Comparison of metabolomics of Dendrobium officinale in different habitats by UPLC-Q-TOF-MS

Dendrobium officinale has been considered over past centuries to be extremely valuable for use as an herbal medicine in South Asian countries. In this work, the chemical profiles of D. officinale from different habitats were systematically characterized using ultra-performance liquid chromatography time-of-flight mass spectrometry (UPLC-Q-TOF-MS) and multivariate analysis. The principal component analysis (PCA), partial least squares discriminate analysis (PLS-DA) and orthogonal partial least squares analysis (OPLS-DA) of UPLC-Q-TOF-MS data displayed an obvious separation. Several flavonoids and terpenoids derivatives contribute to the quantitative chemotypic variation within and between the samples as observed. These findings lead to a better understanding of the phytochemical variation of D. officinale which can aid in quality control of raw material.     

Phytoconstituents from the leaves of Dracaena cochinchinensis (Lour.) S. C. Chen

Five flavonoids, four feruloyl amide derivatives, pinoresinol, lanost-9-en-3β-ol and three steroids from the leaves of Dracaena cochinchinensis (Lour.) S. C. Chen. Of these, compound 4 was identified as a new homoisoflavanone. This publication is the first reported purification of compounds 3, 4, 6–12 from D. cochinchinensis. We also indicate the chemotaxonomic importance of these metabolites.     

Induced leaf intercellular CO2, photosynthesis, potassium and nitrate retention and strawberry early fruit formation under macronutrient limitation

Relationships between induced high leaf intercellular CO₂ concentrations, leaf K⁺ and NO₃ ^? ion movement and early fruit formation under macronutrient limitation are not well understood. We examined the effects and interactions of reduced K/N input treatments on leaf intercellular CO₂, photosynthesis rate, carboxylation and water use efficiency, berry formation as well as leaf/fruit K⁺, NO₃ ^? and photosynthate retention of strawberry (Fragaria × ananassa Duch.) to enhance low-input agriculture. The field study was conducted in Nova Scotia, eastern Canada during 2009–2010. The experimental treatments consisted of five K₂O rates (0, 6, 12, 18, and 24 kg ha^?1) and five N rates (0, 5, 10, 15, and 20 kg ha^?1), representing respectively, 0, 25, 50, 75, and 100 % of regular macronutrient recommendations based on the soil testing. The treatments were arranged in a split-plot design with three blocks in the field. The cultivar was ‘Mira’, a June-bearing crop. The results showed that strawberry plants treated with 25 %-reduced inputs could induce significantly higher leaf intercellular CO₂ concentrations to improve plant photosynthesis, carboxylation and water use efficiency and translocation of leaf/fruit K⁺ and dissolved solids, which could advance berry formation by 6 days and produce significantly higher marketable yields (P < 0.05). Higher leaf intercellular CO₂ inhibited leaf/fruit NO₃ ^? ion retention, but this inhibition did not occur in leaf/fruit K⁺ retention. Linear interactions of the K/N treatments were significant on fruit marketable yields, intercellular CO₂, net photosynthesis, leaf transpiration rates, and leaf temperatures (P < 0.05). It was concluded that higher leaf CO₂ could enhance plant photosynthesis, promote plant carboxylation and water use efficiency, and advance berry formation, but it could inhibit leaf NO₃ ^? retention. This inhibition did not find in leaf K⁺ ion and dissolved solid retention. Overlay co-limitation of leaf intercellular CO₂ and translocation of leaf/fruit K⁺/NO₃ ^? and total dissolved solids could constrain more fruit formation attributes under full macronutrient supply than reduced inputs. It was suggested that low input would be an optimal and sustainable option for improving small fruit crop physiological development and dealing with macronutrient deficiency challenge.     

Identifying Fagaceae and Lauraceae species using leaf images and convolutional neural networks

Lauraceae and Fagaceae are two large woody plant families that are predominant in the low- and middle-altitude regions in Taiwan. The highly interspecific similarity between some species of the family brings limitations on the management and utilization. This work proposed an approach for identifying 15 Lauraceae species and 20 Fagaceae species using leaf images and convolutional neural networks (CNNs). Leaf specimens of 35 species were collected from the northern, central, and southern parts of Taiwan. Images of the leaves were acquired using flat-bed scanners. Three CNN architectures—DenseNet-121, MobileNet V2, and Xception—were trained. Xception achieved the highest mean test accuracy of 99.39%, and MobileNet V2 required the shortest mean test time of 17.1 ms per image using a GPU. The saliency maps revealed that the characteristics learned by models matched the leaf features used by botanists. A pruning algorithm, gate decorator, was applied to the trained models for reducing the number of parameters and number of floating-point operations of the MobileNet V2 by 55.4% and 69.1%, respectively, while the model accuracy was maintained at 92.03%. Thus, MobileNet V2 has the potential to be used for identifying the Lauraceae and Fagaceae species on mobile devices.     

Fungal endophyte communities in above- and belowground olive tree organs and the effect of season and geographic location on their structures

Studies comparing fungal endophytes between above- and belowground woody crop organs and the factors that may structure their communities are lacking. Due to its great impact on the Mediterranean Basin, the olive tree was chosen for the isolation of endophytic fungi from roots, leaves and twigs in two seasons in north-eastern Portugal. Nine hundred seventy-six isolates belonging to 38 fungal species were obtained. Phomopsis columnaris, Fusarium oxysporum and Trichoderma gamsii were the most frequently isolated, collectively representing 69% of the isolates. Fungal diversity in the roots was higher than in the aboveground organs and higher in spring than autumn. Endophyte community similarity between the above- and belowground organs and between seasons was low. Species composition also varied spatially, with the fungal composition of the roots varying more among locations than that of the aboveground organs. Our results suggest olive tree endophyte community structure is affected by plant organ, location and season.