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High-quality tea requires leaves of similar size and tenderness. The grade of the fresh leaves determines the quality of the tea. The automated classification of fresh tea leaves improves resource utilization and reduces manual picking costs. The present study proposes a method based on an improved genetic algorithm for identifying fresh tea leaves in high-speed parabolic motion using the phenotypic characteristics of the leaves. During parabolic flight, light is transmitted through the tea leaves, and six types of fresh tea leaves can be quickly identified by a camera.The influence of combinations of morphology, color, and custom corner-point morphological features on the classification results were investigated, and the necessary dimensionality of the model was tested. After feature selection and combination, the classification performance of the Naive Bayes, k-nearest neighbor, and support vector machine algorithms were compared. The recognition time of Naive Bayes was the shortest, whereas the accuracy of support vector machine had the best classification accuracy at approximately 97%. The support vector machine algorithm with only three feature dimensions (equivalent diameter, circularity, and skeleton endpoints) can meet production requirements with an accuracy rate reaching 92.5%. The proposed algorithm was tested by using the Swedish leaf and Flavia data sets, on which it achieved accuracies of 99.57% and 99.44%, respectively, demonstrating the flexibility and efficiency of the recognition scheme detailed in the present study.This research provides an efficient tea leaves recognition system that can be applied to production lines to reduce manual picking costs. © 2022 Society of Chemical Industry.

High temperature and strong light could induce bitterness and astringency of tea (Camellia sinensis (L.) O. Kuntze) in summer. Arbuscular mycorrhizal (AM) fungus and shading could change tea growth surroundings and improve its quality. The present study evaluated the inoculated effects of an arbuscular mycorrhizal fungus (AMF), Glomus etunicatum, on plant growth, root morphology, leaf nutrient status, phytohormones and the relative expression of root CsCPC, CsTTG1, CsAUX1, CsYUCCA1, CsNCED2, CsGA3OX1, CsDWF4 and CsAOS genes in Camellia sinensis ‘Xinyang population’ seedlings in sands under shading conditions. After 14 weeks of AMF inoculation, root mycorrhizal colonization ranged from 18.5% to 48.00%. AMF inoculation and shading heavily increased plant height, shoot and root biomass, total root length and volume, leaf nutrients content (except Fe), respectively. Both mycorrhizal inoculation and shading significantly increased root hair growth respectively, in company with up-regulation gene CsCPC and down-regulation gene CsTTG1. Root auxin level and its transport gene CsAUX1 was both up-regulated by mycorrhizal inoculation and shading. Interestingly, auxin biosynthesis gene CsYUCCA1 has not been affected, which suggested that both mycorrhizal and shading mainly regulate auxin transport but not biosynthesis pathway. The contents of gibberellin (GA) and brassinosteroid (BR) in root were notably increased by mycorrhizal inoculation and shading, accompanied with up-regulation of its biosynthesis genes, CsGA3OX1 and CsDWF4. With regard to the growth inhibiting phytohormones abscisic acid (ABA) and jasmonic acid (JA), mycorrhizal inoculation and shading significantly decreased their levels in root, in company with down-regulation of biosynthesis genes, CsNCED2 and CsAOS. These results implied that both AMF inoculation and shading could enhance the tea plant stress resistance and increase nutrient absorption, root biomass and the contents of root phytohormones by up-regulating its transport and biosynthesis pathway.

Plant root hairs are cylindrical tubular projections from root epidermal cells. They increase the root surface area, which is important for the acquisition of water and nutrients, microbe interactions, and plant anchorage. The root hair specification, the effect of root hairs on nutrient acquisition and the mechanisms of nutrients (calcium, iron, magnesium, nitrogen, phosphorus, and potassium) that affect root hair development and growth were reviewed. The gene regulatory network on root hair specification in the plant kingdom was highlighted. More work is needed to clone the genes of additional root hair mutants and elucidate their roles, as well as undertaking reverse genetics and mutant complementation studies to add to the current knowledge of the signaling networks, which are involved in root hair development and growth regulated by nutrients.