Plant growth-promoting microorganisms as biocontrol agents of plant diseases: Mechanisms, challenges and future perspectives

Plant diseases and pests are risk factors that threaten global food security. Excessive chemical pesticide applications are commonly used to reduce the effects of plant diseases caused by bacterial and fungal pathogens. A major concern, as we strive toward more sustainable agriculture, is to increase crop yields for the increasing population. Microbial biological control agents (MBCAs) have proved their efficacy to be a green strategy to manage plant diseases, stimulate plant growth and performance, and increase yield. Besides their role in growth enhancement, plant growth-promoting rhizobacteria/fungi (PGPR/PGPF) could suppress plant diseases by producing inhibitory chemicals and inducing immune responses in plants against phytopathogens. As biofertilizers and biopesticides, PGPR and PGPF are considered as feasible, attractive economic approach for sustainable agriculture; thus, resulting in a “win-win” situation. Several PGPR and PGPF strains have been identified as effective BCAs under environmentally controlled conditions. In general, any MBCA must overcome certain challenges before it can be registered or widely utilized to control diseases/pests. Successful MBCAs offer a practical solution to improve greenhouse crop performance with reduced fertilizer inputs and chemical pesticide applications. This current review aims to fill the gap in the current knowledge of plant growth-promoting microorganisms (PGPM), provide attention about the scientific basis for policy development, and recommend further research related to the applications of PGPM used for commercial purposes

Crop Yield Prediction Using Multi Sensors Remote Sensing (Review Article)

Pre-harvest prediction of a crop yield may prevent a disastrous situation and help decision-makers to apply more reliable and accurate strategies regarding food security. Remote sensing has numerous returns in the area of crop monitoring and yield prediction which are closely related to differences in soil, climate, and any biophysical and biochemical changes. Different remote techniques could be used for crop monitoring and yield prediction including multi and hyper spectral data, radar and lidar imagery. This study reviews the potentialities, advantages and disadvantages of each technique and the applicability of these techniques under different agricultural conditions. It also shows the different methods in which these techniques could be used efficiently. In addition, the study expects future scenarios of remote sensing applications in vegetation monitoring and the ways to overcome any obstacles that may face this work. It was found that using satellite data with high spatial resolution are still the most powerful method to be used for crop monitoring and to monitor crop parameters. Assessment of crop spectroscopic parameters through field or laboratory devices could be used to identify and quantify many crop biochemical and biophysical parameters. They could be also used as early indicators of plant infections; however, these techniques are not efficient for crop monitoring over large areas

Brainhack: Developing a culture of open, inclusive, community-driven neuroscience

International audienceBrainhack is an innovative meeting format that promotes scientific collaboration and education in an open, inclusive environment. This NeuroView describes the myriad benefits for participants and the research community and how Brainhacks complement conventional formats to augment scientific progress

Brainhack: Developing a culture of open, inclusive, community-driven neuroscience

Brainhack is an innovative meeting format that promotes scientific collaboration and education in an open, inclusive environment. This NeuroView describes the myriad benefits for participants and the research community and how Brainhacks complement conventional formats to augment scientific progress