Construction of apricot variety search engine based on deep learning

Apricot has a long history of cultivation and has many varieties and types. The traditional variety identification methods are timeconsuming and labor-consuming, posing grand challenges to apricot resource management. Tool development in this regard will help researchers quickly identify variety information. This study photographed apricot fruits outdoors and indoors and constructed a dataset that can precisely classify the fruits using a U-net model (F-score:99%), which helps to obtain the fruit's size, shape, and color features. Meanwhile, a variety search engine was constructed, which can search and identify variety from the database according to the above features. Besides, a mobile and web application (ApricotView) was developed, and the construction mode can be also applied to other varieties of fruit trees.Additionally, we have collected four difficult-to-identify seed datasets and used the VGG16 model for training, with an accuracy of 97%, which provided an important basis for ApricotView. To address the difficulties in data collection bottlenecking apricot phenomics research, we developed the first apricot database platform of its kind (ApricotDIAP, http://apricotdiap.com/) to accumulate, manage, and publicize scientific data of apricot.

Amino acid profiles and protein quality of Siberian apricot(Prunus sibirica L.)kernels from Inner Mongolia

Siberian apricot(Prunus sibirica L.)is a traditional nut tree species in East Asia and Siberia and is a possible contribution to healthy diets.However,it has attracted little research attention and information on the nutritional value of its kernel is limited.In this study,the profile,nutritional value and variation of amino acids were investigated in eight provenances.The kernels contained29×10-2 g/g protein and were rich in glutamic acid(26.5%),aspartic acid(11.3%)and arginine(10.1%).They showed higher essential amino acids(EAA)than similar protein values for almonds.The variation coefficients of amino acids ranged from 3.8 to 43.7%,and the levels of seven amino acids were significantly different among the eight provenances.The proportion of essential amino acids to total amino acids and amino acid score were also quite different.Protein was negatively correlated with some amino acids and protein quality values.In conclusion,there were two superior provenances(Wanjiagou and Horinger County)with high EAA contents and protein quality,and could be used in the large-scale development of this species.

Cadmium pollution enhanced ozone damage to winter wheat:biochemical and physiological evidences

Combined effects of ozone （O3） and cadmium （Cd） on growth and physiology of winter wheat （Triticum aestivum L. cv. JM22） were determined. Wheat plants were grown without or with Cd and exposed to charcoal-filtered air （〈 10 ppb O3） or elevated O3 （80 ＋ 5 ppb, 7 hr/day） for 20 days. Results showed that O3 considerably depressed light saturated net photosynthetic rate （-20%）, stomatal conductance （-33%）, chlorophyll content （-33%）, and total biomass （-29%） without Cd. The corresponding decreases were further enhanced by 45%, 56%, 60% and 59%, respectively with Cd, indicating a synergistic effect of O3 and Cd on wheat. Ozone significantly increased the activity of superoxide dismutase （46%）, catalase （48%） and peroxidase （56%）. However, great increases in malondialdehyde （MDA） content （2.55 folds） and intercellular CO2 concentration （1.13 folds） were noted in O3＋Cd treatment compared to control. Our findings demonstrated that the increased anti-oxidative activities in wheat plants exposed to O3＋Cd might not be enough to overcome the adverse effects of the combination of both pollutants as evidenced by further increase in MDA content, which is an important indicator of lipid peroxidation. Precise prediction model on O3 damages to crop should be conducted to ensure agricultural production security by considering environmental constraints in an agricultural system in peri-urban regions.

Genome-wide screening of long non-coding RNAs involved in rubber biosynthesis in Eucommia ulmoides

Increasing evidence indicates that long non- coding RNAs （IncRNAs） play pivotal roles in regulatory networks controlling plant and animal gene expression. However, IncRNA roles in regulating rubber biosynthesis in Eucommia ulmoides, an emerging source of natural rubber （Eu-rubber）, are currently unknown. Here, we report on RNA deep-sequencing of E. ulmoides fruits at two developmental stages. Based on application of a stringent pipeline, 29,1o3 IncRNAs and 9,048 transcripts of uncertain coding potential （TUCPs） were identified.Two differentially expressed （DE）TUCPs appear to simultaneously regulate 12 protein-coding genes involved in Eu-rubber biosynthesis （GIEBs）, as well as 95 DE genes. Functional categorization of these 95 DE genes indicated their involvement in subcellular microstructures and cellular processes, such as cell wall, cell division, and growth. These DE genes may participate in the differentiation and development of laticifers, where Eu-rubber is synthesized. A model is proposed in which ＂commanders＂ （DE TUCPs） direct the ＂builders＂ （DE genes） to construct a ＂storehouse＂ of materials needed for Eu-rubber synthesis, and the ＂workers＂ （GIEBs） to synthesize Eu-rubber. These findings provide insights into both cis- and trans-polyisoprene biosynthesis in plants, laying the foundation for additional studies of this crucial process.