First Report of Diaporthe eres Causing Stem Canker on Peach (Prunus persica) in Italy

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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

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 in‐depth 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 species‐level 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 species‐level knowledge) to explain and predict their international transport, maximum latitude and host breadth using Bayesian phylogenetic generalised linear mixed models. 3. In the best‐performing 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. Root‐attacking species were reported in more countries, and on more host plant families than foliar‐attacking species. Host generalist pathogens had thicker‐walled resting structures (stress‐tolerant oospores) and faster growth rates at their optima. Cold‐tolerant 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 trait‐based framework to support horizon‐scanning approaches for identifying pathogens with greater potential for global‐scale 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 under‐reported species, with similar traits and/or phylogenetic proximity to other high‐impact species. Priority traits to measure for emerging species may be thermal minima, oospore wall index and growth rate at optimum temperature. Trait‐based horizon‐scanning approaches would benefit from the development of international and cross‐sectoral 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 plant–pathogen interactions in gymnosperm forest trees, including kauri