143 research outputs found
Postharvest quality and health of kiwifruit ‘Hayward’ affected by Pseudomonas syringae pv. actinidiae
First Report of Phytopythium vexans causing decline syndrome of Actinidia deliciosa âHaywardâ in Italy
La resistenza ai fungicidi in Monilinia spp. da pesche e nettarine e in Venturia inaequalis da mele
Long-Range Low-Power Soil Water Content Monitoring System for Precision Agriculture
World population growth and desertification are increasing the food demand. Food production must increase to ensure food security in the following years. Smart agriculture tries to improve food production thanks to the adoption of electronic sensors to monitor and control fruit and vegetable crops. Another critical point in agriculture is the use of potable water. Precision irrigation strategies can be implemented to reduce water waste and increase crop production. This paper proposes a long-range, low-power sensor node to monitor soil water content. It is possible to place multiple sensor nodes in the field and use the gathered data to determine the most suitable irrigation strategy. The node communicates thanks to the LoRa protocol and it can also be used in remote areas where it is impossible to have an internet connection
Rapid Detection of Monilinia fructicola and Monilinia laxa on Peach and Nectarine using Loop-Mediated Isothermal Amplification
Betti numbers for numerical semigroup rings
We survey results related to the magnitude of the Betti numbers of numerical
semigroup rings and of their tangent cones.Comment: 22 pages; v2: updated references. To appear in Multigraded Algebra
and Applications (V. Ene, E. Miller Eds.
Evolutionary trait-based approaches for predicting future global impacts of plant pathogens in the genus Phytophthora
1. Plant pathogens are introduced to new geographical regions ever more frequently as global connectivity increases. Predicting the threat they pose to plant health can be difficult without inâdepth knowledge of behaviour, distribution and spread. Here, we evaluate the potential for using biological traits and phylogeny to predict global threats from emerging pathogens.
2. We use a speciesâlevel trait database and phylogeny for 179 Phytophthora species: oomycete pathogens impacting natural, agricultural, horticultural and forestry settings. We compile host and distribution reports for Phytophthora species across 178 countries and evaluate the power of traits, phylogeny and time since description (reflecting speciesâlevel knowledge) to explain and predict their international transport, maximum latitude and host breadth using Bayesian phylogenetic generalised linear mixed models.
3. In the bestâperforming models, traits, phylogeny and time since description together explained up to 90%, 97% and 87% of variance in number of countries reached, latitudinal limits and host range, respectively. Traits and phylogeny together explained up to 26%, 41% and 34% of variance in the number of countries reached, maximum latitude and host plant families affected, respectively, but time since description had the strongest effect.
4. Rootâattacking species were reported in more countries, and on more host plant families than foliarâattacking species. Host generalist pathogens had thickerâwalled resting structures (stressâtolerant oospores) and faster growth rates at their optima. Coldâtolerant species are reported in more countries and at higher latitudes, though more accurate interspecific empirical data are needed to confirm this finding.
5. Policy implications. We evaluate the potential of an evolutionary traitâbased framework to support horizonâscanning approaches for identifying pathogens with greater potential for globalâscale impacts. Potential future threats from Phytophthora include Phytophthora x heterohybrida, P. lactucae, P. glovera, P. x incrassata, P. amnicola and P. aquimorbida, which are recently described, possibly underâreported species, with similar traits and/or phylogenetic proximity to other highâimpact species. Priority traits to measure for emerging species may be thermal minima, oospore wall index and growth rate at optimum temperature. Traitâbased horizonâscanning approaches would benefit from the development of international and crossâsectoral collaborations to deliver centralised databases incorporating pathogen distributions, traits and phylogeny
Functional analysis of RXLR effectors from the New Zealand kauri dieback pathogen Phytophthora agathidicida
New Zealand kauri is an ancient, iconic, gymnosperm tree species that is under threat from a lethal dieback disease caused by the oomycete Phytophthora agathidicida. To gain insight into this pathogen, we determined whether proteinaceous effectors of P. agathidicida interact with the immune system of a model angiosperm, Nicotiana, as previously shown for Phytophthora pathogens of angiosperms. From the P. agathidicida genome, we defined and analysed a set of RXLR effectors, a class of proteins that typically have important roles in suppressing or activating the plant immune system. RXLRs were screened for their ability to activate or suppress the Nicotiana plant immune system using Agrobacterium tumefaciens transient transformation assays. Nine P. agathidicida RXLRs triggered cell death or suppressed plant immunity in Nicotiana, of which three were expressed in kauri. For the most highly expressed, P. agathidicida (Pa) RXLR24, candidate cognate immune receptors associated with cell death were identified in Nicotiana benthamiana using RNA silencing-based approaches. Our results show that RXLRs of a pathogen of gymnosperms can interact with the immune system of an angiosperm species. This study provides an important foundation for studying the molecular basis of plantâpathogen interactions in gymnosperm forest trees, including kauri
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