Spatial scales of interactions among bacteria and between bacteria and the leaf surface.

Microbial life on plant leaves is characterized by a multitude of interactions between leaf colonizers and their environment. While the existence of many of these interactions has been confirmed, their spatial scale or reach often remained unknown. In this study, we applied spatial point pattern analysis to 244 distribution patterns of Pantoea agglomerans and Pseudomonas syringae on bean leaves. The results showed that bacterial colonizers of leaves interact with their environment at different spatial scales. Interactions among bacteria were often confined to small spatial scales up to 5-20 μm, compared to interactions between bacteria and leaf surface structures such as trichomes which could be observed in excess of 100 μm. Spatial point-pattern analyses prove a comprehensive tool to determine the different spatial scales of bacterial interactions on plant leaves and will help microbiologists to better understand the interplay between these interactions

Evolution of plant reproduction: from fusion and dispersal to interaction and communication

Based on the existing data concerning the evolution of the sexual reproduction, it is argued that the processes of sex differentiation and interactions play a key role in evolution. From the beginning environment and organism are unified. In a changing dynamic environment life originates and the interaction between life and environment develops from simple to more complex organisms. Sexual reproduction is introduced after the origin of meiosis and is a key process in evolution. The asexual reproduction process prepares to dispersal. Sexual reproduction process adds the genome renewal and the gamete-gamete interaction. Reproduction and dispersal are connected and the process of reproduction has similarities between asexual and sexual reproduction. Unicellular algae develop the physiological and morphological sex differentiation. Sex differentiation is connected with the way of dispersal. The step to multicellular plants introduces cell isolation after meiosis and by the stay on the mother plant within a cell or organ, plant-cell apoplastic interaction originates and by prolonged stay the plant-plant interaction. This stay influences the type of dispersal. A life cycle with alternation of generations and two moments of dispersal permits plants to go on land. In ferns a shift in the moment of sex differentiation to meiospore happens and the stay of the macrospore leads to the seed plants. In water all types of sexual reproduction, interactions and the alternation of generations are prepared and these are used to conquest land. On land the biotic dispersal is realized. The phylogeny of sexual reproduction reveals that the sex differentiation and interaction are the main causes in the evolution of sexual reproduction. Sexual reproduction shows interactions during gamete fusion, between organism and environment and in multicellular plants between organisms. With respect to other types of interaction as in symbiosis or the nutrient chain, interaction is considered as an important action which is based on a persisting cooperation and points to a push during evolution. The push is expressed as communication: the driving force in the evolution. Based on the interactions between organisms and interactions between organisms and the dynamic environment, communication is considered as a driving force leading to the evolution as explained in the development of plant reproduction. Consequences for reproduction, its regulation and the process of evolution are discusse

Estimation of the solubility parameters of model plant surfaces and agrochemicals: a valuable tool for understanding plant surface interactions

Background Most aerial plant parts are covered with a hydrophobic lipid-rich cuticle, which is the interface between the plant organs and the surrounding environment. Plant surfaces may have a high degree of hydrophobicity because of the combined effects of surface chemistry and roughness. The physical and chemical complexity of the plant cuticle limits the development of models that explain its internal structure and interactions with surface-applied agrochemicals. In this article we introduce a thermodynamic method for estimating the solubilities of model plant surface constituents and relating them to the effects of agrochemicals. Results Following the van Krevelen and Hoftyzer method, we calculated the solubility parameters of three model plant species and eight compounds that differ in hydrophobicity and polarity. In addition, intact tissues were examined by scanning electron microscopy and the surface free energy, polarity, solubility parameter and work of adhesion of each were calculated from contact angle measurements of three liquids with different polarities. By comparing the affinities between plant surface constituents and agrochemicals derived from (a) theoretical calculations and (b) contact angle measurements we were able to distinguish the physical effect of surface roughness from the effect of the chemical nature of the epicuticular waxes. A solubility parameter model for plant surfaces is proposed on the basis of an increasing gradient from the cuticular surface towards the underlying cell wall. Conclusions The procedure enabled us to predict the interactions among agrochemicals, plant surfaces, and cuticular and cell wall components, and promises to be a useful tool for improving our understanding of biological surface interactions

Do interactions between plant roots and the rhizosphere affect parasitoid behaviour?

Multitrophic interactions are powerful forces shaping the structure of living communities. Plants encounter a great diversity of organisms in their environment: some of these interactions are beneficial (e.g. symbiotic fungi and insect pollinators) while some are detrimental (e.g. herbivorous insects and pathogenic micro-organisms). Multitrophic interactions between below-ground and above-ground organisms are receiving increasing attention because they may influence plant defences against biotic and abiotic stresses. In this study we show that an arbuscular mycorrhizal symbiosis makes tomato plants significantly more resistant towards aphids, by enhancing both direct defences, both attractivity towards aphid parasitoids

Proceedings of the COST SUSVAR/ECO-PB Workshop on organic plant breeding strategies and the use of molecular markers

In many countries,national projects are in progress to investigate the sustainable low-input approach.In the present COST network,these projects are coordinated by means of exchange of materials,establishing common methods for assessment and statistical analyses and by combining national experimental results.The common framework is cereal production in low-input sustainable systems with emphasis on crop diversity.The network is organised into six Working Groups,five focusing on specific research areas and one focusing on the practical application of the research results for variety testing:1)plant genetics and plant breeding,2)biostatistics,3)plant nutrition and soil microbiology,4)weed biology and plant competition,5)plant pathology and plant disease resistance biology and 6)variety testing and certification.It is essential that scientists from many disciplines work together to investigate the complex interactions between the crop and its environment,in order to be able to exploit the natural regulatory mechanisms of different agricultural systems for stabilising and increasing yield and quality.The results of this cooperation will contribute to commercial plant breeding as well as official variety testing,when participants from these areas disperse the knowledge achieved through the EU COST Action

Robotic sensing and stimuli provision for guided plant growth

Robot systems are actively researched for manipulation of natural plants, typically restricted to agricultural automation activities such as harvest, irrigation, and mechanical weed control. Extending this research, we introduce here a novel methodology to manipulate the directional growth of plants via their natural mechanisms for signaling and hormone distribution. An effective methodology of robotic stimuli provision can open up possibilities for new experimentation with later developmental phases in plants, or for new biotechnology applications such as shaping plants for green walls. Interaction with plants presents several robotic challenges, including short-range sensing of small and variable plant organs, and the controlled actuation of plant responses that are impacted by the environment in addition to the provided stimuli. In order to steer plant growth, we develop a group of immobile robots with sensors to detect the proximity of growing tips, and with diodes to provide light stimuli that actuate phototropism. The robots are tested with the climbing common bean, Phaseolus vulgaris, in experiments having durations up to five weeks in a controlled environment. With robots sequentially emitting blue light—peak emission at wavelength 465 nm—plant growth is successfully steered through successive binary decisions along mechanical supports to reach target positions. Growth patterns are tested in a setup up to 180 cm in height, with plant stems grown up to roughly 250 cm in cumulative length over a period of approximately seven weeks. The robots coordinate themselves and operate fully autonomously. They detect approaching plant tips by infrared proximity sensors and communicate via radio to switch between blue light stimuli and dormant status, as required. Overall, the obtained results support the effectiveness of combining robot and plant experiment methodologies, for the study of potentially complex interactions between natural and engineered autonomous systems

Integrated disease management using environmental control in tea fields

The occurrence of plant disease depends on interactions between the host plant, a pathogen, and the environment in a dynamic called "the disease triangle". Bacterial shoot blight (BSB) disease, caused by _Pseudomonas syringae_ pv. _theae_ (_Pst_), is a major bacterial disease of tea plants in Japan and substantially reduces tea productivity. BSB mainly occurs in the low-temperature season, and lesion formation by _Pst_ is enhanced by both low temperature and the presence of ice nucleation-active _Xanthomonas campestris_ (INAX), which catalyses ice formation at -2 to -4^o^C and is frequently co-isolated with _Pst_ from tea plants^5^. Low temperature is thus the most important environmental factor to influence the incident; however, the effects of environmental controls in fields on the occurrence of the disease are poorly understood. Here we show that the natural incidence of BSB in the field is closely related to low temperatures in late autumn. Frost protection in late autumn, which protected tea plants against extremely low temperatures, significantly decreased the incidence of BSB, and frost protection combined with bactericide application held the incident under the economic threshold level. Our data indicate that environmental control in the field based on microbial interactions in the host offers a new strategy for plant disease control using integrated plant disease management based on the disease triangle concept

A multi-trait multi-environment QTL mixed model with an application to drought and nitrogen stress trials in maize (Zea mays L.)

Despite QTL mapping being a routine procedure in plant breeding, approaches that fully exploit data from multi-trait multi-environment (MTME) trials are limited. Mixed models have been proposed both for multi-trait QTL analysis and multi-environment QTL analysis, but these approaches break down when the number of traits and environments increases. We present models for an efficient QTL analysis of MTME data with mixed models by reducing the dimensionality of the genetic variance¿covariance matrix by structuring this matrix using direct products of relatively simple matrices representing variation in the trait and environmental dimension. In the context of MTME data, we address how to model QTL by environment interactions and the genetic basis of heterogeneity of variance and correlations between traits and environments. We illustrate our approach with an example including five traits across eight stress trials in CIMMYT maize. We detected 36 QTLs affecting yield, anthesis-silking interval, male flowering, ear number, and plant height in maize. Our approach does not require specialised software as it can be implemented in any statistical package with mixed model facilities