https://hal.archives-ouvertes.fr/hal-00457602/document

A global overview of drought and heat-induced tree mortality reveals emerging climate change risks for forests

The latest generation of convolutional neural networks (CNNs) has achieved impressive results in the field of image classification. This paper is concerned with a new approach to the development of plant disease recognition model, based on leaf image classification, by the use of deep convolutional networks. Novel way of training and the methodology used facilitate a quick and easy system implementation in practice. The developed model is able to recognize 13 different types of plant diseases out of healthy leaves, with the ability to distinguish plant leaves from their surroundings. According to our knowledge, this method for plant disease recognition has been proposed for the first time. All essential steps required for implementing this disease recognition model are fully described throughout the paper, starting from gathering images in order to create a database, assessed by agricultural experts. Caffe, a deep learning framework developed by Berkley Vision and Learning Centre, was used to perform the deep CNN training. The experimental results on the developed model achieved precision between 91% and 98%, for separate class tests, on average 96.3%.

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Deep Neural Networks Based Recognition of Plant Diseases by Leaf Image Classification

Virus diseases that have emerged in the past two decades limit the production of important vegetable crops in tropical, subtropical, and temperate regions worldwide, and many of the causal viruses are transmitted by whiteflies (order Hemiptera, family Aleyrodidae). Most of these whitefly-transmitted viruses are begomoviruses (family Geminiviridae), although whiteflies are also vectors of criniviruses, ipomoviruses, torradoviruses, and some carlaviruses. Factors driving the emergence and establishment of whitefly-transmitted diseases include genetic changes in the virus through mutation and recombination, changes in the vector populations coupled with polyphagy of the main vector, Bemisia tabaci, and long distance traffic of plant material or vector insects due to trade of vegetables and ornamental plants. The role of humans in increasing the emergence of virus diseases is obvious, and the effect that climate change may have in the future is unclear.

Emerging Virus Diseases Transmitted by Whiteflies

The extent to which crop pests and pathogens have altered their latitudinal ranges in response to climate change remains largely unknown. Now observations of hundreds of pests and pathogens reveal an average poleward shift of 2.7±0.8 km yr−1 since 1960, supporting the hypothesis of climate-driven pest movement.

Crop pests and pathogens move polewards in a warming world

Global warming leads to the concurrence of a number of abiotic and biotic stresses, thus affecting agricultural productivity. Occurrence of abiotic stresses can alter plant-pest interactions by enhancing host plant susceptibility to pathogenic organisms, insects, and by reducing competitive ability with weeds. On the contrary, some pests may alter plant response to abiotic stress factors. Therefore, systematic studies are pivotal to understand the effect of concurrent abiotic and biotic stress conditions on crop productivity. However, to date, a collective database on the occurrence of various stress combinations in agriculturally-prominent areas is not available. This review attempts to assemble published information on this topic, with a particular focus on the impact of combined drought and pathogen stresses on crop productivity. In doing so, this review highlights some agriculturally important morpho-physiological traits that can be utilized to identify genotypes with combined stress tolerance. In addition, this review outlines potential role of recent genomic tools in deciphering combined stress tolerance in plants. This review will, therefore, be helpful for agronomists and field pathologists in assessing the impact of the interactions between drought and plant-pathogens on crop performance. Further, the review will be helpful for physiologists and molecular biologists to design agronomically relevant strategies for the development of broad spectrum stress tolerant crops.

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Impact of Combined Abiotic and Biotic Stresses on Plant Growth and Avenues for Crop Improvement by Exploiting Physio-morphological Traits

Research in the effects of climate change on plant disease continues to be limited, but some striking progress has been made. At the genomic level, advances in technologies for the high-throughput analysis of gene expression have made it possible to begin discriminating responses to different biotic and abiotic stressors and potential trade-offs in responses. At the scale of the individual plant, enough experiments have been performed to begin synthesizing the effects of climate variables on infection rates, though pathosystemspecific characteristics make synthesis challenging. Models of plant disease have now been developed to incorporate more sophisticated climate predictions. At the population level, the adaptive potential of plant and pathogen populations may prove to be one of the most important predictors of the magnitude of climate change effects. Ecosystem ecologists are now addressing the role of plant disease in ecosystem processes and the challenge of scaling up from individual infection probabilities to epidemics and broader impacts.

/pdf/climate-change-effects-on-plant-disease-genomes-to-5e13s601ta.pdf

Climate Change Effects on Plant Disease: Genomes to Ecosystems

Ecology and epidemiology in R: Modeling dispersal gradients

Ecology and epidemiology in R: Spatial pattern analysis

Dispersal by grazing and browsing animals has the potential to structure plant-associated microbes in plant communities. Bison are one of the largest grazing animals in North America and charismatic symbols of the Great Plains. They have an important role in maintaining plant communities in tallgrass prairie and may have played a significant role in microbial dispersal across the Great Plains, along with other grazers and herbivores. To determine whether bison saliva could maintain viable fungal propagules, we sampled saliva from bison at Konza Prairie Biological Station. Fifty-nine ITS (Internal Transcribed Spacer) sequences were recovered from distinct fungal colonies on media selective for Fusarium species and Macrophomina phaseolina, representing at least 26 fungal species. Most sequences were identified as originating from potential plant pathogens, indicating that bison may play a role in spreading plant pathogens throughout the prairie. Given their historic numbers and extensive migration across North America, bison may have had a role in establishing the current structure of the prairie microbiome.

E. E. Frank

Papers

Climate Change Effects on Plant Disease: Genomes to Ecosystems

Ecology and epidemiology in R: Modeling dispersal gradients

Ecology and epidemiology in R: Spatial pattern analysis

Phytobiome stampede: Bison as potential dispersal agents for the tallgrass prairie microbiome