Identification of a bio-signature for barley resistance against Pyrenophora teres infection based on physiological, molecular and sensor-based phenotyping.

Necrotic and chlorotic symptoms induced during Pyrenophora teres infection in barley leaves indicate a compatible interaction that allows the hemi-biotrophic fungus Pyrenophora teres to colonise the host. However, it is unexplored how this fungus affects the physiological responses of resistant and susceptible cultivars during infection. To assess the degree of resistance in four different cultivars, we quantified visible symptoms and fungal DNA and performed expression analyses of genes involved in plant defence and ROS scavenging. To obtain insight into the interaction between fungus and host, we determined the activity of 19 key enzymes of carbohydrate and antioxidant metabolism. The pathogen impact was also phenotyped non-invasively by sensor-based multireflectance and -fluorescence imaging. Symptoms, regulation of stress-related genes and pathogen DNA content distinguished the cultivar Guld as being resistant. Severity of net blotch symptoms was also strongly correlated with the dynamics of enzyme activities already within the first day of infection. In contrast to the resistant cultivar, the three susceptible cultivars showed a higher reflectance over seven spectral bands and higher fluorescence intensities at specific excitation wavelengths. The combination of semi high-throughput physiological and molecular analyses with non-invasive phenotyping enabled the identification of bio-signatures that discriminates the resistant from susceptible cultivars.

Computer Vision and Less Complex Image Analyses to Monitor Potato Traits in Fields.

Field phenotyping of crops has recently gained considerable attention leading to the development of new protocols for recording plant traits of interest. Phenotyping in field conditions can be performed by various cameras, sensors, and imaging platforms. In this chapter, practical aspects as well as advantages and disadvantages of aboveground phenotyping platforms are highlighted with a focus on drone-based imaging and relevant image analysis for field conditions. It includes useful planning tips for experimental design as well as protocols, sources, and tools for image acquisition, preprocessing, feature extraction, and machine learning highlighting the possibilities with computer vision. Several open and free resources are given to speed up data analysis for biologists.This chapter targets professionals and researchers with limited computational background performing or wishing to perform phenotyping of field crops, especially with a drone-based platform. The advice and methods described focus on potato but can mostly be used for field phenotyping of any crops.

Extension of Plant Phenotypes by the Foliar Microbiome.

The foliar microbiome can extend the host plant phenotype by expanding its genomic and metabolic capabilities. Despite increasing recognition of the importance of the foliar microbiome for plant fitness, stress physiology, and yield, the diversity, function, and contribution of foliar microbiomes to plant phenotypic traits remain largely elusive. The recent adoption of high-throughput technologies is helping to unravel the diversityand spatiotemporal dynamics of foliar microbiomes, but we have yet to resolve their functional importance for plant growth, development, and ecology. Here, we focus on the processes that govern the assembly of the foliar microbiome and the potential mechanisms involved in extended plant phenotypes. We highlight knowledge gaps and provide suggestions for new research directions that can propel the field forward. These efforts will be instrumental in maximizing the functional potential of the foliar microbiome for sustainable crop production.

Bacillus licheniformis FMCH001 Increases Water Use Efficiency via Growth Stimulation in Both Normal and Drought Conditions.

Increasing agricultural losses due to biotic and abiotic stresses caused by climate change challenge food security worldwide. A promising strategy to sustain crop productivity under conditions of limited water availability is the use of plant growth promoting rhizobacteria (PGPR). Here, the effects of spore forming Bacillus licheniformis (FMCH001) on growth and physiology of maize (Zea mays L. cv. Ronaldinho) under well-watered and drought stressed conditions were investigated. Pot experiments were conducted in the automated high-throughput phenotyping platform PhenoLab and under greenhouse conditions. Results of the PhenoLab experiments showed that plants inoculated with B. licheniformis FMCH001 exhibited increased root dry weight (DW) and plant water use efficiency (WUE) compared to uninoculated plants. In greenhouse experiments, root and shoot DW significantly increased by more than 15% in inoculated plants compared to uninoculated control plants. Also, the WUE increased in FMCH001 plants up to 46% in both well-watered and drought stressed plants. Root and shoot activities of 11 carbohydrate and eight antioxidative enzymes were characterized in response to FMCH001 treatments. This showed a higher antioxidant activity of catalase (CAT) in roots of FMCH001 treated plants compared to uninoculated plants. The higher CAT activity was observed irrespective of the water regime. These findings show that seed coating with Gram positive spore forming B. licheniformis could be used as biostimulants for enhancing plant WUE under both normal and drought stress conditions.

The tmRDB and SRPDB resources.

Maintained at the University of Texas Health Science Center at Tyler, Texas, the tmRNA database (tmRDB) is accessible at the URL http://psyche.uthct.edu/dbs/tmRDB/tmRDB.html with mirror sites located at Auburn University, Auburn, Alabama (http://www.ag.auburn.edu/mirror/tmRDB/) and the Royal Veterinary and Agricultural University, Denmark (http://tmrdb.kvl.dk/). The signal recognition particle database (SRPDB) at http://psyche.uthct.edu/dbs/SRPDB/SRPDB.html is mirrored at http://srpdb.kvl.dk/ and the University of Goteborg (http://bio.lundberg.gu.se/dbs/SRPDB/SRPDB.html). The databases assist in investigations of the tmRNP (a ribonucleoprotein complex which liberates stalled bacterial ribosomes) and the SRP (a particle which recognizes signal sequences and directs secretory proteins to cell membranes). The curated tmRNA and SRP RNA alignments consider base pairs supported by comparative sequence analysis. Also shown are alignments of the tmRNA-associated proteins SmpB, ribosomal protein S1, alanyl-tRNA synthetase and Elongation Factor Tu, as well as the SRP proteins SRP9, SRP14, SRP19, SRP21, SRP54 (Ffh), SRP68, SRP72, cpSRP43, Flhf, SRP receptor (alpha) and SRP receptor (beta). All alignments can be easily examined using a new exploratory browser. The databases provide links to high-resolution structures and serve as depositories for structures obtained by molecular modeling.