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1. 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 |
2. 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 |
3. An On-farm Experimental Philosophy for Farmer-centric Digital InnovationIn this paper, we review learnings gained from early On-Farm Experiments (OFE) conducted in the broadacre Australian grain industry from the 1990s to the present day. Although the initiative was originally centered around the possibilities of new data and analytics in precision agriculture, we discovered that OFEs could represent a platform for engaging farmers around digital technologies and innovation. Insight from interacting closely with farmers and advisors leads us to argue for a change... S. Cook, M. Lacoste, F. Evans, M. Ridout, M. Gibberd, T. Oberthur |
4. On-Farm Experimentation and Decision-Support WorkshopThis 3-hour workshop discusses the requirements, methods and theories that may be used to assist in making optimal crop management decisions. The first part will focus on on-farm experimentation (OFE): 1) organization and benefits of OFE; 2) social processes and engagement; 3) designs, data and statistics. The second part will demonstrate how to generate insights applicable at the individual farm level using results from research trials collected in a diversity of contexts. Data sharing, meta-analyses... S. Cook, M. Lacoste, F. Evans, N. Tremblay, V. Adamchuk |