Plant diseases are one of the major threats to global food production. Efficient monitoring and detection of plant pathogens are instrumental in restricting and effectively managing the spread of the disease and reducing the cost of pesticides. Traditional, molecular, and serological methods that are widely used for plant disease detection are often ineffective if not applied during the initial stages of pathogenesis, when no or very weak symptoms appear. Moreover, they are almost useless in acquiring spatialized diagnostic results on plant diseases. On the other hand, remote sensing (RS) techniques utilizing drones are very effective for the rapid identification of plant diseases in their early stages. Currently, drones, play a pivotal role in the monitoring of plant pathogen spread, detection, and diagnosis to ensure crops’ health status. The advantages of drone technology include high spatial resolution (as several sensors are carried aboard), high efficiency, usage flexibility, and more significantly, quick detection of plant diseases across a large area with low cost, reliability, and provision of high-resolution data. Drone technology employs an automated procedure that begins with gathering images of diseased plants using various sensors and cameras. After extracting features, image processing approaches use the appropriate traditional machine learning or deep learning algorithms. Features are extracted from images of leaves using edge detection and histogram equalization methods. Drones have many potential uses in agriculture, including reducing manual labor and increasing productivity. Drones may be able to provide early warning of plant diseases, allowing farmers to prevent costly crop failures.

In the past and present, human activities have been involved in triggering global warming, causing drought stresses that affect animals and plants. Plants are more defenseless against drought stress; and therefore, plant development and productive output are decreased. To decrease the effect of drought stress on plants, it is crucial to establish a plant feedback mechanism of resistance to drought. The drought reflex mechanisms include the physical stature physiology and biochemical, cellular, and molecular-based processes. Briefly, improving the root system, leaf structure, osmotic-balance, comparative water contents and stomatal adjustment are considered as most prominent features against drought resistance in crop plants. In addition, the signal transduction pathway and reactive clearance of oxygen are crucial mechanisms for coping with drought stress via calcium and phytohormones such as abscisic acid, salicylic acid, jasmonic acid, auxin, gibberellin, ethylene, brassinosteroids and peptide molecules. Furthermore, microorganisms, such as fungal and bacterial organisms, play a vital role in increasing resistance against drought stress in plants. The number of characteristic loci, transgenic methods and the application of exogenous substances [nitric oxide, (C₂₈H₄₈O₆) 24-epibrassinolide, proline, and glycine betaine] are also equally important for enhancing the drought resistance of plants. In a nutshell, the current review will mainly focus on the role of phytohormones and related mechanisms involved in drought tolerance in various crop plants.

Rhizoctonia solan Kühn (teleomorph: Thanatephorus cucumeris (Frank) Donk ( R. solani ) is a soil-borne phytopathogenic species complex as well as a necrotic fungus that causes significant crop yield losses worldwide. Agronomic practices (crop rotation), resistant cultivars, and chemical pesticides are widely used to control R. solani . However, these practices are insufficient to control the pest. Moreover, the application of chemical pesticides is harmful to both the environment and human health. Therefore, the use of biocontrol agents (BCAs) and that of plant-growth promoting bacteria (PGPB) are considered to be potentially sustainable, cost-effective, efficient, and eco-friendly ways to control R. solani . Several microorganisms have been used as biocontrol agents (BCAs) to manage R. solani . Among these, biocontrol agents (BCAs) Bacillus spp. are used to promote plant growth. Furthermore, due to its broad range of antibiotic-producing abilities, Bacillus spp. is widely used against R. solani . In this review, current and previous studies about the ability of Bacillus spp. to control diseases caused by R. solani are reported . It also focuses on the plant-growth promotion attributes of Bacillus spp. in response to the deleterious effects of R. solani.

Malaria, the exterminator of ~1.5 to 2.7 million human lives yearly, is a notorious disease known throughout the world. The eradication of this disease is difficult and a challenge to scientists. Vector elimination and effective chemotherapy for the patients are key tactics to be used in the fight against malaria. However, drug resistance and environmental and social concerns are the main hurdles in this fight against malaria. Overcoming these limitations is the major challenge for the 21st-century malarial researchers. Adapting the principles of nano-biotechnology to both vector control and patient therapy is the only solution to the problem. Several compounds such as lipids, proteins, nucleic acid and metallic nanoparticles (NPs) have been successfully used for the control of this lethal malaria disease. Other useful natural reagents such as microbes and their products, carbohydrates, vitamins, plant extracts and biodegradable polymers, are also used to control this disease. Among these particles, the plant-based particles such as leaf, root, stem, latex, and seed give the best antagonistic response against malaria. In the present review, we describe certain efforts related to the control, prevention and treatment of malaria. We hope that this review will open new doors for malarial research.

Soil types and cropping systems influence the diversity and composition of the rhizospheric microbial communities. Coptis chinensis Franch is one of the most important medicinal plants in China. In the current study, we provide detailed information regarding the diversity and composition of rhizospheric fungal communities of the C. chinensis plants in continuous cropping fields and fallow fields in two seasons (winter and summer), using next-generation sequencing. Alpha diversity was higher in the five-year C. chinensis field and lower in fallow fields. Significant differences analysis confirmed more fungi in the cultivated field soil than in fallow fields. Additionally, PCoA of beta diversity indices revealed that samples associated with the cultivated fields and fallow fields in different seasons were separated. Five fungal phyla (Ascomycota, Basidiomycota, Chytridiomycota, Glomeromycota and Mucoromycota) were identified from the soil samples in addition to the unclassified fungal taxa and Cryptomycota, and among these phyla, Ascomycota was predominantly found. FUNGuild fungal functional prediction revealed that saprotroph was the dominant trophic type in all two time-series soil samples. Redundancy analysis (RDA) of the dominant phyla data and soil physiochemical properties revealed the variations in fungal community structure in the soil samples. Knowledge from the present study could provide a valuable reference for solving the continuous cropping problems and promote the sustainable development of the C. chinensis industry.