Theanine is the most abundant non-protein amino acid in Camellia sinensis, but it is not known how a tea plant accumulates such high levels of theanine. The endophyte isolated from in vitro grown plantlets of C. sinensis cultivars was identified as Luteibacter spp., showing strong biocatalytic activity for converting both glutamine and ethylamine to theanine. Theanine was secreted outside of the bacteria. The endophyte isolated from in vitro plantlets of Camellia oleifera cultivar was identified as Bacillus safensis and did not convert glutamine and ethylamine to theanine. Enzymatic assays in vitro indicated that γ-glutamyltranspeptidases rCsEGGTs from the endophyte Luteibacter strains converted glutamine and ethylamine to theanine at higher rates than rCsGGTs from C. sinensis. This is the first report on theanine biosynthesis by an endophyte from C. sinensis, which provides a new pathway to explore the mechanism of theanine biosynthesis in C. sinensis and the interactions between an endophyte and tea plants.

Parapoynx crisonalis is an important pest of many aquatic vegetables including water chestnuts. Understanding the relationship between temperature variations and the population growth rates of P. crisonalis is essential to predicting its population dynamics in water chestnuts ponds. These relationships were examined in this study based on the age-stage, two-sex life table of P. crisonalis developed in the laboratory at 21, 24, 27, 30, 33 and 36°C. The results showed that the values of Sxj (age-stage–specific survival rate), fxj (age-stage-specific fecundity), lx (age specific survival rate) and mx (age-specific fecundity) increased as the temperature rose from 21 to 27°C, then decreased from 30 to 36°C. Temperature also had a significant effect on the net reproductive rate (R0), gross reproductive rate (GRR), intrinsic rate of increase (r) and finite rate of increase (λ). The value of these parameters were at low levels at 21, 33, and 36°C. Further, the r value decreased as the temperature rose from 24 to 30°C, while the GRR reached its highest level at 27°C. The results indicated that optimal growth and development of P. crisonalis occurred at temperatures between 24°C to 30°C when compared to the lowest temperature (21°C) and higher temperatures of 33°C and 36°C.

It is difficult to accurately identify and extract bodies of water and underwater vegetation from satellite images using conventional vegetation indices, as the strong absorption of water weakens the spectral feature of high near-infrared (NIR) reflected by underwater vegetation in shallow lakes. This study used the shallow Lake Ulansuhai in the semi-arid region of China as a research site, and proposes a new concave-convex decision function to detect submerged aquatic vegetation (SAV) and identify bodies of water using Gao Fen 1 (GF-1) multi-spectral satellite images with a resolution of 16 meters acquired in July and August 2015. At the same time, emergent vegetation, "Huangtai algae bloom", and SAV were classified simultaneously by a decision tree method. Through investigation and verification by field samples, classification accuracy in July and August was 92.17% and 91.79%, respectively, demonstrating that GF-1 data with four-day short revisit period and high spatial resolution can meet the standards of accuracy required by aquatic vegetation extraction. The results indicated that the concave-convex decision function is superior to traditional classification methods in distinguishing water and SAV, thus significantly improving SAV classification accuracy. The concave-convex decision function can be applied to waters with SAV coverage greater than 40% above 0.3 m and SAV coverage 40% above 0.1 m under 1.5 m transparency, which can provide new methods for the accurate extraction of SAV in other regions.

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