Phenolic compounds arise from the shikimic and acetic acid (polyketide) metabolic pathways in plants. They are but one category of the many secondary metabolites implicated in plant allelopathy. Phenolic allelochemicals have been observed in both natural and managed ecosystems, where they cause a number of ecological and economic problems, such as declines in crop yield due to soil sickness, regeneration failure of natural forests, and replanting problems in orchards. Phenolic allelochemical structures and modes of action are diverse and may offer potential lead compounds for the development of future herbicides or pesticides. This article reviews allelopathic effects, analysis methods, and allelopathic mechanisms underlying the activity of plant phenolic compounds. Additionally, the currently debated topic in plant allelopathy of whether catechin and 8-hydroxyquinoline play an important role in Centaurea maculata and Centaurea diffusa invasion success is discussed. Overall, the main purpose of this review is to highlight the allelopacthic potential of phenolic compounds to provide us with methods to solve various ecology problems, especially in regard to the sustainable development of agriculture, forestry, nature resources and environment conservation.

Extensive research revealed tremendous details about how plants sense pathogen effectors during effector-triggered immunity (ETI). However, less is known about downstream signaling events. In this report, we demonstrate that prolonged activation of MPK3 and MPK6, two Arabidopsis pathogen-responsive mitogen-activated protein kinases (MPKs), is essential to ETI mediated by both coiled coil-nucleotide binding site-leucine rich repeats (CNLs) and toll/interleukin-1 receptor nucleotide binding site-leucine rich repeats (TNLs) types of R proteins. MPK3/MPK6 activation rapidly alters the expression of photosynthesis-related genes and inhibits photosynthesis, which promotes the accumulation of superoxide () and hydrogen peroxide (H2O2), two major reactive oxygen species (ROS), in chloroplasts under light. In the chemical-genetically rescued mpk3 mpk6 double mutants, ETI-induced photosynthetic inhibition and chloroplastic ROS accumulation are compromised, which correlates with delayed hypersensitive response (HR) cell death and compromised resistance. Furthermore, protection of chloroplasts by expressing a plastid-targeted cyanobacterial flavodoxin (pFLD) delays photosynthetic inhibition and compromises ETI. Collectively, this study highlights a critical role of MPK3/MPK6 in manipulating plant photosynthetic activities to promote ROS accumulation in chloroplasts and HR cell death, which contributes to the robustness of ETI. Furthermore, the dual functionality of MPK3/MPK6 cascade in promoting defense and inhibiting photosynthesis potentially allow it to orchestrate the trade-off between plant growth and defense in plant immunity.

Background: Substrates of the Hippo pathway kinases Lats1/2 are largely unknown besides YAP/TAZ. Results: Phosphorylation of angiomotin by Lats1/2 inhibits interaction with F-actin thus impairs cell migration and angiogenesis. Conclusion: AMOTp130 is a physiological and functional substrate of Lats1/2 and the Hippo pathway. Significance: Demonstrating how identification of novel substrates would facilitate understanding the physiology of the Hippo pathway.

The involvement of cytokinins (CTKs) in the repression of phosphate (Pi)-starvation signalling has been widely documented. However, the full physiological and molecular relevance of this role remains unclear. To gain further insights into the regulation system of CTK repression of Pi-starvation signalling, a global analysis of gene expression events in rice seedlings under Pi starvation, and the exogenous CTK treatment under Pi-sufficient (+P) and Pi-deficient ( -P) conditions, was conducted using oligonucleotide array analysis. Physiological and biochemical adaptation was observed after 10 d Pi starvation in rice seedlings. A global reduction of the Pi-starvation signalling was detected after 3 d treatment of exogenous CTK. Expression profiling data indicate that, together with a significant increase of intracellular Pi content, many expression changes responsive to Pi starvation were reversed by exogenous CTK treatment while CTK-responsive genes behaved normally under -P condition. These results suggest that the interplay of CTK signal and Pi-starvation response can be partially explained by the rise of Pi concentration after exogenous CTK treatment. Microarray data also revealed that a small number of genes have different CTK response patterns under different Pi levels, suggesting a subtle interaction between CTK and Pi-starvation signalling pathway.

Summary The rapid selection of salinity‐tolerant crops to increase food production in salinized lands is important for sustainable agriculture. Recently, high‐throughput plant phenotyping technologies have been adopted that use plant morphological and physiological measurements in a non‐destructive manner to accelerate plant breeding processes. Here, a hyperspectral imaging (HSI) technique was implemented to monitor the plant phenotypes of 13 okra (Abelmoschus esculentus L.) genotypes after 2 and 7 days of salt treatment. Physiological and biochemical traits, such as fresh weight, SPAD, elemental contents and photosynthesis‐related parameters, which require laborious, time‐consuming measurements, were also investigated. Traditional laboratory‐based methods indicated the diverse performance levels of different okra genotypes in response to salinity stress. We introduced improved plant and leaf segmentation approaches to RGB images extracted from HSI imaging based on deep learning. The state‐of‐the‐art performance of the deep‐learning approach for segmentation resulted in an intersection over union score of 0.94 for plant segmentation and a symmetric best dice score of 85.4 for leaf segmentation. Moreover, deleterious effects of salinity affected the physiological and biochemical processes of okra, which resulted in substantial changes in the spectral information. Four sample predictions were constructed based on the spectral data, with correlation coefficients of 0.835, 0.704, 0.609 and 0.588 for SPAD, sodium concentration, photosynthetic rate and transpiration rate, respectively. The results confirmed the usefulness of high‐throughput phenotyping for studying plant salinity stress using a combination of HSI and deep‐learning approaches.