974 resultados para rotation crops


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This study analyzed the health and overall landcover of citrus crops in Florida. The analysis was completed using Landsat satellite imagery available free of charge from the University of Maryland Global Landcover Change Facility. The project hypothesized that combining citrus production (economic) data with citrus area per county derived from spectral signatures would yield correlations between observable spectral reflectance throughout the year, and the fiscal impact of citrus on local economies. A positive correlation between these two data types would allow us to predict the economic impact of citrus using spectral data analysis to determine final crop harvests.

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Peer reviewed

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This work contributes to the ELUM (Ecosystem Land Use Modelling & Soil Carbon GHG Flux Trial) project, which was commissioned and funded by the Energy Technologies Institute (ETI). We acknowledge the E-OBS data set from the EU-FP6 project ENSEMBLES (http://ensembles-eu.metoffice.com) and the data providers in the ECA&D project (http://www.ecad.eu).

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Mémoire numérisé par la Direction des bibliothèques de l'Université de Montréal.

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Mémoire numérisé par la Direction des bibliothèques de l'Université de Montréal.

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Research has consistently found sex differences in mental rotation. Twin research has suggested that females with male co-twins perform better than females with female co-twins on mental rotation. Because twins share both pre-natal and post-natal environments, it is not possible to test whether this advantage is due to in-uterine transmission of testosterone from males to females or due to socialisation processes. The present study explored whether the advantage of females with brothers can be observed in non-twin siblings. Participants (N = 1799) were assessed on mental rotation. The observed group differences were overall small: males performed significantly better than females; females with sisters performed similarly to females with brothers; importantly, males with brothers performed significantly better than both female groups. The results suggest that sex differences in mental rotation are driven by the group of males with brothers.

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In computer vision, training a model that performs classification effectively is highly dependent on the extracted features, and the number of training instances. Conventionally, feature detection and extraction are performed by a domain-expert who, in many cases, is expensive to employ and hard to find. Therefore, image descriptors have emerged to automate these tasks. However, designing an image descriptor still requires domain-expert intervention. Moreover, the majority of machine learning algorithms require a large number of training examples to perform well. However, labelled data is not always available or easy to acquire, and dealing with a large dataset can dramatically slow down the training process. In this paper, we propose a novel Genetic Programming based method that automatically synthesises a descriptor using only two training instances per class. The proposed method combines arithmetic operators to evolve a model that takes an image and generates a feature vector. The performance of the proposed method is assessed using six datasets for texture classification with different degrees of rotation, and is compared with seven domain-expert designed descriptors. The results show that the proposed method is robust to rotation, and has significantly outperformed, or achieved a comparable performance to, the baseline methods.

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On-site detection of inoculum of polycyclic plant pathogens could potentially contribute to management of disease outbreaks. A 6-min, in-field competitive immunochromatographic lateral flow device (CLFD) assay was developed for detection of Alternaria brassicae (the cause of dark leaf spot in brassica crops) in air sampled above the crop canopy. Visual recording of the test result by eye provides a detection threshold of approximately 50 dark leaf spot conidia. Assessment using a portable reader improved test sensitivity. In combination with a weather-driven infection model, CLFD assays were evaluated as part of an in-field risk assessment to identify periods when brassica crops were at risk from A. brassicae infection. The weather-driven model overpredicted A. brassicae infection. An automated 7-day multivial cyclone air sampler combined with a daily in-field CLFD assay detected A. brassicae conidia air samples from above the crops. Integration of information from an in-field detection system (CLFD) with weather-driven mathematical models predicting pathogen infection have the potential for use within disease management systems.

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Botrytis cinerea (Grey mould) is a necrotrophic fungus infecting over 230 plant species worldwide. It can cause major pre- and post-harvest diseases of many agronomic and horticultural crops. Botrytis cinerea causes annual economic losses of 10–100 billion US dollars worldwide and instability in the food supply (Jin and Wu, 2015). Grey mould losses, either at the farm gate or later in the food chain, could be reduced with improved knowledge of inoculum availability during production. In this paper, we report on the ability to monitor Botrytis spore concentration in glasshouse tomato production ahead of symptom development on plants. Using a light weight and portable air sampler (microtitre immunospore trap) it was possible to quantify inoculum availability within hours. Also, this study investigated the spatial aspect of the pathogen with an increase of B. cinerea concentration in bio-aerosols collected in the lower part of the glasshouse (0.5 m) and adjacent to the trained stems of the tomato plants. No obvious relationship was observed between B. cinerea concentration and the internal glasshouse environmental parameters of temperature and relative humidity. However the occurrence of higher outside wind speeds did increase the prevalence of B. cinerea conidia in the cropping environment of a vented glasshouse. Knowledge of inoculum availability at time periods when the environmental risk of pathogen infection is high should improve the targeted use and effectiveness of control inputs.