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[en] ON ADDRESSING IRREGULARITIES IN ELECTRICITY LOAD TIME-SERIES AND SHORT TERM LOAD FORECASTING / [es] UN SISTEMA INTEGRADO DE MONITORAMIENTO Y PREVISIÓN DE CARGA ELÉCTRICA A CORTO PLAZO / [pt] UM SISTEMA INTEGRADO DE MONITORAÇÃO E PREVISÃO DE CARGA ELÉTRICA DE CURTO PRAZOHELIO FRANCISCO DA SILVA 19 July 2001 (has links)
[pt] As alterações na legislação do Setor de Energia Elétrica
Brasileiro em fins do milênio passado, provocou profundas
mudanças no planejamento da Operação do Sistema e na
Comercialização de energia elétrica no Brasil.
O desmembramento das atividades de geração, de transmissão
e de distribuição de energia elétrica criou novas
características no comportamento dos Agentes
Concessionários e as previsões de demanda por energia
elétrica, que sempre foram ferramenta importante, por
exemplo, na programação da operação, passaram a ser
indispensáveis também, na comercialização de energia
elétrica no mercado livre.
Neste novo cenário, a obtenção e o armazenamento de dados
confiáveis passou a ser parte integrante do patrimônio das
Empresas e um sistema eficiente de previsões de
carga passou a ser um diferencial na mesa de negociações.
Os Agentes concessionários e o Operador Nacional do Sistema
Elétrico vêm fazendo investimentos para aperfeiçoar os seus
sistemas de aquisição de dados, entretanto em
sistemas de multipontos algumas falhas imprevistas durante
a sincronização da telemedição podem ocorrer, provocando
defeitos nas séries.
Nas séries de minuto em minuto, por exemplo, uma falha de
algumas horas acarreta centenas de registros defeituosos e
as principais publicações a respeito de modelagens de
séries temporais para tratamento de dados não abordam as
dificuldades encontradas diante de grandes falhas
consecutivas nos dados. / [en] As a result of the continuing privatization process within
the energy sector,electricity load forecasting is a ritical
tool for decision-making in the Industry.
Reliable forecasts are now needed not only for developing
strategies for business planning and short term operational
scheduling, but also to define the spot market
electricity price. The forecasting process is data-ntensive
and interest has been driven to shorter and shorter
intervals. Large investments are being made in modernizing
and improving metering systems, so as to make more data
available to the forecaster. However, the forecaster is
still faced with irregular time-series.
Gaps, missing values, spurious information or repeated
values in the time-series can result from transmission
errors or small failures in the recording process. These so-
called irregularities have led to research that focused on
either iterative processes,like the Kalman filter and the
EM algorithm, or applications of the statistical literature
on treatment of missing values and outliers. Nevertheless,
these methods often result in large forecast errors when
confronted with consecutive failures in the data.
On the other hand, the minute to minute series have a large
amount of points and so the one day ahead forecast horizont
becomes very large to handling with the conventional
methods. In this context, we propose an alternative to
detect and replace values and present a methodology to
perform the forecasting process by using of other
information in the time-series that relate to the
variability and seasonality, which are commonly encountered
in electricity load-forecasting data.
We illustrate the method and address the problem as part of
a wider project that aims at the development of an
automatic on line system for tracking the Brazilian
Interlinked Electric Network Operation and performing short
term load forecasting.
The data were collected by ONS / ELETROBRAS - Brazil. We
concentrate on 10 minutes data for the years 1997-1999 of
Light Serviços de Eletricidade S.A. (Rio de Janeiro and its
surroundings). / [es] Las alteraciones en la legislación del Sector de Energía
Elétrica Brasilero a finales del milenio pasado, provocó
profundos cambios en el planificación de la Operación del
Sistema y en la Comercialización de energía eléctrica en
Brasil. La desarticulación de las actividades de
generación, de transmisión y de distribuición de energía
eléctrica creó nuevas características en el comportamiento
de los Agentes Concesionarios. Así, las previsiones de
demanda por energía eléctrica, que siempre fueron una
herramienta importante, por ejemplo, en la programación de
la operación, pasaron a ser indispensables también en la
comercialización de energía eléctrica en el mercado libre.
En este nuevo escenario, la obtención y almacenamiento de
datos confiables pasó a ser parte integrante del patrimonio
de las Empresas y un sistema eficiente de previsiones de
carga constituye un diferencial en la mesa de
negociaciones. Los Agentes concesionarios y el Operador
Nacional del Sistema Eléctrico han invertido en el
perfeccionamiento de sus sistemas de adquisición de datos.
Sin embargo, en sistemas de multipuntos algunas fallas
imprevistas durante la sincronización de la telemedición
pueden ocurrir, provocando defectos en las series. En las
series de minuto en minuto, por ejemplo, una falla de
algunas horas trae consigo centenas de registros
defectuosos y las principales publicaciones sobre modelos
de series temporales para tratamiento de datos no abordan
las dificuldades encontradas frente a grandes fallas
consecutivas en los datos.
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Contribution à l’évaluation et à l’amélioration multicritères en contexte incertain : application à la conception préliminaire / Contribution to multi-criteria assessment and improvement in uncertain context : Application to preliminary designSow, Diadié 18 December 2017 (has links)
Dans un environnement fortement concurrentiel, les industriels doivent constamment améliorer leurs produits pour rester compétitifs et satisfaire au mieux leurs clients tout en minimisant les coûts et la prise de risques en conception. En phase préliminaire de conception ou de (re-)engineering, prédire les performances de nouveaux produits est une tâche difficile. En effet, l’impact des changements opérés sur les caractéristiques du produit relativement aux performances de celui-ci ne peut être estimé que de façon imprécise. Décideurs et concepteurs doivent pourtant identifier les performances à améliorer en limitant les efforts d’ingénierie déployés pour des améliorations innovantes. Bien que plusieurs indicateurs de plus-value aient été proposés par la communauté de la décision multicritère pour évaluer a priori l’amélioration que confère un changement de configuration à un produit, ils semblent néanmoins reposer sur des hypothèses de réalisabilité des gains de performance peu réalistes dans le contexte manufacturier.Sur la base de techniques d’analyse multicritère et de théorie des possibilités, cette thèse propose une extension de ces indices de plus-values lorsque la vraisemblance des améliorations espérées ne peut être évaluée de façon précise comme c’est le cas en phase de conception préliminaire. Cette connaissance imparfaite des relations entre les actions d’amélioration et les performances espérées rend la question « comment se fixer des objectifs ambitieux lorsque l’on conçoit ou améliore un produit tout en faisant en sorte que ces objectifs restent à la portée du manufacturier ? » d’autant plus complexe. Ainsi, les améliorations qu’il faut planifier doivent à la fois avoir un impact significatif sur la performance du produit et correspondre à des compétences maîtrisées par le manufacturier. Plusieurs approches de la littérature se sont intéressées à ces deux aspects de l’amélioration, mais peu d’entre elles les considèrent conjointement. Nous proposons dans cette thèse plusieurs approches qualitatives et possibilistes qui concilient les deux points de vue à travers des problèmes d’optimisation multi-attributs. La notion d’interaction entre deux dimensions de la performance y est centrale. Un exemple relatif à la conception d’un robot autonome est proposé pour illustrer chacune de nos propositions. Cette étude de cas est issue du challenge Robafis qui est organisé annuellement par l’Association Française d’ingénierie Système (AFIS) pour promouvoir l’ingénierie système dans les écoles d’ingénieurs. / In a highly competitive and unstable environment, manufacturers must constantly improve their products to remain competitive and satisfy their customers while minimizing incurred costs and risk taking at the design stage. At the early stages of (re-)engineering, performances forecasting of new product is complicated. Indeed, the impacts of any characteristic change on the product performance are not precisely known. Decision makers must thus identify the performances to be improved while limiting the engineering efforts spent on innovative upgrades. Although some theoretical worth indexes have been proposed in the multiple criteria decision-making literature to estimate the expectable gains when improving changes are planned, they generally rely on non-realistic assumptions on the achievability of the expected improvements that cannot hold in manufacturing contexts. Based on multi-criteria decision analysis techniques and uncertainty theory, this thesis proposes an extension of the worth index concept when the likelihood of the expected improvements is not precisely known as it is the case at the preliminary stages of design activities. This poor knowledge of the relationships between improvement actions and expected performances makes the issue “how to set ambitious targets when improving or designing product while these targets remain within the reach of the manufacturer” all the thornier. Thus, improvements to be focused on are those which both have a significant positive impact on product performance and correspond to operational changes properly under control by the manufacturer. While some approaches in the literature have already addressed each of the two aspects of the improvement problem, few deal with both of them at the same time. We investigate several qualitative and possibilistic approaches that conciliate both points of view as multi attributes optimization problems. The notion of interaction between any two objectives to be simultaneously satisfied is central in our framework. An illustrative example related to the design phase of autonomous robot is provided. This case study is issued from the robotic challenge Robafis that is organized annually by the French association of Systems Engineering AFIS to promote Systems Engineering practice in engineers’ schools.
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Mapeamento das áreas de risco e impactos potenciais das mudanças climáticas globais para ocorrência da ferrugem do eucaliptoMorais, Willian Bucker 30 July 2009 (has links)
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Previous issue date: 2009-07-30 / The Rust, caused by the fungus Puccinia psidii Winter, is one of the most important diseases to the eucalypt host. The pathogen causes the disease in clonal minigarden and in young plants in the field, mostly in leaves and in young shoots. The favorable climatic conditions to infection of these pathogen in eucalypt include temperature between 18 to 25 ºC, with periods of at least 6 hours of leaf wetness for 5 to 7 days. Considering the interaction between environment and pathogen, the present study has as objective : (a) to map risk areas for the establishment of eucalyptus rust by exploiting the principle of space-time escape and (b) evaluate the potential impacts of global climate change on the spatial distribution of areas of risk for the occurrence of eucalyptus rust. (a) For the mapping of risk areas, it was calculated the rate of infection from the average daily maximum temperature and leaf wetness, and from this generated the risk index. The data used were obtained from the meteorological database, of the Regional Aracruz and São Mateus (Espírito Santo) and Regional Teixeira de Freitas (Bahia) for the years 2001 to 2006, a total of 23 weather stations. Based on the value of the index of occurrence risk of the eucalyptus rust, were prepared maps of spatial and temporal distribution of the disease, for which it was observed that the risk index varied according to the studied area and months of the year. The months from May to November were more favorable for the occurrence of eucalyptus rust. Thus, the results obtained in this study allowed the working principle of space-time escape, making it possible to schedule the harvest season, driving regrowth and planting of clones according to the level of resistance to disease. (b) To study the potential impacts of global climate change on the distribution of eucalypt rust, were prepared monthly maps of risk areas for the occurrence of disease, considering the current climatic conditions, based on a historical series from 1961 to 1990 and future scenarios A2 and B2, for the decades 2020, 2050 and 2080 provided by the Intergovermental Panel on Climate Change (IPCC). The weather conditions were classified into three categories, according to the potential risk of disease occurrence, considering the temperature (T) and relative humidity (RH): ): i) high risk (18 ≤ T ≤ 25 ºC and UR ≥ 90%); ii) medium risk (T  18 ou T > 25 ºC e UR 90%; T < 18 ou T  25 ºC e UR ≥ 90%); and iii) low risk (T 18 ou T > 25 ºC e UR
90%). Data about the future climate scenarios were provided by the GCM Change Fields. It was used in this work the simulation model Hadley Center for Climate Prediction and Research (HadCM3) using the Idrisi 32. Based on the results obtained observed that there will be reduction in the area favorable for the occurrence of eucalyptus rust, and this reduction will be gradual for the decades of 2020, 2050 and 2080 being more pronounced in scenario A2 than in B2. However, it is important to note that large areas still remain favorable for disease development, especially in the colder months of the year, in other words, from May to July. Thus, the knowledge generated in this work, coupled with the development of predictive models of the disease, can be important tools in the integrated management of eucalyptus rust / A ferrugem, causada pelo fungo Puccinia psidii Winter, é um das doenças mais importantes para a eucaliptocultura. O patógeno causa doença em minijardim clonal e em plantas novas no campo, principalmente em folhas e em brotações jovens. As condições climáticas favoráveis para infecção deste patógeno em eucalipto incluem temperatura entre 18 a 25 °C, com períodos de pelo menos 6 horas de molhamento foliar, por 5 a 7 dias consecutivos. Considerando a interação entre ambiente e patógeno, o presente trabalho teve como objetivos: (a) mapear áreas de risco ao estabelecimento da ferrugem do eucalipto explorando o princípio de escape espaço-temporal; e (b) avaliar os potenciais impactos das mudanças climáticas globais sobre a distribuição espacial das áreas de risco para ocorrência da ferrugem do eucalipto. (a) Para o mapeamento das áreas de risco, foi calculado o índice de infecção, a partir da média diária da temperatura máxima e do período de molhamento foliar, sendo a partir deste gerado o índice de risco. Os dados utilizados foram obtidos do banco de dados meteorológicos, das Regionais Aracruz e São Mateus (Espírito Santo) e da Regional Teixeira de Freitas (Bahia), referentes aos anos de 2001 a 2006, totalizando 23 estações meteorológicas. Com base no valor do índice de risco de ocorrência da ferrugem do eucalipto, elaboraram-se mapas de distribuição espaço-temporal da doença, pelos quais foi possível observar que o índice de risco variou em função da área estudada e dos meses do ano. Os meses de maio a novembro apresentaram maior favorabilidade para ocorrência da ferrugem do eucalipto. Sendo assim, os resultados obtidos nesse estudo permitiram trabalhar o princípio de escape espaço-temporal, tornando possível a programação da época de colheita, condução de rebrota e plantio de clones de acordo com o nível de resistência à doença. (b) Para o estudo dos impactos potenciais das mudanças climáticas globais sobre a distribuição da ferrugem do eucalipto, elaboraram-se mapas mensais das áreas de risco para ocorrência da doença, considerando as condições climáticas atuais, com base em uma série histórica de 1961 a 1990 e os cenários futuros A2 e B2, para as décadas de 2020, 2050 e 2080 disponibilizados pelo Intergovermental Panel on Climate Change (IPCC). As condições climáticas foram classificadas em três categorias, de acordo com o risco potencial de ocorrência da doença, considerando a temperatura (T) e umidade relativa do ar (UR): i) alto risco (18 ≤ T ≤ 25 ºC e UR ≥ 90%); ii) médio risco (T  18 ou T > 25 ºC e UR 90%; T < 18 ou T  25 ºC e UR ≥ 90%); e iii) baixo risco (T 18 ou T > 25 ºC e UR 90%). Os dados sobre os cenários climáticos futuros foram fornecidos pelo GCM Change Fields. Empregou-se neste trabalho o modelo de simulação Hadley Centre for Climate Prediction and Research (HadCm3), utilizando o software Idrisi 32. Com base nos resultados obtidos observou-se que haverá redução da área favorável para ocorrência da ferrugem do eucalipto, sendo que esta redução será gradativa para as décadas de 2020, 2050 e 2080, sendo mais acentuada no cenário A2 que no B2. Entretanto, é importante ressaltar que extensas áreas ainda continuarão favoráveis ao desenvolvimento da doença, principalmente nos meses mais frios do ano, ou seja, maio a julho. Desta forma, os conhecimentos gerados neste trabalho, aliados com o desenvolvimento de modelos de previsão da doença, podem constituir ferramentas importantes no manejo integrado da ferrugem do eucalipto
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Análise da situação financeira da Cooperativa Agroindustrial Lar em relação a 31 cooperativas agropecuárias do estado do Paraná: uma análise aplicando um modelo de previsão de insolvência / Analysis of the financial situation of the Lar Agro-Industrial Cooperative compared to 31 agricultural cooperatives from the state of Paraná: an analysis applying an insolvency prevision modelVieira, Daliana Carla 09 March 2007 (has links)
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Previous issue date: 2007-03-09 / The aim of this dissertation was to accomplish an analysis of the financial situation of the Lar Agro-Industrial Cooperative compared to 31 cooperatives from the State of Paraná, through an insolvency prevision model, from the year 2000 to 2004. Thus, some financial indexes of the cooperatives studied were examined in accordance to the standard indexes. The Gimenes and Opazo (2001) insolvency prevision model was used to verify the financial solvency or insolvency situation of the cooperatives. Then the similarity among the group of agricultural cooperatives was analyzed through Cluster Analysis. The results lead to a general conclusion that, in the period analyzed, Lar Agro-Industrial Cooperative presented a highly satisfactory performance, a particular characteristic of this cooperative, due to the fact that high similarities between Lar cooperative and other cooperatives were not verified / O objetivo deste trabalho foi realizar uma análise da situação financeira da Cooperativa Agroindustrial Lar em relação a 31 cooperativas do Estado do Paraná, através de um modelo de previsão de insolvência, no período de 2000 a 2004. Para tanto, examinaram-se alguns indicadores financeiros das cooperativas em estudo a partir da classificação segundo os índices-padrão. Para verificar a situação de solvência ou insolvência financeira das cooperativas foi utilizado o modelo de previsão de insolvência de Gimenes e Opazo (2001). Finalmente, foi analisada a similaridade entre o conjunto das cooperativas agropecuárias por meio da análise multivariada de agrupamento ou Cluster Analysis. Os resultados obtidos permitem concluir, de uma forma geral, que, no período analisado, a Cooperativa Agroindustrial Lar apresentou um desempenho financeiro bastante satisfatório, característica muito particular desta cooperativa, já que não se verificou alta similaridade entre a cooperativa Lar e as demais cooperativas
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[en] VERY SHORT TERM LOAD FORECASTING IN THE NEW BRAZILIAN ELECTRICAL SCENARIO / [es] PREVISIÓN DE CARGA A CORTÍSIMO PLAZO EN EL NUEVO ESCENARIO ELÉCTRICO BRASILERO / [pt] PREVISÃO DE CARGA DE CURTÍSSIMO PRAZO NO NOVO CENÁRIO ELÉTRICO BRASILEIROGUILHERME MARTINS RIZZO 19 July 2001 (has links)
[pt] Nesta dissertação é proposto um modelo híbrido para
previsão de carga de curtíssimo prazo, combinando
amortecimento exponencial simples e redes neurais
artificiais do topo feed-forward. O modelo fornece
previsões pontuais e limites superiores e inferiores para um
horizonte de quinze dias. Estes limites formam um intervalo
ao qual pode ser associado um nível de confiança empírico,
estimado através de um teste fora da amostra. O desempenho
do modelo é avaliado ao longo de uma simulação realizada
com dados reais de duas concessionárias de energia elétrica
brasileiras. / [en] This thesis presents an hibrid short term load forecasting
model that mixes simple exponential smoothing with feed-
forward neural networks. The model gives point predictions
with upper and lower limits for 15-day-ahead horizon. These
limits yields an interval with associated empirical
confidence level, estimated by an out of sample test. The
model's performance is evaluated through a simulation with
real data obtained from two Brazilian utilities. / [es] En esta disertación se propone un modelo híbrido para
previsión de carga de cortísimo plazo, combinando
amortecimiento exponencial simple y redes neurales
artificiales tipo feed-forward. EL modelo nos da las
previsiones puntuales y los límites superiores e inferiores
para un horizonte de quince días. Estos límites forman un
intervalo al cual se le puede asociar un nível de confianza
empírico, estimado a través de un test out of sample. EL
desempeño del modelo se evalúa utilizando datos reales de
dos concesionarias de energía eléctrica brasileras.
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Modélisation des pertes de rendement des cultures de blé dhiver au Grand-Duché de Luxembourg sur base de létude des surfaces photosynthétiquement actives./Yield loss modélisation of wheat based on photosynthetic active area studies.Mackels, Christophe 06 April 2009 (has links)
Au Grand-Duché de Luxembourg, le développement de modèles opérationnels pour la prévision
des rendements se heurte actuellement au problème de la non prise en compte de la diminution de la
surface verte utile et de sa relation avec des processus biotiques et abiotiques incriminés en situation
de production. Pourtant, il apparaît que lélaboration dun modèle reliant la perte de surface verte à la
baisse de rayonnement absorbé est la façon la plus adéquate daméliorer les prévisions de perte de
rendement aux champs. De nombreuses manières destimer les rendements existent et se basent sur
différentes approches et méthodes. Lobjectif de ce travail est de proposer un modèle destimation des
rendements basé sur létude de la dégradation de la surface verte foliaire du blé et du rayonnement
intercepté par cette surface tout au long de sa dégradation.
Lapproche envisagée consiste, dans un premier temps, à utiliser les deux principaux modèles
existants qui décrivent linterception du rayonnement par les surfaces foliaires vertes avec des
données issues dexpérimentations aux champs, au Grand-Duché de Luxembourg en 2006 et 2007.
Différentes méthodes dobtention des principales données dentrée de ces modèles ont été comparées
et leurs avantages ont été mis en évidence. Ces données sont le LAI (Leaf Area Index) et le
pourcentage de surface foliaire verte. Un LAI de référence, obtenu à laide dune méthode danalyse
dimages de feuilles a été validé et comparé à une méthode dobtention du LAI basée sur la mesure
du rayonnement intercepté par le couvert ainsi quà une méthode fournissant la couverture verte du
sol à partir dimages aériennes de courte distance. Il a été montré que le LAI issu de la mesure du
rayonnement intercepté et la couverture verte du sol sont obtenus plus rapidement et pour de plus
grandes surfaces, mais quils ne sont pas suffisamment corrélés au LAI de référence pour être utilisés
afin dobtenir le LAI réel. Le pourcentage de la surface foliaire verte de référence a également été
obtenu à laide de la méthode danalyse dimages de feuilles. La comparaison de celui-ci aux
estimations visuelles du pourcentage de surface verte foliaire a montré que cette méthode est plus
rapide, mais engendre une surestimation du pourcentage de surface foliaire verte. Une relation
linéaire significative entre la couverture verte du sol par prise dimages aériennes et le pourcentage de
surface foliaire verte a été obtenue. Une amélioration de la prise dimages aériennes de courte
distance pourrait mener à une substitution du pourcentage de surface foliaire verte par la couverture
verte du sol sur de grandes surfaces à lavenir.
Les deux principaux modèles décrivant linterception du rayonnement par les surfaces foliaires
vertes ont été utilisés avec le LAI et le pourcentage de surface foliaire verte de référence. Une
simplification de ces modèles par lutilisation de la dernière ou des deux dernières strates foliaires à la
place des trois dernières pour le pourcentage de surface verte a montré que la simplification ne menait
pas à une amélioration des résultats dans la plupart des cas. Dautre part, une estimation des biais
introduits en utilisant les pourcentages de surface verte issus de lestimation visuelle à la place des
estimations par lanalyse dimages montre que lestimation visuelle introduit un biais allant jusquà
20%. La comparaison des deux modèles testés a mené à la sélection du modèle aux sorties fournissant
la meilleure relation avec les rendements. Cest une relation linéaire simple entre les paramètres de la
courbe décrivant lévolution des sorties du modèle dit du « calcul de la matière sèche » au cours de la
saison de culture et le rendement qui a été retenue.
Dans un deuxième temps, le modèle sélectionné a été utilisé avec des données issues
dexpérimentations menées de lannée 2000 à 2005, afin dobtenir une relation linéaire plus stable
entre les rendements et les sorties de ce modèle. La relation obtenue montre des résultats significatifs
et expliquant plus de 66% des rendements si une variété au comportement atypique est exclue. Un
effet significatif de lannée, du précédent et de la variété sur cette relation a été mis en évidence.
Dans un troisième temps, laspect prédictif du modèle destimation des rendements basé sur la
relation linéaire simple retenue a été étudié sur deux années de données extérieures aux années
utilisées pour la construction de celui-ci. Les données dentrée nécessaires au fonctionnement du
modèle ont dû être obtenues de manière prédictive, afin de réaliser des estimations du rendement à
venir à partir de la floraison. Le modèle Proculture, basé sur la simulation de lévolution des
symptômes de la septoriose, a permis dobtenir des estimations en prévision des pourcentages de
surface verte, et le LAI a été considéré comme constant par variété dune année à lautre. Le modèle
destimation utilisé a permis dobtenir des prévisions de rendement ~20% supérieures aux rendements
réels./In the Grand Duchy of Luxembourg, the development of operational models for predicting
yields currently runs against the failure to take into account the green leaf area decline and its
relationship with biotic and non biotic processes involved in a situation of production. Yet it
appears that the development of a model linking the loss of green leaf area to lower radiation
absorbed is the most adequate to improve prediction of yield loss in the fields. Many ways to
estimate yields exist and are based on different approaches and methods. The objective of
this work is to propose a model for estimating yields based on the study of the green leaf area
decline of wheat and radiation intercepted by this area throughout the season.
The approach is, first, to use the two main existing models that describe the interception of
radiation by green leaf area with data from experiments in the field, in the Grand Duchy of
Luxembourg in 2006 and 2007. Different methods for obtaining key data entry of these
models were compared and their benefits have been identified. These data are LAI (Leaf
Area Index) and the percentage of green leaf area. The reference method, obtained using
image analysis of leaves has been validated and compared to a method for obtaining LAI
based on the measurement of radiation intercepted by the canopy as well as a method based
on the green cover soil obtained from short distance aerial images. It was shown that the LAI
obtained from the measurement of radiation intercepted and the green land cover obtained
from short distance aerial images are obtained faster and for larger surfaces, but they are not
sufficiently correlated with the LAI from the reference method to be used in place of
reference LAI. The percentage of green leaf area of reference has also been obtained using
the image analysis of leaves. Comparing it to visual estimates of the percentage of green leaf
area has shown that this method is faster and creates an overestimation of the percentage of
green leaf area. A significant linear relationship between green land cover from short
distance aerial images analysis and the percentage of green leaf area was obtained. An
improved short distance aerial image could lead to the substitution of the percentage of green
leaf area by the green land cover over large areas in the future. The two main models
describing the interception of radiation by green leaf area were used with the LAI and the
percentage of green leaf area of reference. A simplification of these models by using only the
upper leaf or the two last leaves to emerge in place of the last three leaves to emerge for the
percentage of green area has shown that simplification did not lead to improved results in
most cases. On the other hand, an estimate of bias using the percentage of green leaf area
from the visual estimate in place of estimates by image analysis shows that visual estimate
introduce an approximate bias of 20%. A comparison of the two models tested led to the
selection of the model outputs providing the best relationship with yields. It is a simple linear
relationship between parameters of the curve describing the evolution of model outputs socalled
calculation of dry matter during the growing season and yield that was chosen.
In a second time, the selected model was used with data from experiments conducted from
2000 to 2005 to obtain a more stable linear relationship between yields and output of the
model. The relationship obtained shows significant results and explains over 66% yields if
datas from an atypical variety are excluded. A significant effect of years, precedent and
variety on this relationship was highlighted.
In a third time, the predictive aspect of the model to estimate yields based on the simple
linear relationship has been studied on two years of external data used for years to build it.
The input data needed to run the model had to be obtained on a predictive way to make
estimates of future performance from flowering. The model Proculture, based on the
simulation of the progression of septoriose disease, allowed obtaining estimates in
anticipation of the percentage of green area, and LAI was considered constant variety from
one year to another. The estimation model used resulted in expected future performance ~
20% higher than actual yields.
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