Geographical distribution and potential distribution prediction of thirteen species of Citrus L. in China.

Using DIVA-GIS software to study the spatial accumulation of Citrus species, an important economic crop in China. Draw the distribution maps of Citrus to concerning altitude and vegetation, and use DIVA-GIS' Bioclim ecological model and maximum information entropy model Maxent software to estimate the potential distribution areas of various Citrus species. The results show that the Citrus genus is located in the south of Qinling Mountains, mainly in the southwest of China and the coast of southeastern China. Sichuan and Chongqing are the most densely distributed regions of Citrus. The distribution of Citrus is closely related to the vegetation type and altitude. The vegetation types in the distribution area is evergreen broad-leaved forest, evergreen shrub, deciduous broad-leaved forest, mixed-leaf forest coverage area, deciduous coniferous forest, farmland, trees, other vegetation coverage, and evergreen coniferous forest. The current potential distribution area of Citrus is mainly in Guizhou, Hubei, Hunan, Guangdong, Guangxi, Yunnan, Sichuan, Chongqing, and other provinces and municipalities and their borders, while the potential distribution area in the future moves northward and enter Henan and southern Gansu. At the same time, climate warming changes the distribution of suitable areas of Citrus, which makes the suitable areas of C. sinensis Osbeck, C. reticulata Blanco, and other crops greatly increased. Planning the planting area will effectively improve the yield and quality in the future. Planning presents new challenges.

An Autonomous Fruit and Vegetable Harvester with a Low-Cost Gripper Using a 3D Sensor.

Reliable and robust systems to detect and harvest fruits and vegetables in unstructured environments are crucial for harvesting robots. In this paper, we propose an autonomous system that harvests most types of crops with peduncles. A geometric approach is first applied to obtain the cutting points of the peduncle based on the fruit bounding box, for which we have adapted the model of the state-of-the-art object detector named Mask Region-based Convolutional Neural Network (Mask R-CNN). We designed a novel gripper that simultaneously clamps and cuts the peduncles of crops without contacting the flesh. We have conducted experiments with a robotic manipulator to evaluate the effectiveness of the proposed harvesting system in being able to efficiently harvest most crops in real laboratory environments.

Using UHPLC Q-Trap/MS as a complementary technique to in-depth mine UPLC Q-TOF/MS data for identifying modified nucleosides in urine.

Modified nucleosides, metabolites of RNA, are potential biomarkers of cancer before the appearance of morphological abnormalities. It is of great significance to comprehensively detect and identify nucleosides in human urine for discovery of cancer biomarkers. However, the lower abundance, the greater polarity and the matrix effects make it difficult to detect urinary nucleosides. In this paper, an integrated method consisted of sample preparation followed by ultraperformance liquid chromatography quadrupole time-of-flight mass spectrometry (UPLC Q-TOF/MS) detection and primary identification, then ultra-high performance liquid chromatography coupled with hybrid triple quadrupole linear ion trap mass spectrometer (UHPLC Q-Trap/MS) further identification and validation were introduced. Firstly, to enrich the nucleosides and eliminate the urine matrix effects, different sorbent materials of solid phase extraction (SPE) and the elution conditions were screened. Secondly, UPLC Q-TOF/MS was used to acquire mass data in MSE mode. The structural formulas of nucleosides in urine sample were primarily identified according to retention time, accurate mass precursor ions and fragment ions from in-house database and online database. Thirdly, the preliminary identified nucleoside structures lacking of characteristic fragment ions were verified by UHPLC Q-Trap/MS in multiple reaction monitoring trigger enhanced product ion scan (MRM-EPI) and neutral loss scan (NL). At last, phenylboronic acid (PBA)-based SPE was utilized due to its higher MS signal and weaker matrix effects under optimized extraction conditions. Fifty-five nucleosides were primarily identified by UPLC Q-TOF/MS, among which 50 nucleosides were confirmed by UHPLC Q-Trap/MS. Five nucleosides, namely 4',5'-didehydro-5'-deoxyadenosine, 4',5'-didehydro-5'-deoxyinosine, isonicotinamide riboside, peroxywybutosine and hydroxywybutosine, were found from urine for the first time. The results will expand the Human Metabolome Database (HMDB).