Proceedings
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| Filter results5 paper(s) found. |
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1. Early Identification Of Leaf Rust On Wheat Leaves With Robust Fitting Of Hyperspectral SignaturesEarly recognition of pathogen infection is of great relevance in precision plant protection. Disease detection before the occurrence of visual symptoms is of particular interest. By use of a laserfluoroscope, UV-light induced fluorescence data were collected from healthy and with leaf rust infected wheat leaves of the susceptible cv. Ritmo 2-4 days after inoculation under controlled conditions. In order to evaluate disease impact on spectral characteristics 215 wavelengths in the range of 370-800... C. R, T. Rumpf, K. B, M. Hunsche, L. Pl, G. Noga |
2. Suitability Of Fluorescence Sensors To Estimate The Susceptibility Degree Of Spring Barley To Powdery Mildew And Leaf RustThe overall role of precision agriculture is not restricted to those systems for in-field and in-season sensing of the impact of stresses. Much more, its contribution comprises the prevention of stresses, amongst others by supporting the selection of appropriate and stress-tolerant genotypes in breeding programs. In this context, the development, selection and use of cultivars which are tolerant to pathogens establish an essential tool for a more sustainable and environmental-friendly... G. Leufen, G. Noga, M. Hunsche |
3. Selection Of Fluorescence Indices For The Proximal Sensing Of Single And Multiple Stresses In Sugar BeetThe use of fluorescence indices for sensing the impact of abiotic and biotic stresses in agricultural crops is well documented in the literature. Pigment fluorescence gives a precise picture about the plant physiology and its changes following the occurrence of stresses. In general, alterations in such optical signals is caused either by the stress-induced accumulation of one or more fluorophores, or the degradation of specific molecules like chlorophyll. Unfortunately, many stresses... G. Leufen, G. Noga, M. Hunsche |
4. Detection and Monitoring the Risk Level for Lameness and Lesions in Dairy Herds by Alternative Machine-Learning AlgorithmsMachine-learning methods may play an increasing role in the development of precision agriculture tools to provide predictive insights in dairy farming operations and to routinely monitor the status of dairy cows. In the present study, we explored the use of a machine-learning approach to detect and monitor the welfare status of dairy herds in terms of lameness and lesions based on pre-recorded farm-based records. Animal-based measurements such as lameness and lesions are time-consuming, expensive... D. Warner, R. Lacroix, E. Vasseur, D. Lefebvre |
5. Usage of Milk Revenue Per Minute of Boxtime to Assess Cows Selection and Farm Profitability in Automatic Milking SystemsThe number of farms implementing robotic milking systems, usually referred as automatic milking systems (AMS), is increasing rapidly. AMS efficiency is a priority to achieve high milk production and higher incomes from dairy herds. Recent studies suggested that milkability (i.e., amount of milk produced per total time spent in the AMS [kg milk/ minute of boxtime]) could be used for as a criteria for genetic evaluations. Therefore, an indicator of milkability was developed, which combines economical... L. Fadul-pacheco, G. Bisson, R. Lacroix, M. Séguin, R. Roy, E. Vasseur, D. Lefebvre |