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DNA methylation is a highly conserved epigenetic modification involved in many biological processes, including growth and development, stress response, and secondary metabolism. DNA demethylase (DNA-deMTase) genes have been identified in some plant species; however, there are no reports on the identification and analysis of DNA-deMTase genes in Foxtail millet (Setaria italica L.). In this study, seven DNA-deMTases were identified in S. italica. These DNA-deMTase genes were divided into four subfamilies (DML5, DML4, DML3, and ROS1) by phylogenetic and gene structure analysis. Further analysis shows that the physical and chemical properties of these DNA-deMTases proteins are similar, contain the typical conserved domains of ENCO3c and are located in the nucleus. Furthermore, multiple cis-acting elements were observed in DNA-deMTases, including light responsiveness, phytohormone responsiveness, stress responsiveness, and elements related to plant growth and development. The DNA-deMTase genes are expressed in all tissues detected with certain tissue specificity. Then, we investigated the abundance of DNA-deMTase transcripts under abiotic stresses (cold, drought, salt, ABA, and MeJA). The results showed that different genes of DNA-deMTases were involved in the regulation of different abiotic stresses. In total, our findings will provide a basis for the roles of DNA-deMTase in response to abiotic stress. [ABSTRACT FROM AUTHOR]

The effects of curing temperature (20°C, 40°C and 60°C) and the addition of limestone powder (LP) (6% and 12%) on the capillary water absorption (CWA) of high-volume fly ash (HVFA) cement mortar were investigated. X-ray diffraction analysis and tests for chemically bound water content (CBWC), compressive strength and porosity were also conducted. It was found that, for a fly ash (FA) content exceeding 30%, the CWA increased significantly. When the FA content was 50%, the curing temperature was raised to 40°C or the LP content was 12%, the CBWC increased greatly. Increasing the curing temperature or adding LP increased the compressive strength and decreased the porosity of the HVFA cement mortar. Prediction of the water penetration depth in the HVFA cement mortar was consistent with the CWA results. The results of this work indicate that an increase in curing temperature or the addition of LP could be an efficient way of improving the CWA performance of HVFA cement mortar. [ABSTRACT FROM AUTHOR]

Excessive nitrogen (N) fertilization poses environmental risks at regional and global levels. Satellite remote sensing provides a novel approach for large-scale N monitoring. In this study, we evaluated the performance of different types of spectral bands and indices (SIs) coupled with ensemble learning models (ELMs) at retrieving the plant N concentration (PNC) and plant aboveground biomass (AGB) of potato from Sentinel-2 images. Cloud-free Sentinel-2 imagery was acquired during the tuber-formation to starch-accumulation stages from 2020 to 2021. Fourteen optimal SIs were selected using the successive projections algorithm (SPA) and principal component analysis (PCA). The PNC and AGB estimation models were then built using an ELMs. The results showed that the SIs based on chlorophyll absorption bands were strongly related to potato PNC and AGB. Also, the N-correlated bands were mainly concentrated in the red-edge (705 nm) and short-wave infrared (1610 and 2190 nm) regions. The ELMs successfully predicted PNC and AGB (R2PNC = 0.74; R2AGB = 0.82). Compared with the other five base models (k-nearest neighbor (KNN), partial least squares regression (PLSR), support vector regression (SVR), random forest (RF), and Gaussian process regression (GPR)), the ELMs provided higher PNC and AGB estimation accuracy and effectively reduced overfitting to training data. This study demonstrated that the promising solution of using SPA-PCA coupled with an ensemble learning model improves the estimation accuracy of potato PNC and AGB based on Sentinel-2 imagery data. [ABSTRACT FROM AUTHOR]