Chuangchuang Yuan, Tonghai Liu^*, Shuang Song, Fangyu Gao, Rui Zhang

Phyton-International Journal of Experimental Botany, Vol.92, No.4, pp. 1037-1058, 2023, DOI:10.32604/phyton.2023.025343

Abstract Plant species recognition is an important research area in image recognition in recent years. However, the existing plant species recognition methods have low recognition accuracy and do not meet professional requirements in terms of recognition accuracy. Therefore, ShuffleNetV2 was improved by combining the current hot concern mechanism, convolution kernel size adjustment, convolution tailoring, and CSP technology to improve the accuracy and reduce the amount of computation in this study. Six convolutional neural network models with sufficient trainable parameters were designed for differentiation learning. The SGD algorithm is used to optimize the training process to avoid overfitting or falling into the… More >

Zhiguo Lu¹, Yuhong Zheng^1,*, Pengchong Zhang², Boyuan Fan³, Aimin Yu⁴, Li Fu^3,*

Phyton-International Journal of Experimental Botany, Vol.91, No.11, pp. 2549-2558, 2022, DOI:10.32604/phyton.2022.021288

Abstract In this communication, we used electrochemical sensor for recording the electrochemical profiles of eleven species of Yulania spp. from leaf extract. Two solvents and two buffer conditions were used for electrochemical fingerprints collection. Their electrochemical fingerprints can be converted to different patterns and consequently for species recognition. The results indicate the pattern recognition is much convenient than that of the recognition of species directly using voltammetric signal. The current information in electrochemical fingerprinting represents the type and amount of electrochemically active molecules, which linked to the genetic differences among the plants. Therefore, the electrochemical fingerprints were applied for further phylogenetic… More >

Ayman Altameem¹, Sandeep Kumar², Ramesh Chandra Poonia³, Abdul Khader Jilani Saudagar^4,*

CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 4719-4736, 2022, DOI:10.32604/cmc.2022.022177

Abstract Since the beginning of time, humans have relied on plants for food, energy, and medicine. Plants are recognized by leaf, flower, or fruit and linked to their suitable cluster. Classification methods are used to extract and select traits that are helpful in identifying a plant. In plant leaf image categorization, each plant is assigned a label according to its classification. The purpose of classifying plant leaf images is to enable farmers to recognize plants, leading to the management of plants in several aspects. This study aims to present a modified whale optimization algorithm and categorizes plant leaf images into classes.… More >

Villa-Hernández JM¹, B García-Ocón², E del C Sierra-Palacios², C Pelayo-Zaldivar³, F Díaz de León-Sánchez¹, LJ Pérez-Flores¹, JA Mendoza-Espinoza²

Phyton-International Journal of Experimental Botany, Vol.87, pp. 72-78, 2018, DOI:10.32604/phyton.2018.87.072

Abstract Mexico bears witness to a long-standing tradition in the use of plants for medicinal purposes; nevertheless, standardized methodological approaches for the proper identification of these are still needed. The problem is especially noticeable during the validation of ingredients in herbal preparations, as so many of them are sold as powders. It is for these reasons that the present study aims to compare the results of classic taxonomical assessments with those obtained using more modern molecular techniques (e.g. PCR-amplified 18S ribosomal RNA gene analysis) in one ethnobotanical case-study carried out in the “Desierto de los Leones” National Park in Mexico City,… More >