Redes neurais de retropropagação.
Ano: 2006 URL: http://www.alice.cnptia.embrapa.br/handle/doc/118193
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Development and evaluation of neural network models to estimate daily solar radiation at Córdoba, Argentina PAB
Bocco,Mónica; Ovando,Gustavo; Sayago,Silvina.
The objective of this work was to develop neural network models of backpropagation type to estimate solar radiation based on extraterrestrial radiation data, daily temperature range, precipitation, cloudiness and relative sunshine duration. Data from Córdoba, Argentina, were used for development and validation. The behaviour and adjustment between values observed and estimates obtained by neural networks for different combinations of input were assessed. These estimations showed root mean square error between 3.15 and 3.88 MJ m-2 d-1 . The latter corresponds to the model that calculates radiation using only precipitation and daily temperature range. In all models, results show good adjustment to seasonal solar radiation. These results allow inferring the...
Tipo: Info:eu-repo/semantics/article Palavras-chave: Modelling; Prediction; Backpropagation neural networks.
Ano: 2006 URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0100-204X2006000200001
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Development and evaluation of prediction equations for methane emission from Nellore cattle Dry matter intake (DMI Animal Sciences
Sobrinho, Tatiana Lucila Pires; Branco, Renata Helena; Magnani, Elaine; Berndt, Alexandre; Canesin, Roberta Carrilho; Mercadante, Maria Eugênia Zerlotti.
  
Tipo: Info:eu-repo/semantics/article Palavras-chave: Beef cattle; Dry matter intake; Greenhouse gas; Prediction; Sulfur hexafluoride..
Ano: 2018 URL: http://periodicos.uem.br/ojs/index.php/ActaSciAnimSci/article/view/42559
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Espacialização de espécies florestais por classe diamétrica usando máxima entropia no sudoeste da Amazônia. Repositório Alice
FIGUEIREDO, S. M. de M.; FIGUEIREDO, E. O..
O objetivo do estudo foi analisar a predição da distribuição de espécies florestais madeireiras, em escala local, utilizando dados de ocorrência agrupados por classe diamétrica. Para estimar a distribuição foi utilizado o método de máxima entropia (Maxent) e as ocorrências são de inventário florestal de planos de manejo. Foram selecionadas seis variáveis preditoras, por espécie, pelo método de todas as regressões possíveis. Os modelos tiveram em média bom desempenho (AUC = 0,7; taxa de omissão = 8,8%), demonstrando a viabilidade de se predizer a distribuição de espécies por classe diamétrica. De acordo com os modelos, Astonium lecointei, Clarisia racemosa e Ceiba pentandra com diâmetro a altura do peito (DAP) ≥ 100 cm têm maior probabilidade de...
Tipo: Artigo em anais de congresso (ALICE) Palavras-chave: Árboles forestales; Inventario forestal; Biodiversidad; Prácticas de conservación; Manejo florestal; Manejo forestal; Sistemas de información geográfica; Teledetección; Método da Máxima Entropia (Maxent); Maximum Entropy Method (Maxent); Modeflora; Predição; Predicción; Embrapa Acre; Instituto de Meio Ambiente do Acre; Acre; Amazônia Ocidental; Western Amazon; Amazonia Occidental; Árvore Florestal; Diâmetro; Biogeografia; Inventário Florestal; Biodiversidade; Conservação; Administração Florestal; Sistema de Informação Geográfica; Sensoriamento Remoto; Dendrometria; Forest trees; Biogeography; Forest inventory; Biodiversity; Conservation practices; Forest management; Geographic information systems; Remote sensing; Forest mensuration; Prediction.
Ano: 2019 URL: http://www.alice.cnptia.embrapa.br/alice/handle/doc/1110086
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Estimation of 90Sr and 137Cs transfer from the Black Sea to the Mediterranean Basin after the Chernobyl NPP accident IBSS Repository
Egorov, V. N.; Polikarpov, G. G.; Stokozov, N. A.; Mirzoyeva, N. Yu..
The 90Sr and 137Cs inputs from the Black Sea to the Mediterranean Basin through the Bosporus Strait after the Chernobyl NPP accident were estimated. It is obtained that the 90Sr and 137Cs fluxes from the Black Sea to the Sea of Marmara are decreased with an effective exponential half-lives (T05) 9.5 years and 6.4 years, respectively. The estimations have shown that 110 TBq 90Sr and 250 TBq 137Cs in 1986-2000 was delivered from the Black Sea to the Mediterranean Basin after the Chernobyl NPP accident. The radioactive pollution of the Mediterranean Basin will continue for 5 half-lives, i.e. 47 years for 90Sr and 32 years for 137Cs. The total 90Sr and l37Cs inputs from the Black Sea into the Mediterranean Basin have been assessed as 168 TBq and 311 TBq,...
Tipo: Journal Contribution Palavras-chave: Сhernobyl NPP accident; 90Sr and 137Cs fluxes; Prediction; The Bosporus currents; Black Sea; Mediterranean Basin; Авария на Чернобыльской АЭС; Потоки 90Sr и 137Cs; Прогноз; Босфорское течение; Черное море; Средиземноморский бассейн Prediction Prediction http://aims.fao.org/aos/agrovoc/c_29367.
Ano: 2005 URL: http://repository.ibss.org.ua/dspace/handle/99011/243
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Estimation of light lamb carcass composition by in vivo real-time ultrasonography at four anatomical locations IPB - Escola Superior Agrária
Ripoll, G.; Joy, M.; Álvarez-Rodríguez, J.; Sanz, B.; Teixeira, A..
The objectives of this study were to study the relationship between in vivo ultrasound measurements and cold carcass measurements at 4 anatomical points of the backbone, and to establish regression equations to estimate carcass composition within the cold carcass weight range for Ternasco lambs (8 to 12.5 kg) by using ultrasonic measurements taken at a single location. Measurements of subcutaneous fat and skin thickness and of muscle depth and width were taken over the 10th to 11th and 12th to 13th thoracic vertebrae and the 1st to 2nd and 3rd to 4th lumbar vertebrae. These measurements were taken at 2 and 4 cm from the nearest end of the LM to the backbone and at 1/3 of the LM width with the probe perpendicular to and parallel to the backbone. The left...
Tipo: Article Palavras-chave: Carcass composition; Fat thickness; Muscle depth; Prediction; Regression; Ultrasound.
Ano: 2009 URL: http://hdl.handle.net/10198/4907
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Hazard warning: model misuse ahead ArchiMer
Dickey-collas, Mark; Payne, Mark R.; Trenkel, Verena M.; Nash, Richard D. M..
The use of modelling approaches in marine science, and in particular fisheries science, is explored. We highlight that the choice of model used for an analysis should account for the question being posed or the context of the management problem. We examine a model-classification scheme based on Richard Levins' 1966 work suggesting that models can only achieve two of three desirable model attributes: realism, precision, and generality. Model creation, therefore, requires trading-off of one of these attributes in favour of the other two: however, this is often in conflict with the desires of end-users (i.e. mangers or policy developers). The combination of attributes leads to models that are considered to have empirical, mechanistic, or analytical...
Tipo: Text Palavras-chave: Climate; Fisheries; GAM; Management; Prediction; Projection; Recruitment; Time-series analysis.
Ano: 2014 URL: http://archimer.ifremer.fr/doc/00222/33371/32179.pdf
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Homology modeling and epitope prediction of Der f 33 BJMBR
Teng,Feixiang; Sun,Jinxia; Yu,Lili; Li,Qisong; Cui,Yubao.
Dermatophagoides farinae (Der f), one of the main species of house dust mites, produces more than 30 allergens. A recently identified allergen belonging to the alpha-tubulin protein family, Der f 33, has not been characterized in detail. In this study, we used bioinformatics tools to construct the secondary and tertiary structures and predict the B and T cell epitopes of Der f 33. First, protein attribution, protein patterns, and physicochemical properties were predicted. Then, a reasonable tertiary structure was constructed by homology modeling. In addition, six B cell epitopes (amino acid positions 34–45, 63–67, 103–108, 224–230, 308–316, and 365–377) and four T cell epitopes (positions 178–186, 241–249, 335–343, and 402–410) were predicted. These...
Tipo: Info:eu-repo/semantics/article Palavras-chave: Der f 33; Homology modeling; B-cell epitope; T-cell epitope; Prediction.
Ano: 2018 URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0100-879X2018000500601
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Identifying agriculture land acquisitions for alleviating future food security concerns Ciênc. Tecnol. Aliment.
ABDULLAH,Ahsan.
Abstract The total available land for food, fuel, or forests is finite, while land demand is increasing and expected to increase further in the coming decades; resulting in deterioration of food security. Therefore, the corporate world adopted a solution of acquiring international agricultural land. Consequently, the global demand for land has progressively risen, but the question requiring decision support is - which lands to acquire for food production to ensure future food security? Food Science and Technology has vital pivotal roles to play in improving this situation, as food science is inherently multidisciplinary and motivated by the use of new technologies. In this paper, we endeavour to address this multidisciplinary food science question, by...
Tipo: Info:eu-repo/semantics/article Palavras-chave: Food science; Prediction; Food security; Decision support; Middle East North Africa.
Ano: 2019 URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0101-20612019000200301
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